System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an image input by a user; means for analyzing the image to determine a specific place or landmark; means for acquiring tourist spot information based on the determined place or landmark; means for automatically generating a travel schedule based on the tourist spot information; means for estimating a travel cost based on the travel schedule; means for generating a travel bookmark including the travel schedule and the cost estimate; and means for presenting the travel bookmark to the user.SELECTED DRAWING: Figure 1

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] Planning a trip requires a lot of time and effort, which can be a burden, especially for busy people in their 20s and 30s. It's also difficult to maintain initial motivation, which often leads to abandonment midway through the planning process. Furthermore, there is a need for a method for efficiently planning a trip that effectively highlights the attractions of tourist destinations. The purpose of this invention is to solve these problems and provide a means for making trip plans easily and effectively. [Means for solving the problem]

[0005] The present invention solves these problems by the following means.

[0006] 1. A means of accepting user-entered images.

[0007] 2. A means for analyzing said image to identify specific locations or landmarks.

[0008] 3. A means for obtaining tourist destination information based on the determined locations and landmarks.

[0009] 4. A means for automatically generating a travel schedule based on the tourist destination information.

[0010] 5. A means for estimating travel costs based on said travel schedule.

[0011] 6. A means for generating a travel itinerary including said travel schedule and cost estimate.

[0012] 7. A means for presenting the travel guide to a user.

[0013] By combining these methods, users can easily plan their trips while maintaining their initial motivation for the trip. It also makes it easy to maximize the appeal of tourist destinations and create efficient travel plans.

[0014] "User" means an individual or organization that uses the System to make travel plans.

[0015] "Image" means a photograph or drawing uploaded by a User to the System to represent a location or landmark for a proposed trip.

[0016] "Analysis" is the process of extracting characteristic information from the input image and recognizing specific locations or landmarks based on that information.

[0017] A "landmark" is a specific location or building that serves as a starting point for travel planning, such as a tourist spot or famous place.

[0018] "Tourist destination information" is detailed data about a particular tourist destination, including tourist attractions, restaurants, accommodations, transportation options, etc.

[0019] A "travel schedule" is a timeline that defines the tourist spots to be visited during the user's travel period, as well as related activities and transportation plans.

[0020] A "cost estimate" is a calculation of the total cost of your trip, including transportation, accommodation, and meals.

[0021] A "travel guide" is a document that compiles the generated travel itinerary and cost estimates and can be used as a reference during a trip by the user.

[0022] "Presenting" is the act or process of visually showing the generated travel guide to the user. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] User interface (terminal side)

[0045] The present invention begins with the user uploading images of their travel plans via a device. This device can be a smartphone, tablet, PC, or any other device with an internet connection. The user selects a photo or image of their travel plan and clicks the "Upload Images" button in the application. At this point, the device sends the image to the server.

[0046] Image analysis (server side)

[0047] The server receives the image sent from the device and begins image analysis. This analysis process uses an image recognition engine (e.g., TensorFlow, OpenCV). The server identifies key landmarks and place names in the image and extracts their location information and related data. Once the analysis results are obtained, the process proceeds to the next stage.

[0048] Examples:

[0049] When a user uploads a photo of Mount Fuji, the server uses an image analysis engine to recognize Mount Fuji and identify surrounding landmarks (e.g., the Fuji Five Lakes, Fuji-Q Highland, etc.).

[0050] Obtaining tourist information (server side)

[0051] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). The tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc.

[0052] Examples:

[0053] The server collects information about the Fuji Five Lakes and Fuji-Q Highland, and also obtains data on related accommodations and restaurants.

[0054] Travel schedule generation (server side)

[0055] Based on the collected tourist destination information, the server automatically generates a travel schedule. This schedule generation process takes into account the user's desired travel period, travel time, and time spent at the destinations. The generated schedule includes specific activities for each day.

[0056] Examples:

[0057] The server plans a three-day trip, with the first day visiting the Fuji Five Lakes, the second day visiting Fuji-Q Highland, and the third day visiting nearby hot springs.

[0058] Cost Estimate (Server Side)

[0059] Based on the travel itinerary, the server estimates the cost of the entire trip, including the sum of individual costs such as transportation, accommodation, meals, etc. It uses an external API to obtain real-time pricing information and provides an accurate estimate.

[0060] Travel itinerary generation (server side)

[0061] Finally, the server generates a "trip itinerary" that summarizes the trip schedule and cost estimates, which can be made easily accessible to users in PDF or HTML format.

[0062] Examples:

[0063] The final itinerary includes a schedule for each day, detailed information about the places visited and a breakdown of estimated costs, which users can download and refer to during their trip.

[0064] Displaying the results (terminal side)

[0065] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[0066] User confirmation and final adjustments

[0067] The user can review the presented itinerary and, if satisfied, proceed with the trip. If changes are needed, they can send a request to the server via the terminal and make the necessary adjustments.

[0068] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The user uploads images of their proposed trip to their device.

[0072] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[0073] Step 2:

[0074] The device compresses the uploaded image and sends it to the server.

[0075] The device compresses the input image data and sends it to the server as an HTTP request, which includes the image data and necessary metadata (user ID, timestamp).

[0076] Step 3:

[0077] The server analyzes the received image.

[0078] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[0079] Step 4:

[0080] The server collects tourist destination information based on the identified landmarks.

[0081] Based on the identified landmarks and place names, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[0082] Step 5:

[0083] A travel schedule is automatically generated based on tourist destination information collected by the server.

[0084] Based on the acquired information, the server generates a schedule that matches the user's desired travel period, including tourist spots to visit, travel time, stay time, rest time, etc.

[0085] Step 6:

[0086] The server estimates the travel cost based on the travel schedule.

[0087] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[0088] Step 7:

[0089] The server generates the travel guide.

[0090] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[0091] Step 8:

[0092] The server transmits the generated travel guide to the terminal.

[0093] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[0094] Step 9:

[0095] The device displays the trip itinerary to the user.

[0096] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[0097] Step 10:

[0098] The user reviews the travel itinerary and makes the final decision.

[0099] The user can review the presented itinerary and, if satisfied, proceed with the travel plan. If changes are needed, they can send a request via the device and make the necessary adjustments.

[0100] Example 1

[0101] 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."

[0102] Planning a trip requires a wide range of tasks, such as gathering information on tourist spots, adjusting schedules, and estimating costs, placing a heavy burden on users. Additionally, it is difficult to select reliable information from the overwhelming amount of information available on the Internet, which makes planning time-consuming and stressful. Furthermore, the lack of tools that allow users to centrally manage travel schedules and costs makes it difficult for users to efficiently plan their trips.

[0103] 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.

[0104] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places or landmarks, means for acquiring location information based on the identified places or landmarks, means for automatically generating a travel plan based on the location information, means for estimating travel costs based on the travel plan, means for generating a guide including the travel plan and cost estimate, and means for presenting the guide to the user, thereby reducing the burden on the user and enabling efficient travel planning.

[0105] "User" refers to a person who uses the system to make travel plans.

[0106] "Means for accepting images" refers to the mechanism for receiving image files uploaded by users.

[0107] "Means for analyzing images to identify specific places and landmarks" refers to technology for recognizing input images and identifying specific places and landmarks present within the images.

[0108] "Means for obtaining location information" refers to the mechanism for obtaining information related to identified locations and landmarks from external databases or APIs.

[0109] "Means for automatically generating travel plans" refers to a system that automatically creates a travel schedule based on acquired location information, taking into account the user's desired period and means of transportation.

[0110] "Means for estimating travel costs" refers to a mechanism for calculating and totaling the costs required for each journey based on the generated travel plan.

[0111] "Means for generating guidance" refers to a mechanism for creating a document that integrates travel plans and cost estimates and presents them to the user.

[0112] "Presentation means" refers to a mechanism for visually displaying the generated guidance to the user.

[0113] The present invention is a system that aims to enable users to make travel plans efficiently and easily. An embodiment of the system of the present invention will be described below.

[0114] User interface (terminal side)

[0115] Users upload images of potential travel destinations to the system using their own devices. These devices include devices with internet connectivity, such as smartphones, tablets, and PCs. Users select photos or images of potential travel destinations and click the "Upload Images" button in the application. This action causes the device to send the image files to the server.

[0116] Examples:

[0117] When a user wants to upload a photo of Mt. Fuji, he or she selects a photo of Mt. Fuji from the gallery of the smartphone and clicks the upload button.

[0118] Image analysis (server side)

[0119] The server receives the image file sent from the device and saves it in the appropriate directory. It then loads the saved image file and uses an image recognition engine such as TensorFlow or OpenCV to identify key landmarks and place names in the image. The server extracts the location information and related data of the recognized landmarks and proceeds to the next step.

[0120] Examples:

[0121] The server receives a photo of Mt. Fuji and uses an image analysis engine to recognize Mt. Fuji and identify surrounding landmarks (e.g., Fuji Five Lakes, Fuji-Q Highland).

[0122] Obtaining tourist information (server side)

[0123] Based on the landmarks identified by image analysis, the server collects related tourist destination information using external APIs (e.g., Google Places API, Yelp API), including tourist attractions, restaurants, accommodations, and transportation options.

[0124] Examples:

[0125] The server uses the Google Places API to obtain information about the Fuji Five Lakes and Fuji-Q Highland, as well as data on related accommodations and restaurants.

[0126] Travel schedule generation (server side)

[0127] Based on the collected tourist destination information, the server automatically generates a travel schedule, taking into consideration information provided by the user, such as the desired travel period, travel time, and length of stay at the destinations.

[0128] Examples:

[0129] The server creates a three-day travel plan, with the first day planned to be spent sightseeing at the Fuji Five Lakes, the second day to enjoy Fuji-Q Highland, and the third day to visit nearby hot spring resorts.

[0130] Cost Estimate (Server Side)

[0131] Based on the generated itinerary, the server retrieves real-time pricing information using an external API and estimates the cost of the entire trip, including transportation, accommodation, and meals.

[0132] Travel itinerary generation (server side)

[0133] The server compiles the generated travel schedule and cost estimates and generates a "travel guide" in PDF or HTML format for easy access by the user.

[0134] Examples:

[0135] The final itinerary includes a detailed schedule for each day, information about tourist attractions, and a breakdown of estimated costs, which users can download and refer to during their trip.

[0136] Displaying the results (terminal side)

[0137] The generated travel bookmark is sent from the server to the device, which receives it and visually displays it to the user. The user can then review the bookmark and submit change requests if necessary.

[0138] Examples:

[0139] The travel bookmark is displayed on the user's terminal, and the user checks the contents of the bookmark.

[0140] Examples of prompt statements

[0141] Here are some example prompts to input to a generative AI model:

[0142] "Please upload photos of Mt. Fuji and create a three-day itinerary. Please include information on attractions, accommodations, and restaurants, as well as a cost estimate."

[0143] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0144] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0145] Step 1:

[0146] The user selects an image of a potential travel destination and clicks the "Upload Image" button in the application on the device. The input is the selected image file, and the output is the image file sent to the server.

[0147] Specific behavior:

[0148] The user selects a photo of Mt. Fuji from their smartphone's gallery and presses the "Upload Image" button in the application.

[0149] Step 2:

[0150] The server receives the image file sent from the terminal. The image file arrives at the server as input, and the image file is saved in the appropriate directory on the server as output.

[0151] Specific behavior:

[0152] The server receives the photo of Mt. Fuji and saves it in the " / uploaded_images" directory.

[0153] Step 3:

[0154] The server loads the saved image files and performs image analysis using image recognition engines such as TensorFlow and OpenCV. The saved image files are used as input, and the output is information about identified landmarks and places.

[0155] Specific behavior:

[0156] The server loads a photo of Mount Fuji and uses TensorFlow to recognize Mount Fuji in the image and extract its location information.

[0157] Step 4:

[0158] The server uses the Google Places API and Yelp API to retrieve information related to the identified landmarks and places. The input is the location information of the identified landmarks, and the output is the collection of information about related tourist attractions.

[0159] Specific behavior:

[0160] The server uses the Google Places API to collect information about the Fuji Five Lakes and Fuji-Q Highland.

[0161] Step 5:

[0162] The server automatically generates a travel schedule using the collected tourist destination information based on the user's desired travel information (desired travel period, travel time, length of stay, etc.) The input is tourist destination information and the user's desired information, and the output is a specific travel schedule.

[0163] Specific behavior:

[0164] The server takes into consideration the user's desired three-day period and creates a schedule that visits the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a hot spring resort on the third day.

[0165] Step 6:

[0166] The server estimates the cost of the trip based on the generated itinerary, which involves retrieving real-time pricing information using an external API and adding up the individual costs. The input is the itinerary, and the output is the estimated cost of the entire trip.

[0167] Specific behavior:

[0168] The server tallies up accommodation, transportation, meal costs, etc., and calculates the total cost of the entire trip.

[0169] Step 7:

[0170] The server integrates the travel schedule and cost estimate information to generate a "travel guide" in a user-friendly format (PDF or HTML). The input is the travel schedule and cost estimate, and the output is a travel guide.

[0171] Specific behavior:

[0172] The server compiles the schedule and cost estimates and generates a detailed travel guide in PDF format.

[0173] Step 8:

[0174] The server sends the generated itinerary to the user's terminal. The input is the generated itinerary, and the output is the itinerary sent to the terminal.

[0175] Specific behavior:

[0176] The server sends a PDF travel guide to the user's smartphone.

[0177] Step 9:

[0178] The terminal visually displays the received travel itinerary to the user. The input is the received travel itinerary, and the output is the visual display to the user.

[0179] Specific behavior:

[0180] The travel bookmark will be displayed on the smartphone screen and the user will be able to check it.

[0181] Step 10:

[0182] The user checks the displayed travel bookmark and sends a change request to the server if necessary. The input is the displayed travel bookmark, and the output can be a change request.

[0183] Specific behavior:

[0184] The user presses the "Request Changes" button in the application to send any complaints about the bookmark to the server.

[0185] (Application example 1)

[0186] 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."

[0187] In the modern tourism industry, users need to collect and adjust a lot of information to plan a trip. This process is time-consuming and extremely difficult, especially for users who have little information about the place they are visiting for the first time. Furthermore, online tourism information and services cannot fully replace the actual travel experience, and there are limited ways to simulate a trip. To solve these issues, a system is needed that not only allows users to easily plan their trip, but also provides a tourism experience in a virtual space.

[0188] 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.

[0189] In this invention, the server includes means for accepting images input by a user, means for analyzing the images to identify specific places and landmarks, means for acquiring tourist attraction information based on the identified places and landmarks, means for automatically generating a travel itinerary based on the tourist attraction information, means for estimating travel costs based on the travel schedule, means for generating a travel guidebook including the travel schedule and cost estimate, means for presenting the travel guidebook to the user, and means for providing a tourist experience in a virtual space based on the tourist attraction information. This allows users to efficiently and easily plan their trip and further enables them to experience tourist attractions in the virtual space before their actual trip.

[0190] The "means for accepting user-entered images" refers to a function that allows a user to upload images of potential travel destinations through the interface.

[0191] The "means for analyzing the image to identify specific locations and landmarks" refers to a technology for processing the image received on the server side and identifying major landmarks and place names using an image analysis engine.

[0192] The "means for acquiring tourist attraction information based on the identified locations and landmarks" is a function for collecting tourist attraction information related to landmarks identified by image analysis from an external API, etc.

[0193] The "means for automatically generating a travel schedule based on the tourist attraction information" is a technology that automatically generates a travel schedule that meets the user's wishes based on the collected tourist attraction information.

[0194] The "means for estimating travel expenses based on the travel schedule" is a function for calculating the total cost of transportation, accommodation, meals, etc. based on the generated travel schedule.

[0195] The "means for generating a travel guide including the travel schedule and cost estimate" refers to a technology for creating a document including the travel schedule and cost estimate in PDF or HTML format.

[0196] The "means for presenting the travel itinerary to the user" is a function for transmitting the generated travel itinerary to the user's terminal and visually displaying it.

[0197] "Means for providing a tourist experience in a virtual space based on the tourist destination information" refers to technology that enables users to have an immersive tourist experience in a virtual space based on the collected tourist destination information.

[0198] This invention is a virtual tourist guide system that allows users to upload images of potential travel destinations and provides sightseeing experiences in a virtual space based on the uploaded images. This system is implemented using devices such as smart glasses and a server.

[0199] Hardware and software usage

[0200] Hardware:

[0201] Smart glasses: A device that allows users to upload images and visually confirm their virtual tourism experience.

[0202] Server: A central computing resource that analyzes images, collects tourist information, generates travel schedules, estimates costs, and generates travel guides.

[0203] software:

[0204] TensorFlow: A deep learning framework used to analyze images.

[0205] OpenCV: Used as an image processing library.

[0206] Google Places API: An external API used to collect tourist destination information.

[0207] Data processing and data calculation processing

[0208] 1. User uploads an image:

[0209] Users use the smart glasses interface to upload images of potential travel destinations, which are then sent to a server.

[0210] 2. Image Analysis:

[0211] The server analyzes the received image using TensorFlow and OpenCV to identify major landmarks and place names, and proceeds to the next step based on the analysis results.

[0212] 3. Obtaining tourist information:

[0213] The server uses the Google Places API to retrieve tourist information based on the identified landmarks, collecting detailed data on tourist attractions, restaurants, accommodations, etc.

[0214] 4. Generate travel schedule:

[0215] The server automatically generates a travel schedule based on the collected tourist destination information, taking into consideration the user's desired travel period and travel time.

[0216] 5. Cost Estimate:

[0217] The server estimates the travel costs, including transportation, accommodation, and meals, based on the generated itinerary, using real-time pricing information from an external API.

[0218] 6. Travel bookmark generation:

[0219] The server generates a travel itinerary that includes the travel schedule and cost estimates, and creates it in PDF and HTML formats.

[0220] 7. Providing tourism experiences:

[0221] The server provides users with a sightseeing experience in a virtual space based on tourist destination information and travel bookmarks, which are projected onto the smart glasses.

[0222] 8. Presentation of results:

[0223] The generated travel itinerary and virtual sightseeing experience are displayed on the smart glasses' display, where users can review it and submit change requests if necessary.

[0224] Adding specific examples

[0225] For example, if a user uploads a photo of Mt. Fuji, the system works as follows:

[0226] A user uploads a photo of Mount Fuji.

[0227] The server uses TensorFlow to recognize Mt. Fuji and uses the Google Places API to collect information about tourist spots around Mt. Fuji (e.g., Fuji Five Lakes, Fuji-Q Highland).

[0228] The server generates a three-day travel schedule, planning a visit to the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a visit to nearby hot springs on the third day.

[0229] Estimate costs based on your travel schedule and generate a travel guide.

[0230] The generated travel guide is displayed on smart glasses, allowing users to experience tourist spots in a virtual space.

[0231] Prompt Sentence Examples

[0232] "Upload photos of Mt. Fuji, gather information on nearby tourist attractions, and create a three-day travel plan."

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] The user uses the smart glasses interface to upload an image of a potential travel destination, with the image of the user's choice as input, and the device then sends the image to the server.

[0236] Step 2:

[0237] The server receives images sent from the device. Using the received image file as input, it performs image analysis using TensorFlow and OpenCV. Specifically, the server extracts features within the image and identifies major landmarks and place names. The identified landmarks and place names are output as the analysis results.

[0238] Step 3:

[0239] The server uses the results of image analysis to collect tourist information related to the identified landmarks and place names. Using the analysis results as input, the server calls the Google Places API to retrieve tourist information. Specifically, the server sends API requests to collect data on tourist attractions, restaurants, accommodations, etc. This information is the output.

[0240] Step 4:

[0241] The server automatically generates a travel schedule based on the collected tourist destination information. Using the tourist destination information as input, it creates a specific daily plan taking into account the user's desired travel period, travel time, and time spent at each destination. The output of this process is a detailed travel schedule.

[0242] Step 5:

[0243] The server estimates the cost of the trip based on the generated itinerary. It uses the itinerary as input and sums up the individual costs such as transportation, accommodation, and meals. It uses an external API to get real-time pricing information and provides an accurate estimate. The output is the total cost and a breakdown of the individual costs.

[0244] Step 6:

[0245] The server compiles the travel schedule and cost estimates to generate a travel itinerary. It uses the travel schedule and cost estimates as input and creates a travel itinerary in PDF or HTML format. Specifically, it generates a document that includes the schedule for each day, detailed information about the places visited, and a breakdown of costs. The output is the completed travel itinerary.

[0246] Step 7:

[0247] The server sends the generated itinerary to the terminal and presents it visually to the user. It uses the generated itinerary as input and sends it to the terminal. The terminal receives it and displays it on the smart glasses display. The user reviews it and, if satisfied, can proceed with the trip. It is also possible to send change requests if necessary.

[0248] Step 8:

[0249] The server provides a sightseeing experience in a virtual space based on tourist destination information. It uses the collected tourist destination information as input and creates a virtual tour using virtual reality technology. Specifically, it displays 3D models and images so that users can experience the tourist destination realistically through smart glasses. The output is a sightseeing experience in a virtual space.

[0250] 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.

[0251] User interface (terminal side)

[0252] The present invention begins with the step where a user uploads images of potential travel destinations via a terminal and uses an emotion engine to analyze the user's emotions. The terminal can be a smartphone, tablet, PC, or other device that can connect to the Internet. The user selects a photo or image of a potential travel destination and clicks the "Upload Image" button in the application. At this point, the terminal sends the image to the server, and the emotion engine simultaneously analyzes the user's emotions.

[0253] Image analysis and emotion analysis (server side)

[0254] The server receives the image sent from the device and begins image analysis. Image analysis libraries (e.g., TensorFlow, OpenCV) are used to identify key landmarks and place names in the image. An emotion engine also analyzes the user's voice and text input to identify their current emotional state (e.g., excited, relaxed, excitement-seeking).

[0255] Examples:

[0256] If a user uploads a photo of Mount Fuji, the server will use an image analysis engine to recognize the mountain, and an emotion engine will analyze that the user has a "spirit of adventure."

[0257] Obtaining tourist destination information and adjusting it based on emotions (server side)

[0258] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). Tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc. Based on the information from the emotion engine, the server selects and adjusts tourist attractions and activities that match the user's current emotional state.

[0259] Examples:

[0260] The server collects information on tourist spots around Mount Fuji and suggests hiking trails and outdoor activities to adventurous users.

[0261] Travel schedule generation and sentiment-based optimization (server side)

[0262] Based on the collected tourist destination information and the results of the emotion engine, the server automatically generates a travel schedule, taking into account the user's desired travel period, travel time, stay time, and emotional state to create an optimized schedule.

[0263] Examples:

[0264] The server plans a three-day trip, with the first day being canoeing on the Fuji Five Lakes, the second day climbing Mount Fuji, and the third day relaxing at a hot spring resort.

[0265] Cost Estimate (Server Side)

[0266] The server estimates the total cost of the trip based on the travel itinerary, calculates individual costs such as transportation, accommodation, and meals, and uses external APIs to obtain real-time pricing information to provide an accurate estimate.

[0267] Travel itinerary generation (server side)

[0268] Finally, the server generates a "travel bookmark" that summarizes the trip itinerary and cost estimates, in PDF or HTML format for easy user access, and adjusts the bookmark content based on the results of the emotion engine.

[0269] Examples:

[0270] The final itinerary includes a schedule for each day, detailed information about the places to visit, a breakdown of expected costs, and highlights special activities for the more adventurous user.

[0271] Displaying the results (terminal side)

[0272] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[0273] User confirmation and final adjustments

[0274] Users can review the presented travel plan and, if satisfied, proceed with their travel plans. Because it includes suggestions based on the results of the emotion engine, users can enjoy travel plans that are even more tailored to their needs. If changes are needed, the device sends a request to the server again, and the necessary adjustments are made.

[0275] In this way, the system of the present invention enables users to easily and effectively plan their trips while taking their emotions into consideration, thereby improving the user's travel experience.

[0276] The processing flow will be explained below.

[0277] Step 1:

[0278] The user uploads images of their proposed trip to their device.

[0279] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[0280] Step 2:

[0281] The device sends the uploaded images and the user's voice and text input to the server.

[0282] The device compresses the input image data and the user's voice and text data, and sends them to the server as an HTTP request. This request includes the image data, voice data, text data, and necessary metadata (user ID, timestamp).

[0283] Step 3:

[0284] The server analyzes the received image.

[0285] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[0286] Step 4:

[0287] The server analyzes the user's emotions.

[0288] The server uses an emotion analysis engine to analyze the user's voice or text input to determine the user's current emotional state, using speech recognition and text analysis algorithms.

[0289] Examples:

[0290] If a user uploads an image of Mount Fuji and enters the text "I want to have an adventure," the server will recognize Mount Fuji through image analysis and detect the "spirit of adventure" through emotional analysis.

[0291] Step 5:

[0292] The server collects tourist destination information based on the identified landmarks and the user's emotions.

[0293] Based on the identified landmarks, place names, and user sentiment information, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[0294] Step 6:

[0295] The server generates a travel schedule adjusted based on the emotions.

[0296] The server takes into account the acquired tourist destination information and the user's emotional state to generate a schedule that matches the user's desired travel period. This schedule includes tourist destinations to visit, travel time, stay time, rest time, etc.

[0297] Examples:

[0298] For adventurous users, the server will suggest schedules that include mountain climbing and adventure sports.

[0299] Step 7:

[0300] The server estimates the travel cost based on the travel schedule.

[0301] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[0302] Step 8:

[0303] The server generates the travel guide.

[0304] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[0305] Examples:

[0306] The travel guide details hiking and outdoor activities and breakdowns of expected expenses for the more adventurous user.

[0307] Step 9:

[0308] The server transmits the generated travel guide to the terminal.

[0309] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[0310] Step 10:

[0311] The device displays the trip itinerary to the user.

[0312] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[0313] Step 11:

[0314] The user reviews the travel itinerary and makes the final decision.

[0315] The user checks the presented itinerary and, if satisfied, proceeds with the travel plan. If changes are needed, the user sends a request to the server via the device and makes the necessary adjustments.

[0316] Example 2

[0317] 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."

[0318] Conventional travel planning systems often provide simple tourist information without considering the user's emotional state, making it difficult to create travel plans that meet individual needs. Furthermore, they require the user to manually search multiple sites to gather information, and they also require excessive effort in scheduling and estimating costs. Given these circumstances, there is a need for a method to automatically create travel plans that take the user's emotions into account, allowing for efficient and accurate travel planning.

[0319] 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.

[0320] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for analyzing the user's emotions, means for acquiring tourist destination information based on the identified places and landmarks and the user's emotions, means for automatically generating a travel itinerary based on the tourist destination information and emotion analysis, means for estimating travel costs based on the travel schedule, means for generating a travel itinerary including the travel schedule and cost estimate, and means for presenting the travel itinerary to the user. This enables automatic generation and optimization of a travel plan according to the user's emotional state.

[0321] "User" refers to an individual or organization that uses this system to plan a trip.

[0322] "Device" refers to a device that can connect to the Internet, such as a smartphone, tablet, or PC.

[0323] "Images" refers to photographs and graphic data uploaded by users via their devices.

[0324] "Server" refers to a central processing unit that performs image analysis, emotion analysis, acquisition of tourist destination information, generation of travel schedules, cost estimates, and generation of travel guides.

[0325] "Image analysis" refers to the process of identifying specific places or landmarks from uploaded images.

[0326] "Emotion analysis" refers to the process of identifying a user's emotions based on the voice and text data entered by the user.

[0327] "Tourist destination information" refers to data about tourist attractions, restaurants, accommodations, transportation, etc. related to a specific location or landmark.

[0328] "Travel schedule" refers to travel itineraries and activity plans automatically generated based on tourist destination information and the user's emotional state.

[0329] "Cost Estimate" refers to the total travel cost calculated based on the generated travel itinerary.

[0330] "Travel Guide" means a travel itinerary provided to a User, including a travel schedule and cost estimate.

[0331] This invention provides a system that automatically generates travel plans that take users' emotions into consideration and provides optimal travel schedules. Specifically, the system allows users to upload images via their devices, and generates travel plans that meet the user's needs by analyzing the images and the user's emotions. This system uses the following hardware and software:

[0332] Hardware and software used

[0333] Device: Refers to a device that can connect to the internet, such as a smartphone, tablet, or PC. Users use these devices to input images, text, voice, etc.

[0334] Server: A central processing unit used to execute programs that perform the following processes:

[0335] Image analysis libraries (e.g. TensorFlow, OpenCV)

[0336] Sentiment Analysis Engine

[0337] External APIs (e.g. Google Places API, Yelp API)

[0338] Program processing

[0339] The device sends the user-uploaded images and necessary text and audio data to the server. The server analyzes the received images using image analysis libraries such as TensorFlow and OpenCV to identify specific locations and landmarks. It then uses a sentiment analysis engine to analyze emotions from the user's input text and audio.

[0340] The server uses the Google Places API and Yelp API to collect tourist information based on the identified landmarks and the analyzed emotional state. This tourist information includes tourist attractions, restaurants, accommodations, and transportation options. Based on the collected information and the results of the emotional analysis, the server automatically generates an optimized travel itinerary. Furthermore, it estimates travel costs based on the generated schedule and generates the final travel itinerary in PDF or HTML format.

[0341] Adding specific examples

[0342] Examples:

[0343] When a user uploads a photo of Mount Fuji, the server analyzes the photo to recognize the mountain and identifies emotions such as "adventure" and "excitement" through a sentiment analysis engine. It then uses the Google Places API to retrieve information on hiking trails, outdoor activities, accommodations, and other information around Mount Fuji. Finally, the server creates a three-day itinerary, including canoeing around the Fuji Five Lakes on the first day, climbing Mount Fuji on the second day, and relaxing at a hot spring resort on the third day. This includes travel and accommodation costs, and a detailed travel itinerary is generated.

[0344] Prompt Sentence Examples

[0345] "Upload an image of Mount Fuji, perform sentiment analysis, generate a three-day travel itinerary suitable for adventurous users, and create a travel bookmark with cost estimates."

[0346] In this way, the system of the present invention can make travel plans with high accuracy and efficiency while taking into account the user's emotions.

[0347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0348] Step 1:

[0349] The user selects an image or photo of a potential travel destination and clicks the "Upload Image" button in the application. The device receives the image file and the user's emotion as input and sends it to the server. The specific operation involves implementing the image file selection and upload functions using programming languages ​​such as JavaScript and Python.

[0350] Step 2:

[0351] The device receives image data and additional emotion data (text or voice) input by the user and sends it to the server. The input data is image and text or voice data, which is packetized and sent to the server. Specifically, the device performs communication processing to send data to the server via an HTTP request.

[0352] Step 3:

[0353] The server analyzes the image data received from the device using image analysis libraries such as TensorFlow and OpenCV. The input for image analysis is image data, and the output is identification information for specific locations and landmarks. The server identifies key landmarks based on the analyzed information. Specifically, it calls the TensorFlow API and processes the image data.

[0354] Step 4:

[0355] The server analyzes the text or voice data sent by the user using a sentiment analysis engine. The input is text or voice data, and the output is the user's emotional state (e.g., excited, relaxed, adventurous). Specifically, sentiment analysis is performed using a natural language processing (NLP) library.

[0356] Step 5:

[0357] Based on the results of image analysis and sentiment analysis, the server obtains tourist information for specific landmarks and locations using external APIs (e.g., Google Places API, Yelp API). The input is the landmark's identification information and emotional state, and the output is tourist information (tourist attractions, restaurants, accommodations, and transportation). Specifically, the server sends an API request and stores the obtained data in an internal database.

[0358] Step 6:

[0359] The server generates an optimal travel schedule based on the acquired tourist destination information and the user's emotional state. The input is tourist destination information and the emotional state, and the output is a detailed travel schedule. Specifically, the server runs a schedule generation algorithm to create a schedule that takes into account the user's desired travel period and activity balance.

[0360] Step 7:

[0361] The server estimates the travel cost based on the generated travel schedule. The input is the travel schedule and the output is the cost estimate. Specifically, the server retrieves the cost data for each activity from the API and calculates the total cost.

[0362] Step 8:

[0363] The server compiles the travel schedule and cost estimates to generate a travel itinerary. The input is the schedule and cost estimate, and the output is the travel itinerary (in PDF or HTML format). Specifically, the server inserts the data into a format-defined template to create the final travel itinerary.

[0364] Step 9:

[0365] The device receives the generated travel bookmark from the server and displays it visually to the user. The input is the travel bookmark (PDF or HTML file) and the output is a visual display. Specifically, the device displays the bookmark using a PDF viewer or browser component.

[0366] Step 10:

[0367] The user checks the presented travel itinerary and, if necessary, sends a change request to the server through the terminal. The input is the user's confirmation feedback, and the output is the updated travel schedule. Specifically, the terminal sends the change request to the server again, and the server readjusts the schedule.

[0368] (Application example 2)

[0369] 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."

[0370] When creating travel schedules, there is a need to create optimal plans that take user emotions into consideration and then provide the user with a virtual experience using virtual reality technology. However, while current systems can perform image analysis and acquire travel information, they have difficulty analyzing user emotions and reflecting them in schedules or providing virtual experiences. This poses a challenge in that they are unable to provide sophisticated travel plans that respond to the individual needs and emotions of users.

[0371] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for acquiring tourist destination information based on the identified places and landmarks, means for analyzing the user's emotions, means for automatically generating a travel itinerary based on the results of the emotion analysis and the tourist destination information, means for estimating travel costs based on the travel schedule, means for generating a travel booklet including the travel schedule and cost estimates, and means for presenting the travel booklet to the user and providing a virtual experience using virtual reality technology. This makes it possible to create an optimal travel plan based on the user's emotions and to provide the plan as a virtual experience.

[0372] "User" means any person or entity that uses the present invention.

[0373] "Means for receiving an image" refers to a function or device that receives an image input by a user.

[0374] "Means for analyzing images to identify specific places or landmarks" refers to algorithms or software that analyze input images and recognize and identify specific places or landmarks within the images.

[0375] "Means for acquiring tourist attraction information" refers to a function or device that acquires information on related tourist attractions based on a specific location or landmark from an external database or API.

[0376] "Means for analyzing emotions" refers to algorithms or software that analyze users' emotions from input such as voice or text.

[0377] "Means for automatically generating travel schedules" refers to a function or device that automatically creates an optimal travel schedule based on acquired tourist destination information and analyzed emotion data.

[0378] "Means for estimating travel costs" refers to a function or device that calculates the total cost of a trip based on the generated travel schedule.

[0379] "Means for generating a travel guide" refers to a function or device that creates a travel guide to be provided to a user based on a travel schedule and cost estimate.

[0380] "Means for providing a virtual experience using virtual reality technology" refers to software or hardware for providing users with a virtual experience of a travel destination using virtual reality technology based on the generated travel guide.

[0381] System Configuration

[0382] This system performs emotion and image analysis based on user input, generates an optimal travel schedule, and provides a virtual experience of it. The main hardware and software configurations are as follows:

[0383] Hardware Configuration

[0384] 1. Terminal device: A device that can connect to the Internet, such as a smartphone, tablet, or PC.

[0385] 2. Server equipment: Servers with high-performance data processing and storage.

[0386] 3. VR headset: A device for providing a virtual reality experience, such as the Oculus Quest 2.

[0387] Software Configuration

[0388] 1. Image analysis library: Uses TensorFlow, OpenCV, etc. to analyze input images and recognize specific locations and landmarks.

[0389] 2. Sentiment Analysis Engine: Algorithms and models for analyzing user sentiment from speech and text.

[0390] 3. Tourist attraction information acquisition library: Obtains tourist attraction information using Google Places API, Yelp API, etc.

[0391] 4. VR simulation software: Tools for building VR environments, such as Unity.

[0392] Processing flow

[0393] 1. Uploading images on the device

[0394] The user uploads images of their proposed trips to the application using a terminal device, which then transmits the images to the server device.

[0395] 2. Server-side image and sentiment analysis

[0396] The server analyzes the submitted image using an image analysis library (TensorFlow, OpenCV, etc.) to identify major landmarks and place names. At the same time, it uses a sentiment analysis engine to analyze emotions from the user's voice and text input. For example, if a user uploads a photo of a mountain as a potential travel destination and enters the phrase "I want to relax," the server will analyze the emotion "relaxed."

[0397] 3. Obtaining tourist information and adjusting it based on emotions

[0398] Based on the analysis results, the server retrieves related tourist destination information using the Google Places API. It then generates a travel itinerary optimized for the user, reflecting the results of the sentiment analysis. For example, if the emotion "I want to relax" is analyzed, hot springs and relaxation spots will be added to the itinerary.

[0399] 4. Travel Schedule and Cost Estimate

[0400] Based on the generated travel schedule, the server estimates the travel costs for each activity and place visited, and then creates a travel booklet based on the schedule and cost estimates.

[0401] 5. Providing travel guides and VR experiences

[0402] The generated travel guide is then sent back to the user's device and presented to them. Furthermore, users can enjoy virtual travel experiences through the VR environment built using Unity. For example, a user planning to visit a hot spring resort can virtually experience the hot spring resort in a VR environment beforehand.

[0403] Examples and prompts

[0404] For example, if a user uploads an image of Arashiyama, Kyoto, and types "I want to relax":

[0405] 1. Image URL: https: / / example.com / arashiyama.jpg

[0406] 2. User Emotion: I want to relax

[0407] 3. Trip duration: 2 days

[0408] Using this information, the server retrieves tourist destination information and generates a travel itinerary based on the user's feelings, including, for example, a stroll through a bamboo forest on Day 1 and relaxation at a hot spring facility on Day 2. This itinerary is provided to the user as a PDF travel guidebook along with cost estimates, and it is also possible to have a virtual experience of Arashiyama using a VR headset.

[0409] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0410] Step 1:

[0411] The device displays an interface that allows the user to upload images of potential trips. The user uploads the images and clicks the "Upload Images" button. The input is an image file of the potential trip locations. The device then sends this image file to the specified server.

[0412] Step 2:

[0413] The server receives image files sent from the device. The input data is the image uploaded by the user. The server analyzes this image using an image analysis library (e.g., TensorFlow or OpenCV) to identify and distinguish key landmarks and place names. The output is the analysis results, which are the specific landmarks and place names.

[0414] Step 3:

[0415] The server retrieves tourist destination information based on the identified specific landmarks and place names. The input data is the image analysis result from step 2. A tourist destination information retrieval library (e.g., Google Places API) is used to collect related tourist destination information from an external database. The output is tourist destination information (tourist attractions, restaurants, accommodations, etc.).

[0416] Step 4:

[0417] The server receives the user's voice and text data acquired from the device to analyze the user's emotions. The input data is the user's voice and text. An emotion analysis engine is used to identify the user's current emotional state (e.g., excited, relaxed, excitement-seeking) from the content of the voice and text. The output is the user's emotional state.

[0418] Step 5:

[0419] The server automatically generates a travel schedule based on tourist destination information and the user's emotional state. The input data is tourist destination information and the user's emotional state. Using a generative AI model, an optimal schedule is created that takes into account the user's desired travel period and emotional state. The output is a travel schedule.

[0420] Step 6:

[0421] The server estimates the travel cost based on the generated travel schedule. The input data is the travel schedule. It uses an external API to obtain real-time pricing information such as transportation costs, accommodation costs, and meal costs, and calculates the accurate travel cost. The output is a cost estimate.

[0422] Step 7:

[0423] The server generates a travel guide based on the travel schedule and cost estimate. The input data are the travel schedule and cost estimate. The guide is generated in PDF or HTML format and sent to the terminal. The travel guide is obtained as the output.

[0424] Step 8:

[0425] The terminal receives the travel itinerary sent from the server and visually displays it to the user. The user can check the bookmark and send a change request if necessary. The input data is the generated travel itinerary, and the output is the user's confirmation status and change request.

[0426] Step 9:

[0427] The server receives the change request and re-adjusts and optimizes the travel schedule. The input data is the change request from the user. The generative AI model is used again to create an optimal schedule. The output is the re-adjusted travel schedule.

[0428] Step 10:

[0429] The server uses VR simulation software such as Unity to create a VR experience of the selected tourist spots. The input data is the tourist spot information from the travel itinerary. The server creates a VR environment and allows users to experience a virtual trip with a VR headset. The output is the VR content for the virtual experience.

[0430] Examples of prompts:

[0431] 1. Image URL: https: / / example.com / arashiyama.jpg

[0432] 2. User Emotion: I want to relax

[0433] 3. Trip duration: 2 days

[0434] This allows the optimal travel plan to be created based on the user's emotional state, and the plan can be experienced virtually in VR.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] [Second embodiment]

[0439] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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).

[0445] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] In the smart glasses 214, the 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.

[0450] 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."

[0451] User interface (terminal side)

[0452] The present invention begins with the user uploading images of their travel plans via a device. This device can be a smartphone, tablet, PC, or any other device with an internet connection. The user selects a photo or image of their travel plan and clicks the "Upload Images" button in the application. At this point, the device sends the image to the server.

[0453] Image analysis (server side)

[0454] The server receives the image sent from the device and begins image analysis. This analysis process uses an image recognition engine (e.g., TensorFlow, OpenCV). The server identifies key landmarks and place names in the image and extracts their location information and related data. Once the analysis results are obtained, the process proceeds to the next stage.

[0455] Examples:

[0456] When a user uploads a photo of Mount Fuji, the server uses an image analysis engine to recognize Mount Fuji and identify surrounding landmarks (e.g., the Fuji Five Lakes, Fuji-Q Highland, etc.).

[0457] Obtaining tourist information (server side)

[0458] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). The tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc.

[0459] Examples:

[0460] The server collects information about the Fuji Five Lakes and Fuji-Q Highland, and also obtains data on related accommodations and restaurants.

[0461] Travel schedule generation (server side)

[0462] Based on the collected tourist destination information, the server automatically generates a travel schedule. This schedule generation process takes into account the user's desired travel period, travel time, and time spent at the destinations. The generated schedule includes specific activities for each day.

[0463] Examples:

[0464] The server plans a three-day trip, with the first day visiting the Fuji Five Lakes, the second day visiting Fuji-Q Highland, and the third day visiting nearby hot springs.

[0465] Cost Estimate (Server Side)

[0466] Based on the travel itinerary, the server estimates the cost of the entire trip, including the sum of individual costs such as transportation, accommodation, meals, etc. It uses an external API to obtain real-time pricing information and provides an accurate estimate.

[0467] Travel itinerary generation (server side)

[0468] Finally, the server generates a "trip itinerary" that summarizes the trip schedule and cost estimates, which can be made easily accessible to users in PDF or HTML format.

[0469] Examples:

[0470] The final itinerary includes a schedule for each day, detailed information about the places visited and a breakdown of estimated costs, which users can download and refer to during their trip.

[0471] Displaying the results (terminal side)

[0472] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[0473] User confirmation and final adjustments

[0474] The user can review the presented itinerary and, if satisfied, proceed with the trip. If changes are needed, they can send a request to the server via the terminal and make the necessary adjustments.

[0475] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0476] The processing flow will be explained below.

[0477] Step 1:

[0478] The user uploads images of their proposed trip to their device.

[0479] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[0480] Step 2:

[0481] The device compresses the uploaded image and sends it to the server.

[0482] The device compresses the input image data and sends it to the server as an HTTP request, which includes the image data and necessary metadata (user ID, timestamp).

[0483] Step 3:

[0484] The server analyzes the received image.

[0485] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[0486] Step 4:

[0487] The server collects tourist destination information based on the identified landmarks.

[0488] Based on the identified landmarks and place names, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[0489] Step 5:

[0490] A travel schedule is automatically generated based on tourist destination information collected by the server.

[0491] Based on the acquired information, the server generates a schedule that matches the user's desired travel period, including tourist spots to visit, travel time, stay time, rest time, etc.

[0492] Step 6:

[0493] The server estimates the travel cost based on the travel schedule.

[0494] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[0495] Step 7:

[0496] The server generates the travel guide.

[0497] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[0498] Step 8:

[0499] The server transmits the generated travel guide to the terminal.

[0500] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[0501] Step 9:

[0502] The device displays the trip itinerary to the user.

[0503] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[0504] Step 10:

[0505] The user reviews the travel itinerary and makes the final decision.

[0506] The user can review the presented itinerary and, if satisfied, proceed with the travel plan. If changes are needed, they can send a request via the device and make the necessary adjustments.

[0507] Example 1

[0508] 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."

[0509] Planning a trip requires a wide range of tasks, such as gathering information on tourist spots, adjusting schedules, and estimating costs, placing a heavy burden on users. Additionally, it is difficult to select reliable information from the overwhelming amount of information available on the Internet, which makes planning time-consuming and stressful. Furthermore, the lack of tools that allow users to centrally manage travel schedules and costs makes it difficult for users to efficiently plan their trips.

[0510] 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.

[0511] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places or landmarks, means for acquiring location information based on the identified places or landmarks, means for automatically generating a travel plan based on the location information, means for estimating travel costs based on the travel plan, means for generating a guide including the travel plan and cost estimate, and means for presenting the guide to the user, thereby reducing the burden on the user and enabling efficient travel planning.

[0512] "User" refers to a person who uses the system to make travel plans.

[0513] "Means for accepting images" refers to the mechanism for receiving image files uploaded by users.

[0514] "Means for analyzing images to identify specific places and landmarks" refers to technology for recognizing input images and identifying specific places and landmarks present within the images.

[0515] "Means for obtaining location information" refers to the mechanism for obtaining information related to identified locations and landmarks from external databases or APIs.

[0516] "Means for automatically generating travel plans" refers to a system that automatically creates a travel schedule based on acquired location information, taking into account the user's desired period and means of transportation.

[0517] "Means for estimating travel costs" refers to a mechanism for calculating and totaling the costs required for each journey based on the generated travel plan.

[0518] "Means for generating guidance" refers to a mechanism for creating a document that integrates travel plans and cost estimates and presents them to the user.

[0519] "Presentation means" refers to a mechanism for visually displaying the generated guidance to the user.

[0520] The present invention is a system that aims to enable users to make travel plans efficiently and easily. An embodiment of the system of the present invention will be described below.

[0521] User interface (terminal side)

[0522] Users upload images of potential travel destinations to the system using their own devices. These devices include devices with internet connectivity, such as smartphones, tablets, and PCs. Users select photos or images of potential travel destinations and click the "Upload Images" button in the application. This action causes the device to send the image files to the server.

[0523] Examples:

[0524] When a user wants to upload a photo of Mt. Fuji, he or she selects a photo of Mt. Fuji from the gallery of the smartphone and clicks the upload button.

[0525] Image analysis (server side)

[0526] The server receives the image file sent from the device and saves it in the appropriate directory. It then loads the saved image file and uses an image recognition engine such as TensorFlow or OpenCV to identify key landmarks and place names in the image. The server extracts the location information and related data of the recognized landmarks and proceeds to the next step.

[0527] Examples:

[0528] The server receives a photo of Mt. Fuji and uses an image analysis engine to recognize Mt. Fuji and identify surrounding landmarks (e.g., Fuji Five Lakes, Fuji-Q Highland).

[0529] Obtaining tourist information (server side)

[0530] Based on the landmarks identified by image analysis, the server collects related tourist destination information using external APIs (e.g., Google Places API, Yelp API), including tourist attractions, restaurants, accommodations, and transportation options.

[0531] Examples:

[0532] The server uses the Google Places API to obtain information about the Fuji Five Lakes and Fuji-Q Highland, as well as data on related accommodations and restaurants.

[0533] Travel schedule generation (server side)

[0534] Based on the collected tourist destination information, the server automatically generates a travel schedule, taking into consideration information provided by the user, such as the desired travel period, travel time, and length of stay at the destinations.

[0535] Examples:

[0536] The server creates a three-day travel plan, with the first day planned to be spent sightseeing at the Fuji Five Lakes, the second day to enjoy Fuji-Q Highland, and the third day to visit nearby hot spring resorts.

[0537] Cost Estimate (Server Side)

[0538] Based on the generated itinerary, the server retrieves real-time pricing information using an external API and estimates the cost of the entire trip, including transportation, accommodation, and meals.

[0539] Travel itinerary generation (server side)

[0540] The server compiles the generated travel schedule and cost estimates and generates a "travel guide" in PDF or HTML format for easy access by the user.

[0541] Examples:

[0542] The final itinerary includes a detailed schedule for each day, information about tourist attractions, and a breakdown of estimated costs, which users can download and refer to during their trip.

[0543] Displaying the results (terminal side)

[0544] The generated travel bookmark is sent from the server to the device, which receives it and visually displays it to the user. The user can then review the bookmark and submit change requests if necessary.

[0545] Examples:

[0546] The travel bookmark is displayed on the user's terminal, and the user checks the contents of the bookmark.

[0547] Examples of prompt statements

[0548] Here are some example prompts to input to a generative AI model:

[0549] "Please upload photos of Mt. Fuji and create a three-day itinerary. Please include information on attractions, accommodations, and restaurants, as well as a cost estimate."

[0550] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0551] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0552] Step 1:

[0553] The user selects an image of a potential travel destination and clicks the "Upload Image" button in the application on the device. The input is the selected image file, and the output is the image file sent to the server.

[0554] Specific behavior:

[0555] The user selects a photo of Mt. Fuji from their smartphone's gallery and presses the "Upload Image" button in the application.

[0556] Step 2:

[0557] The server receives the image file sent from the terminal. The image file arrives at the server as input, and the image file is saved in the appropriate directory on the server as output.

[0558] Specific behavior:

[0559] The server receives the photo of Mt. Fuji and saves it in the " / uploaded_images" directory.

[0560] Step 3:

[0561] The server loads the saved image files and performs image analysis using image recognition engines such as TensorFlow and OpenCV. The saved image files are used as input, and the output is information about identified landmarks and places.

[0562] Specific behavior:

[0563] The server loads a photo of Mount Fuji and uses TensorFlow to recognize Mount Fuji in the image and extract its location information.

[0564] Step 4:

[0565] The server uses the Google Places API and Yelp API to retrieve information related to the identified landmarks and places. The input is the location information of the identified landmarks, and the output is the collection of information about related tourist attractions.

[0566] Specific behavior:

[0567] The server uses the Google Places API to collect information about the Fuji Five Lakes and Fuji-Q Highland.

[0568] Step 5:

[0569] The server automatically generates a travel schedule using the collected tourist destination information based on the user's desired travel information (desired travel period, travel time, length of stay, etc.) The input is tourist destination information and the user's desired information, and the output is a specific travel schedule.

[0570] Specific behavior:

[0571] The server takes into consideration the user's desired three-day period and creates a schedule that visits the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a hot spring resort on the third day.

[0572] Step 6:

[0573] The server estimates the cost of the trip based on the generated itinerary, which involves retrieving real-time pricing information using an external API and adding up the individual costs. The input is the itinerary, and the output is the estimated cost of the entire trip.

[0574] Specific behavior:

[0575] The server tallies up accommodation, transportation, meal costs, etc., and calculates the total cost of the entire trip.

[0576] Step 7:

[0577] The server integrates the travel schedule and cost estimate information to generate a "travel guide" in a user-friendly format (PDF or HTML). The input is the travel schedule and cost estimate, and the output is a travel guide.

[0578] Specific behavior:

[0579] The server compiles the schedule and cost estimates and generates a detailed travel guide in PDF format.

[0580] Step 8:

[0581] The server sends the generated itinerary to the user's terminal. The input is the generated itinerary, and the output is the itinerary sent to the terminal.

[0582] Specific behavior:

[0583] The server sends a PDF travel guide to the user's smartphone.

[0584] Step 9:

[0585] The terminal visually displays the received travel itinerary to the user. The input is the received travel itinerary, and the output is the visual display to the user.

[0586] Specific behavior:

[0587] The travel bookmark will be displayed on the smartphone screen and the user will be able to check it.

[0588] Step 10:

[0589] The user checks the displayed travel bookmark and sends a change request to the server if necessary. The input is the displayed travel bookmark, and the output can be a change request.

[0590] Specific behavior:

[0591] The user presses the "Request Changes" button in the application to send any complaints about the bookmark to the server.

[0592] (Application example 1)

[0593] 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."

[0594] In the modern tourism industry, users need to collect and adjust a lot of information to plan a trip. This process is time-consuming and extremely difficult, especially for users who have little information about the place they are visiting for the first time. Furthermore, online tourism information and services cannot fully replace the actual travel experience, and there are limited ways to simulate a trip. To solve these issues, a system is needed that not only allows users to easily plan their trip, but also provides a tourism experience in a virtual space.

[0595] 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.

[0596] In this invention, the server includes means for accepting images input by a user, means for analyzing the images to identify specific places and landmarks, means for acquiring tourist attraction information based on the identified places and landmarks, means for automatically generating a travel itinerary based on the tourist attraction information, means for estimating travel costs based on the travel schedule, means for generating a travel guidebook including the travel schedule and cost estimate, means for presenting the travel guidebook to the user, and means for providing a tourist experience in a virtual space based on the tourist attraction information. This allows users to efficiently and easily plan their trip and further enables them to experience tourist attractions in the virtual space before their actual trip.

[0597] The "means for accepting user-entered images" refers to a function that allows a user to upload images of potential travel destinations through the interface.

[0598] The "means for analyzing the image to identify specific locations and landmarks" refers to a technology for processing the image received on the server side and identifying major landmarks and place names using an image analysis engine.

[0599] The "means for acquiring tourist attraction information based on the identified locations and landmarks" is a function for collecting tourist attraction information related to landmarks identified by image analysis from an external API, etc.

[0600] The "means for automatically generating a travel schedule based on the tourist attraction information" is a technology that automatically generates a travel schedule that meets the user's wishes based on the collected tourist attraction information.

[0601] The "means for estimating travel expenses based on the travel schedule" is a function for calculating the total cost of transportation, accommodation, meals, etc. based on the generated travel schedule.

[0602] The "means for generating a travel guide including the travel schedule and cost estimate" refers to a technology for creating a document including the travel schedule and cost estimate in PDF or HTML format.

[0603] The "means for presenting the travel itinerary to the user" is a function for transmitting the generated travel itinerary to the user's terminal and visually displaying it.

[0604] "Means for providing a tourist experience in a virtual space based on the tourist destination information" refers to technology that enables users to have an immersive tourist experience in a virtual space based on the collected tourist destination information.

[0605] This invention is a virtual tourist guide system that allows users to upload images of potential travel destinations and provides sightseeing experiences in a virtual space based on the uploaded images. This system is implemented using devices such as smart glasses and a server.

[0606] Hardware and software usage

[0607] Hardware:

[0608] Smart glasses: A device that allows users to upload images and visually confirm their virtual tourism experience.

[0609] Server: A central computing resource that analyzes images, collects tourist information, generates travel schedules, estimates costs, and generates travel guides.

[0610] software:

[0611] TensorFlow: A deep learning framework used to analyze images.

[0612] OpenCV: Used as an image processing library.

[0613] Google Places API: An external API used to collect tourist destination information.

[0614] Data processing and data calculation processing

[0615] 1. User uploads an image:

[0616] Users use the smart glasses interface to upload images of potential travel destinations, which are then sent to a server.

[0617] 2. Image Analysis:

[0618] The server analyzes the received image using TensorFlow and OpenCV to identify major landmarks and place names, and proceeds to the next step based on the analysis results.

[0619] 3. Obtaining tourist information:

[0620] The server uses the Google Places API to retrieve tourist information based on the identified landmarks, collecting detailed data on tourist attractions, restaurants, accommodations, etc.

[0621] 4. Generate travel schedule:

[0622] The server automatically generates a travel schedule based on the collected tourist destination information, taking into consideration the user's desired travel period and travel time.

[0623] 5. Cost Estimate:

[0624] The server estimates the travel costs, including transportation, accommodation, and meals, based on the generated itinerary, using real-time pricing information from an external API.

[0625] 6. Travel bookmark generation:

[0626] The server generates a travel itinerary that includes the travel schedule and cost estimates, and creates it in PDF and HTML formats.

[0627] 7. Providing tourism experiences:

[0628] The server provides users with a sightseeing experience in a virtual space based on tourist destination information and travel bookmarks, which are projected onto the smart glasses.

[0629] 8. Presentation of results:

[0630] The generated travel itinerary and virtual sightseeing experience are displayed on the smart glasses' display, where users can review it and submit change requests if necessary.

[0631] Adding specific examples

[0632] For example, if a user uploads a photo of Mt. Fuji, the system works as follows:

[0633] A user uploads a photo of Mount Fuji.

[0634] The server uses TensorFlow to recognize Mt. Fuji and uses the Google Places API to collect information about tourist spots around Mt. Fuji (e.g., Fuji Five Lakes, Fuji-Q Highland).

[0635] The server generates a three-day travel schedule, planning a visit to the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a visit to nearby hot springs on the third day.

[0636] Estimate costs based on your travel schedule and generate a travel guide.

[0637] The generated travel guide is displayed on smart glasses, allowing users to experience tourist spots in a virtual space.

[0638] Prompt Sentence Examples

[0639] "Upload photos of Mt. Fuji, gather information on nearby tourist attractions, and create a three-day travel plan."

[0640] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0641] Step 1:

[0642] The user uses the smart glasses interface to upload an image of a potential travel destination, with the image of the user's choice as input, and the device then sends the image to the server.

[0643] Step 2:

[0644] The server receives images sent from the device. Using the received image file as input, it performs image analysis using TensorFlow and OpenCV. Specifically, the server extracts features within the image and identifies major landmarks and place names. The identified landmarks and place names are output as the analysis results.

[0645] Step 3:

[0646] The server uses the results of image analysis to collect tourist information related to the identified landmarks and place names. Using the analysis results as input, the server calls the Google Places API to retrieve tourist information. Specifically, the server sends API requests to collect data on tourist attractions, restaurants, accommodations, etc. This information is the output.

[0647] Step 4:

[0648] The server automatically generates a travel schedule based on the collected tourist destination information. Using the tourist destination information as input, it creates a specific daily plan taking into account the user's desired travel period, travel time, and time spent at each destination. The output of this process is a detailed travel schedule.

[0649] Step 5:

[0650] The server estimates the cost of the trip based on the generated itinerary. It uses the itinerary as input and sums up the individual costs such as transportation, accommodation, and meals. It uses an external API to get real-time pricing information and provides an accurate estimate. The output is the total cost and a breakdown of the individual costs.

[0651] Step 6:

[0652] The server compiles the travel schedule and cost estimates to generate a travel itinerary. It uses the travel schedule and cost estimates as input and creates a travel itinerary in PDF or HTML format. Specifically, it generates a document that includes the schedule for each day, detailed information about the places visited, and a breakdown of costs. The output is the completed travel itinerary.

[0653] Step 7:

[0654] The server sends the generated itinerary to the terminal and presents it visually to the user. It uses the generated itinerary as input and sends it to the terminal. The terminal receives it and displays it on the smart glasses display. The user reviews it and, if satisfied, can proceed with the trip. It is also possible to send change requests if necessary.

[0655] Step 8:

[0656] The server provides a sightseeing experience in a virtual space based on tourist destination information. It uses the collected tourist destination information as input and creates a virtual tour using virtual reality technology. Specifically, it displays 3D models and images so that users can experience the tourist destination realistically through smart glasses. The output is a sightseeing experience in a virtual space.

[0657] 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.

[0658] User interface (terminal side)

[0659] The present invention begins with the step where a user uploads images of potential travel destinations via a terminal and uses an emotion engine to analyze the user's emotions. The terminal can be a smartphone, tablet, PC, or other device that can connect to the Internet. The user selects a photo or image of a potential travel destination and clicks the "Upload Image" button in the application. At this point, the terminal sends the image to the server, and the emotion engine simultaneously analyzes the user's emotions.

[0660] Image analysis and emotion analysis (server side)

[0661] The server receives the image sent from the device and begins image analysis. Image analysis libraries (e.g., TensorFlow, OpenCV) are used to identify key landmarks and place names in the image. An emotion engine also analyzes the user's voice and text input to identify their current emotional state (e.g., excited, relaxed, excitement-seeking).

[0662] Examples:

[0663] If a user uploads a photo of Mount Fuji, the server will use an image analysis engine to recognize the mountain, and an emotion engine will analyze that the user has a "spirit of adventure."

[0664] Obtaining tourist destination information and adjusting it based on emotions (server side)

[0665] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). Tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc. Based on the information from the emotion engine, the server selects and adjusts tourist attractions and activities that match the user's current emotional state.

[0666] Examples:

[0667] The server collects information on tourist spots around Mount Fuji and suggests hiking trails and outdoor activities to adventurous users.

[0668] Travel schedule generation and sentiment-based optimization (server side)

[0669] Based on the collected tourist destination information and the results of the emotion engine, the server automatically generates a travel schedule, taking into account the user's desired travel period, travel time, stay time, and emotional state to create an optimized schedule.

[0670] Examples:

[0671] The server plans a three-day trip, with the first day being canoeing on the Fuji Five Lakes, the second day climbing Mount Fuji, and the third day relaxing at a hot spring resort.

[0672] Cost Estimate (Server Side)

[0673] The server estimates the total cost of the trip based on the travel itinerary, calculates individual costs such as transportation, accommodation, and meals, and uses external APIs to obtain real-time pricing information to provide an accurate estimate.

[0674] Travel itinerary generation (server side)

[0675] Finally, the server generates a "travel bookmark" that summarizes the trip itinerary and cost estimates, in PDF or HTML format for easy user access, and adjusts the bookmark content based on the results of the emotion engine.

[0676] Examples:

[0677] The final itinerary includes a schedule for each day, detailed information about the places to visit, a breakdown of expected costs, and highlights special activities for the more adventurous user.

[0678] Displaying the results (terminal side)

[0679] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[0680] User confirmation and final adjustments

[0681] Users can review the presented travel plan and, if satisfied, proceed with their travel plans. Because it includes suggestions based on the results of the emotion engine, users can enjoy travel plans that are even more tailored to their needs. If changes are needed, the device sends a request to the server again, and the necessary adjustments are made.

[0682] In this way, the system of the present invention enables users to easily and effectively plan their trips while taking their emotions into consideration, thereby improving the user's travel experience.

[0683] The processing flow will be explained below.

[0684] Step 1:

[0685] The user uploads images of their proposed trip to their device.

[0686] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[0687] Step 2:

[0688] The device sends the uploaded images and the user's voice and text input to the server.

[0689] The device compresses the input image data and the user's voice and text data, and sends them to the server as an HTTP request. This request includes the image data, voice data, text data, and necessary metadata (user ID, timestamp).

[0690] Step 3:

[0691] The server analyzes the received image.

[0692] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[0693] Step 4:

[0694] The server analyzes the user's emotions.

[0695] The server uses an emotion analysis engine to analyze the user's voice or text input to determine the user's current emotional state, using speech recognition and text analysis algorithms.

[0696] Examples:

[0697] If a user uploads an image of Mount Fuji and enters the text "I want to have an adventure," the server will recognize Mount Fuji through image analysis and detect the "spirit of adventure" through emotional analysis.

[0698] Step 5:

[0699] The server collects tourist destination information based on the identified landmarks and the user's emotions.

[0700] Based on the identified landmarks, place names, and user sentiment information, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[0701] Step 6:

[0702] The server generates a travel schedule adjusted based on the emotions.

[0703] The server takes into account the acquired tourist destination information and the user's emotional state to generate a schedule that matches the user's desired travel period. This schedule includes tourist destinations to visit, travel time, stay time, rest time, etc.

[0704] Examples:

[0705] For adventurous users, the server will suggest schedules that include mountain climbing and adventure sports.

[0706] Step 7:

[0707] The server estimates the travel cost based on the travel schedule.

[0708] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[0709] Step 8:

[0710] The server generates the travel guide.

[0711] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[0712] Examples:

[0713] The travel guide details hiking and outdoor activities and breakdowns of expected expenses for the more adventurous user.

[0714] Step 9:

[0715] The server transmits the generated travel guide to the terminal.

[0716] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[0717] Step 10:

[0718] The device displays the trip itinerary to the user.

[0719] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[0720] Step 11:

[0721] The user reviews the travel itinerary and makes the final decision.

[0722] The user checks the presented itinerary and, if satisfied, proceeds with the travel plan. If changes are needed, the user sends a request to the server via the device and makes the necessary adjustments.

[0723] Example 2

[0724] 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."

[0725] Conventional travel planning systems often provide simple tourist information without considering the user's emotional state, making it difficult to create travel plans that meet individual needs. Furthermore, they require the user to manually search multiple sites to gather information, and they also require excessive effort in scheduling and estimating costs. Given these circumstances, there is a need for a method to automatically create travel plans that take the user's emotions into account, allowing for efficient and accurate travel planning.

[0726] 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.

[0727] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for analyzing the user's emotions, means for acquiring tourist destination information based on the identified places and landmarks and the user's emotions, means for automatically generating a travel itinerary based on the tourist destination information and emotion analysis, means for estimating travel costs based on the travel schedule, means for generating a travel itinerary including the travel schedule and cost estimate, and means for presenting the travel itinerary to the user. This enables automatic generation and optimization of a travel plan according to the user's emotional state.

[0728] "User" refers to an individual or organization that uses this system to plan a trip.

[0729] "Device" refers to a device that can connect to the Internet, such as a smartphone, tablet, or PC.

[0730] "Images" refers to photographs and graphic data uploaded by users via their devices.

[0731] "Server" refers to a central processing unit that performs image analysis, emotion analysis, acquisition of tourist destination information, generation of travel schedules, cost estimates, and generation of travel guides.

[0732] "Image analysis" refers to the process of identifying specific places or landmarks from uploaded images.

[0733] "Emotion analysis" refers to the process of identifying a user's emotions based on the voice and text data entered by the user.

[0734] "Tourist destination information" refers to data about tourist attractions, restaurants, accommodations, transportation, etc. related to a specific location or landmark.

[0735] "Travel schedule" refers to travel itineraries and activity plans automatically generated based on tourist destination information and the user's emotional state.

[0736] "Cost Estimate" refers to the total travel cost calculated based on the generated travel itinerary.

[0737] "Travel Guide" means a travel itinerary provided to a User, including a travel schedule and cost estimate.

[0738] This invention provides a system that automatically generates travel plans that take users' emotions into consideration and provides optimal travel schedules. Specifically, the system allows users to upload images via their devices, and generates travel plans that meet the user's needs by analyzing the images and the user's emotions. This system uses the following hardware and software:

[0739] Hardware and software used

[0740] Device: Refers to a device that can connect to the internet, such as a smartphone, tablet, or PC. Users use these devices to input images, text, voice, etc.

[0741] Server: A central processing unit used to execute programs that perform the following processes:

[0742] Image analysis libraries (e.g. TensorFlow, OpenCV)

[0743] Sentiment Analysis Engine

[0744] External APIs (e.g. Google Places API, Yelp API)

[0745] Program processing

[0746] The device sends the user-uploaded images and necessary text and audio data to the server. The server analyzes the received images using image analysis libraries such as TensorFlow and OpenCV to identify specific locations and landmarks. It then uses a sentiment analysis engine to analyze emotions from the user's input text and audio.

[0747] The server uses the Google Places API and Yelp API to collect tourist information based on the identified landmarks and the analyzed emotional state. This tourist information includes tourist attractions, restaurants, accommodations, and transportation options. Based on the collected information and the results of the emotional analysis, the server automatically generates an optimized travel itinerary. Furthermore, it estimates travel costs based on the generated schedule and generates the final travel itinerary in PDF or HTML format.

[0748] Adding specific examples

[0749] Examples:

[0750] When a user uploads a photo of Mount Fuji, the server analyzes the photo to recognize the mountain and identifies emotions such as "adventure" and "excitement" through a sentiment analysis engine. It then uses the Google Places API to retrieve information on hiking trails, outdoor activities, accommodations, and other information around Mount Fuji. Finally, the server creates a three-day itinerary, including canoeing around the Fuji Five Lakes on the first day, climbing Mount Fuji on the second day, and relaxing at a hot spring resort on the third day. This includes travel and accommodation costs, and a detailed travel itinerary is generated.

[0751] Prompt Sentence Examples

[0752] "Upload an image of Mount Fuji, perform sentiment analysis, generate a three-day travel itinerary suitable for adventurous users, and create a travel bookmark with cost estimates."

[0753] In this way, the system of the present invention can make travel plans with high accuracy and efficiency while taking into account the user's emotions.

[0754] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0755] Step 1:

[0756] The user selects an image or photo of a potential travel destination and clicks the "Upload Image" button in the application. The device receives the image file and the user's emotion as input and sends it to the server. The specific operation involves implementing the image file selection and upload functions using programming languages ​​such as JavaScript and Python.

[0757] Step 2:

[0758] The device receives image data and additional emotion data (text or voice) input by the user and sends it to the server. The input data is image and text or voice data, which is packetized and sent to the server. Specifically, the device performs communication processing to send data to the server via an HTTP request.

[0759] Step 3:

[0760] The server analyzes the image data received from the device using image analysis libraries such as TensorFlow and OpenCV. The input for image analysis is image data, and the output is identification information for specific locations and landmarks. The server identifies key landmarks based on the analyzed information. Specifically, it calls the TensorFlow API and processes the image data.

[0761] Step 4:

[0762] The server analyzes the text or voice data sent by the user using a sentiment analysis engine. The input is text or voice data, and the output is the user's emotional state (e.g., excited, relaxed, adventurous). Specifically, sentiment analysis is performed using a natural language processing (NLP) library.

[0763] Step 5:

[0764] Based on the results of image analysis and sentiment analysis, the server obtains tourist information for specific landmarks and locations using external APIs (e.g., Google Places API, Yelp API). The input is the landmark's identification information and emotional state, and the output is tourist information (tourist attractions, restaurants, accommodations, and transportation). Specifically, the server sends an API request and stores the obtained data in an internal database.

[0765] Step 6:

[0766] The server generates an optimal travel schedule based on the acquired tourist destination information and the user's emotional state. The input is tourist destination information and the emotional state, and the output is a detailed travel schedule. Specifically, the server runs a schedule generation algorithm to create a schedule that takes into account the user's desired travel period and activity balance.

[0767] Step 7:

[0768] The server estimates the travel cost based on the generated travel schedule. The input is the travel schedule and the output is the cost estimate. Specifically, the server retrieves the cost data for each activity from the API and calculates the total cost.

[0769] Step 8:

[0770] The server compiles the travel schedule and cost estimates to generate a travel itinerary. The input is the schedule and cost estimate, and the output is the travel itinerary (in PDF or HTML format). Specifically, the server inserts the data into a format-defined template to create the final travel itinerary.

[0771] Step 9:

[0772] The device receives the generated travel bookmark from the server and displays it visually to the user. The input is the travel bookmark (PDF or HTML file) and the output is a visual display. Specifically, the device displays the bookmark using a PDF viewer or browser component.

[0773] Step 10:

[0774] The user checks the presented travel itinerary and, if necessary, sends a change request to the server through the terminal. The input is the user's confirmation feedback, and the output is the updated travel schedule. Specifically, the terminal sends the change request to the server again, and the server readjusts the schedule.

[0775] (Application example 2)

[0776] 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."

[0777] When creating travel schedules, there is a need to create optimal plans that take user emotions into consideration and then provide the user with a virtual experience using virtual reality technology. However, while current systems can perform image analysis and acquire travel information, they have difficulty analyzing user emotions and reflecting them in schedules or providing virtual experiences. This poses a challenge in that they are unable to provide sophisticated travel plans that respond to the individual needs and emotions of users.

[0778] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for acquiring tourist destination information based on the identified places and landmarks, means for analyzing the user's emotions, means for automatically generating a travel itinerary based on the results of the emotion analysis and the tourist destination information, means for estimating travel costs based on the travel schedule, means for generating a travel booklet including the travel schedule and cost estimates, and means for presenting the travel booklet to the user and providing a virtual experience using virtual reality technology. This makes it possible to create an optimal travel plan based on the user's emotions and to provide the plan as a virtual experience.

[0779] "User" means any person or entity that uses the present invention.

[0780] "Means for receiving an image" refers to a function or device that receives an image input by a user.

[0781] "Means for analyzing images to identify specific places or landmarks" refers to algorithms or software that analyze input images and recognize and identify specific places or landmarks within the images.

[0782] "Means for acquiring tourist attraction information" refers to a function or device that acquires information on related tourist attractions based on a specific location or landmark from an external database or API.

[0783] "Means for analyzing emotions" refers to algorithms or software that analyze users' emotions from input such as voice or text.

[0784] "Means for automatically generating travel schedules" refers to a function or device that automatically creates an optimal travel schedule based on acquired tourist destination information and analyzed emotion data.

[0785] "Means for estimating travel costs" refers to a function or device that calculates the total cost of a trip based on the generated travel schedule.

[0786] "Means for generating a travel guide" refers to a function or device that creates a travel guide to be provided to a user based on a travel schedule and cost estimate.

[0787] "Means for providing a virtual experience using virtual reality technology" refers to software or hardware for providing users with a virtual experience of a travel destination using virtual reality technology based on the generated travel guide.

[0788] System Configuration

[0789] This system performs emotion and image analysis based on user input, generates an optimal travel schedule, and provides a virtual experience of it. The main hardware and software configurations are as follows:

[0790] Hardware Configuration

[0791] 1. Terminal device: A device that can connect to the Internet, such as a smartphone, tablet, or PC.

[0792] 2. Server equipment: Servers with high-performance data processing and storage.

[0793] 3. VR headset: A device for providing a virtual reality experience, such as the Oculus Quest 2.

[0794] Software Configuration

[0795] 1. Image analysis library: Uses TensorFlow, OpenCV, etc. to analyze input images and recognize specific locations and landmarks.

[0796] 2. Sentiment Analysis Engine: Algorithms and models for analyzing user sentiment from speech and text.

[0797] 3. Tourist attraction information acquisition library: Obtains tourist attraction information using Google Places API, Yelp API, etc.

[0798] 4. VR simulation software: Tools for building VR environments, such as Unity.

[0799] Processing flow

[0800] 1. Uploading images on the device

[0801] The user uploads images of their proposed trips to the application using a terminal device, which then transmits the images to the server device.

[0802] 2. Server-side image and sentiment analysis

[0803] The server analyzes the submitted image using an image analysis library (TensorFlow, OpenCV, etc.) to identify major landmarks and place names. At the same time, it uses a sentiment analysis engine to analyze emotions from the user's voice and text input. For example, if a user uploads a photo of a mountain as a potential travel destination and enters the phrase "I want to relax," the server will analyze the emotion "relaxed."

[0804] 3. Obtaining tourist information and adjusting it based on emotions

[0805] Based on the analysis results, the server retrieves related tourist destination information using the Google Places API. It then generates a travel itinerary optimized for the user, reflecting the results of the sentiment analysis. For example, if the emotion "I want to relax" is analyzed, hot springs and relaxation spots will be added to the itinerary.

[0806] 4. Travel Schedule and Cost Estimate

[0807] Based on the generated travel schedule, the server estimates the travel costs for each activity and place visited, and then creates a travel booklet based on the schedule and cost estimates.

[0808] 5. Providing travel guides and VR experiences

[0809] The generated travel guide is then sent back to the user's device and presented to them. Furthermore, users can enjoy virtual travel experiences through the VR environment built using Unity. For example, a user planning to visit a hot spring resort can virtually experience the hot spring resort in a VR environment beforehand.

[0810] Examples and prompts

[0811] For example, if a user uploads an image of Arashiyama, Kyoto, and types "I want to relax":

[0812] 1. Image URL: https: / / example.com / arashiyama.jpg

[0813] 2. User Emotion: I want to relax

[0814] 3. Trip duration: 2 days

[0815] Using this information, the server retrieves tourist destination information and generates a travel itinerary based on the user's feelings, including, for example, a stroll through a bamboo forest on Day 1 and relaxation at a hot spring facility on Day 2. This itinerary is provided to the user as a PDF travel guidebook along with cost estimates, and it is also possible to have a virtual experience of Arashiyama using a VR headset.

[0816] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0817] Step 1:

[0818] The device displays an interface that allows the user to upload images of potential trips. The user uploads the images and clicks the "Upload Images" button. The input is an image file of the potential trip locations. The device then sends this image file to the specified server.

[0819] Step 2:

[0820] The server receives image files sent from the device. The input data is the image uploaded by the user. The server analyzes this image using an image analysis library (e.g., TensorFlow or OpenCV) to identify and distinguish key landmarks and place names. The output is the analysis results, which are the specific landmarks and place names.

[0821] Step 3:

[0822] The server retrieves tourist destination information based on the identified specific landmarks and place names. The input data is the image analysis result from step 2. A tourist destination information retrieval library (e.g., Google Places API) is used to collect related tourist destination information from an external database. The output is tourist destination information (tourist attractions, restaurants, accommodations, etc.).

[0823] Step 4:

[0824] The server receives the user's voice and text data acquired from the device to analyze the user's emotions. The input data is the user's voice and text. An emotion analysis engine is used to identify the user's current emotional state (e.g., excited, relaxed, excitement-seeking) from the content of the voice and text. The output is the user's emotional state.

[0825] Step 5:

[0826] The server automatically generates a travel schedule based on tourist destination information and the user's emotional state. The input data is tourist destination information and the user's emotional state. Using a generative AI model, an optimal schedule is created that takes into account the user's desired travel period and emotional state. The output is a travel schedule.

[0827] Step 6:

[0828] The server estimates the travel cost based on the generated travel schedule. The input data is the travel schedule. It uses an external API to obtain real-time pricing information such as transportation costs, accommodation costs, and meal costs, and calculates the accurate travel cost. The output is a cost estimate.

[0829] Step 7:

[0830] The server generates a travel guide based on the travel schedule and cost estimate. The input data are the travel schedule and cost estimate. The guide is generated in PDF or HTML format and sent to the terminal. The travel guide is obtained as the output.

[0831] Step 8:

[0832] The terminal receives the travel itinerary sent from the server and visually displays it to the user. The user can check the bookmark and send a change request if necessary. The input data is the generated travel itinerary, and the output is the user's confirmation status and change request.

[0833] Step 9:

[0834] The server receives the change request and re-adjusts and optimizes the travel schedule. The input data is the change request from the user. The generative AI model is used again to create an optimal schedule. The output is the re-adjusted travel schedule.

[0835] Step 10:

[0836] The server uses VR simulation software such as Unity to create a VR experience of the selected tourist spots. The input data is the tourist spot information from the travel itinerary. The server creates a VR environment and allows users to experience a virtual trip with a VR headset. The output is the VR content for the virtual experience.

[0837] Examples of prompts:

[0838] 1. Image URL: https: / / example.com / arashiyama.jpg

[0839] 2. User Emotion: I want to relax

[0840] 3. Trip duration: 2 days

[0841] This allows the optimal travel plan to be created based on the user's emotional state, and the plan can be experienced virtually in VR.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] [Third embodiment]

[0846] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0847] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0848] 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).

[0849] 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.

[0850] 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.

[0851] 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).

[0852] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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."

[0858] User interface (terminal side)

[0859] The present invention begins with the user uploading images of their travel plans via a device. This device can be a smartphone, tablet, PC, or any other device with an internet connection. The user selects a photo or image of their travel plan and clicks the "Upload Images" button in the application. At this point, the device sends the image to the server.

[0860] Image analysis (server side)

[0861] The server receives the image sent from the device and begins image analysis. This analysis process uses an image recognition engine (e.g., TensorFlow, OpenCV). The server identifies key landmarks and place names in the image and extracts their location information and related data. Once the analysis results are obtained, the process proceeds to the next stage.

[0862] Examples:

[0863] When a user uploads a photo of Mount Fuji, the server uses an image analysis engine to recognize Mount Fuji and identify surrounding landmarks (e.g., the Fuji Five Lakes, Fuji-Q Highland, etc.).

[0864] Obtaining tourist information (server side)

[0865] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). The tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc.

[0866] Examples:

[0867] The server collects information about the Fuji Five Lakes and Fuji-Q Highland, and also obtains data on related accommodations and restaurants.

[0868] Travel schedule generation (server side)

[0869] Based on the collected tourist destination information, the server automatically generates a travel schedule. This schedule generation process takes into account the user's desired travel period, travel time, and time spent at the destinations. The generated schedule includes specific activities for each day.

[0870] Examples:

[0871] The server plans a three-day trip, with the first day visiting the Fuji Five Lakes, the second day visiting Fuji-Q Highland, and the third day visiting nearby hot springs.

[0872] Cost Estimate (Server Side)

[0873] Based on the travel itinerary, the server estimates the cost of the entire trip, including the sum of individual costs such as transportation, accommodation, meals, etc. It uses an external API to obtain real-time pricing information and provides an accurate estimate.

[0874] Travel itinerary generation (server side)

[0875] Finally, the server generates a "trip itinerary" that summarizes the trip schedule and cost estimates, which can be made easily accessible to users in PDF or HTML format.

[0876] Examples:

[0877] The final itinerary includes a schedule for each day, detailed information about the places visited and a breakdown of estimated costs, which users can download and refer to during their trip.

[0878] Displaying the results (terminal side)

[0879] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[0880] User confirmation and final adjustments

[0881] The user can review the presented itinerary and, if satisfied, proceed with the trip. If changes are needed, they can send a request to the server via the terminal and make the necessary adjustments.

[0882] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0883] The processing flow will be explained below.

[0884] Step 1:

[0885] The user uploads images of their proposed trip to their device.

[0886] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[0887] Step 2:

[0888] The device compresses the uploaded image and sends it to the server.

[0889] The device compresses the input image data and sends it to the server as an HTTP request, which includes the image data and necessary metadata (user ID, timestamp).

[0890] Step 3:

[0891] The server analyzes the received image.

[0892] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[0893] Step 4:

[0894] The server collects tourist destination information based on the identified landmarks.

[0895] Based on the identified landmarks and place names, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[0896] Step 5:

[0897] A travel schedule is automatically generated based on tourist destination information collected by the server.

[0898] Based on the acquired information, the server generates a schedule that matches the user's desired travel period, including tourist spots to visit, travel time, stay time, rest time, etc.

[0899] Step 6:

[0900] The server estimates the travel cost based on the travel schedule.

[0901] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[0902] Step 7:

[0903] The server generates the travel guide.

[0904] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[0905] Step 8:

[0906] The server transmits the generated travel guide to the terminal.

[0907] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[0908] Step 9:

[0909] The device displays the trip itinerary to the user.

[0910] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[0911] Step 10:

[0912] The user reviews the travel itinerary and makes the final decision.

[0913] The user can review the presented itinerary and, if satisfied, proceed with the travel plan. If changes are needed, they can send a request via the device and make the necessary adjustments.

[0914] Example 1

[0915] 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."

[0916] Planning a trip requires a wide range of tasks, such as gathering information on tourist spots, adjusting schedules, and estimating costs, placing a heavy burden on users. Additionally, it is difficult to select reliable information from the overwhelming amount of information available on the Internet, which makes planning time-consuming and stressful. Furthermore, the lack of tools that allow users to centrally manage travel schedules and costs makes it difficult for users to efficiently plan their trips.

[0917] 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.

[0918] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places or landmarks, means for acquiring location information based on the identified places or landmarks, means for automatically generating a travel plan based on the location information, means for estimating travel costs based on the travel plan, means for generating a guide including the travel plan and cost estimate, and means for presenting the guide to the user, thereby reducing the burden on the user and enabling efficient travel planning.

[0919] "User" refers to a person who uses the system to make travel plans.

[0920] "Means for accepting images" refers to the mechanism for receiving image files uploaded by users.

[0921] "Means for analyzing images to identify specific places and landmarks" refers to technology for recognizing input images and identifying specific places and landmarks present within the images.

[0922] "Means for obtaining location information" refers to the mechanism for obtaining information related to identified locations and landmarks from external databases or APIs.

[0923] "Means for automatically generating travel plans" refers to a system that automatically creates a travel schedule based on acquired location information, taking into account the user's desired period and means of transportation.

[0924] "Means for estimating travel costs" refers to a mechanism for calculating and totaling the costs required for each journey based on the generated travel plan.

[0925] "Means for generating guidance" refers to a mechanism for creating a document that integrates travel plans and cost estimates and presents them to the user.

[0926] "Presentation means" refers to a mechanism for visually displaying the generated guidance to the user.

[0927] The present invention is a system that aims to enable users to make travel plans efficiently and easily. An embodiment of the system of the present invention will be described below.

[0928] User interface (terminal side)

[0929] Users upload images of potential travel destinations to the system using their own devices. These devices include devices with internet connectivity, such as smartphones, tablets, and PCs. Users select photos or images of potential travel destinations and click the "Upload Images" button in the application. This action causes the device to send the image files to the server.

[0930] Examples:

[0931] When a user wants to upload a photo of Mt. Fuji, he or she selects a photo of Mt. Fuji from the gallery of the smartphone and clicks the upload button.

[0932] Image analysis (server side)

[0933] The server receives the image file sent from the device and saves it in the appropriate directory. It then loads the saved image file and uses an image recognition engine such as TensorFlow or OpenCV to identify key landmarks and place names in the image. The server extracts the location information and related data of the recognized landmarks and proceeds to the next step.

[0934] Examples:

[0935] The server receives a photo of Mt. Fuji and uses an image analysis engine to recognize Mt. Fuji and identify surrounding landmarks (e.g., Fuji Five Lakes, Fuji-Q Highland).

[0936] Obtaining tourist information (server side)

[0937] Based on the landmarks identified by image analysis, the server collects related tourist destination information using external APIs (e.g., Google Places API, Yelp API), including tourist attractions, restaurants, accommodations, and transportation options.

[0938] Examples:

[0939] The server uses the Google Places API to obtain information about the Fuji Five Lakes and Fuji-Q Highland, as well as data on related accommodations and restaurants.

[0940] Travel schedule generation (server side)

[0941] Based on the collected tourist destination information, the server automatically generates a travel schedule, taking into consideration information provided by the user, such as the desired travel period, travel time, and length of stay at the destinations.

[0942] Examples:

[0943] The server creates a three-day travel plan, with the first day planned to be spent sightseeing at the Fuji Five Lakes, the second day to enjoy Fuji-Q Highland, and the third day to visit nearby hot spring resorts.

[0944] Cost Estimate (Server Side)

[0945] Based on the generated itinerary, the server retrieves real-time pricing information using an external API and estimates the cost of the entire trip, including transportation, accommodation, and meals.

[0946] Travel itinerary generation (server side)

[0947] The server compiles the generated travel schedule and cost estimates and generates a "travel guide" in PDF or HTML format for easy access by the user.

[0948] Examples:

[0949] The final itinerary includes a detailed schedule for each day, information about tourist attractions, and a breakdown of estimated costs, which users can download and refer to during their trip.

[0950] Displaying the results (terminal side)

[0951] The generated travel bookmark is sent from the server to the device, which receives it and visually displays it to the user. The user can then review the bookmark and submit change requests if necessary.

[0952] Examples:

[0953] The travel bookmark is displayed on the user's terminal, and the user checks the contents of the bookmark.

[0954] Examples of prompt statements

[0955] Here are some example prompts to input to a generative AI model:

[0956] "Please upload photos of Mt. Fuji and create a three-day itinerary. Please include information on attractions, accommodations, and restaurants, as well as a cost estimate."

[0957] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[0958] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0959] Step 1:

[0960] The user selects an image of a potential travel destination and clicks the "Upload Image" button in the application on the device. The input is the selected image file, and the output is the image file sent to the server.

[0961] Specific behavior:

[0962] The user selects a photo of Mt. Fuji from their smartphone's gallery and presses the "Upload Image" button in the application.

[0963] Step 2:

[0964] The server receives the image file sent from the terminal. The image file arrives at the server as input, and the image file is saved in the appropriate directory on the server as output.

[0965] Specific behavior:

[0966] The server receives the photo of Mt. Fuji and saves it in the " / uploaded_images" directory.

[0967] Step 3:

[0968] The server loads the saved image files and performs image analysis using image recognition engines such as TensorFlow and OpenCV. The saved image files are used as input, and the output is information about identified landmarks and places.

[0969] Specific behavior:

[0970] The server loads a photo of Mount Fuji and uses TensorFlow to recognize Mount Fuji in the image and extract its location information.

[0971] Step 4:

[0972] The server uses the Google Places API and Yelp API to retrieve information related to the identified landmarks and places. The input is the location information of the identified landmarks, and the output is the collection of information about related tourist attractions.

[0973] Specific behavior:

[0974] The server uses the Google Places API to collect information about the Fuji Five Lakes and Fuji-Q Highland.

[0975] Step 5:

[0976] The server automatically generates a travel schedule using the collected tourist destination information based on the user's desired travel information (desired travel period, travel time, length of stay, etc.) The input is tourist destination information and the user's desired information, and the output is a specific travel schedule.

[0977] Specific behavior:

[0978] The server takes into consideration the user's desired three-day period and creates a schedule that visits the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a hot spring resort on the third day.

[0979] Step 6:

[0980] The server estimates the cost of the trip based on the generated itinerary, which involves retrieving real-time pricing information using an external API and adding up the individual costs. The input is the itinerary, and the output is the estimated cost of the entire trip.

[0981] Specific behavior:

[0982] The server tallies up accommodation, transportation, meal costs, etc., and calculates the total cost of the entire trip.

[0983] Step 7:

[0984] The server integrates the travel schedule and cost estimate information to generate a "travel guide" in a user-friendly format (PDF or HTML). The input is the travel schedule and cost estimate, and the output is a travel guide.

[0985] Specific behavior:

[0986] The server compiles the schedule and cost estimates and generates a detailed travel guide in PDF format.

[0987] Step 8:

[0988] The server sends the generated itinerary to the user's terminal. The input is the generated itinerary, and the output is the itinerary sent to the terminal.

[0989] Specific behavior:

[0990] The server sends a PDF travel guide to the user's smartphone.

[0991] Step 9:

[0992] The terminal visually displays the received travel itinerary to the user. The input is the received travel itinerary, and the output is the visual display to the user.

[0993] Specific behavior:

[0994] The travel bookmark will be displayed on the smartphone screen and the user will be able to check it.

[0995] Step 10:

[0996] The user checks the displayed travel bookmark and sends a change request to the server if necessary. The input is the displayed travel bookmark, and the output can be a change request.

[0997] Specific behavior:

[0998] The user presses the "Request Changes" button in the application to send any complaints about the bookmark to the server.

[0999] (Application example 1)

[1000] 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."

[1001] In the modern tourism industry, users need to collect and adjust a lot of information to plan a trip. This process is time-consuming and extremely difficult, especially for users who have little information about the place they are visiting for the first time. Furthermore, online tourism information and services cannot fully replace the actual travel experience, and there are limited ways to simulate a trip. To solve these issues, a system is needed that not only allows users to easily plan their trip, but also provides a tourism experience in a virtual space.

[1002] 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.

[1003] In this invention, the server includes means for accepting images input by a user, means for analyzing the images to identify specific places and landmarks, means for acquiring tourist attraction information based on the identified places and landmarks, means for automatically generating a travel itinerary based on the tourist attraction information, means for estimating travel costs based on the travel schedule, means for generating a travel guidebook including the travel schedule and cost estimate, means for presenting the travel guidebook to the user, and means for providing a tourist experience in a virtual space based on the tourist attraction information. This allows users to efficiently and easily plan their trip and further enables them to experience tourist attractions in the virtual space before their actual trip.

[1004] The "means for accepting user-entered images" refers to a function that allows a user to upload images of potential travel destinations through the interface.

[1005] The "means for analyzing the image to identify specific locations and landmarks" refers to a technology for processing the image received on the server side and identifying major landmarks and place names using an image analysis engine.

[1006] The "means for acquiring tourist attraction information based on the identified locations and landmarks" is a function for collecting tourist attraction information related to landmarks identified by image analysis from an external API, etc.

[1007] The "means for automatically generating a travel schedule based on the tourist attraction information" is a technology that automatically generates a travel schedule that meets the user's wishes based on the collected tourist attraction information.

[1008] The "means for estimating travel expenses based on the travel schedule" is a function for calculating the total cost of transportation, accommodation, meals, etc. based on the generated travel schedule.

[1009] The "means for generating a travel guide including the travel schedule and cost estimate" refers to a technology for creating a document including the travel schedule and cost estimate in PDF or HTML format.

[1010] The "means for presenting the travel itinerary to the user" is a function for transmitting the generated travel itinerary to the user's terminal and visually displaying it.

[1011] "Means for providing a tourist experience in a virtual space based on the tourist destination information" refers to technology that enables users to have an immersive tourist experience in a virtual space based on the collected tourist destination information.

[1012] This invention is a virtual tourist guide system that allows users to upload images of potential travel destinations and provides sightseeing experiences in a virtual space based on the uploaded images. This system is implemented using devices such as smart glasses and a server.

[1013] Hardware and software usage

[1014] Hardware:

[1015] Smart glasses: A device that allows users to upload images and visually confirm their virtual tourism experience.

[1016] Server: A central computing resource that analyzes images, collects tourist information, generates travel schedules, estimates costs, and generates travel guides.

[1017] software:

[1018] TensorFlow: A deep learning framework used to analyze images.

[1019] OpenCV: Used as an image processing library.

[1020] Google Places API: An external API used to collect tourist destination information.

[1021] Data processing and data calculation processing

[1022] 1. User uploads an image:

[1023] Users use the smart glasses interface to upload images of potential travel destinations, which are then sent to a server.

[1024] 2. Image Analysis:

[1025] The server analyzes the received image using TensorFlow and OpenCV to identify major landmarks and place names, and proceeds to the next step based on the analysis results.

[1026] 3. Obtaining tourist information:

[1027] The server uses the Google Places API to retrieve tourist information based on the identified landmarks, collecting detailed data on tourist attractions, restaurants, accommodations, etc.

[1028] 4. Generate travel schedule:

[1029] The server automatically generates a travel schedule based on the collected tourist destination information, taking into consideration the user's desired travel period and travel time.

[1030] 5. Cost Estimate:

[1031] The server estimates the travel costs, including transportation, accommodation, and meals, based on the generated itinerary, using real-time pricing information from an external API.

[1032] 6. Travel bookmark generation:

[1033] The server generates a travel itinerary that includes the travel schedule and cost estimates, and creates it in PDF and HTML formats.

[1034] 7. Providing tourism experiences:

[1035] The server provides users with a sightseeing experience in a virtual space based on tourist destination information and travel bookmarks, which are projected onto the smart glasses.

[1036] 8. Presentation of results:

[1037] The generated travel itinerary and virtual sightseeing experience are displayed on the smart glasses' display, where users can review it and submit change requests if necessary.

[1038] Adding specific examples

[1039] For example, if a user uploads a photo of Mt. Fuji, the system works as follows:

[1040] A user uploads a photo of Mount Fuji.

[1041] The server uses TensorFlow to recognize Mt. Fuji and uses the Google Places API to collect information about tourist spots around Mt. Fuji (e.g., Fuji Five Lakes, Fuji-Q Highland).

[1042] The server generates a three-day travel schedule, planning a visit to the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a visit to nearby hot springs on the third day.

[1043] Estimate costs based on your travel schedule and generate a travel guide.

[1044] The generated travel guide is displayed on smart glasses, allowing users to experience tourist spots in a virtual space.

[1045] Prompt Sentence Examples

[1046] "Upload photos of Mt. Fuji, gather information on nearby tourist attractions, and create a three-day travel plan."

[1047] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1048] Step 1:

[1049] The user uses the smart glasses interface to upload an image of a potential travel destination, with the image of the user's choice as input, and the device then sends the image to the server.

[1050] Step 2:

[1051] The server receives images sent from the device. Using the received image file as input, it performs image analysis using TensorFlow and OpenCV. Specifically, the server extracts features within the image and identifies major landmarks and place names. The identified landmarks and place names are output as the analysis results.

[1052] Step 3:

[1053] The server uses the results of image analysis to collect tourist information related to the identified landmarks and place names. Using the analysis results as input, the server calls the Google Places API to retrieve tourist information. Specifically, the server sends API requests to collect data on tourist attractions, restaurants, accommodations, etc. This information is the output.

[1054] Step 4:

[1055] The server automatically generates a travel schedule based on the collected tourist destination information. Using the tourist destination information as input, it creates a specific daily plan taking into account the user's desired travel period, travel time, and time spent at each destination. The output of this process is a detailed travel schedule.

[1056] Step 5:

[1057] The server estimates the cost of the trip based on the generated itinerary. It uses the itinerary as input and sums up the individual costs such as transportation, accommodation, and meals. It uses an external API to get real-time pricing information and provides an accurate estimate. The output is the total cost and a breakdown of the individual costs.

[1058] Step 6:

[1059] The server compiles the travel schedule and cost estimates to generate a travel itinerary. It uses the travel schedule and cost estimates as input and creates a travel itinerary in PDF or HTML format. Specifically, it generates a document that includes the schedule for each day, detailed information about the places visited, and a breakdown of costs. The output is the completed travel itinerary.

[1060] Step 7:

[1061] The server sends the generated itinerary to the terminal and presents it visually to the user. It uses the generated itinerary as input and sends it to the terminal. The terminal receives it and displays it on the smart glasses display. The user reviews it and, if satisfied, can proceed with the trip. It is also possible to send change requests if necessary.

[1062] Step 8:

[1063] The server provides a sightseeing experience in a virtual space based on tourist destination information. It uses the collected tourist destination information as input and creates a virtual tour using virtual reality technology. Specifically, it displays 3D models and images so that users can experience the tourist destination realistically through smart glasses. The output is a sightseeing experience in a virtual space.

[1064] 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.

[1065] User interface (terminal side)

[1066] The present invention begins with the step where a user uploads images of potential travel destinations via a terminal and uses an emotion engine to analyze the user's emotions. The terminal can be a smartphone, tablet, PC, or other device that can connect to the Internet. The user selects a photo or image of a potential travel destination and clicks the "Upload Image" button in the application. At this point, the terminal sends the image to the server, and the emotion engine simultaneously analyzes the user's emotions.

[1067] Image analysis and emotion analysis (server side)

[1068] The server receives the image sent from the device and begins image analysis. Image analysis libraries (e.g., TensorFlow, OpenCV) are used to identify key landmarks and place names in the image. An emotion engine also analyzes the user's voice and text input to identify their current emotional state (e.g., excited, relaxed, excitement-seeking).

[1069] Examples:

[1070] If a user uploads a photo of Mount Fuji, the server will use an image analysis engine to recognize the mountain, and an emotion engine will analyze that the user has a "spirit of adventure."

[1071] Obtaining tourist destination information and adjusting it based on emotions (server side)

[1072] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). Tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc. Based on the information from the emotion engine, the server selects and adjusts tourist attractions and activities that match the user's current emotional state.

[1073] Examples:

[1074] The server collects information on tourist spots around Mount Fuji and suggests hiking trails and outdoor activities to adventurous users.

[1075] Travel schedule generation and sentiment-based optimization (server side)

[1076] Based on the collected tourist destination information and the results of the emotion engine, the server automatically generates a travel schedule, taking into account the user's desired travel period, travel time, stay time, and emotional state to create an optimized schedule.

[1077] Examples:

[1078] The server plans a three-day trip, with the first day being canoeing on the Fuji Five Lakes, the second day climbing Mount Fuji, and the third day relaxing at a hot spring resort.

[1079] Cost Estimate (Server Side)

[1080] The server estimates the total cost of the trip based on the travel itinerary, calculates individual costs such as transportation, accommodation, and meals, and uses external APIs to obtain real-time pricing information to provide an accurate estimate.

[1081] Travel itinerary generation (server side)

[1082] Finally, the server generates a "travel bookmark" that summarizes the trip itinerary and cost estimates, in PDF or HTML format for easy user access, and adjusts the bookmark content based on the results of the emotion engine.

[1083] Examples:

[1084] The final itinerary includes a schedule for each day, detailed information about the places to visit, a breakdown of expected costs, and highlights special activities for the more adventurous user.

[1085] Displaying the results (terminal side)

[1086] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[1087] User confirmation and final adjustments

[1088] Users can review the presented travel plan and, if satisfied, proceed with their travel plans. Because it includes suggestions based on the results of the emotion engine, users can enjoy travel plans that are even more tailored to their needs. If changes are needed, the device sends a request to the server again, and the necessary adjustments are made.

[1089] In this way, the system of the present invention enables users to easily and effectively plan their trips while taking their emotions into consideration, thereby improving the user's travel experience.

[1090] The processing flow will be explained below.

[1091] Step 1:

[1092] The user uploads images of their proposed trip to their device.

[1093] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[1094] Step 2:

[1095] The device sends the uploaded images and the user's voice and text input to the server.

[1096] The device compresses the input image data and the user's voice and text data, and sends them to the server as an HTTP request. This request includes the image data, voice data, text data, and necessary metadata (user ID, timestamp).

[1097] Step 3:

[1098] The server analyzes the received image.

[1099] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[1100] Step 4:

[1101] The server analyzes the user's emotions.

[1102] The server uses an emotion analysis engine to analyze the user's voice or text input to determine the user's current emotional state, using speech recognition and text analysis algorithms.

[1103] Examples:

[1104] If a user uploads an image of Mount Fuji and enters the text "I want to have an adventure," the server will recognize Mount Fuji through image analysis and detect the "spirit of adventure" through emotional analysis.

[1105] Step 5:

[1106] The server collects tourist destination information based on the identified landmarks and the user's emotions.

[1107] Based on the identified landmarks, place names, and user sentiment information, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[1108] Step 6:

[1109] The server generates a travel schedule adjusted based on the emotions.

[1110] The server takes into account the acquired tourist destination information and the user's emotional state to generate a schedule that matches the user's desired travel period. This schedule includes tourist destinations to visit, travel time, stay time, rest time, etc.

[1111] Examples:

[1112] For adventurous users, the server will suggest schedules that include mountain climbing and adventure sports.

[1113] Step 7:

[1114] The server estimates the travel cost based on the travel schedule.

[1115] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[1116] Step 8:

[1117] The server generates the travel guide.

[1118] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[1119] Examples:

[1120] The travel guide details hiking and outdoor activities and breakdowns of expected expenses for the more adventurous user.

[1121] Step 9:

[1122] The server transmits the generated travel guide to the terminal.

[1123] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[1124] Step 10:

[1125] The device displays the trip itinerary to the user.

[1126] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[1127] Step 11:

[1128] The user reviews the travel itinerary and makes the final decision.

[1129] The user checks the presented itinerary and, if satisfied, proceeds with the travel plan. If changes are needed, the user sends a request to the server via the device and makes the necessary adjustments.

[1130] Example 2

[1131] 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."

[1132] Conventional travel planning systems often provide simple tourist information without considering the user's emotional state, making it difficult to create travel plans that meet individual needs. Furthermore, they require the user to manually search multiple sites to gather information, and they also require excessive effort in scheduling and estimating costs. Given these circumstances, there is a need for a method to automatically create travel plans that take the user's emotions into account, allowing for efficient and accurate travel planning.

[1133] 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.

[1134] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for analyzing the user's emotions, means for acquiring tourist destination information based on the identified places and landmarks and the user's emotions, means for automatically generating a travel itinerary based on the tourist destination information and emotion analysis, means for estimating travel costs based on the travel schedule, means for generating a travel itinerary including the travel schedule and cost estimate, and means for presenting the travel itinerary to the user. This enables automatic generation and optimization of a travel plan according to the user's emotional state.

[1135] "User" refers to an individual or organization that uses this system to plan a trip.

[1136] "Device" refers to a device that can connect to the Internet, such as a smartphone, tablet, or PC.

[1137] "Images" refers to photographs and graphic data uploaded by users via their devices.

[1138] "Server" refers to a central processing unit that performs image analysis, emotion analysis, acquisition of tourist destination information, generation of travel schedules, cost estimates, and generation of travel guides.

[1139] "Image analysis" refers to the process of identifying specific places or landmarks from uploaded images.

[1140] "Emotion analysis" refers to the process of identifying a user's emotions based on the voice and text data entered by the user.

[1141] "Tourist destination information" refers to data about tourist attractions, restaurants, accommodations, transportation, etc. related to a specific location or landmark.

[1142] "Travel schedule" refers to travel itineraries and activity plans automatically generated based on tourist destination information and the user's emotional state.

[1143] "Cost Estimate" refers to the total travel cost calculated based on the generated travel itinerary.

[1144] "Travel Guide" means a travel itinerary provided to a User, including a travel schedule and cost estimate.

[1145] This invention provides a system that automatically generates travel plans that take users' emotions into consideration and provides optimal travel schedules. Specifically, the system allows users to upload images via their devices, and generates travel plans that meet the user's needs by analyzing the images and the user's emotions. This system uses the following hardware and software:

[1146] Hardware and software used

[1147] Device: Refers to a device that can connect to the internet, such as a smartphone, tablet, or PC. Users use these devices to input images, text, voice, etc.

[1148] Server: A central processing unit used to execute programs that perform the following processes:

[1149] Image analysis libraries (e.g. TensorFlow, OpenCV)

[1150] Sentiment Analysis Engine

[1151] External APIs (e.g. Google Places API, Yelp API)

[1152] Program processing

[1153] The device sends the user-uploaded images and necessary text and audio data to the server. The server analyzes the received images using image analysis libraries such as TensorFlow and OpenCV to identify specific locations and landmarks. It then uses a sentiment analysis engine to analyze emotions from the user's input text and audio.

[1154] The server uses the Google Places API and Yelp API to collect tourist information based on the identified landmarks and the analyzed emotional state. This tourist information includes tourist attractions, restaurants, accommodations, and transportation options. Based on the collected information and the results of the emotional analysis, the server automatically generates an optimized travel itinerary. Furthermore, it estimates travel costs based on the generated schedule and generates the final travel itinerary in PDF or HTML format.

[1155] Adding specific examples

[1156] Examples:

[1157] When a user uploads a photo of Mount Fuji, the server analyzes the photo to recognize the mountain and identifies emotions such as "adventure" and "excitement" through a sentiment analysis engine. It then uses the Google Places API to retrieve information on hiking trails, outdoor activities, accommodations, and other information around Mount Fuji. Finally, the server creates a three-day itinerary, including canoeing around the Fuji Five Lakes on the first day, climbing Mount Fuji on the second day, and relaxing at a hot spring resort on the third day. This includes travel and accommodation costs, and a detailed travel itinerary is generated.

[1158] Prompt Sentence Examples

[1159] "Upload an image of Mount Fuji, perform sentiment analysis, generate a three-day travel itinerary suitable for adventurous users, and create a travel bookmark with cost estimates."

[1160] In this way, the system of the present invention can make travel plans with high accuracy and efficiency while taking into account the user's emotions.

[1161] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1162] Step 1:

[1163] The user selects an image or photo of a potential travel destination and clicks the "Upload Image" button in the application. The device receives the image file and the user's emotion as input and sends it to the server. The specific operation involves implementing the image file selection and upload functions using programming languages ​​such as JavaScript and Python.

[1164] Step 2:

[1165] The device receives image data and additional emotion data (text or voice) input by the user and sends it to the server. The input data is image and text or voice data, which is packetized and sent to the server. Specifically, the device performs communication processing to send data to the server via an HTTP request.

[1166] Step 3:

[1167] The server analyzes the image data received from the device using image analysis libraries such as TensorFlow and OpenCV. The input for image analysis is image data, and the output is identification information for specific locations and landmarks. The server identifies key landmarks based on the analyzed information. Specifically, it calls the TensorFlow API and processes the image data.

[1168] Step 4:

[1169] The server analyzes the text or voice data sent by the user using a sentiment analysis engine. The input is text or voice data, and the output is the user's emotional state (e.g., excited, relaxed, adventurous). Specifically, sentiment analysis is performed using a natural language processing (NLP) library.

[1170] Step 5:

[1171] Based on the results of image analysis and sentiment analysis, the server obtains tourist information for specific landmarks and locations using external APIs (e.g., Google Places API, Yelp API). The input is the landmark's identification information and emotional state, and the output is tourist information (tourist attractions, restaurants, accommodations, and transportation). Specifically, the server sends an API request and stores the obtained data in an internal database.

[1172] Step 6:

[1173] The server generates an optimal travel schedule based on the acquired tourist destination information and the user's emotional state. The input is tourist destination information and the emotional state, and the output is a detailed travel schedule. Specifically, the server runs a schedule generation algorithm to create a schedule that takes into account the user's desired travel period and activity balance.

[1174] Step 7:

[1175] The server estimates the travel cost based on the generated travel schedule. The input is the travel schedule and the output is the cost estimate. Specifically, the server retrieves the cost data for each activity from the API and calculates the total cost.

[1176] Step 8:

[1177] The server compiles the travel schedule and cost estimates to generate a travel itinerary. The input is the schedule and cost estimate, and the output is the travel itinerary (in PDF or HTML format). Specifically, the server inserts the data into a format-defined template to create the final travel itinerary.

[1178] Step 9:

[1179] The device receives the generated travel bookmark from the server and displays it visually to the user. The input is the travel bookmark (PDF or HTML file) and the output is a visual display. Specifically, the device displays the bookmark using a PDF viewer or browser component.

[1180] Step 10:

[1181] The user checks the presented travel itinerary and, if necessary, sends a change request to the server through the terminal. The input is the user's confirmation feedback, and the output is the updated travel schedule. Specifically, the terminal sends the change request to the server again, and the server readjusts the schedule.

[1182] (Application example 2)

[1183] 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."

[1184] When creating travel schedules, there is a need to create optimal plans that take user emotions into consideration and then provide the user with a virtual experience using virtual reality technology. However, while current systems can perform image analysis and acquire travel information, they have difficulty analyzing user emotions and reflecting them in schedules or providing virtual experiences. This poses a challenge in that they are unable to provide sophisticated travel plans that respond to the individual needs and emotions of users.

[1185] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for acquiring tourist destination information based on the identified places and landmarks, means for analyzing the user's emotions, means for automatically generating a travel itinerary based on the results of the emotion analysis and the tourist destination information, means for estimating travel costs based on the travel schedule, means for generating a travel booklet including the travel schedule and cost estimates, and means for presenting the travel booklet to the user and providing a virtual experience using virtual reality technology. This makes it possible to create an optimal travel plan based on the user's emotions and to provide the plan as a virtual experience.

[1186] "User" means any person or entity that uses the present invention.

[1187] "Means for receiving an image" refers to a function or device that receives an image input by a user.

[1188] "Means for analyzing images to identify specific places or landmarks" refers to algorithms or software that analyze input images and recognize and identify specific places or landmarks within the images.

[1189] "Means for acquiring tourist attraction information" refers to a function or device that acquires information on related tourist attractions based on a specific location or landmark from an external database or API.

[1190] "Means for analyzing emotions" refers to algorithms or software that analyze users' emotions from input such as voice or text.

[1191] "Means for automatically generating travel schedules" refers to a function or device that automatically creates an optimal travel schedule based on acquired tourist destination information and analyzed emotion data.

[1192] "Means for estimating travel costs" refers to a function or device that calculates the total cost of a trip based on the generated travel schedule.

[1193] "Means for generating a travel guide" refers to a function or device that creates a travel guide to be provided to a user based on a travel schedule and cost estimate.

[1194] "Means for providing a virtual experience using virtual reality technology" refers to software or hardware for providing users with a virtual experience of a travel destination using virtual reality technology based on the generated travel guide.

[1195] System Configuration

[1196] This system performs emotion and image analysis based on user input, generates an optimal travel schedule, and provides a virtual experience of it. The main hardware and software configurations are as follows:

[1197] Hardware Configuration

[1198] 1. Terminal device: A device that can connect to the Internet, such as a smartphone, tablet, or PC.

[1199] 2. Server equipment: Servers with high-performance data processing and storage.

[1200] 3. VR headset: A device for providing a virtual reality experience, such as the Oculus Quest 2.

[1201] Software Configuration

[1202] 1. Image analysis library: Uses TensorFlow, OpenCV, etc. to analyze input images and recognize specific locations and landmarks.

[1203] 2. Sentiment Analysis Engine: Algorithms and models for analyzing user sentiment from speech and text.

[1204] 3. Tourist attraction information acquisition library: Obtains tourist attraction information using Google Places API, Yelp API, etc.

[1205] 4. VR simulation software: Tools for building VR environments, such as Unity.

[1206] Processing flow

[1207] 1. Uploading images on the device

[1208] The user uploads images of their proposed trips to the application using a terminal device, which then transmits the images to the server device.

[1209] 2. Server-side image and sentiment analysis

[1210] The server analyzes the submitted image using an image analysis library (TensorFlow, OpenCV, etc.) to identify major landmarks and place names. At the same time, it uses a sentiment analysis engine to analyze emotions from the user's voice and text input. For example, if a user uploads a photo of a mountain as a potential travel destination and enters the phrase "I want to relax," the server will analyze the emotion "relaxed."

[1211] 3. Obtaining tourist information and adjusting it based on emotions

[1212] Based on the analysis results, the server retrieves related tourist destination information using the Google Places API. It then generates a travel itinerary optimized for the user, reflecting the results of the sentiment analysis. For example, if the emotion "I want to relax" is analyzed, hot springs and relaxation spots will be added to the itinerary.

[1213] 4. Travel Schedule and Cost Estimate

[1214] Based on the generated travel schedule, the server estimates the travel costs for each activity and place visited, and then creates a travel booklet based on the schedule and cost estimates.

[1215] 5. Providing travel guides and VR experiences

[1216] The generated travel guide is then sent back to the user's device and presented to them. Furthermore, users can enjoy virtual travel experiences through the VR environment built using Unity. For example, a user planning to visit a hot spring resort can virtually experience the hot spring resort in a VR environment beforehand.

[1217] Examples and prompts

[1218] For example, if a user uploads an image of Arashiyama, Kyoto, and types "I want to relax":

[1219] 1. Image URL: https: / / example.com / arashiyama.jpg

[1220] 2. User Emotion: I want to relax

[1221] 3. Trip duration: 2 days

[1222] Using this information, the server retrieves tourist destination information and generates a travel itinerary based on the user's feelings, including, for example, a stroll through a bamboo forest on Day 1 and relaxation at a hot spring facility on Day 2. This itinerary is provided to the user as a PDF travel guidebook along with cost estimates, and it is also possible to have a virtual experience of Arashiyama using a VR headset.

[1223] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1224] Step 1:

[1225] The device displays an interface that allows the user to upload images of potential trips. The user uploads the images and clicks the "Upload Images" button. The input is an image file of the potential trip locations. The device then sends this image file to the specified server.

[1226] Step 2:

[1227] The server receives image files sent from the device. The input data is the image uploaded by the user. The server analyzes this image using an image analysis library (e.g., TensorFlow or OpenCV) to identify and distinguish key landmarks and place names. The output is the analysis results, which are the specific landmarks and place names.

[1228] Step 3:

[1229] The server retrieves tourist destination information based on the identified specific landmarks and place names. The input data is the image analysis result from step 2. A tourist destination information retrieval library (e.g., Google Places API) is used to collect related tourist destination information from an external database. The output is tourist destination information (tourist attractions, restaurants, accommodations, etc.).

[1230] Step 4:

[1231] The server receives the user's voice and text data acquired from the device to analyze the user's emotions. The input data is the user's voice and text. An emotion analysis engine is used to identify the user's current emotional state (e.g., excited, relaxed, excitement-seeking) from the content of the voice and text. The output is the user's emotional state.

[1232] Step 5:

[1233] The server automatically generates a travel schedule based on tourist destination information and the user's emotional state. The input data is tourist destination information and the user's emotional state. Using a generative AI model, an optimal schedule is created that takes into account the user's desired travel period and emotional state. The output is a travel schedule.

[1234] Step 6:

[1235] The server estimates the travel cost based on the generated travel schedule. The input data is the travel schedule. It uses an external API to obtain real-time pricing information such as transportation costs, accommodation costs, and meal costs, and calculates the accurate travel cost. The output is a cost estimate.

[1236] Step 7:

[1237] The server generates a travel guide based on the travel schedule and cost estimate. The input data are the travel schedule and cost estimate. The guide is generated in PDF or HTML format and sent to the terminal. The travel guide is obtained as the output.

[1238] Step 8:

[1239] The terminal receives the travel itinerary sent from the server and visually displays it to the user. The user can check the bookmark and send a change request if necessary. The input data is the generated travel itinerary, and the output is the user's confirmation status and change request.

[1240] Step 9:

[1241] The server receives the change request and re-adjusts and optimizes the travel schedule. The input data is the change request from the user. The generative AI model is used again to create an optimal schedule. The output is the re-adjusted travel schedule.

[1242] Step 10:

[1243] The server uses VR simulation software such as Unity to create a VR experience of the selected tourist spots. The input data is the tourist spot information from the travel itinerary. The server creates a VR environment and allows users to experience a virtual trip with a VR headset. The output is the VR content for the virtual experience.

[1244] Examples of prompts:

[1245] 1. Image URL: https: / / example.com / arashiyama.jpg

[1246] 2. User Emotion: I want to relax

[1247] 3. Trip duration: 2 days

[1248] This allows the optimal travel plan to be created based on the user's emotional state, and the plan can be experienced virtually in VR.

[1249] 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.

[1250] 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.

[1251] 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.

[1252] [Fourth embodiment]

[1253] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1254] 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.

[1255] 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).

[1256] 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.

[1257] 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.

[1258] 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).

[1259] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1260] 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.

[1261] 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.

[1262] 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.

[1263] 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.

[1264] 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.

[1265] 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."

[1266] User interface (terminal side)

[1267] The present invention begins with the user uploading images of their travel plans via a device. This device can be a smartphone, tablet, PC, or any other device with an internet connection. The user selects a photo or image of their travel plan and clicks the "Upload Images" button in the application. At this point, the device sends the image to the server.

[1268] Image analysis (server side)

[1269] The server receives the image sent from the device and begins image analysis. This analysis process uses an image recognition engine (e.g., TensorFlow, OpenCV). The server identifies key landmarks and place names in the image and extracts their location information and related data. Once the analysis results are obtained, the process proceeds to the next stage.

[1270] Examples:

[1271] When a user uploads a photo of Mount Fuji, the server uses an image analysis engine to recognize Mount Fuji and identify surrounding landmarks (e.g., the Fuji Five Lakes, Fuji-Q Highland, etc.).

[1272] Obtaining tourist information (server side)

[1273] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). The tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc.

[1274] Examples:

[1275] The server collects information about the Fuji Five Lakes and Fuji-Q Highland, and also obtains data on related accommodations and restaurants.

[1276] Travel schedule generation (server side)

[1277] Based on the collected tourist destination information, the server automatically generates a travel schedule. This schedule generation process takes into account the user's desired travel period, travel time, and time spent at the destinations. The generated schedule includes specific activities for each day.

[1278] Examples:

[1279] The server plans a three-day trip, with the first day visiting the Fuji Five Lakes, the second day visiting Fuji-Q Highland, and the third day visiting nearby hot springs.

[1280] Cost Estimate (Server Side)

[1281] Based on the travel itinerary, the server estimates the cost of the entire trip, including the sum of individual costs such as transportation, accommodation, meals, etc. It uses an external API to obtain real-time pricing information and provides an accurate estimate.

[1282] Travel itinerary generation (server side)

[1283] Finally, the server generates a "trip itinerary" that summarizes the trip schedule and cost estimates, which can be made easily accessible to users in PDF or HTML format.

[1284] Examples:

[1285] The final itinerary includes a schedule for each day, detailed information about the places visited and a breakdown of estimated costs, which users can download and refer to during their trip.

[1286] Displaying the results (terminal side)

[1287] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[1288] User confirmation and final adjustments

[1289] The user can review the presented itinerary and, if satisfied, proceed with the trip. If changes are needed, they can send a request to the server via the terminal and make the necessary adjustments.

[1290] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[1291] The processing flow will be explained below.

[1292] Step 1:

[1293] The user uploads images of their proposed trip to their device.

[1294] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[1295] Step 2:

[1296] The device compresses the uploaded image and sends it to the server.

[1297] The device compresses the input image data and sends it to the server as an HTTP request, which includes the image data and necessary metadata (user ID, timestamp).

[1298] Step 3:

[1299] The server analyzes the received image.

[1300] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[1301] Step 4:

[1302] The server collects tourist destination information based on the identified landmarks.

[1303] Based on the identified landmarks and place names, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[1304] Step 5:

[1305] A travel schedule is automatically generated based on tourist destination information collected by the server.

[1306] Based on the acquired information, the server generates a schedule that matches the user's desired travel period, including tourist spots to visit, travel time, stay time, rest time, etc.

[1307] Step 6:

[1308] The server estimates the travel cost based on the travel schedule.

[1309] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[1310] Step 7:

[1311] The server generates the travel guide.

[1312] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[1313] Step 8:

[1314] The server transmits the generated travel guide to the terminal.

[1315] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[1316] Step 9:

[1317] The device displays the trip itinerary to the user.

[1318] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[1319] Step 10:

[1320] The user reviews the travel itinerary and makes the final decision.

[1321] The user can review the presented itinerary and, if satisfied, proceed with the travel plan. If changes are needed, they can send a request via the device and make the necessary adjustments.

[1322] Example 1

[1323] 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."

[1324] Planning a trip requires a wide range of tasks, such as gathering information on tourist spots, adjusting schedules, and estimating costs, placing a heavy burden on users. Additionally, it is difficult to select reliable information from the overwhelming amount of information available on the Internet, which makes planning time-consuming and stressful. Furthermore, the lack of tools that allow users to centrally manage travel schedules and costs makes it difficult for users to efficiently plan their trips.

[1325] 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.

[1326] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places or landmarks, means for acquiring location information based on the identified places or landmarks, means for automatically generating a travel plan based on the location information, means for estimating travel costs based on the travel plan, means for generating a guide including the travel plan and cost estimate, and means for presenting the guide to the user, thereby reducing the burden on the user and enabling efficient travel planning.

[1327] "User" refers to a person who uses the system to make travel plans.

[1328] "Means for accepting images" refers to the mechanism for receiving image files uploaded by users.

[1329] "Means for analyzing images to identify specific places and landmarks" refers to technology for recognizing input images and identifying specific places and landmarks present within the images.

[1330] "Means for obtaining location information" refers to the mechanism for obtaining information related to identified locations and landmarks from external databases or APIs.

[1331] "Means for automatically generating travel plans" refers to a system that automatically creates a travel schedule based on acquired location information, taking into account the user's desired period and means of transportation.

[1332] "Means for estimating travel costs" refers to a mechanism for calculating and totaling the costs required for each journey based on the generated travel plan.

[1333] "Means for generating guidance" refers to a mechanism for creating a document that integrates travel plans and cost estimates and presents them to the user.

[1334] "Presentation means" refers to a mechanism for visually displaying the generated guidance to the user.

[1335] The present invention is a system that aims to enable users to make travel plans efficiently and easily. An embodiment of the system of the present invention will be described below.

[1336] User interface (terminal side)

[1337] Users upload images of potential travel destinations to the system using their own devices. These devices include devices with internet connectivity, such as smartphones, tablets, and PCs. Users select photos or images of potential travel destinations and click the "Upload Images" button in the application. This action causes the device to send the image files to the server.

[1338] Examples:

[1339] When a user wants to upload a photo of Mt. Fuji, he or she selects a photo of Mt. Fuji from the gallery of the smartphone and clicks the upload button.

[1340] Image analysis (server side)

[1341] The server receives the image file sent from the device and saves it in the appropriate directory. It then loads the saved image file and uses an image recognition engine such as TensorFlow or OpenCV to identify key landmarks and place names in the image. The server extracts the location information and related data of the recognized landmarks and proceeds to the next step.

[1342] Examples:

[1343] The server receives a photo of Mt. Fuji and uses an image analysis engine to recognize Mt. Fuji and identify surrounding landmarks (e.g., Fuji Five Lakes, Fuji-Q Highland).

[1344] Obtaining tourist information (server side)

[1345] Based on the landmarks identified by image analysis, the server collects related tourist destination information using external APIs (e.g., Google Places API, Yelp API), including tourist attractions, restaurants, accommodations, and transportation options.

[1346] Examples:

[1347] The server uses the Google Places API to obtain information about the Fuji Five Lakes and Fuji-Q Highland, as well as data on related accommodations and restaurants.

[1348] Travel schedule generation (server side)

[1349] Based on the collected tourist destination information, the server automatically generates a travel schedule, taking into consideration information provided by the user, such as the desired travel period, travel time, and length of stay at the destinations.

[1350] Examples:

[1351] The server creates a three-day travel plan, with the first day planned to be spent sightseeing at the Fuji Five Lakes, the second day to enjoy Fuji-Q Highland, and the third day to visit nearby hot spring resorts.

[1352] Cost Estimate (Server Side)

[1353] Based on the generated itinerary, the server retrieves real-time pricing information using an external API and estimates the cost of the entire trip, including transportation, accommodation, and meals.

[1354] Travel itinerary generation (server side)

[1355] The server compiles the generated travel schedule and cost estimates and generates a "travel guide" in PDF or HTML format for easy access by the user.

[1356] Examples:

[1357] The final itinerary includes a detailed schedule for each day, information about tourist attractions, and a breakdown of estimated costs, which users can download and refer to during their trip.

[1358] Displaying the results (terminal side)

[1359] The generated travel bookmark is sent from the server to the device, which receives it and visually displays it to the user. The user can then review the bookmark and submit change requests if necessary.

[1360] Examples:

[1361] The travel bookmark is displayed on the user's terminal, and the user checks the contents of the bookmark.

[1362] Examples of prompt statements

[1363] Here are some example prompts to input to a generative AI model:

[1364] "Please upload photos of Mt. Fuji and create a three-day itinerary. Please include information on attractions, accommodations, and restaurants, as well as a cost estimate."

[1365] In this way, the system of the present invention significantly reduces the burden on the user and enables them to make travel plans efficiently and easily.

[1366] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1367] Step 1:

[1368] The user selects an image of a potential travel destination and clicks the "Upload Image" button in the application on the device. The input is the selected image file, and the output is the image file sent to the server.

[1369] Specific behavior:

[1370] The user selects a photo of Mt. Fuji from their smartphone's gallery and presses the "Upload Image" button in the application.

[1371] Step 2:

[1372] The server receives the image file sent from the terminal. The image file arrives at the server as input, and the image file is saved in the appropriate directory on the server as output.

[1373] Specific behavior:

[1374] The server receives the photo of Mt. Fuji and saves it in the " / uploaded_images" directory.

[1375] Step 3:

[1376] The server loads the saved image files and performs image analysis using image recognition engines such as TensorFlow and OpenCV. The saved image files are used as input, and the output is information about identified landmarks and places.

[1377] Specific behavior:

[1378] The server loads a photo of Mount Fuji and uses TensorFlow to recognize Mount Fuji in the image and extract its location information.

[1379] Step 4:

[1380] The server uses the Google Places API and Yelp API to retrieve information related to the identified landmarks and places. The input is the location information of the identified landmarks, and the output is the collection of information about related tourist attractions.

[1381] Specific behavior:

[1382] The server uses the Google Places API to collect information about the Fuji Five Lakes and Fuji-Q Highland.

[1383] Step 5:

[1384] The server automatically generates a travel schedule using the collected tourist destination information based on the user's desired travel information (desired travel period, travel time, length of stay, etc.) The input is tourist destination information and the user's desired information, and the output is a specific travel schedule.

[1385] Specific behavior:

[1386] The server takes into consideration the user's desired three-day period and creates a schedule that visits the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a hot spring resort on the third day.

[1387] Step 6:

[1388] The server estimates the cost of the trip based on the generated itinerary, which involves retrieving real-time pricing information using an external API and adding up the individual costs. The input is the itinerary, and the output is the estimated cost of the entire trip.

[1389] Specific behavior:

[1390] The server tallies up accommodation, transportation, meal costs, etc., and calculates the total cost of the entire trip.

[1391] Step 7:

[1392] The server integrates the travel schedule and cost estimate information to generate a "travel guide" in a user-friendly format (PDF or HTML). The input is the travel schedule and cost estimate, and the output is a travel guide.

[1393] Specific behavior:

[1394] The server compiles the schedule and cost estimates and generates a detailed travel guide in PDF format.

[1395] Step 8:

[1396] The server sends the generated itinerary to the user's terminal. The input is the generated itinerary, and the output is the itinerary sent to the terminal.

[1397] Specific behavior:

[1398] The server sends a PDF travel guide to the user's smartphone.

[1399] Step 9:

[1400] The terminal visually displays the received travel itinerary to the user. The input is the received travel itinerary, and the output is the visual display to the user.

[1401] Specific behavior:

[1402] The travel bookmark will be displayed on the smartphone screen and the user will be able to check it.

[1403] Step 10:

[1404] The user checks the displayed travel bookmark and sends a change request to the server if necessary. The input is the displayed travel bookmark, and the output can be a change request.

[1405] Specific behavior:

[1406] The user presses the "Request Changes" button in the application to send any complaints about the bookmark to the server.

[1407] (Application example 1)

[1408] 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."

[1409] In the modern tourism industry, users need to collect and adjust a lot of information to plan a trip. This process is time-consuming and extremely difficult, especially for users who have little information about the place they are visiting for the first time. Furthermore, online tourism information and services cannot fully replace the actual travel experience, and there are limited ways to simulate a trip. To solve these issues, a system is needed that not only allows users to easily plan their trip, but also provides a tourism experience in a virtual space.

[1410] 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.

[1411] In this invention, the server includes means for accepting images input by a user, means for analyzing the images to identify specific places and landmarks, means for acquiring tourist attraction information based on the identified places and landmarks, means for automatically generating a travel itinerary based on the tourist attraction information, means for estimating travel costs based on the travel schedule, means for generating a travel guidebook including the travel schedule and cost estimate, means for presenting the travel guidebook to the user, and means for providing a tourist experience in a virtual space based on the tourist attraction information. This allows users to efficiently and easily plan their trip and further enables them to experience tourist attractions in the virtual space before their actual trip.

[1412] The "means for accepting user-entered images" refers to a function that allows a user to upload images of potential travel destinations through the interface.

[1413] The "means for analyzing the image to identify specific locations and landmarks" refers to a technology for processing the image received on the server side and identifying major landmarks and place names using an image analysis engine.

[1414] The "means for acquiring tourist attraction information based on the identified locations and landmarks" is a function for collecting tourist attraction information related to landmarks identified by image analysis from an external API, etc.

[1415] The "means for automatically generating a travel schedule based on the tourist attraction information" is a technology that automatically generates a travel schedule that meets the user's wishes based on the collected tourist attraction information.

[1416] The "means for estimating travel expenses based on the travel schedule" is a function for calculating the total cost of transportation, accommodation, meals, etc. based on the generated travel schedule.

[1417] The "means for generating a travel guide including the travel schedule and cost estimate" refers to a technology for creating a document including the travel schedule and cost estimate in PDF or HTML format.

[1418] The "means for presenting the travel itinerary to the user" is a function for transmitting the generated travel itinerary to the user's terminal and visually displaying it.

[1419] "Means for providing a tourist experience in a virtual space based on the tourist destination information" refers to technology that enables users to have an immersive tourist experience in a virtual space based on the collected tourist destination information.

[1420] This invention is a virtual tourist guide system that allows users to upload images of potential travel destinations and provides sightseeing experiences in a virtual space based on the uploaded images. This system is implemented using devices such as smart glasses and a server.

[1421] Hardware and software usage

[1422] Hardware:

[1423] Smart glasses: A device that allows users to upload images and visually confirm their virtual tourism experience.

[1424] Server: A central computing resource that analyzes images, collects tourist information, generates travel schedules, estimates costs, and generates travel guides.

[1425] software:

[1426] TensorFlow: A deep learning framework used to analyze images.

[1427] OpenCV: Used as an image processing library.

[1428] Google Places API: An external API used to collect tourist destination information.

[1429] Data processing and data calculation processing

[1430] 1. User uploads an image:

[1431] Users use the smart glasses interface to upload images of potential travel destinations, which are then sent to a server.

[1432] 2. Image Analysis:

[1433] The server analyzes the received image using TensorFlow and OpenCV to identify major landmarks and place names, and proceeds to the next step based on the analysis results.

[1434] 3. Obtaining tourist information:

[1435] The server uses the Google Places API to retrieve tourist information based on the identified landmarks, collecting detailed data on tourist attractions, restaurants, accommodations, etc.

[1436] 4. Generate travel schedule:

[1437] The server automatically generates a travel schedule based on the collected tourist destination information, taking into consideration the user's desired travel period and travel time.

[1438] 5. Cost Estimate:

[1439] The server estimates the travel costs, including transportation, accommodation, and meals, based on the generated itinerary, using real-time pricing information from an external API.

[1440] 6. Travel bookmark generation:

[1441] The server generates a travel itinerary that includes the travel schedule and cost estimates, and creates it in PDF and HTML formats.

[1442] 7. Providing tourism experiences:

[1443] The server provides users with a sightseeing experience in a virtual space based on tourist destination information and travel bookmarks, which are projected onto the smart glasses.

[1444] 8. Presentation of results:

[1445] The generated travel itinerary and virtual sightseeing experience are displayed on the smart glasses' display, where users can review it and submit change requests if necessary.

[1446] Adding specific examples

[1447] For example, if a user uploads a photo of Mt. Fuji, the system works as follows:

[1448] A user uploads a photo of Mount Fuji.

[1449] The server uses TensorFlow to recognize Mt. Fuji and uses the Google Places API to collect information about tourist spots around Mt. Fuji (e.g., Fuji Five Lakes, Fuji-Q Highland).

[1450] The server generates a three-day travel schedule, planning a visit to the Fuji Five Lakes on the first day, Fuji-Q Highland on the second day, and a visit to nearby hot springs on the third day.

[1451] Estimate costs based on your travel schedule and generate a travel guide.

[1452] The generated travel guide is displayed on smart glasses, allowing users to experience tourist spots in a virtual space.

[1453] Prompt Sentence Examples

[1454] "Upload photos of Mt. Fuji, gather information on nearby tourist attractions, and create a three-day travel plan."

[1455] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1456] Step 1:

[1457] The user uses the smart glasses interface to upload an image of a potential travel destination, with the image of the user's choice as input, and the device then sends the image to the server.

[1458] Step 2:

[1459] The server receives images sent from the device. Using the received image file as input, it performs image analysis using TensorFlow and OpenCV. Specifically, the server extracts features within the image and identifies major landmarks and place names. The identified landmarks and place names are output as the analysis results.

[1460] Step 3:

[1461] The server uses the results of image analysis to collect tourist information related to the identified landmarks and place names. Using the analysis results as input, the server calls the Google Places API to retrieve tourist information. Specifically, the server sends API requests to collect data on tourist attractions, restaurants, accommodations, etc. This information is the output.

[1462] Step 4:

[1463] The server automatically generates a travel schedule based on the collected tourist destination information. Using the tourist destination information as input, it creates a specific daily plan taking into account the user's desired travel period, travel time, and time spent at each destination. The output of this process is a detailed travel schedule.

[1464] Step 5:

[1465] The server estimates the cost of the trip based on the generated itinerary. It uses the itinerary as input and sums up the individual costs such as transportation, accommodation, and meals. It uses an external API to get real-time pricing information and provides an accurate estimate. The output is the total cost and a breakdown of the individual costs.

[1466] Step 6:

[1467] The server compiles the travel schedule and cost estimates to generate a travel itinerary. It uses the travel schedule and cost estimates as input and creates a travel itinerary in PDF or HTML format. Specifically, it generates a document that includes the schedule for each day, detailed information about the places visited, and a breakdown of costs. The output is the completed travel itinerary.

[1468] Step 7:

[1469] The server sends the generated itinerary to the terminal and presents it visually to the user. It uses the generated itinerary as input and sends it to the terminal. The terminal receives it and displays it on the smart glasses display. The user reviews it and, if satisfied, can proceed with the trip. It is also possible to send change requests if necessary.

[1470] Step 8:

[1471] The server provides a sightseeing experience in a virtual space based on tourist destination information. It uses the collected tourist destination information as input and creates a virtual tour using virtual reality technology. Specifically, it displays 3D models and images so that users can experience the tourist destination realistically through smart glasses. The output is a sightseeing experience in a virtual space.

[1472] 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.

[1473] User interface (terminal side)

[1474] The present invention begins with the step where a user uploads images of potential travel destinations via a terminal and uses an emotion engine to analyze the user's emotions. The terminal can be a smartphone, tablet, PC, or other device that can connect to the Internet. The user selects a photo or image of a potential travel destination and clicks the "Upload Image" button in the application. At this point, the terminal sends the image to the server, and the emotion engine simultaneously analyzes the user's emotions.

[1475] Image analysis and emotion analysis (server side)

[1476] The server receives the image sent from the device and begins image analysis. Image analysis libraries (e.g., TensorFlow, OpenCV) are used to identify key landmarks and place names in the image. An emotion engine also analyzes the user's voice and text input to identify their current emotional state (e.g., excited, relaxed, excitement-seeking).

[1477] Examples:

[1478] If a user uploads a photo of Mount Fuji, the server will use an image analysis engine to recognize the mountain, and an emotion engine will analyze that the user has a "spirit of adventure."

[1479] Obtaining tourist destination information and adjusting it based on emotions (server side)

[1480] Next, the server collects tourist information based on the identified landmarks. This information is obtained using external APIs (e.g., Google Places API, Yelp API). Tourist information includes tourist attractions, restaurants, accommodations, transportation options, etc. Based on the information from the emotion engine, the server selects and adjusts tourist attractions and activities that match the user's current emotional state.

[1481] Examples:

[1482] The server collects information on tourist spots around Mount Fuji and suggests hiking trails and outdoor activities to adventurous users.

[1483] Travel schedule generation and sentiment-based optimization (server side)

[1484] Based on the collected tourist destination information and the results of the emotion engine, the server automatically generates a travel schedule, taking into account the user's desired travel period, travel time, stay time, and emotional state to create an optimized schedule.

[1485] Examples:

[1486] The server plans a three-day trip, with the first day being canoeing on the Fuji Five Lakes, the second day climbing Mount Fuji, and the third day relaxing at a hot spring resort.

[1487] Cost Estimate (Server Side)

[1488] The server estimates the total cost of the trip based on the travel itinerary, calculates individual costs such as transportation, accommodation, and meals, and uses external APIs to obtain real-time pricing information to provide an accurate estimate.

[1489] Travel itinerary generation (server side)

[1490] Finally, the server generates a "travel bookmark" that summarizes the trip itinerary and cost estimates, in PDF or HTML format for easy user access, and adjusts the bookmark content based on the results of the emotion engine.

[1491] Examples:

[1492] The final itinerary includes a schedule for each day, detailed information about the places to visit, a breakdown of expected costs, and highlights special activities for the more adventurous user.

[1493] Displaying the results (terminal side)

[1494] The generated itinerary is sent from the server to the terminal, which receives it and visually displays it to the user. The user can check the itinerary and send a change request if necessary.

[1495] User confirmation and final adjustments

[1496] Users can review the presented travel plan and, if satisfied, proceed with their travel plans. Because it includes suggestions based on the results of the emotion engine, users can enjoy travel plans that are even more tailored to their needs. If changes are needed, the device sends a request to the server again, and the necessary adjustments are made.

[1497] In this way, the system of the present invention enables users to easily and effectively plan their trips while taking their emotions into consideration, thereby improving the user's travel experience.

[1498] The processing flow will be explained below.

[1499] Step 1:

[1500] The user uploads images of their proposed trip to their device.

[1501] In the application on your device, click the "Upload Images" button, select and upload photos or images of your potential travel destinations.

[1502] Step 2:

[1503] The device sends the uploaded images and the user's voice and text input to the server.

[1504] The device compresses the input image data and the user's voice and text data, and sends them to the server as an HTTP request. This request includes the image data, voice data, text data, and necessary metadata (user ID, timestamp).

[1505] Step 3:

[1506] The server analyzes the received image.

[1507] The server uses image analysis libraries (e.g., TensorFlow, OpenCV) to identify landmarks and place names in the images, which involves using image recognition algorithms to extract features in the image and match them with an existing database.

[1508] Step 4:

[1509] The server analyzes the user's emotions.

[1510] The server uses an emotion analysis engine to analyze the user's voice or text input to determine the user's current emotional state, using speech recognition and text analysis algorithms.

[1511] Examples:

[1512] If a user uploads an image of Mount Fuji and enters the text "I want to have an adventure," the server will recognize Mount Fuji through image analysis and detect the "spirit of adventure" through emotional analysis.

[1513] Step 5:

[1514] The server collects tourist destination information based on the identified landmarks and the user's emotions.

[1515] Based on the identified landmarks, place names, and user sentiment information, the server calls external APIs (e.g., Google Places API, Yelp API) to obtain detailed information such as tourist destination information, restaurants, accommodations, and transportation options.

[1516] Step 6:

[1517] The server generates a travel schedule adjusted based on the emotions.

[1518] The server takes into account the acquired tourist destination information and the user's emotional state to generate a schedule that matches the user's desired travel period. This schedule includes tourist destinations to visit, travel time, stay time, rest time, etc.

[1519] Examples:

[1520] For adventurous users, the server will suggest schedules that include mountain climbing and adventure sports.

[1521] Step 7:

[1522] The server estimates the travel cost based on the travel schedule.

[1523] The server calculates the cost of transportation, accommodation, and meals for each tourist spot to estimate the total cost, which includes using an external API to retrieve real-time pricing information.

[1524] Step 8:

[1525] The server generates the travel guide.

[1526] The server generates the final itinerary as a "travel guide" in text or PDF format, including a detailed schedule and cost estimates.

[1527] Examples:

[1528] The travel guide details hiking and outdoor activities and breakdowns of expected expenses for the more adventurous user.

[1529] Step 9:

[1530] The server transmits the generated travel guide to the terminal.

[1531] The generated bookmark is sent as an HTTP response to the device, which receives this data.

[1532] Step 10:

[1533] The device displays the trip itinerary to the user.

[1534] The device displays the received travel itinerary to the user, allowing the user to review the contents. If necessary, the user can enter corrections and resubmit the request.

[1535] Step 11:

[1536] The user reviews the travel itinerary and makes the final decision.

[1537] The user checks the presented itinerary and, if satisfied, proceeds with the travel plan. If changes are needed, the user sends a request to the server via the device and makes the necessary adjustments.

[1538] Example 2

[1539] 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."

[1540] Conventional travel planning systems often provide simple tourist information without considering the user's emotional state, making it difficult to create travel plans that meet individual needs. Furthermore, they require the user to manually search multiple sites to gather information, and they also require excessive effort in scheduling and estimating costs. Given these circumstances, there is a need for a method to automatically create travel plans that take the user's emotions into account, allowing for efficient and accurate travel planning.

[1541] 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.

[1542] In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for analyzing the user's emotions, means for acquiring tourist destination information based on the identified places and landmarks and the user's emotions, means for automatically generating a travel itinerary based on the tourist destination information and emotion analysis, means for estimating travel costs based on the travel schedule, means for generating a travel itinerary including the travel schedule and cost estimate, and means for presenting the travel itinerary to the user. This enables automatic generation and optimization of a travel plan according to the user's emotional state.

[1543] "User" refers to an individual or organization that uses this system to plan a trip.

[1544] "Device" refers to a device that can connect to the Internet, such as a smartphone, tablet, or PC.

[1545] "Images" refers to photographs and graphic data uploaded by users via their devices.

[1546] "Server" refers to a central processing unit that performs image analysis, emotion analysis, acquisition of tourist destination information, generation of travel schedules, cost estimates, and generation of travel guides.

[1547] "Image analysis" refers to the process of identifying specific places or landmarks from uploaded images.

[1548] "Emotion analysis" refers to the process of identifying a user's emotions based on the voice and text data entered by the user.

[1549] "Tourist destination information" refers to data about tourist attractions, restaurants, accommodations, transportation, etc. related to a specific location or landmark.

[1550] "Travel schedule" refers to travel itineraries and activity plans automatically generated based on tourist destination information and the user's emotional state.

[1551] "Cost Estimate" refers to the total travel cost calculated based on the generated travel itinerary.

[1552] "Travel Guide" means a travel itinerary provided to a User, including a travel schedule and cost estimate.

[1553] This invention provides a system that automatically generates travel plans that take users' emotions into consideration and provides optimal travel schedules. Specifically, the system allows users to upload images via their devices, and generates travel plans that meet the user's needs by analyzing the images and the user's emotions. This system uses the following hardware and software:

[1554] Hardware and software used

[1555] Device: Refers to a device that can connect to the internet, such as a smartphone, tablet, or PC. Users use these devices to input images, text, voice, etc.

[1556] Server: A central processing unit used to execute programs that perform the following processes:

[1557] Image analysis libraries (e.g. TensorFlow, OpenCV)

[1558] Sentiment Analysis Engine

[1559] External APIs (e.g. Google Places API, Yelp API)

[1560] Program processing

[1561] The device sends the user-uploaded images and necessary text and audio data to the server. The server analyzes the received images using image analysis libraries such as TensorFlow and OpenCV to identify specific locations and landmarks. It then uses a sentiment analysis engine to analyze emotions from the user's input text and audio.

[1562] The server uses the Google Places API and Yelp API to collect tourist information based on the identified landmarks and the analyzed emotional state. This tourist information includes tourist attractions, restaurants, accommodations, and transportation options. Based on the collected information and the results of the emotional analysis, the server automatically generates an optimized travel itinerary. Furthermore, it estimates travel costs based on the generated schedule and generates the final travel itinerary in PDF or HTML format.

[1563] Adding specific examples

[1564] Examples:

[1565] When a user uploads a photo of Mount Fuji, the server analyzes the photo to recognize the mountain and identifies emotions such as "adventure" and "excitement" through a sentiment analysis engine. It then uses the Google Places API to retrieve information on hiking trails, outdoor activities, accommodations, and other information around Mount Fuji. Finally, the server creates a three-day itinerary, including canoeing around the Fuji Five Lakes on the first day, climbing Mount Fuji on the second day, and relaxing at a hot spring resort on the third day. This includes travel and accommodation costs, and a detailed travel itinerary is generated.

[1566] Prompt Sentence Examples

[1567] "Upload an image of Mount Fuji, perform sentiment analysis, generate a three-day travel itinerary suitable for adventurous users, and create a travel bookmark with cost estimates."

[1568] In this way, the system of the present invention can make travel plans with high accuracy and efficiency while taking into account the user's emotions.

[1569] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1570] Step 1:

[1571] The user selects an image or photo of a potential travel destination and clicks the "Upload Image" button in the application. The device receives the image file and the user's emotion as input and sends it to the server. The specific operation involves implementing the image file selection and upload functions using programming languages ​​such as JavaScript and Python.

[1572] Step 2:

[1573] The device receives image data and additional emotion data (text or voice) input by the user and sends it to the server. The input data is image and text or voice data, which is packetized and sent to the server. Specifically, the device performs communication processing to send data to the server via an HTTP request.

[1574] Step 3:

[1575] The server analyzes the image data received from the device using image analysis libraries such as TensorFlow and OpenCV. The input for image analysis is image data, and the output is identification information for specific locations and landmarks. The server identifies key landmarks based on the analyzed information. Specifically, it calls the TensorFlow API and processes the image data.

[1576] Step 4:

[1577] The server analyzes the text or voice data sent by the user using a sentiment analysis engine. The input is text or voice data, and the output is the user's emotional state (e.g., excited, relaxed, adventurous). Specifically, sentiment analysis is performed using a natural language processing (NLP) library.

[1578] Step 5:

[1579] Based on the results of image analysis and sentiment analysis, the server obtains tourist information for specific landmarks and locations using external APIs (e.g., Google Places API, Yelp API). The input is the landmark's identification information and emotional state, and the output is tourist information (tourist attractions, restaurants, accommodations, and transportation). Specifically, the server sends an API request and stores the obtained data in an internal database.

[1580] Step 6:

[1581] The server generates an optimal travel schedule based on the acquired tourist destination information and the user's emotional state. The input is tourist destination information and the emotional state, and the output is a detailed travel schedule. Specifically, the server runs a schedule generation algorithm to create a schedule that takes into account the user's desired travel period and activity balance.

[1582] Step 7:

[1583] The server estimates the travel cost based on the generated travel schedule. The input is the travel schedule and the output is the cost estimate. Specifically, the server retrieves the cost data for each activity from the API and calculates the total cost.

[1584] Step 8:

[1585] The server compiles the travel schedule and cost estimates to generate a travel itinerary. The input is the schedule and cost estimate, and the output is the travel itinerary (in PDF or HTML format). Specifically, the server inserts the data into a format-defined template to create the final travel itinerary.

[1586] Step 9:

[1587] The device receives the generated travel bookmark from the server and displays it visually to the user. The input is the travel bookmark (PDF or HTML file) and the output is a visual display. Specifically, the device displays the bookmark using a PDF viewer or browser component.

[1588] Step 10:

[1589] The user checks the presented travel itinerary and, if necessary, sends a change request to the server through the terminal. The input is the user's confirmation feedback, and the output is the updated travel schedule. Specifically, the terminal sends the change request to the server again, and the server readjusts the schedule.

[1590] (Application example 2)

[1591] 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."

[1592] When creating travel schedules, there is a need to create optimal plans that take user emotions into consideration and then provide the user with a virtual experience using virtual reality technology. However, while current systems can perform image analysis and acquire travel information, they have difficulty analyzing user emotions and reflecting them in schedules or providing virtual experiences. This poses a challenge in that they are unable to provide sophisticated travel plans that respond to the individual needs and emotions of users.

[1593] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting an image input by a user, means for analyzing the image to identify specific places and landmarks, means for acquiring tourist destination information based on the identified places and landmarks, means for analyzing the user's emotions, means for automatically generating a travel itinerary based on the results of the emotion analysis and the tourist destination information, means for estimating travel costs based on the travel schedule, means for generating a travel booklet including the travel schedule and cost estimates, and means for presenting the travel booklet to the user and providing a virtual experience using virtual reality technology. This makes it possible to create an optimal travel plan based on the user's emotions and to provide the plan as a virtual experience.

[1594] "User" means any person or entity that uses the present invention.

[1595] "Means for receiving an image" refers to a function or device that receives an image input by a user.

[1596] "Means for analyzing images to identify specific places or landmarks" refers to algorithms or software that analyze input images and recognize and identify specific places or landmarks within the images.

[1597] "Means for acquiring tourist attraction information" refers to a function or device that acquires information on related tourist attractions based on a specific location or landmark from an external database or API.

[1598] "Means for analyzing emotions" refers to algorithms or software that analyze users' emotions from input such as voice or text.

[1599] "Means for automatically generating travel schedules" refers to a function or device that automatically creates an optimal travel schedule based on acquired tourist destination information and analyzed emotion data.

[1600] "Means for estimating travel costs" refers to a function or device that calculates the total cost of a trip based on the generated travel schedule.

[1601] "Means for generating a travel guide" refers to a function or device that creates a travel guide to be provided to a user based on a travel schedule and cost estimate.

[1602] "Means for providing a virtual experience using virtual reality technology" refers to software or hardware for providing users with a virtual experience of a travel destination using virtual reality technology based on the generated travel guide.

[1603] System Configuration

[1604] This system performs emotion and image analysis based on user input, generates an optimal travel schedule, and provides a virtual experience of it. The main hardware and software configurations are as follows:

[1605] Hardware Configuration

[1606] 1. Terminal device: A device that can connect to the Internet, such as a smartphone, tablet, or PC.

[1607] 2. Server equipment: Servers with high-performance data processing and storage.

[1608] 3. VR headset: A device for providing a virtual reality experience, such as the Oculus Quest 2.

[1609] Software Configuration

[1610] 1. Image analysis library: Uses TensorFlow, OpenCV, etc. to analyze input images and recognize specific locations and landmarks.

[1611] 2. Sentiment Analysis Engine: Algorithms and models for analyzing user sentiment from speech and text.

[1612] 3. Tourist attraction information acquisition library: Obtains tourist attraction information using Google Places API, Yelp API, etc.

[1613] 4. VR simulation software: Tools for building VR environments, such as Unity.

[1614] Processing flow

[1615] 1. Uploading images on the device

[1616] The user uploads images of their proposed trips to the application using a terminal device, which then transmits the images to the server device.

[1617] 2. Server-side image and sentiment analysis

[1618] The server analyzes the submitted image using an image analysis library (TensorFlow, OpenCV, etc.) to identify major landmarks and place names. At the same time, it uses a sentiment analysis engine to analyze emotions from the user's voice and text input. For example, if a user uploads a photo of a mountain as a potential travel destination and enters the phrase "I want to relax," the server will analyze the emotion "relaxed."

[1619] 3. Obtaining tourist information and adjusting it based on emotions

[1620] Based on the analysis results, the server retrieves related tourist destination information using the Google Places API. It then generates a travel itinerary optimized for the user, reflecting the results of the sentiment analysis. For example, if the emotion "I want to relax" is analyzed, hot springs and relaxation spots will be added to the itinerary.

[1621] 4. Travel Schedule and Cost Estimate

[1622] Based on the generated travel schedule, the server estimates the travel costs for each activity and place visited, and then creates a travel booklet based on the schedule and cost estimates.

[1623] 5. Providing travel guides and VR experiences

[1624] The generated travel guide is then sent back to the user's device and presented to them. Furthermore, users can enjoy virtual travel experiences through the VR environment built using Unity. For example, a user planning to visit a hot spring resort can virtually experience the hot spring resort in a VR environment beforehand.

[1625] Examples and prompts

[1626] For example, if a user uploads an image of Arashiyama, Kyoto, and types "I want to relax":

[1627] 1. Image URL: https: / / example.com / arashiyama.jpg

[1628] 2. User Emotion: I want to relax

[1629] 3. Trip duration: 2 days

[1630] Using this information, the server retrieves tourist destination information and generates a travel itinerary based on the user's feelings, including, for example, a stroll through a bamboo forest on Day 1 and relaxation at a hot spring facility on Day 2. This itinerary is provided to the user as a PDF travel guidebook along with cost estimates, and it is also possible to have a virtual experience of Arashiyama using a VR headset.

[1631] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1632] Step 1:

[1633] The device displays an interface that allows the user to upload images of potential trips. The user uploads the images and clicks the "Upload Images" button. The input is an image file of the potential trip locations. The device then sends this image file to the specified server.

[1634] Step 2:

[1635] The server receives image files sent from the device. The input data is the image uploaded by the user. The server analyzes this image using an image analysis library (e.g., TensorFlow or OpenCV) to identify and distinguish key landmarks and place names. The output is the analysis results, which are the specific landmarks and place names.

[1636] Step 3:

[1637] The server retrieves tourist destination information based on the identified specific landmarks and place names. The input data is the image analysis result from step 2. A tourist destination information retrieval library (e.g., Google Places API) is used to collect related tourist destination information from an external database. The output is tourist destination information (tourist attractions, restaurants, accommodations, etc.).

[1638] Step 4:

[1639] The server receives the user's voice and text data acquired from the device to analyze the user's emotions. The input data is the user's voice and text. An emotion analysis engine is used to identify the user's current emotional state (e.g., excited, relaxed, excitement-seeking) from the content of the voice and text. The output is the user's emotional state.

[1640] Step 5:

[1641] The server automatically generates a travel schedule based on tourist destination information and the user's emotional state. The input data is tourist destination information and the user's emotional state. Using a generative AI model, an optimal schedule is created that takes into account the user's desired travel period and emotional state. The output is a travel schedule.

[1642] Step 6:

[1643] The server estimates the travel cost based on the generated travel schedule. The input data is the travel schedule. It uses an external API to obtain real-time pricing information such as transportation costs, accommodation costs, and meal costs, and calculates the accurate travel cost. The output is a cost estimate.

[1644] Step 7:

[1645] The server generates a travel guide based on the travel schedule and cost estimate. The input data are the travel schedule and cost estimate. The guide is generated in PDF or HTML format and sent to the terminal. The travel guide is obtained as the output.

[1646] Step 8:

[1647] The terminal receives the travel itinerary sent from the server and visually displays it to the user. The user can check the bookmark and send a change request if necessary. The input data is the generated travel itinerary, and the output is the user's confirmation status and change request.

[1648] Step 9:

[1649] The server receives the change request and re-adjusts and optimizes the travel schedule. The input data is the change request from the user. The generative AI model is used again to create an optimal schedule. The output is the re-adjusted travel schedule.

[1650] Step 10:

[1651] The server uses VR simulation software such as Unity to create a VR experience of the selected tourist spots. The input data is the tourist spot information from the travel itinerary. The server creates a VR environment and allows users to experience a virtual trip with a VR headset. The output is the VR content for the virtual experience.

[1652] Examples of prompts:

[1653] 1. Image URL: https: / / example.com / arashiyama.jpg

[1654] 2. User Emotion: I want to relax

[1655] 3. Trip duration: 2 days

[1656] This allows the optimal travel plan to be created based on the user's emotional state, and the plan can be experienced virtually in VR.

[1657] 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.

[1658] 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.

[1659] 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.

[1660] 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.

[1661] 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.

[1662] 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.

[1663] 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).

[1664] 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.

[1665] 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."

[1666] 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.

[1667] 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).

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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.

[1675] 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.

[1676] 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.

[1677] 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.

[1678] The following is further disclosed regarding the above embodiment.

[1679] (Claim 1)

[1680] means for accepting a user-supplied image;

[1681] means for analyzing the image to identify specific locations or landmarks;

[1682] a means for acquiring tourist destination information based on the identified places and landmarks;

[1683] means for automatically generating a travel schedule based on the tourist destination information;

[1684] means for estimating travel costs based on the travel schedule;

[1685] means for generating a travel itinerary including the travel schedule and cost estimate;

[1686] means for presenting the travel guide to a user;

[1687] A system including:

[1688] (Claim 2)

[1689] 10. The system of claim 1, further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

[1690] (Claim 3)

[1691] The system of claim 1 , further comprising: means for taking into account a user's desired travel duration when generating the travel schedule.

[1692] "Example 1"

[1693] (Claim 1)

[1694] means for accepting a user-supplied image;

[1695] means for analyzing the image to identify specific locations or landmarks;

[1696] means for acquiring location information based on the determined locations and landmarks;

[1697] means for automatically generating a travel plan based on the location information;

[1698] means for estimating travel costs based on the travel plan;

[1699] means for generating guidance including the travel plan and cost estimate;

[1700] means for presenting said guidance to a user;

[1701] A system including:

[1702] (Claim 2)

[1703] 10. The system of claim 1, further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

[1704] (Claim 3)

[1705] The system of claim 1 , further comprising: means for taking into account a user's desired duration when generating the travel plan.

[1706] "Application Example 1"

[1707] (Claim 1)

[1708] means for accepting a user-supplied image;

[1709] means for analyzing the image to identify specific locations or landmarks;

[1710] a means for acquiring tourist destination information based on the identified places and landmarks;

[1711] means for automatically generating a travel schedule based on the tourist destination information;

[1712] means for estimating travel costs based on the travel schedule;

[1713] means for generating a travel itinerary including the travel schedule and cost estimate;

[1714] means for presenting the travel guide to a user;

[1715] a means for providing a sightseeing experience in a virtual space based on the tourist destination information;

[1716] A system including:

[1717] (Claim 2)

[1718] 10. The system of claim 1, further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

[1719] (Claim 3)

[1720] The system of claim 1 , further comprising: means for taking into account a user's desired travel duration when generating the travel schedule.

[1721] "Example 2: Combining Emotion Engines"

[1722] (Claim 1)

[1723] means for accepting a user-supplied image;

[1724] means for analyzing the image to identify specific locations or landmarks;

[1725] A means of analyzing user emotions,

[1726] means for acquiring tourist destination information based on the determined places and landmarks and the user's emotions;

[1727] means for automatically generating a travel schedule based on the tourist destination information and emotion analysis;

[1728] means for estimating travel costs based on the travel schedule;

[1729] means for generating a travel itinerary including the travel schedule and cost estimate;

[1730] means for presenting the travel guide to a user;

[1731] A system including:

[1732] (Claim 2)

[1733] 10. The system of claim 1, further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

[1734] (Claim 3)

[1735] The system of claim 1 , further comprising: means for considering a desired travel duration and an emotional state of the user when generating the travel itinerary.

[1736] "Application example 2 when combining emotion engines"

[1737] (Claim 1)

[1738] means for accepting a user-supplied image;

[1739] means for analyzing the image to identify specific locations or landmarks;

[1740] a means for acquiring tourist destination information based on the identified places and landmarks;

[1741] A means of analyzing user emotions,

[1742] means for automatically generating a travel schedule based on the result of the emotion analysis and tourist destination information;

[1743] means for estimating travel costs based on the travel schedule;

[1744] means for generating a travel itinerary including the travel schedule and cost estimate;

[1745] means for presenting the travel guide to a user and providing a virtual experience using virtual reality technology;

[1746] A system including:

[1747] (Claim 2)

[1748] 10. The system of claim 1, further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

[1749] (Claim 3)

[1750] The system of claim 1 , further comprising: means for considering a desired travel duration and an emotional state of the user when generating the travel itinerary. [Explanation of symbols]

[1751] 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 accepting a user-supplied image; means for analyzing the image to identify specific locations or landmarks; a means for acquiring tourist destination information based on the identified places and landmarks; means for automatically generating a travel schedule based on the tourist destination information; means for estimating travel costs based on the travel schedule; means for generating a travel itinerary including the travel schedule and cost estimate; means for presenting the travel guide to a user; A system including:

2. The system of claim 1 , further comprising means for retrieving information about places and landmarks determined by analyzing the image from a database.

3. The system of claim 1 , further comprising: means for taking into account a user's desired travel duration when generating the travel schedule.

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