system

Abstract

Provide a system. [Solution] means for receiving image data from a user terminal; means for analyzing the image data and identifying destinations that the user has not yet visited; means for automatically generating an individualized travel plan based on the destination; means for arranging accommodation and transportation based on the user's preferences and budget; a means for recording emotional data during the trip; means for automatically inserting appropriate music into the travel record video based on the emotion data; means for automatically generating the travel record video; a means for sharing said video with a community; A system including:

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] In modern society, busy schedules at work and in daily life mean that people have less time to devote to planning and arranging trips. Travelers are increasingly seeking personal, moving experiences rather than simply sightseeing. However, there is a lack of easy ways to capture the emotions and moments of a trip in beautiful video. Furthermore, there are insufficient effective ways to share these moving experiences with other users. In these circumstances, there is a need for a system that allows users to easily plan, record, and share personalized, moving trips. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: means for receiving image data from a user device; means for analyzing the image data and identifying destinations the user has not yet visited; means for automatically generating a personalized travel plan based on the destinations; means for arranging accommodations and transportation based on the user's preferences and budget; means for recording emotional data during the trip; means for automatically inserting appropriate music into a travel record video based on the emotional data; means for automatically generating the travel record video; and means for sharing the video with a community. By further including means for receiving voice data and text data from the user device and analyzing the emotional data from the voice data and text data, emotions during the trip can be recorded more accurately. Furthermore, by including means for acquiring current location data from the user device and inserting location information into the travel record video based on the location data, local information can be reflected in the travel record video. This provides a personalized travel experience and allows users to easily record and share moving moments with other users.

[0006] A "user terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[0007] "Image data" refers to still images or image files taken by a user using an electronic device.

[0008] "Analysis" is the processing of data to extract useful information.

[0009] A "destination" is a place to travel to, a destination to, or a place to visit.

[0010] "Travel Plan" means a plan that includes places to visit, dates, and associated activities.

[0011] "Accommodation" means a hotel, inn, or other accommodation where you stay during your trip.

[0012] "Transportation" means an airplane, train, bus, or other means of transportation used for travel.

[0013] "Emotion data" is information that represents the user's emotional state, and is obtained from text, audio, images, and the like.

[0014] "Travel recording video" is video created by combining emotional data and various media data recorded during a trip.

[0015] "Music" refers to emotionally appropriate music or background music inserted into travel footage.

[0016] "Community" is an online platform where users can share travel footage and share their impressions and experiences with other users.

[0017] "Audio data" refers to audio files and real-time audio information recorded by users.

[0018] "Text data" refers to documents and messages entered by the user.

[0019] "Location information" is information about the user's current location or the locations visited during a trip, obtained by GPS data or the like. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0042] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0043] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0044] The server then automatically generates a personalized travel plan based on the suggested destinations, taking into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, activities, etc. The user can then select the plan that best suits them.

[0045] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0046] While traveling, users use their devices to record emotional data. While sending photos taken, audio recordings, and text input to a server, the user's current location information is also sent to the server using the GPS function. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0047] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip and moving moments, as well as music that matches the user's emotions. As a result, users can easily create moving travel video.

[0048] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0049] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0050] This system allows users to easily plan a personalized and exciting trip, record the experience, and share it.

[0051] The processing flow will be explained below.

[0052] Step 1:

[0053] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0054] Step 2:

[0055] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0056] Step 3:

[0057] The server loads an AI model to analyze the received image data, which uses image recognition technology to identify destinations the user has not yet visited.

[0058] Step 4:

[0059] The server uses an AI model to analyze the location where the image data was taken and suggests several unvisited destinations. These destination suggestions are then compared with a database to select the most suitable travel destination for the user.

[0060] Step 5:

[0061] Based on the proposed destinations, the server automatically generates a personalized travel plan that takes into account the user's preferences and budget. This travel plan includes destinations, activities, tourist spots, restaurants, etc.

[0062] Step 6:

[0063] The user uses the terminal to check the proposed travel plans and select the one that suits them best, and the selected plan is sent to the server.

[0064] Step 7:

[0065] The server will book accommodation and arrange transportation based on the user's selection. The server will book the best accommodation and transportation based on the user's budget and available offers.

[0066] Step 8:

[0067] The device records the user's emotional data while traveling. The user takes photos, records audio, and writes down their impressions in text. This data is then sent from the device to the server as needed.

[0068] Step 9:

[0069] The server analyzes the emotional data sent during the trip. The server combines photos, voice, text, and GPS data to identify the user's emotions. This data includes emotions such as joy, emotion, and excitement.

[0070] Step 10:

[0071] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0072] Step 11:

[0073] After the trip, the server automatically generates a video recording of the trip based on the recorded emotional data and the selected music. This video includes photos of the places visited during the trip, moving moments, and the selected music.

[0074] Step 12:

[0075] The user uses the device to check the generated travel record video and selects an option to share it with the community. The device then sends a share request to the server.

[0076] Step 13:

[0077] The server receives the request and posts the generated travel video to the community, allowing users to share their moving experiences with other users.

[0078] By following the steps above, users can easily plan a personalized and exciting trip, record the experience, and share it.

[0079] Example 1

[0080] 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."

[0081] In recent years, there has been a demand for personalized travel plans, but there is no system that can automatically generate and manage the entire travel plan, suggesting unvisited destinations based on the user's past visits and preferences. As a result, users must spend a huge amount of time and effort researching and making arrangements themselves, and it is not easy to create memorable videos based on emotional records recorded during the trip. In addition, there is a lack of appropriate means to efficiently analyze emotional data during travel and share it after the trip.

[0082] 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.

[0083] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing photos from the user terminal using image recognition technology to identify destinations the user has not yet visited, and means for analyzing emotional data from photos and audio taken during the trip and adding music that matches the emotions to the travel record video after the trip. This enables users to easily create personalized travel plans, record emotional data during the trip, and create and share moving videos after the trip.

[0084] A "user terminal" is an information processing device that can be operated by a user, and includes a smartphone, a tablet, a computer, and the like.

[0085] "Image data" is digital data that includes visual information such as still images and videos.

[0086] A "server" is an information system that receives and transmits data from user terminals via a network and performs information processing.

[0087] "AI model" refers to an algorithm and its trained model that uses artificial intelligence technology to analyze and predict data.

[0088] A "Travel Plan" is a detailed plan that includes travel destinations, attractions, accommodations, transportation, and activities.

[0089] "Emotion data" is data that reflects the user's psychological state, and is extracted from photographs, recorded voice, text data, and the like.

[0090] "Travel recording video" is video generated based on photos taken and audio recorded by the user during their trip, as well as analyzed emotional data.

[0091] A "community" is a platform for sharing and interacting with user-generated content with other users.

[0092] "Image recognition technology" is a technology for analyzing digital images and recognizing specific objects or features.

[0093] "Music that matches emotions" is music selected based on the user's emotional data during the trip, and is played along with the video.

[0094] The present invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0095] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. The device then sends this image data to the server.

[0096] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis uses image recognition technology. Specifically, it uses a machine learning platform such as TENSORFLOW (registered trademark) to analyze the images. Based on the analysis results, the server presents potential destinations. At this time, it uses a database to identify places the user has not visited before.

[0097] The server uses this information to automatically generate a personalized travel plan that takes into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, and activities. The plan is generated using an automated process using algorithms. This information is then compiled in JSON format and sent to the user's device.

[0098] The user selects the travel plan that best suits their preferences from the multiple options displayed on the device. After the selection, the server arranges the optimal accommodation and transportation (flight or other means of transportation). Specifically, it accesses the hotel and flight reservation systems via API and executes the reservation procedure.

[0099] While traveling, users record emotional data using their smartphones or tablets. Specifically, they send photos they take, audio recordings, written text notes, and GPS location information to a server. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0100] After the trip is completed, the server selects music that matches the emotions based on the recorded emotion data and automatically generates a travel video. For this purpose, a program that combines music and video is executed using a video editing library (e.g., FFmpeg).

[0101] The generated travel video is shared with the community via the user's device. The user taps the "Share" button to make the video public within the community.

[0102] As a concrete example, a user may upload a photo of a city they have visited in the past (e.g., a photo of Tokyo Tower), and Nasu Highlands, which they have not yet visited, may be suggested as their next travel destination. Based on this suggestion, the server automatically generates a travel plan including tourist attractions, restaurants, and activities in Nasu Highlands and presents it to the user. During the trip, photos taken by the user and audio recordings made by the user in Nasu Highlands are sent to the server, and after the trip, a travel video is automatically generated accompanied by music that matches the user's emotions. Users can share this video in the community and share their impressions with other users.

[0103] An example of a prompt sentence is, "I uploaded a photo of Tokyo Tower. Can you recommend some places I haven't visited yet for my next trip?"

[0104] As described above, the system of the present invention enables users to easily create personalized travel plans, record emotional data during their trip, and create and share moving videos after their trip.

[0105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0106] Step 1:

[0107] A user launches a travel planning application on their user device, such as a smartphone or tablet. Next, they select photos of places they have visited in the past and upload the image data. The device sends the selected image data to the server. The input is the photos of places they have visited in the past, and the output is the image data sent to the server. At this point, the user taps the "Upload Image" button and selects a photo from their photo library.

[0108] Step 2:

[0109] The server receives image data from the user's device and analyzes it using an AI model. In this process, image recognition technology is used to analyze the data. The input is the image data received from the user's device, and the output is the analysis results, which are potential unvisited destinations. Specifically, the server runs a Python script and uses TensorFlow to input the image data into the AI ​​model and obtain the analysis results.

[0110] Step 3:

[0111] The server identifies destinations that the user has not visited from the database based on the analysis results. The input is the image recognition analysis result, and the output is a list of candidate destinations that the user has not visited. At this time, the server searches the database using an SQL query to narrow down the list to places that the user has not visited before.

[0112] Step 4:

[0113] The server automatically generates a travel plan from a list of candidate destinations, taking into account the user's preferences and budget. The input is a list of candidate destinations that have not yet been visited, and the user's preferences and budget information, and the output is an automatically generated individual travel plan. The server executes the plan generation algorithm and generates travel plan information in JSON format.

[0114] Step 5:

[0115] The user selects the travel plan that best suits them from multiple plans displayed on the device. The input is the travel plan information displayed on the device, and the output is the selected travel plan. The user selects the desired plan through the application interface and taps the select button.

[0116] Step 6:

[0117] The server arranges accommodation and transportation based on the selected plan. The input is the selected travel plan, and the output is reservation information for accommodation and transportation. The server uses APIs to access hotel reservation systems and airline systems and automatically completes the reservation process.

[0118] Step 7:

[0119] While traveling, users record emotional data using smartphones or tablets. The inputs are photos taken, audio recordings, written text notes, and GPS data, and the output is emotional data sent to a server. The user uploads this data to the server in real time.

[0120] Step 8:

[0121] The server analyzes emotions such as joy, excitement, and so on based on the recorded emotional data. The input is the emotional data transmitted during the trip, and the output is the analyzed emotional data. The server processes the data using an analysis algorithm to determine the emotional state.

[0122] Step 9:

[0123] After the trip is over, the server automatically generates a travel video based on the emotion data. The input is the analyzed emotion data and the video data from the trip, and the output is the automatically generated travel video. To achieve this, the server uses a video editing library such as FFmpeg to run a program that combines music and video.

[0124] Step 10:

[0125] The generated travel record video is shared with the community via the user's device. The input is the automatically generated travel record video, and the output is the information to be shared with the community. The user taps the "Share" button on the application and sets the video to be made public within the community.

[0126] (Application example 1)

[0127] 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."

[0128] In recent years, the amount of information collected when planning a trip has increased, as has the time and effort required to create the plan. Therefore, users need a way to easily and efficiently create travel plans that fit their preferences and budget, and to record their emotions during the trip and preserve them as memories. Another issue is the lack of a system that provides a comprehensive service from planning to execution and recording the trip. The present invention aims to solve these issues and provide users with the ability to create personalized travel plans and create moving travel video records.

[0129] 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.

[0130] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating a personalized travel plan, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing image data from the user terminal and identifying potential destinations using an AI model and inputting prompt text using the generating AI model, and means for automatically suggesting and arranging activities, accommodations, and transportation according to the travel plan generated using the AI ​​model. This enables users to easily obtain personalized travel plans, generate travel record videos based on their emotions, and share them with a community.

[0131] A "user terminal" is an electronic device that can be operated by a user, and includes smartphones, tablets, personal computers, and the like.

[0132] "Image data" refers to data that includes visual information such as photographs and pictures uploaded from a user terminal.

[0133] "Analysis" is the process of extracting features from received image data and using AI models and other technologies to understand the content.

[0134] "Destination" refers to a place or location that the user plans to visit in the future.

[0135] A "travel plan" is a detailed visit plan for a specified destination, including tourist attractions, restaurants, activities, accommodations, transportation, etc.

[0136] An "AI model" is a mathematical algorithm or model that uses artificial intelligence to analyze data and derive appropriate actions or suggestions.

[0137] A "generative AI model" is an AI model that is trained to generate appropriate outputs for a specific purpose.

[0138] A "prompt" is a specific instruction input to a generative AI model that provides the context for deriving the desired output.

[0139] "Activities" are experiences or actions proposed in a travel plan, including sightseeing, activities, and event participation.

[0140] "Accommodation" refers to facilities such as hotels and guesthouses where users stay during their trip.

[0141] "Transportation" refers to the means of transportation used by the user during the trip, including flights, trains, buses, taxis, and the like.

[0142] "Emotion data" is data that represents the emotions felt by the user during the trip, and is analyzed from photographs, voice, text, etc.

[0143] "Travel footage" is footage that records events, places visited, and moving moments during a trip, and is accompanied by emotional music.

[0144] A "community" is an online gathering or platform where people can share travel plans and recorded footage.

[0145] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0146] Program processing

[0147] 1. First, the user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. The device then sends this image data to the server.

[0148] 2. The server analyzes the received image data using an AI model (e.g., ResNet-50) to identify destinations the user has not yet visited. Based on this, multiple destination candidates are suggested. A prompt sentence is input using the generative AI model to generate a specific travel plan.

[0149] 3. Based on the proposed destinations, the server automatically suggests and arranges suitable accommodations and transportation, taking into account the user's preferences and budget. This travel plan includes tourist spots to visit, restaurants, activities, etc. The user can select the plan that best suits them from these suggested plans.

[0150] 4. During the trip, the user uses the device to record emotional data. The photos taken, voice recordings, and text input by the user are sent to the server. The user's current location information is also sent to the server using the GPS function. The server analyzes this data and records the user's emotions.

[0151] 5. Once the trip is over, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0152] 6. The generated travel video is shared with the community via the user's device. Users can share the generated video with other users and share their impressions and experiences within the community.

[0153] Hardware and software used

[0154] The present invention uses the following hardware and software:

[0155] User devices: smartphones, tablets, computers, etc.

[0156] Server: Cloud server or dedicated server

[0157] AI models: Image analysis models such as ResNet-50 and generative AI models

[0158] GPS function: A smartphone function that obtains the user's location information

[0159] Software: Flask (supports Web API), PyTorch (runs AI models)

[0160] Specific examples

[0161] For example, consider a scenario where a user uploads a photo of a city they previously visited. The AI ​​model analyzes the photo and identifies it as a city. The next possible destination is suggested as a beach, and the generative AI model generates a detailed itinerary using the following prompt:

[0162] Prompt: Suggest a destination the user hasn't visited yet (mountain range, beach, city, etc.) and generate a detailed itinerary with activities available there (hiking, swimming, shopping, etc.), the best accommodations, and transportation options from origin to destination.

[0163] The proposed itinerary includes activities such as hiking and swimming, as well as suitable accommodation and flights. After the trip, an inspiring travel video is generated based on the photos taken by the user and the acquired location information, and shared with the community.

[0164] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0165] Step 1:

[0166] The server receives image data uploaded from the user's device. The user launches a travel planning application on their smartphone, tablet, or other device, selects photos of places they have visited, and sends them to the server. The input data in this case is an image file, which the server receives and stores.

[0167] Step 2:

[0168] The server analyzes the received image data and identifies destinations that the user has not yet visited. Specifically, the server uses an AI model (e.g., ResNet-50) to extract image features and analyze their content. The output is a list of destination candidates identified based on the image.

[0169] Step 3:

[0170] The server generates individual travel plans based on the identified destination candidates. Pre-created prompts are input into the generative AI model, which automatically generates detailed travel plans. The inputs are destination candidates and prompts, and the output is a travel plan that includes places to visit, activities, restaurants, accommodations, and transportation at each destination.

[0171] Step 4:

[0172] The server customizes the generated travel plan, taking into account the user's preferences and budget. Specifically, the AI ​​model arranges the optimal accommodation and transportation based on the user's past preference data and budget information. The input here is the user's preference data and budget information, and the output is a customized travel plan.

[0173] Step 5:

[0174] During the trip, the user's device records emotional data. The user uses the device to record photos taken, voice recordings, and input text data during the trip, and sends them to the server. The input data at this time includes photos, voice, text data, GPS location information, etc., and the server receives and analyzes these to determine the user's emotions.

[0175] Step 6:

[0176] When the trip ends, the server generates a travel video based on the recorded emotional data. Specifically, the server selects appropriate music based on the photos and videos the user took during the trip and the analyzed emotional data to create the video. The input here is emotional data, photos, and music information, and the output is an inspiring travel video.

[0177] Step 7:

[0178] The server shares the generated travel video with the community via the user's device. Users can share this video with other users and share their impressions within the community. The input here is the generated travel video, and the output is sharing with the community.

[0179] These steps enable users to easily obtain personalized travel plans, generate emotion-based travel video recordings, and share them with the community.

[0180] 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.

[0181] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates a personalized travel plan. The present invention also focuses on a system that combines an emotion engine that recognizes the user's emotions.

[0182] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0183] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0184] The server then automatically generates a personalized itinerary based on the suggested destinations, taking into account the user's preferences and budget. This itinerary includes recommended tourist spots, restaurants, activities, etc. The user can then select the itinerary that best suits them.

[0185] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0186] While traveling, users use their devices to record emotional data. Photographs taken, voice recordings, and text input are sent to the server, and the user's current location information is also sent to the server using the GPS function. The emotion engine analyzes this data and identifies the user's emotions. The emotion engine integrates voice, text, and image data to recognize emotions in real time.

[0187] The server analyzes the emotion data transmitted during the trip and identifies the user's emotion based on the data. The server dynamically adjusts the travel plan based on the identified emotion data. For example, if the user feels very happy at a particular tourist spot, the server can suggest other fun places related to this place.

[0188] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data, and automatically generates a travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0189] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0190] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0191] This system allows users to easily plan a personalized and inspiring trip, record and share the excitement. The emotion engine recognizes emotions in real time and adjusts the plan appropriately, providing an even more fulfilling travel experience.

[0192] The processing flow will be explained below.

[0193] Step 1:

[0194] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0195] Step 2:

[0196] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0197] Step 3:

[0198] The server analyzes the received image data. The server uses an AI model to recognize the image and identify destinations the user has not yet visited. The AI ​​model compares the image data with a database and suggests multiple potential destinations that the user has not yet visited.

[0199] Step 4:

[0200] The server automatically generates a personalized travel plan based on the proposed destinations, taking into account the user's preferences and budget. The travel plan includes recommended tourist spots, restaurants, activities, etc.

[0201] Step 5:

[0202] The user uses the terminal to check the proposed travel plans and select the plan that suits them best. The selected plan information is sent from the terminal to the server.

[0203] Step 6:

[0204] The server will then arrange the booking of accommodation and transport based on the user's selection. The server will ensure the best accommodation and transport options based on the user's budget and available offers.

[0205] Step 7:

[0206] When the trip begins, the user uses the device to record photos, audio, and text data during the trip, and emotional data is collected. Experiences and impressions at each point during the trip are recorded and sent from the device to the server.

[0207] Step 8:

[0208] The server analyzes the received emotion data using an emotion engine. It integrates photo, voice, and text data to recognize the user's emotions in real time. The emotion engine identifies emotions such as joy, emotion, and excitement.

[0209] Step 9:

[0210] Based on the results of the emotion engine's analysis, the server dynamically adjusts the travel plan. For example, if a user feels joy at a particular tourist spot, it will suggest additional similar places or experiences.

[0211] Step 10:

[0212] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0213] Step 11:

[0214] Once the trip is over, the server automatically generates a travel video based on the recorded emotional data and selected music. This video includes photos of the places visited and moving moments, as well as music.

[0215] Step 12:

[0216] The user uses the device to view the generated travel video and selects the option to share the video with the community.

[0217] Step 13:

[0218] The server posts the generated travel video to the community and shares it with other users, allowing users to share their travel experiences with other users through the video.

[0219] By following these steps, users can easily plan a personalized and exciting trip, record and share their impressions. In addition, by using an emotion engine, users' emotions can be recognized in real time, further enhancing the travel experience.

[0220] Example 2

[0221] 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."

[0222] When planning a trip, users face the challenge of efficiently identifying previously visited and unvisited locations and automatically generating personalized itineraries. It is also difficult to efficiently record emotional data during a trip and adjust itineraries in real time based on that information. Furthermore, there is a lack of a way to automatically generate recorded video footage after a trip and easily share moving experiences with other users. An integrated system that solves these problems is needed.

[0223] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving image data, means for analyzing the image data to identify destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for analyzing the emotional data and dynamically adjusting the travel plan, means for automatically inserting appropriate music into the travel record video based on the emotional data, means for automatically generating the travel record video, and means for sharing the video with a community. This allows the user to identify unvisited destinations based on past travel data and easily create an individual travel plan, adjust the plan in real time according to emotions even during the trip, and automatically generate and share moving record video after the trip.

[0224] A "user terminal" is a portable information processing device that can be operated by a user, such as a smartphone or tablet.

[0225] "Image data" refers to digital data of still images taken with a digital camera, smartphone, etc.

[0226] "Analysis" is the process of processing received data and extracting specific information.

[0227] A "destination" is a geographic location that a user plans to visit.

[0228] A "travel plan" is a detailed plan including the places the user will visit during the trip, the activities to be carried out, the accommodations and transportation to be used, etc.

[0229] "Accommodation" refers to a facility where a user stays during a trip.

[0230] "Transportation" refers to the means of transportation used by the user during a trip, including airplanes, trains, buses, etc.

[0231] "Emotional data" is digital data related to a user's emotions and moods, and includes information analyzed from text, audio, and images.

[0232] "Dynamic adjustment" means changing plans and settings in real time based on acquired data.

[0233] "Travel footage" refers to a digital video file that compiles travel memories, including photos and videos taken during the trip, and appropriate music.

[0234] "Automatic music insertion" means that a program selects music and incorporates it into video or other media based on specific criteria or data.

[0235] "Share with the community" means uploading the generated content to an online platform for public viewing and sharing with other users.

[0236] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Hereinafter, an embodiment of the system will be described in detail.

[0237] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. This image data is then sent from the device to the server.

[0238] The server stores the received image data in storage and analyzes it using an image recognition model (e.g., TensorFlow). Based on the analysis results, it identifies destinations that the user has not yet visited. This identification process is performed by combining image recognition technology and a database.

[0239] The server then automatically generates a personalized itinerary based on the identified destinations, using a user profiling system and recommendation algorithms (e.g., Scikit-Learn), including sightseeing spots, dining options, and activities.

[0240] The user selects the travel plan that best suits them from the presented options. The server then arranges appropriate accommodations and transportation based on the user's selection. A reservation system API (e.g., Booking.com API) is used here.

[0241] To record emotion data while traveling, a user takes photos, records voice, and inputs text using a smartphone or tablet, and the device transmits this data and GPS information to a server. The server then uses an emotion analysis engine (e.g., IBM Watson®) to analyze the data and identify the user's emotion.

[0242] Furthermore, the server dynamically adjusts the itinerary based on the analysis of the emotional data during the trip. For example, if the user feels very happy at a particular tourist spot, it will add other enjoyable places related to this place to the itinerary.

[0243] Once the trip is over, the server aggregates all recorded data, selects music that matches the emotions based on the recorded emotional data, and automatically generates a travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server then uploads the generated video to cloud storage and provides it to the user.

[0244] Finally, users can view the travel video recorded on their own devices and then share it with the community, allowing them to share their impressions and experiences with other users.

[0245] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0246] Examples of prompts to be input to a generative AI model include:

[0247] "I uploaded photos from my past trips. Please suggest the best destinations for my next trip and a travel plan that suits my preferences."

[0248] "Recommend fun places to visit in real time based on your location and sentiment data."

[0249] As described above, the present invention is a system that efficiently supports users in planning their travels, enriches their travel experiences, and enables them to share those experiences with other users.

[0250] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0251] Step 1:

[0252] The user launches a travel planning application from a smartphone or tablet. The application inputs photos from the user's past trips. The user can select photos of places they have visited and upload the image data. The image data is sent from the device to the server. The device then processes the selected image data and sends it to the server via the Internet. When the server receives the image data, it saves it in storage.

[0253] Step 2:

[0254] The server analyzes the received image data using an image recognition model (e.g., TensorFlow). The input is the received image data, and the output is a list of destinations that the user has not visited. Once the server analyzes the image data, it identifies destinations that the user has not visited based on the results. The process of identifying unvisited destinations is carried out by combining image recognition technology with a database.

[0255] Step 3:

[0256] The server generates a travel plan based on the identified destinations and taking into account user profile data (preferences, budget, etc.). The input is destination information and user profile data, and the output is a personalized travel plan. A generative AI model and recommendation algorithm (e.g., Scikit-Learn) are used here. The generated travel plan includes tourist attractions, restaurants, activities, etc. The server presents the generated travel plan to the user.

[0257] Step 4:

[0258] The user selects the travel plan that best suits their preferences from the presented plans. The input is the user's selection, and the output is the selected plan information. The server arranges accommodation and transportation based on the selected plan. It uses a reservation system API (e.g., Booking.com API) to make accommodation reservations and flight arrangements. Once the reservation is complete, the server provides confirmation information to the user.

[0259] Step 5:

[0260] While traveling, users use their smartphones or tablets to take photos, record audio, and input text data. These data become the input for emotion data. GPS information is also acquired. The device sends this data and location information to a server. The server analyzes the received emotion data using an emotion analysis engine (e.g., IBM Watson) to identify the user's emotion. The output is the emotion analysis results.

[0261] Step 6:

[0262] The server dynamically adjusts the travel plan based on the analysis results of the acquired emotion data. The input is the emotion analysis result, and the output is the adjusted plan. For example, if the user feels very happy at a particular tourist spot, the server adds other related enjoyable places to the plan. The server notifies the user of the adjusted plan and receives feedback.

[0263] Step 7:

[0264] When the trip ends, the server selects music that matches the emotion based on the recorded emotional data and generates a travel video. The input is the emotional data and photos and videos taken during the trip, and the output is the travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server uploads the generated video file to cloud storage and provides the user with a download link.

[0265] Step 8:

[0266] The user can view the generated travel video on their own device. After viewing, the user can select the option to share the video with the community. To share the video, the device uploads the video to a social networking site or dedicated community platform via the server and generates a sharing URL. Other users can view the shared video and share their impressions by commenting and reacting.

[0267] (Application example 2)

[0268] 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."

[0269] There is a demand for greater efficiency in robotic work within factories, but with current systems, it is difficult to identify areas or procedures that robots have not yet been to, and work plans must be generated and adjusted manually. Furthermore, it is not possible to analyze the robot's work efficiency and satisfaction in real time and dynamically adjust work plans, making it difficult to maximize work efficiency.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0271] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for receiving image data within a factory and identifying unvisited areas, means for automatically generating an optimal work plan based on the areas, means for recording data during work and analyzing work efficiency, and means for dynamically adjusting the work plan based on the analysis results. This improves the efficiency of robot work within the factory and enables the generation and adjustment of optimal work plans in real time.

[0272] A "user terminal" refers to an information terminal used by a user, such as a mobile phone, tablet, or personal computer.

[0273] "Image data" refers to digital still image data captured by a camera or image sensor.

[0274] "Analysis" is the process of breaking down data using specific algorithms or programs to extract meaning and features.

[0275] An "unvisited destination" is a place or area that the user has no record of having visited before.

[0276] A "personalized itinerary" is a travel plan designed to meet the needs and preferences of a particular user.

[0277] "Accommodation" refers to the hotel or accommodation facility where the user stays during the trip.

[0278] "Transportation" refers to the means of transportation used during travel, such as airplanes, trains, and buses.

[0279] "Emotional data" refers to data such as voice, text, and images that represent the user's emotional state.

[0280] "Travel footage" refers to footage that records the places and events visited during a trip.

[0281] "Share with community" means sharing information with other users through a specific group or social network.

[0282] "In-factory image data" refers to image data obtained from cameras and image sensors installed within the factory.

[0283] An "unvisited area" is an area in the factory where the robot has not yet performed any work.

[0284] A "work plan" is a procedure or schedule for effectively carrying out a specific task.

[0285] "Data during work" refers to the motion data and environmental data recorded when the robot is working.

[0286] "Analyzing efficiency" means quantifying and analyzing data to evaluate the efficiency of work.

[0287] "Dynamic adjustment" means making changes and corrections automatically in real time based on the situation.

[0288] This invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Furthermore, this system also has the function of identifying unvisited areas and dynamically adjusting an optimal work plan to improve the efficiency of robotic work in factories.

[0289] The server first receives image data from the user's device. The user's device can be a smartphone, tablet, or PC, and the image data captured using the device's camera is sent to the server. The server then analyzes the image data using Python image recognition technology and libraries such as TensorFlow and OpenCV to identify destinations the user has not yet visited or areas within the factory where work has not yet been done.

[0290] The server then automatically generates personalized travel plans and optimized work plans based on the analyzed data. Travel plans include tourist spots, restaurants, and activities to visit, while factory work plans include the necessary procedures, tools, and work order. Database management systems and algorithms are used to tailor the plans based on the user's preferences and budget.

[0291] While traveling or working, the user or robot records emotional data. This data includes photos taken, voice recordings, input text data, and data from sensors. This data is sent to a server in real time and analyzed by an emotion engine. The emotion engine analyzes emotions using, for example, NLP libraries and voice analysis tools, and dynamically adjusts travel plans or work plans based on the results.

[0292] Once the trip is over, the server automatically selects music that matches the emotions based on the recorded emotional data and automatically generates a video recording of the trip. The video includes photos of the places visited during the trip, moving moments, and music that matches the emotions. Similarly, in factories, processes can be recorded to maximize work efficiency based on work data, and the data can be used to improve work in the future.

[0293] An example of a specific prompt might be, "Please upload image data to identify areas that the robot has not yet worked on." This allows the system to collect and analyze the necessary data as it goes along, dynamically providing the optimal plan.

[0294] This invention makes it possible to automatically generate individual travel plans and in-factory work plans and adjust them in real time, significantly improving the convenience and efficiency of users and robots.

[0295] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0296] Step 1:

[0297] The user terminal uses a camera to take images of the inside of a factory or a travel destination, and temporarily stores the image data in local storage. This image data is then sent to a server via a network. The input is the image data from the user terminal, and the output is the image data sent to the server.

[0298] Step 2:

[0299] The server analyzes the received image data using an AI model (e.g., TensorFlow or OpenCV). As a result of the analysis, it identifies destinations and areas that have not been visited by the user or robot. The input is the image data received in step 1, and the output is information on the identified destinations and areas that have not been visited.

[0300] Step 3:

[0301] The server generates individual travel plans or factory work plans based on the identified unvisited destinations or unworked areas. The travel plans include tourist spots, restaurants, and activities, while the work plans include work procedures and necessary tools. The input is the destination or area information identified in step 2, and the output is an automatically generated travel or work plan.

[0302] Step 4:

[0303] The server arranges accommodation and transportation based on the user's preferences and budget. It accesses a database and reserves accommodation and transportation that meets the requirements. The input is the user's preferences and budget information, and the output is information about the reserved accommodation and transportation.

[0304] Step 5:

[0305] A user or a robot records emotional data while traveling or working. This emotional data includes photographs, recorded voice, text data, and sensor data. This data is sent to a server in real time. The input is emotional data, and the output is the recorded emotional data.

[0306] Step 6:

[0307] The server analyzes the received emotional data using an emotion engine. The emotion engine analyzes the data using, for example, an NLP library or a voice analysis tool, to identify the emotional state of the user or robot. The input is the emotional data received in step 5, and the output is the analyzed emotional state information.

[0308] Step 7:

[0309] The server dynamically adjusts the travel or work plan based on the analysis of the emotion data. It changes the plan depending on whether the user or robot is satisfied. The input is the emotional state information obtained in step 6, and the output is the adjusted travel or work plan.

[0310] As a concrete example, a prompt sentence could be, "Please upload image data and identify areas that the robot has not yet worked on." By following this prompt, the system can collect the necessary data, analyze it, and dynamically provide the optimal plan.

[0311] 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.

[0312] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0313] 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.

[0314] [Second embodiment]

[0315] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0316] 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.

[0317] 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).

[0318] 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.

[0319] 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.

[0320] 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).

[0321] 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.

[0322] 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.

[0323] 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.

[0324] 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.

[0325] 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.

[0326] 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."

[0327] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0328] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0329] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0330] The server then automatically generates a personalized travel plan based on the suggested destinations, taking into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, activities, etc. The user can then select the plan that best suits them.

[0331] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0332] While traveling, users use their devices to record emotional data. While sending photos taken, audio recordings, and text input to a server, the user's current location information is also sent to the server using the GPS function. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0333] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip and moving moments, as well as music that matches the user's emotions. As a result, users can easily create moving travel video.

[0334] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0335] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0336] This system allows users to easily plan a personalized and exciting trip, record the experience, and share it.

[0337] The processing flow will be explained below.

[0338] Step 1:

[0339] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0340] Step 2:

[0341] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0342] Step 3:

[0343] The server loads an AI model to analyze the received image data, which uses image recognition technology to identify destinations the user has not yet visited.

[0344] Step 4:

[0345] The server uses an AI model to analyze the location where the image data was taken and suggests several unvisited destinations. These destination suggestions are then compared with a database to select the most suitable travel destination for the user.

[0346] Step 5:

[0347] Based on the proposed destinations, the server automatically generates a personalized travel plan that takes into account the user's preferences and budget. This travel plan includes destinations, activities, tourist spots, restaurants, etc.

[0348] Step 6:

[0349] The user uses the terminal to check the proposed travel plans and select the one that suits them best, and the selected plan is sent to the server.

[0350] Step 7:

[0351] The server will book accommodation and arrange transportation based on the user's selection. The server will book the best accommodation and transportation based on the user's budget and available offers.

[0352] Step 8:

[0353] The device records the user's emotional data while traveling. The user takes photos, records audio, and writes down their impressions in text. This data is then sent from the device to the server as needed.

[0354] Step 9:

[0355] The server analyzes the emotional data sent during the trip. The server combines photos, voice, text, and GPS data to identify the user's emotions. This data includes emotions such as joy, emotion, and excitement.

[0356] Step 10:

[0357] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0358] Step 11:

[0359] After the trip, the server automatically generates a video recording of the trip based on the recorded emotional data and the selected music. This video includes photos of the places visited during the trip, moving moments, and the selected music.

[0360] Step 12:

[0361] The user uses the device to check the generated travel record video and selects an option to share it with the community. The device then sends a share request to the server.

[0362] Step 13:

[0363] The server receives the request and posts the generated travel video to the community, allowing users to share their moving experiences with other users.

[0364] By following the steps above, users can easily plan a personalized and exciting trip, record the experience, and share it.

[0365] Example 1

[0366] 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."

[0367] In recent years, there has been a demand for personalized travel plans, but there is no system that can automatically generate and manage the entire travel plan, suggesting unvisited destinations based on the user's past visits and preferences. As a result, users must spend a huge amount of time and effort researching and making arrangements themselves, and it is not easy to create memorable videos based on emotional records recorded during the trip. In addition, there is a lack of appropriate means to efficiently analyze emotional data during travel and share it after the trip.

[0368] 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.

[0369] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing photos from the user terminal using image recognition technology to identify destinations the user has not yet visited, and means for analyzing emotional data from photos and audio taken during the trip and adding music that matches the emotions to the travel record video after the trip. This enables users to easily create personalized travel plans, record emotional data during the trip, and create and share moving videos after the trip.

[0370] A "user terminal" is an information processing device that can be operated by a user, and includes a smartphone, a tablet, a computer, and the like.

[0371] "Image data" is digital data that includes visual information such as still images and videos.

[0372] A "server" is an information system that receives and transmits data from user terminals via a network and performs information processing.

[0373] "AI model" refers to an algorithm and its trained model that uses artificial intelligence technology to analyze and predict data.

[0374] A "Travel Plan" is a detailed plan that includes travel destinations, attractions, accommodations, transportation, and activities.

[0375] "Emotion data" is data that reflects the user's psychological state, and is extracted from photographs, recorded voice, text data, and the like.

[0376] "Travel recording video" is video generated based on photos taken and audio recorded by the user during their trip, as well as analyzed emotional data.

[0377] A "community" is a platform for sharing and interacting with user-generated content with other users.

[0378] "Image recognition technology" is a technology for analyzing digital images and recognizing specific objects or features.

[0379] "Music that matches emotions" is music selected based on the user's emotional data during the trip, and is played along with the video.

[0380] The present invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0381] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. The device then sends this image data to the server.

[0382] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis uses image recognition technology. Specifically, it uses machine learning platforms such as TensorFlow to analyze the images. Based on the analysis results, the server presents potential destinations. At this time, it uses a database to identify places the user has not visited before.

[0383] The server uses this information to automatically generate a personalized travel plan that takes into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, and activities. The plan is generated using an automated process using algorithms. This information is then compiled in JSON format and sent to the user's device.

[0384] The user selects the travel plan that best suits their preferences from the multiple options displayed on the device. After the selection, the server arranges the optimal accommodation and transportation (flight or other means of transportation). Specifically, it accesses the hotel and flight reservation systems via API and executes the reservation procedure.

[0385] While traveling, users record emotional data using their smartphones or tablets. Specifically, they send photos they take, audio recordings, written text notes, and GPS location information to a server. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0386] After the trip is completed, the server selects music that matches the emotions based on the recorded emotion data and automatically generates a travel video. For this purpose, a program that combines music and video is executed using a video editing library (e.g., FFmpeg).

[0387] The generated travel video is shared with the community via the user's device. The user taps the "Share" button to make the video public within the community.

[0388] As a concrete example, a user may upload a photo of a city they have visited in the past (e.g., a photo of Tokyo Tower), and Nasu Highlands, which they have not yet visited, may be suggested as their next travel destination. Based on this suggestion, the server automatically generates a travel plan including tourist attractions, restaurants, and activities in Nasu Highlands and presents it to the user. During the trip, photos taken by the user and audio recordings made by the user in Nasu Highlands are sent to the server, and after the trip, a travel video is automatically generated accompanied by music that matches the user's emotions. Users can share this video in the community and share their impressions with other users.

[0389] An example of a prompt sentence is, "I uploaded a photo of Tokyo Tower. Can you recommend some places I haven't visited yet for my next trip?"

[0390] As described above, the system of the present invention enables users to easily create personalized travel plans, record emotional data during their trip, and create and share moving videos after their trip.

[0391] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0392] Step 1:

[0393] A user launches a travel planning application on their user device, such as a smartphone or tablet. Next, they select photos of places they have visited in the past and upload the image data. The device sends the selected image data to the server. The input is the photos of places they have visited in the past, and the output is the image data sent to the server. At this point, the user taps the "Upload Image" button and selects a photo from their photo library.

[0394] Step 2:

[0395] The server receives image data from the user's device and analyzes it using an AI model. In this process, image recognition technology is used to analyze the data. The input is the image data received from the user's device, and the output is the analysis results, which are potential unvisited destinations. Specifically, the server runs a Python script and uses TensorFlow to input the image data into the AI ​​model and obtain the analysis results.

[0396] Step 3:

[0397] The server identifies destinations that the user has not visited from the database based on the analysis results. The input is the image recognition analysis result, and the output is a list of candidate destinations that the user has not visited. At this time, the server searches the database using an SQL query to narrow down the list to places that the user has not visited before.

[0398] Step 4:

[0399] The server automatically generates a travel plan from a list of candidate destinations, taking into account the user's preferences and budget. The input is a list of candidate destinations that have not yet been visited, and the user's preferences and budget information, and the output is an automatically generated individual travel plan. The server executes the plan generation algorithm and generates travel plan information in JSON format.

[0400] Step 5:

[0401] The user selects the travel plan that best suits them from multiple plans displayed on the device. The input is the travel plan information displayed on the device, and the output is the selected travel plan. The user selects the desired plan through the application interface and taps the select button.

[0402] Step 6:

[0403] The server arranges accommodation and transportation based on the selected plan. The input is the selected travel plan, and the output is reservation information for accommodation and transportation. The server uses APIs to access hotel reservation systems and airline systems and automatically completes the reservation process.

[0404] Step 7:

[0405] While traveling, users record emotional data using smartphones or tablets. The inputs are photos taken, audio recordings, written text notes, and GPS data, and the output is emotional data sent to a server. The user uploads this data to the server in real time.

[0406] Step 8:

[0407] The server analyzes emotions such as joy, excitement, and so on based on the recorded emotional data. The input is the emotional data transmitted during the trip, and the output is the analyzed emotional data. The server processes the data using an analysis algorithm to determine the emotional state.

[0408] Step 9:

[0409] After the trip is over, the server automatically generates a travel video based on the emotion data. The input is the analyzed emotion data and the video data from the trip, and the output is the automatically generated travel video. To achieve this, the server uses a video editing library such as FFmpeg to run a program that combines music and video.

[0410] Step 10:

[0411] The generated travel record video is shared with the community via the user's device. The input is the automatically generated travel record video, and the output is the information to be shared with the community. The user taps the "Share" button on the application and sets the video to be made public within the community.

[0412] (Application example 1)

[0413] 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."

[0414] In recent years, the amount of information collected when planning a trip has increased, as has the time and effort required to create the plan. Therefore, users need a way to easily and efficiently create travel plans that fit their preferences and budget, and to record their emotions during the trip and preserve them as memories. Another issue is the lack of a system that provides a comprehensive service from planning to execution and recording the trip. The present invention aims to solve these issues and provide users with the ability to create personalized travel plans and create moving travel video records.

[0415] 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.

[0416] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating a personalized travel plan, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing image data from the user terminal and identifying potential destinations using an AI model and inputting prompt text using the generating AI model, and means for automatically suggesting and arranging activities, accommodations, and transportation according to the travel plan generated using the AI ​​model. This enables users to easily obtain personalized travel plans, generate travel record videos based on their emotions, and share them with a community.

[0417] A "user terminal" is an electronic device that can be operated by a user, and includes smartphones, tablets, personal computers, and the like.

[0418] "Image data" refers to data that includes visual information such as photographs and pictures uploaded from a user terminal.

[0419] "Analysis" is the process of extracting features from received image data and using AI models and other technologies to understand the content.

[0420] "Destination" refers to a place or location that the user plans to visit in the future.

[0421] A "travel plan" is a detailed visit plan for a specified destination, including tourist attractions, restaurants, activities, accommodations, transportation, etc.

[0422] An "AI model" is a mathematical algorithm or model that uses artificial intelligence to analyze data and derive appropriate actions or suggestions.

[0423] A "generative AI model" is an AI model that is trained to generate appropriate outputs for a specific purpose.

[0424] A "prompt" is a specific instruction input to a generative AI model that provides the context for deriving the desired output.

[0425] "Activities" are experiences or actions proposed in a travel plan, including sightseeing, activities, and event participation.

[0426] "Accommodation" refers to facilities such as hotels and guesthouses where users stay during their trip.

[0427] "Transportation" refers to the means of transportation used by the user during the trip, including flights, trains, buses, taxis, and the like.

[0428] "Emotion data" is data that represents the emotions felt by the user during the trip, and is analyzed from photographs, voice, text, etc.

[0429] "Travel footage" is footage that records events, places visited, and moving moments during a trip, and is accompanied by emotional music.

[0430] A "community" is an online gathering or platform where people can share travel plans and recorded footage.

[0431] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0432] Program processing

[0433] 1. First, the user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. The device then sends this image data to the server.

[0434] 2. The server analyzes the received image data using an AI model (e.g., ResNet-50) to identify destinations the user has not yet visited. Based on this, multiple destination candidates are suggested. A prompt sentence is input using the generative AI model to generate a specific travel plan.

[0435] 3. Based on the proposed destinations, the server automatically suggests and arranges suitable accommodations and transportation, taking into account the user's preferences and budget. This travel plan includes tourist spots to visit, restaurants, activities, etc. The user can select the plan that best suits them from these suggested plans.

[0436] 4. During the trip, the user uses the device to record emotional data. The photos taken, voice recordings, and text input by the user are sent to the server. The user's current location information is also sent to the server using the GPS function. The server analyzes this data and records the user's emotions.

[0437] 5. Once the trip is over, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0438] 6. The generated travel video is shared with the community via the user's device. Users can share the generated video with other users and share their impressions and experiences within the community.

[0439] Hardware and software used

[0440] The present invention uses the following hardware and software:

[0441] User devices: smartphones, tablets, computers, etc.

[0442] Server: Cloud server or dedicated server

[0443] AI models: Image analysis models such as ResNet-50 and generative AI models

[0444] GPS function: A smartphone function that obtains the user's location information

[0445] Software: Flask (supports Web API), PyTorch (runs AI models)

[0446] Specific examples

[0447] For example, consider a scenario where a user uploads a photo of a city they previously visited. The AI ​​model analyzes the photo and identifies it as a city. The next possible destination is suggested as a beach, and the generative AI model generates a detailed itinerary using the following prompt:

[0448] Prompt: Suggest a destination the user hasn't visited yet (mountain range, beach, city, etc.) and generate a detailed itinerary with activities available there (hiking, swimming, shopping, etc.), the best accommodations, and transportation options from origin to destination.

[0449] The proposed itinerary includes activities such as hiking and swimming, as well as suitable accommodation and flights. After the trip, an inspiring travel video is generated based on the photos taken by the user and the acquired location information, and shared with the community.

[0450] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0451] Step 1:

[0452] The server receives image data uploaded from the user's device. The user launches a travel planning application on their smartphone, tablet, or other device, selects photos of places they have visited, and sends them to the server. The input data in this case is an image file, which the server receives and stores.

[0453] Step 2:

[0454] The server analyzes the received image data and identifies destinations that the user has not yet visited. Specifically, the server uses an AI model (e.g., ResNet-50) to extract image features and analyze their content. The output is a list of destination candidates identified based on the image.

[0455] Step 3:

[0456] The server generates individual travel plans based on the identified destination candidates. Pre-created prompts are input into the generative AI model, which automatically generates detailed travel plans. The inputs are destination candidates and prompts, and the output is a travel plan that includes places to visit, activities, restaurants, accommodations, and transportation at each destination.

[0457] Step 4:

[0458] The server customizes the generated travel plan, taking into account the user's preferences and budget. Specifically, the AI ​​model arranges the optimal accommodation and transportation based on the user's past preference data and budget information. The input here is the user's preference data and budget information, and the output is a customized travel plan.

[0459] Step 5:

[0460] During the trip, the user's device records emotional data. The user uses the device to record photos taken, voice recordings, and input text data during the trip, and sends them to the server. The input data at this time includes photos, voice, text data, GPS location information, etc., and the server receives and analyzes these to determine the user's emotions.

[0461] Step 6:

[0462] When the trip ends, the server generates a travel video based on the recorded emotional data. Specifically, the server selects appropriate music based on the photos and videos the user took during the trip and the analyzed emotional data to create the video. The input here is emotional data, photos, and music information, and the output is an inspiring travel video.

[0463] Step 7:

[0464] The server shares the generated travel video with the community via the user's device. Users can share this video with other users and share their impressions within the community. The input here is the generated travel video, and the output is sharing with the community.

[0465] These steps enable users to easily obtain personalized travel plans, generate emotion-based travel video recordings, and share them with the community.

[0466] 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.

[0467] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates a personalized travel plan. The present invention also focuses on a system that combines an emotion engine that recognizes the user's emotions.

[0468] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0469] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0470] The server then automatically generates a personalized itinerary based on the suggested destinations, taking into account the user's preferences and budget. This itinerary includes recommended tourist spots, restaurants, activities, etc. The user can then select the itinerary that best suits them.

[0471] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0472] While traveling, users use their devices to record emotional data. Photographs taken, voice recordings, and text input are sent to the server, and the user's current location information is also sent to the server using the GPS function. The emotion engine analyzes this data and identifies the user's emotions. The emotion engine integrates voice, text, and image data to recognize emotions in real time.

[0473] The server analyzes the emotion data transmitted during the trip and identifies the user's emotion based on the data. The server dynamically adjusts the travel plan based on the identified emotion data. For example, if the user feels very happy at a particular tourist spot, the server can suggest other fun places related to this place.

[0474] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data, and automatically generates a travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0475] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0476] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0477] This system allows users to easily plan a personalized and inspiring trip, record and share the excitement. The emotion engine recognizes emotions in real time and adjusts the plan appropriately, providing an even more fulfilling travel experience.

[0478] The processing flow will be explained below.

[0479] Step 1:

[0480] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0481] Step 2:

[0482] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0483] Step 3:

[0484] The server analyzes the received image data. The server uses an AI model to recognize the image and identify destinations the user has not yet visited. The AI ​​model compares the image data with a database and suggests multiple potential destinations that the user has not yet visited.

[0485] Step 4:

[0486] The server automatically generates a personalized travel plan based on the proposed destinations, taking into account the user's preferences and budget. The travel plan includes recommended tourist spots, restaurants, activities, etc.

[0487] Step 5:

[0488] The user uses the terminal to check the proposed travel plans and select the plan that suits them best. The selected plan information is sent from the terminal to the server.

[0489] Step 6:

[0490] The server will then arrange the booking of accommodation and transport based on the user's selection. The server will ensure the best accommodation and transport options based on the user's budget and available offers.

[0491] Step 7:

[0492] When the trip begins, the user uses the device to record photos, audio, and text data during the trip, and emotional data is collected. Experiences and impressions at each point during the trip are recorded and sent from the device to the server.

[0493] Step 8:

[0494] The server analyzes the received emotion data using an emotion engine. It integrates photo, voice, and text data to recognize the user's emotions in real time. The emotion engine identifies emotions such as joy, emotion, and excitement.

[0495] Step 9:

[0496] Based on the results of the emotion engine's analysis, the server dynamically adjusts the travel plan. For example, if a user feels joy at a particular tourist spot, it will suggest additional similar places or experiences.

[0497] Step 10:

[0498] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0499] Step 11:

[0500] Once the trip is over, the server automatically generates a travel video based on the recorded emotional data and selected music. This video includes photos of the places visited and moving moments, as well as music.

[0501] Step 12:

[0502] The user uses the device to view the generated travel video and selects the option to share the video with the community.

[0503] Step 13:

[0504] The server posts the generated travel video to the community and shares it with other users, allowing users to share their travel experiences with other users through the video.

[0505] By following these steps, users can easily plan a personalized and exciting trip, record and share their impressions. In addition, by using an emotion engine, users' emotions can be recognized in real time, further enhancing the travel experience.

[0506] Example 2

[0507] 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."

[0508] When planning a trip, users face the challenge of efficiently identifying previously visited and unvisited locations and automatically generating personalized itineraries. It is also difficult to efficiently record emotional data during a trip and adjust itineraries in real time based on that information. Furthermore, there is a lack of a way to automatically generate recorded video footage after a trip and easily share moving experiences with other users. An integrated system that solves these problems is needed.

[0509] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving image data, means for analyzing the image data to identify destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for analyzing the emotional data and dynamically adjusting the travel plan, means for automatically inserting appropriate music into the travel record video based on the emotional data, means for automatically generating the travel record video, and means for sharing the video with a community. This allows the user to identify unvisited destinations based on past travel data and easily create an individual travel plan, adjust the plan in real time according to emotions even during the trip, and automatically generate and share moving record video after the trip.

[0510] A "user terminal" is a portable information processing device that can be operated by a user, such as a smartphone or tablet.

[0511] "Image data" refers to digital data of still images taken with a digital camera, smartphone, etc.

[0512] "Analysis" is the process of processing received data and extracting specific information.

[0513] A "destination" is a geographic location that a user plans to visit.

[0514] A "travel plan" is a detailed plan including the places the user will visit during the trip, the activities to be carried out, the accommodations and transportation to be used, etc.

[0515] "Accommodation" refers to a facility where a user stays during a trip.

[0516] "Transportation" refers to the means of transportation used by the user during a trip, including airplanes, trains, buses, etc.

[0517] "Emotional data" is digital data related to a user's emotions and moods, and includes information analyzed from text, audio, and images.

[0518] "Dynamic adjustment" means changing plans and settings in real time based on acquired data.

[0519] "Travel footage" refers to a digital video file that compiles travel memories, including photos and videos taken during the trip, and appropriate music.

[0520] "Automatic music insertion" means that a program selects music and incorporates it into video or other media based on specific criteria or data.

[0521] "Share with the community" means uploading the generated content to an online platform for public viewing and sharing with other users.

[0522] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Hereinafter, an embodiment of the system will be described in detail.

[0523] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. This image data is then sent from the device to the server.

[0524] The server stores the received image data in storage and analyzes it using an image recognition model (e.g., TensorFlow). Based on the analysis results, it identifies destinations that the user has not yet visited. This identification process is performed by combining image recognition technology and a database.

[0525] The server then automatically generates a personalized itinerary based on the identified destinations, using a user profiling system and recommendation algorithms (e.g., Scikit-Learn), including sightseeing spots, dining options, and activities.

[0526] The user selects the travel plan that best suits them from the presented options. The server then arranges appropriate accommodations and transportation based on the user's selection. A reservation system API (e.g., Booking.com API) is used here.

[0527] To record emotion data while traveling, users use their smartphones or tablets to take photos, record voice, input text, etc., and the devices send this data and GPS information to a server. The server then uses an emotion analysis engine (e.g., IBM Watson) to analyze this data and identify the user's emotion.

[0528] Furthermore, the server dynamically adjusts the itinerary based on the analysis of the emotional data during the trip. For example, if the user feels very happy at a particular tourist spot, it will add other enjoyable places related to this place to the itinerary.

[0529] Once the trip is over, the server aggregates all recorded data, selects music that matches the emotions based on the recorded emotional data, and automatically generates a travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server then uploads the generated video to cloud storage and provides it to the user.

[0530] Finally, users can view the travel video recorded on their own devices and then share it with the community, allowing them to share their impressions and experiences with other users.

[0531] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0532] Examples of prompts to be input to a generative AI model include:

[0533] "I uploaded photos from my past trips. Please suggest the best destinations for my next trip and a travel plan that suits my preferences."

[0534] "Recommend fun places to visit in real time based on your location and sentiment data."

[0535] As described above, the present invention is a system that efficiently supports users in planning their travels, enriches their travel experiences, and enables them to share those experiences with other users.

[0536] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0537] Step 1:

[0538] The user launches a travel planning application from a smartphone or tablet. The application inputs photos from the user's past trips. The user can select photos of places they have visited and upload the image data. The image data is sent from the device to the server. The device then processes the selected image data and sends it to the server via the Internet. When the server receives the image data, it saves it in storage.

[0539] Step 2:

[0540] The server analyzes the received image data using an image recognition model (e.g., TensorFlow). The input is the received image data, and the output is a list of destinations that the user has not visited. Once the server analyzes the image data, it identifies destinations that the user has not visited based on the results. The process of identifying unvisited destinations is carried out by combining image recognition technology with a database.

[0541] Step 3:

[0542] The server generates a travel plan based on the identified destinations and taking into account user profile data (preferences, budget, etc.). The input is destination information and user profile data, and the output is a personalized travel plan. A generative AI model and recommendation algorithm (e.g., Scikit-Learn) are used here. The generated travel plan includes tourist attractions, restaurants, activities, etc. The server presents the generated travel plan to the user.

[0543] Step 4:

[0544] The user selects the travel plan that best suits their preferences from the presented plans. The input is the user's selection, and the output is the selected plan information. The server arranges accommodation and transportation based on the selected plan. It uses a reservation system API (e.g., Booking.com API) to make accommodation reservations and flight arrangements. Once the reservation is complete, the server provides confirmation information to the user.

[0545] Step 5:

[0546] While traveling, users use their smartphones or tablets to take photos, record audio, and input text data. These data become the input for emotion data. GPS information is also acquired. The device sends this data and location information to a server. The server analyzes the received emotion data using an emotion analysis engine (e.g., IBM Watson) to identify the user's emotion. The output is the emotion analysis results.

[0547] Step 6:

[0548] The server dynamically adjusts the travel plan based on the analysis results of the acquired emotion data. The input is the emotion analysis result, and the output is the adjusted plan. For example, if the user feels very happy at a particular tourist spot, the server adds other related enjoyable places to the plan. The server notifies the user of the adjusted plan and receives feedback.

[0549] Step 7:

[0550] When the trip ends, the server selects music that matches the emotion based on the recorded emotional data and generates a travel video. The input is the emotional data and photos and videos taken during the trip, and the output is the travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server uploads the generated video file to cloud storage and provides the user with a download link.

[0551] Step 8:

[0552] The user can view the generated travel video on their own device. After viewing, the user can select the option to share the video with the community. To share the video, the device uploads the video to a social networking site or dedicated community platform via the server and generates a sharing URL. Other users can view the shared video and share their impressions by commenting and reacting.

[0553] (Application example 2)

[0554] 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."

[0555] There is a demand for greater efficiency in robotic work within factories, but with current systems, it is difficult to identify areas or procedures that robots have not yet been to, and work plans must be generated and adjusted manually. Furthermore, it is not possible to analyze the robot's work efficiency and satisfaction in real time and dynamically adjust work plans, making it difficult to maximize work efficiency.

[0556] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0557] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for receiving image data within a factory and identifying unvisited areas, means for automatically generating an optimal work plan based on the areas, means for recording data during work and analyzing work efficiency, and means for dynamically adjusting the work plan based on the analysis results. This improves the efficiency of robot work within the factory and enables the generation and adjustment of optimal work plans in real time.

[0558] A "user terminal" refers to an information terminal used by a user, such as a mobile phone, tablet, or personal computer.

[0559] "Image data" refers to digital still image data captured by a camera or image sensor.

[0560] "Analysis" is the process of breaking down data using specific algorithms or programs to extract meaning and features.

[0561] An "unvisited destination" is a place or area that the user has no record of having visited before.

[0562] A "personalized itinerary" is a travel plan designed to meet the needs and preferences of a particular user.

[0563] "Accommodation" refers to the hotel or accommodation facility where the user stays during the trip.

[0564] "Transportation" refers to the means of transportation used during travel, such as airplanes, trains, and buses.

[0565] "Emotional data" refers to data such as voice, text, and images that represent the user's emotional state.

[0566] "Travel footage" refers to footage that records the places and events visited during a trip.

[0567] "Share with community" means sharing information with other users through a specific group or social network.

[0568] "In-factory image data" refers to image data obtained from cameras and image sensors installed within the factory.

[0569] An "unvisited area" is an area in the factory where the robot has not yet performed any work.

[0570] A "work plan" is a procedure or schedule for effectively carrying out a specific task.

[0571] "Data during work" refers to the motion data and environmental data recorded when the robot is working.

[0572] "Analyzing efficiency" means quantifying and analyzing data to evaluate the efficiency of work.

[0573] "Dynamic adjustment" means making changes and corrections automatically in real time based on the situation.

[0574] This invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Furthermore, this system also has the function of identifying unvisited areas and dynamically adjusting an optimal work plan to improve the efficiency of robotic work in factories.

[0575] The server first receives image data from the user's device. The user's device can be a smartphone, tablet, or PC, and the image data captured using the device's camera is sent to the server. The server then analyzes the image data using Python image recognition technology and libraries such as TensorFlow and OpenCV to identify destinations the user has not yet visited or areas within the factory where work has not yet been done.

[0576] The server then automatically generates personalized travel plans and optimized work plans based on the analyzed data. Travel plans include tourist spots, restaurants, and activities to visit, while factory work plans include the necessary procedures, tools, and work order. Database management systems and algorithms are used to tailor the plans based on the user's preferences and budget.

[0577] While traveling or working, the user or robot records emotional data. This data includes photos taken, voice recordings, input text data, and data from sensors. This data is sent to a server in real time and analyzed by an emotion engine. The emotion engine analyzes emotions using, for example, NLP libraries and voice analysis tools, and dynamically adjusts travel plans or work plans based on the results.

[0578] Once the trip is over, the server automatically selects music that matches the emotions based on the recorded emotional data and automatically generates a video recording of the trip. The video includes photos of the places visited during the trip, moving moments, and music that matches the emotions. Similarly, in factories, processes can be recorded to maximize work efficiency based on work data, and the data can be used to improve work in the future.

[0579] An example of a specific prompt might be, "Please upload image data to identify areas that the robot has not yet worked on." This allows the system to collect and analyze the necessary data as it goes along, dynamically providing the optimal plan.

[0580] This invention makes it possible to automatically generate individual travel plans and in-factory work plans and adjust them in real time, significantly improving the convenience and efficiency of users and robots.

[0581] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0582] Step 1:

[0583] The user terminal uses a camera to take images of the inside of a factory or a travel destination, and temporarily stores the image data in local storage. This image data is then sent to a server via a network. The input is the image data from the user terminal, and the output is the image data sent to the server.

[0584] Step 2:

[0585] The server analyzes the received image data using an AI model (e.g., TensorFlow or OpenCV). As a result of the analysis, it identifies destinations and areas that have not been visited by the user or robot. The input is the image data received in step 1, and the output is information on the identified destinations and areas that have not been visited.

[0586] Step 3:

[0587] The server generates individual travel plans or factory work plans based on the identified unvisited destinations or unworked areas. The travel plans include tourist spots, restaurants, and activities, while the work plans include work procedures and necessary tools. The input is the destination or area information identified in step 2, and the output is an automatically generated travel or work plan.

[0588] Step 4:

[0589] The server arranges accommodation and transportation based on the user's preferences and budget. It accesses a database and reserves accommodation and transportation that meets the requirements. The input is the user's preferences and budget information, and the output is information about the reserved accommodation and transportation.

[0590] Step 5:

[0591] A user or a robot records emotional data while traveling or working. This emotional data includes photographs, recorded voice, text data, and sensor data. This data is sent to a server in real time. The input is emotional data, and the output is the recorded emotional data.

[0592] Step 6:

[0593] The server analyzes the received emotional data using an emotion engine. The emotion engine analyzes the data using, for example, an NLP library or a voice analysis tool, to identify the emotional state of the user or robot. The input is the emotional data received in step 5, and the output is the analyzed emotional state information.

[0594] Step 7:

[0595] The server dynamically adjusts the travel or work plan based on the analysis of the emotion data. It changes the plan depending on whether the user or robot is satisfied. The input is the emotional state information obtained in step 6, and the output is the adjusted travel or work plan.

[0596] As a concrete example, a prompt sentence could be, "Please upload image data and identify areas that the robot has not yet worked on." By following this prompt, the system can collect the necessary data, analyze it, and dynamically provide the optimal plan.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] [Third embodiment]

[0601] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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."

[0613] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0614] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0615] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0616] The server then automatically generates a personalized travel plan based on the suggested destinations, taking into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, activities, etc. The user can then select the plan that best suits them.

[0617] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0618] While traveling, users use their devices to record emotional data. While sending photos taken, audio recordings, and text input to a server, the user's current location information is also sent to the server using the GPS function. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0619] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip and moving moments, as well as music that matches the user's emotions. As a result, users can easily create moving travel video.

[0620] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0621] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0622] This system allows users to easily plan a personalized and exciting trip, record the experience, and share it.

[0623] The processing flow will be explained below.

[0624] Step 1:

[0625] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0626] Step 2:

[0627] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0628] Step 3:

[0629] The server loads an AI model to analyze the received image data, which uses image recognition technology to identify destinations the user has not yet visited.

[0630] Step 4:

[0631] The server uses an AI model to analyze the location where the image data was taken and suggests several unvisited destinations. These destination suggestions are then compared with a database to select the most suitable travel destination for the user.

[0632] Step 5:

[0633] Based on the proposed destinations, the server automatically generates a personalized travel plan that takes into account the user's preferences and budget. This travel plan includes destinations, activities, tourist spots, restaurants, etc.

[0634] Step 6:

[0635] The user uses the terminal to check the proposed travel plans and select the one that suits them best, and the selected plan is sent to the server.

[0636] Step 7:

[0637] The server will book accommodation and arrange transportation based on the user's selection. The server will book the best accommodation and transportation based on the user's budget and available offers.

[0638] Step 8:

[0639] The device records the user's emotional data while traveling. The user takes photos, records audio, and writes down their impressions in text. This data is then sent from the device to the server as needed.

[0640] Step 9:

[0641] The server analyzes the emotional data sent during the trip. The server combines photos, voice, text, and GPS data to identify the user's emotions. This data includes emotions such as joy, emotion, and excitement.

[0642] Step 10:

[0643] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0644] Step 11:

[0645] After the trip, the server automatically generates a video recording of the trip based on the recorded emotional data and the selected music. This video includes photos of the places visited during the trip, moving moments, and the selected music.

[0646] Step 12:

[0647] The user uses the device to check the generated travel record video and selects an option to share it with the community. The device then sends a share request to the server.

[0648] Step 13:

[0649] The server receives the request and posts the generated travel video to the community, allowing users to share their moving experiences with other users.

[0650] By following the steps above, users can easily plan a personalized and exciting trip, record the experience, and share it.

[0651] Example 1

[0652] 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."

[0653] In recent years, there has been a demand for personalized travel plans, but there is no system that can automatically generate and manage the entire travel plan, suggesting unvisited destinations based on the user's past visits and preferences. As a result, users must spend a huge amount of time and effort researching and making arrangements themselves, and it is not easy to create memorable videos based on emotional records recorded during the trip. In addition, there is a lack of appropriate means to efficiently analyze emotional data during travel and share it after the trip.

[0654] 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.

[0655] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing photos from the user terminal using image recognition technology to identify destinations the user has not yet visited, and means for analyzing emotional data from photos and audio taken during the trip and adding music that matches the emotions to the travel record video after the trip. This enables users to easily create personalized travel plans, record emotional data during the trip, and create and share moving videos after the trip.

[0656] A "user terminal" is an information processing device that can be operated by a user, and includes a smartphone, a tablet, a computer, and the like.

[0657] "Image data" is digital data that includes visual information such as still images and videos.

[0658] A "server" is an information system that receives and transmits data from user terminals via a network and performs information processing.

[0659] "AI model" refers to an algorithm and its trained model that uses artificial intelligence technology to analyze and predict data.

[0660] A "Travel Plan" is a detailed plan that includes travel destinations, attractions, accommodations, transportation, and activities.

[0661] "Emotion data" is data that reflects the user's psychological state, and is extracted from photographs, recorded voice, text data, and the like.

[0662] "Travel recording video" is video generated based on photos taken and audio recorded by the user during their trip, as well as analyzed emotional data.

[0663] A "community" is a platform for sharing and interacting with user-generated content with other users.

[0664] "Image recognition technology" is a technology for analyzing digital images and recognizing specific objects or features.

[0665] "Music that matches emotions" is music selected based on the user's emotional data during the trip, and is played along with the video.

[0666] The present invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0667] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. The device then sends this image data to the server.

[0668] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis uses image recognition technology. Specifically, it uses machine learning platforms such as TensorFlow to analyze the images. Based on the analysis results, the server presents potential destinations. At this time, it uses a database to identify places the user has not visited before.

[0669] The server uses this information to automatically generate a personalized travel plan that takes into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, and activities. The plan is generated using an automated process using algorithms. This information is then compiled in JSON format and sent to the user's device.

[0670] The user selects the travel plan that best suits their preferences from the multiple options displayed on the device. After the selection, the server arranges the optimal accommodation and transportation (flight or other means of transportation). Specifically, it accesses the hotel and flight reservation systems via API and executes the reservation procedure.

[0671] While traveling, users record emotional data using their smartphones or tablets. Specifically, they send photos they take, audio recordings, written text notes, and GPS location information to a server. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0672] After the trip is completed, the server selects music that matches the emotions based on the recorded emotion data and automatically generates a travel video. For this purpose, a program that combines music and video is executed using a video editing library (e.g., FFmpeg).

[0673] The generated travel video is shared with the community via the user's device. The user taps the "Share" button to make the video public within the community.

[0674] As a concrete example, a user may upload a photo of a city they have visited in the past (e.g., a photo of Tokyo Tower), and Nasu Highlands, which they have not yet visited, may be suggested as their next travel destination. Based on this suggestion, the server automatically generates a travel plan including tourist attractions, restaurants, and activities in Nasu Highlands and presents it to the user. During the trip, photos taken by the user and audio recordings made by the user in Nasu Highlands are sent to the server, and after the trip, a travel video is automatically generated accompanied by music that matches the user's emotions. Users can share this video in the community and share their impressions with other users.

[0675] An example of a prompt sentence is, "I uploaded a photo of Tokyo Tower. Can you recommend some places I haven't visited yet for my next trip?"

[0676] As described above, the system of the present invention enables users to easily create personalized travel plans, record emotional data during their trip, and create and share moving videos after their trip.

[0677] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0678] Step 1:

[0679] A user launches a travel planning application on their user device, such as a smartphone or tablet. Next, they select photos of places they have visited in the past and upload the image data. The device sends the selected image data to the server. The input is the photos of places they have visited in the past, and the output is the image data sent to the server. At this point, the user taps the "Upload Image" button and selects a photo from their photo library.

[0680] Step 2:

[0681] The server receives image data from the user's device and analyzes it using an AI model. In this process, image recognition technology is used to analyze the data. The input is the image data received from the user's device, and the output is the analysis results, which are potential unvisited destinations. Specifically, the server runs a Python script and uses TensorFlow to input the image data into the AI ​​model and obtain the analysis results.

[0682] Step 3:

[0683] The server identifies destinations that the user has not visited from the database based on the analysis results. The input is the image recognition analysis result, and the output is a list of candidate destinations that the user has not visited. At this time, the server searches the database using an SQL query to narrow down the list to places that the user has not visited before.

[0684] Step 4:

[0685] The server automatically generates a travel plan from a list of candidate destinations, taking into account the user's preferences and budget. The input is a list of candidate destinations that have not yet been visited, and the user's preferences and budget information, and the output is an automatically generated individual travel plan. The server executes the plan generation algorithm and generates travel plan information in JSON format.

[0686] Step 5:

[0687] The user selects the travel plan that best suits them from multiple plans displayed on the device. The input is the travel plan information displayed on the device, and the output is the selected travel plan. The user selects the desired plan through the application interface and taps the select button.

[0688] Step 6:

[0689] The server arranges accommodation and transportation based on the selected plan. The input is the selected travel plan, and the output is reservation information for accommodation and transportation. The server uses APIs to access hotel reservation systems and airline systems and automatically completes the reservation process.

[0690] Step 7:

[0691] While traveling, users record emotional data using smartphones or tablets. The inputs are photos taken, audio recordings, written text notes, and GPS data, and the output is emotional data sent to a server. The user uploads this data to the server in real time.

[0692] Step 8:

[0693] The server analyzes emotions such as joy, excitement, and so on based on the recorded emotional data. The input is the emotional data transmitted during the trip, and the output is the analyzed emotional data. The server processes the data using an analysis algorithm to determine the emotional state.

[0694] Step 9:

[0695] After the trip is over, the server automatically generates a travel video based on the emotion data. The input is the analyzed emotion data and the video data from the trip, and the output is the automatically generated travel video. To achieve this, the server uses a video editing library such as FFmpeg to run a program that combines music and video.

[0696] Step 10:

[0697] The generated travel record video is shared with the community via the user's device. The input is the automatically generated travel record video, and the output is the information to be shared with the community. The user taps the "Share" button on the application and sets the video to be made public within the community.

[0698] (Application example 1)

[0699] 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."

[0700] In recent years, the amount of information collected when planning a trip has increased, as has the time and effort required to create the plan. Therefore, users need a way to easily and efficiently create travel plans that fit their preferences and budget, and to record their emotions during the trip and preserve them as memories. Another issue is the lack of a system that provides a comprehensive service from planning to execution and recording the trip. The present invention aims to solve these issues and provide users with the ability to create personalized travel plans and create moving travel video records.

[0701] 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.

[0702] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating a personalized travel plan, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing image data from the user terminal and identifying potential destinations using an AI model and inputting prompt text using the generating AI model, and means for automatically suggesting and arranging activities, accommodations, and transportation according to the travel plan generated using the AI ​​model. This enables users to easily obtain personalized travel plans, generate travel record videos based on their emotions, and share them with a community.

[0703] A "user terminal" is an electronic device that can be operated by a user, and includes smartphones, tablets, personal computers, and the like.

[0704] "Image data" refers to data that includes visual information such as photographs and pictures uploaded from a user terminal.

[0705] "Analysis" is the process of extracting features from received image data and using AI models and other technologies to understand the content.

[0706] "Destination" refers to a place or location that the user plans to visit in the future.

[0707] A "travel plan" is a detailed visit plan for a specified destination, including tourist attractions, restaurants, activities, accommodations, transportation, etc.

[0708] An "AI model" is a mathematical algorithm or model that uses artificial intelligence to analyze data and derive appropriate actions or suggestions.

[0709] A "generative AI model" is an AI model that is trained to generate appropriate outputs for a specific purpose.

[0710] A "prompt" is a specific instruction input to a generative AI model that provides the context for deriving the desired output.

[0711] "Activities" are experiences or actions proposed in a travel plan, including sightseeing, activities, and event participation.

[0712] "Accommodation" refers to facilities such as hotels and guesthouses where users stay during their trip.

[0713] "Transportation" refers to the means of transportation used by the user during the trip, including flights, trains, buses, taxis, and the like.

[0714] "Emotion data" is data that represents the emotions felt by the user during the trip, and is analyzed from photographs, voice, text, etc.

[0715] "Travel footage" is footage that records events, places visited, and moving moments during a trip, and is accompanied by emotional music.

[0716] A "community" is an online gathering or platform where people can share travel plans and recorded footage.

[0717] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0718] Program processing

[0719] 1. First, the user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. The device then sends this image data to the server.

[0720] 2. The server analyzes the received image data using an AI model (e.g., ResNet-50) to identify destinations the user has not yet visited. Based on this, multiple destination candidates are suggested. A prompt sentence is input using the generative AI model to generate a specific travel plan.

[0721] 3. Based on the proposed destinations, the server automatically suggests and arranges suitable accommodations and transportation, taking into account the user's preferences and budget. This travel plan includes tourist spots to visit, restaurants, activities, etc. The user can select the plan that best suits them from these suggested plans.

[0722] 4. During the trip, the user uses the device to record emotional data. The photos taken, voice recordings, and text input by the user are sent to the server. The user's current location information is also sent to the server using the GPS function. The server analyzes this data and records the user's emotions.

[0723] 5. Once the trip is over, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0724] 6. The generated travel video is shared with the community via the user's device. Users can share the generated video with other users and share their impressions and experiences within the community.

[0725] Hardware and software used

[0726] The present invention uses the following hardware and software:

[0727] User devices: smartphones, tablets, computers, etc.

[0728] Server: Cloud server or dedicated server

[0729] AI models: Image analysis models such as ResNet-50 and generative AI models

[0730] GPS function: A smartphone function that obtains the user's location information

[0731] Software: Flask (supports Web API), PyTorch (runs AI models)

[0732] Specific examples

[0733] For example, consider a scenario where a user uploads a photo of a city they previously visited. The AI ​​model analyzes the photo and identifies it as a city. The next possible destination is suggested as a beach, and the generative AI model generates a detailed itinerary using the following prompt:

[0734] Prompt: Suggest a destination the user hasn't visited yet (mountain range, beach, city, etc.) and generate a detailed itinerary with activities available there (hiking, swimming, shopping, etc.), the best accommodations, and transportation options from origin to destination.

[0735] The proposed itinerary includes activities such as hiking and swimming, as well as suitable accommodation and flights. After the trip, an inspiring travel video is generated based on the photos taken by the user and the acquired location information, and shared with the community.

[0736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0737] Step 1:

[0738] The server receives image data uploaded from the user's device. The user launches a travel planning application on their smartphone, tablet, or other device, selects photos of places they have visited, and sends them to the server. The input data in this case is an image file, which the server receives and stores.

[0739] Step 2:

[0740] The server analyzes the received image data and identifies destinations that the user has not yet visited. Specifically, the server uses an AI model (e.g., ResNet-50) to extract image features and analyze their content. The output is a list of destination candidates identified based on the image.

[0741] Step 3:

[0742] The server generates individual travel plans based on the identified destination candidates. Pre-created prompts are input into the generative AI model, which automatically generates detailed travel plans. The inputs are destination candidates and prompts, and the output is a travel plan that includes places to visit, activities, restaurants, accommodations, and transportation at each destination.

[0743] Step 4:

[0744] The server customizes the generated travel plan, taking into account the user's preferences and budget. Specifically, the AI ​​model arranges the optimal accommodation and transportation based on the user's past preference data and budget information. The input here is the user's preference data and budget information, and the output is a customized travel plan.

[0745] Step 5:

[0746] During the trip, the user's device records emotional data. The user uses the device to record photos taken, voice recordings, and input text data during the trip, and sends them to the server. The input data at this time includes photos, voice, text data, GPS location information, etc., and the server receives and analyzes these to determine the user's emotions.

[0747] Step 6:

[0748] When the trip ends, the server generates a travel video based on the recorded emotional data. Specifically, the server selects appropriate music based on the photos and videos the user took during the trip and the analyzed emotional data to create the video. The input here is emotional data, photos, and music information, and the output is an inspiring travel video.

[0749] Step 7:

[0750] The server shares the generated travel video with the community via the user's device. Users can share this video with other users and share their impressions within the community. The input here is the generated travel video, and the output is sharing with the community.

[0751] These steps enable users to easily obtain personalized travel plans, generate emotion-based travel video recordings, and share them with the community.

[0752] 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.

[0753] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates a personalized travel plan. The present invention also focuses on a system that combines an emotion engine that recognizes the user's emotions.

[0754] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0755] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0756] The server then automatically generates a personalized itinerary based on the suggested destinations, taking into account the user's preferences and budget. This itinerary includes recommended tourist spots, restaurants, activities, etc. The user can then select the itinerary that best suits them.

[0757] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0758] While traveling, users use their devices to record emotional data. Photographs taken, voice recordings, and text input are sent to the server, and the user's current location information is also sent to the server using the GPS function. The emotion engine analyzes this data and identifies the user's emotions. The emotion engine integrates voice, text, and image data to recognize emotions in real time.

[0759] The server analyzes the emotion data transmitted during the trip and identifies the user's emotion based on the data. The server dynamically adjusts the travel plan based on the identified emotion data. For example, if the user feels very happy at a particular tourist spot, the server can suggest other fun places related to this place.

[0760] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data, and automatically generates a travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[0761] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0762] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0763] This system allows users to easily plan a personalized and inspiring trip, record and share the excitement. The emotion engine recognizes emotions in real time and adjusts the plan appropriately, providing an even more fulfilling travel experience.

[0764] The processing flow will be explained below.

[0765] Step 1:

[0766] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0767] Step 2:

[0768] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0769] Step 3:

[0770] The server analyzes the received image data. The server uses an AI model to recognize the image and identify destinations the user has not yet visited. The AI ​​model compares the image data with a database and suggests multiple potential destinations that the user has not yet visited.

[0771] Step 4:

[0772] The server automatically generates a personalized travel plan based on the proposed destinations, taking into account the user's preferences and budget. The travel plan includes recommended tourist spots, restaurants, activities, etc.

[0773] Step 5:

[0774] The user uses the terminal to check the proposed travel plans and select the plan that suits them best. The selected plan information is sent from the terminal to the server.

[0775] Step 6:

[0776] The server will then arrange the booking of accommodation and transport based on the user's selection. The server will ensure the best accommodation and transport options based on the user's budget and available offers.

[0777] Step 7:

[0778] When the trip begins, the user uses the device to record photos, audio, and text data during the trip, and emotional data is collected. Experiences and impressions at each point during the trip are recorded and sent from the device to the server.

[0779] Step 8:

[0780] The server analyzes the received emotion data using an emotion engine. It integrates photo, voice, and text data to recognize the user's emotions in real time. The emotion engine identifies emotions such as joy, emotion, and excitement.

[0781] Step 9:

[0782] Based on the results of the emotion engine's analysis, the server dynamically adjusts the travel plan. For example, if a user feels joy at a particular tourist spot, it will suggest additional similar places or experiences.

[0783] Step 10:

[0784] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0785] Step 11:

[0786] Once the trip is over, the server automatically generates a travel video based on the recorded emotional data and selected music. This video includes photos of the places visited and moving moments, as well as music.

[0787] Step 12:

[0788] The user uses the device to view the generated travel video and selects the option to share the video with the community.

[0789] Step 13:

[0790] The server posts the generated travel video to the community and shares it with other users, allowing users to share their travel experiences with other users through the video.

[0791] By following these steps, users can easily plan a personalized and exciting trip, record and share their impressions. In addition, by using an emotion engine, users' emotions can be recognized in real time, further enhancing the travel experience.

[0792] Example 2

[0793] 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."

[0794] When planning a trip, users face the challenge of efficiently identifying previously visited and unvisited locations and automatically generating personalized itineraries. It is also difficult to efficiently record emotional data during a trip and adjust itineraries in real time based on that information. Furthermore, there is a lack of a way to automatically generate recorded video footage after a trip and easily share moving experiences with other users. An integrated system that solves these problems is needed.

[0795] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving image data, means for analyzing the image data to identify destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for analyzing the emotional data and dynamically adjusting the travel plan, means for automatically inserting appropriate music into the travel record video based on the emotional data, means for automatically generating the travel record video, and means for sharing the video with a community. This allows the user to identify unvisited destinations based on past travel data and easily create an individual travel plan, adjust the plan in real time according to emotions even during the trip, and automatically generate and share moving record video after the trip.

[0796] A "user terminal" is a portable information processing device that can be operated by a user, such as a smartphone or tablet.

[0797] "Image data" refers to digital data of still images taken with a digital camera, smartphone, etc.

[0798] "Analysis" is the process of processing received data and extracting specific information.

[0799] A "destination" is a geographic location that a user plans to visit.

[0800] A "travel plan" is a detailed plan including the places the user will visit during the trip, the activities to be carried out, the accommodations and transportation to be used, etc.

[0801] "Accommodation" refers to a facility where a user stays during a trip.

[0802] "Transportation" refers to the means of transportation used by the user during a trip, including airplanes, trains, buses, etc.

[0803] "Emotional data" is digital data related to a user's emotions and moods, and includes information analyzed from text, audio, and images.

[0804] "Dynamic adjustment" means changing plans and settings in real time based on acquired data.

[0805] "Travel footage" refers to a digital video file that compiles travel memories, including photos and videos taken during the trip, and appropriate music.

[0806] "Automatic music insertion" means that a program selects music and incorporates it into video or other media based on specific criteria or data.

[0807] "Share with the community" means uploading the generated content to an online platform for public viewing and sharing with other users.

[0808] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Hereinafter, an embodiment of the system will be described in detail.

[0809] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. This image data is then sent from the device to the server.

[0810] The server stores the received image data in storage and analyzes it using an image recognition model (e.g., TensorFlow). Based on the analysis results, it identifies destinations that the user has not yet visited. This identification process is performed by combining image recognition technology and a database.

[0811] The server then automatically generates a personalized itinerary based on the identified destinations, using a user profiling system and recommendation algorithms (e.g., Scikit-Learn), including sightseeing spots, dining options, and activities.

[0812] The user selects the travel plan that best suits them from the presented options. The server then arranges appropriate accommodations and transportation based on the user's selection. A reservation system API (e.g., Booking.com API) is used here.

[0813] To record emotion data while traveling, users use their smartphones or tablets to take photos, record voice, input text, etc., and the devices send this data and GPS information to a server. The server then uses an emotion analysis engine (e.g., IBM Watson) to analyze this data and identify the user's emotion.

[0814] Furthermore, the server dynamically adjusts the itinerary based on the analysis of the emotional data during the trip. For example, if the user feels very happy at a particular tourist spot, it will add other enjoyable places related to this place to the itinerary.

[0815] Once the trip is over, the server aggregates all recorded data, selects music that matches the emotions based on the recorded emotional data, and automatically generates a travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server then uploads the generated video to cloud storage and provides it to the user.

[0816] Finally, users can view the travel video recorded on their own devices and then share it with the community, allowing them to share their impressions and experiences with other users.

[0817] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0818] Examples of prompts to be input to a generative AI model include:

[0819] "I uploaded photos from my past trips. Please suggest the best destinations for my next trip and a travel plan that suits my preferences."

[0820] "Recommend fun places to visit in real time based on your location and sentiment data."

[0821] As described above, the present invention is a system that efficiently supports users in planning their travels, enriches their travel experiences, and enables them to share those experiences with other users.

[0822] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0823] Step 1:

[0824] The user launches a travel planning application from a smartphone or tablet. The application inputs photos from the user's past trips. The user can select photos of places they have visited and upload the image data. The image data is sent from the device to the server. The device then processes the selected image data and sends it to the server via the Internet. When the server receives the image data, it saves it in storage.

[0825] Step 2:

[0826] The server analyzes the received image data using an image recognition model (e.g., TensorFlow). The input is the received image data, and the output is a list of destinations that the user has not visited. Once the server analyzes the image data, it identifies destinations that the user has not visited based on the results. The process of identifying unvisited destinations is carried out by combining image recognition technology with a database.

[0827] Step 3:

[0828] The server generates a travel plan based on the identified destinations and taking into account user profile data (preferences, budget, etc.). The input is destination information and user profile data, and the output is a personalized travel plan. A generative AI model and recommendation algorithm (e.g., Scikit-Learn) are used here. The generated travel plan includes tourist attractions, restaurants, activities, etc. The server presents the generated travel plan to the user.

[0829] Step 4:

[0830] The user selects the travel plan that best suits their preferences from the presented plans. The input is the user's selection, and the output is the selected plan information. The server arranges accommodation and transportation based on the selected plan. It uses a reservation system API (e.g., Booking.com API) to make accommodation reservations and flight arrangements. Once the reservation is complete, the server provides confirmation information to the user.

[0831] Step 5:

[0832] While traveling, users use their smartphones or tablets to take photos, record audio, and input text data. These data become the input for emotion data. GPS information is also acquired. The device sends this data and location information to a server. The server analyzes the received emotion data using an emotion analysis engine (e.g., IBM Watson) to identify the user's emotion. The output is the emotion analysis results.

[0833] Step 6:

[0834] The server dynamically adjusts the travel plan based on the analysis results of the acquired emotion data. The input is the emotion analysis result, and the output is the adjusted plan. For example, if the user feels very happy at a particular tourist spot, the server adds other related enjoyable places to the plan. The server notifies the user of the adjusted plan and receives feedback.

[0835] Step 7:

[0836] When the trip ends, the server selects music that matches the emotion based on the recorded emotional data and generates a travel video. The input is the emotional data and photos and videos taken during the trip, and the output is the travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server uploads the generated video file to cloud storage and provides the user with a download link.

[0837] Step 8:

[0838] The user can view the generated travel video on their own device. After viewing, the user can select the option to share the video with the community. To share the video, the device uploads the video to a social networking site or dedicated community platform via the server and generates a sharing URL. Other users can view the shared video and share their impressions by commenting and reacting.

[0839] (Application example 2)

[0840] 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."

[0841] There is a demand for greater efficiency in robotic work within factories, but with current systems, it is difficult to identify areas or procedures that robots have not yet been to, and work plans must be generated and adjusted manually. Furthermore, it is not possible to analyze the robot's work efficiency and satisfaction in real time and dynamically adjust work plans, making it difficult to maximize work efficiency.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0843] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for receiving image data within a factory and identifying unvisited areas, means for automatically generating an optimal work plan based on the areas, means for recording data during work and analyzing work efficiency, and means for dynamically adjusting the work plan based on the analysis results. This improves the efficiency of robot work within the factory and enables the generation and adjustment of optimal work plans in real time.

[0844] A "user terminal" refers to an information terminal used by a user, such as a mobile phone, tablet, or personal computer.

[0845] "Image data" refers to digital still image data captured by a camera or image sensor.

[0846] "Analysis" is the process of breaking down data using specific algorithms or programs to extract meaning and features.

[0847] An "unvisited destination" is a place or area that the user has no record of having visited before.

[0848] A "personalized itinerary" is a travel plan designed to meet the needs and preferences of a particular user.

[0849] "Accommodation" refers to the hotel or accommodation facility where the user stays during the trip.

[0850] "Transportation" refers to the means of transportation used during travel, such as airplanes, trains, and buses.

[0851] "Emotional data" refers to data such as voice, text, and images that represent the user's emotional state.

[0852] "Travel footage" refers to footage that records the places and events visited during a trip.

[0853] "Share with community" means sharing information with other users through a specific group or social network.

[0854] "In-factory image data" refers to image data obtained from cameras and image sensors installed within the factory.

[0855] An "unvisited area" is an area in the factory where the robot has not yet performed any work.

[0856] A "work plan" is a procedure or schedule for effectively carrying out a specific task.

[0857] "Data during work" refers to the motion data and environmental data recorded when the robot is working.

[0858] "Analyzing efficiency" means quantifying and analyzing data to evaluate the efficiency of work.

[0859] "Dynamic adjustment" means making changes and corrections automatically in real time based on the situation.

[0860] This invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Furthermore, this system also has the function of identifying unvisited areas and dynamically adjusting an optimal work plan to improve the efficiency of robotic work in factories.

[0861] The server first receives image data from the user's device. The user's device can be a smartphone, tablet, or PC, and the image data captured using the device's camera is sent to the server. The server then analyzes the image data using Python image recognition technology and libraries such as TensorFlow and OpenCV to identify destinations the user has not yet visited or areas within the factory where work has not yet been done.

[0862] The server then automatically generates personalized travel plans and optimized work plans based on the analyzed data. Travel plans include tourist spots, restaurants, and activities to visit, while factory work plans include the necessary procedures, tools, and work order. Database management systems and algorithms are used to tailor the plans based on the user's preferences and budget.

[0863] While traveling or working, the user or robot records emotional data. This data includes photos taken, voice recordings, input text data, and data from sensors. This data is sent to a server in real time and analyzed by an emotion engine. The emotion engine analyzes emotions using, for example, NLP libraries and voice analysis tools, and dynamically adjusts travel plans or work plans based on the results.

[0864] Once the trip is over, the server automatically selects music that matches the emotions based on the recorded emotional data and automatically generates a video recording of the trip. The video includes photos of the places visited during the trip, moving moments, and music that matches the emotions. Similarly, in factories, processes can be recorded to maximize work efficiency based on work data, and the data can be used to improve work in the future.

[0865] An example of a specific prompt might be, "Please upload image data to identify areas that the robot has not yet worked on." This allows the system to collect and analyze the necessary data as it goes along, dynamically providing the optimal plan.

[0866] This invention makes it possible to automatically generate individual travel plans and in-factory work plans and adjust them in real time, significantly improving the convenience and efficiency of users and robots.

[0867] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0868] Step 1:

[0869] The user terminal uses a camera to take images of the inside of a factory or a travel destination, and temporarily stores the image data in local storage. This image data is then sent to a server via a network. The input is the image data from the user terminal, and the output is the image data sent to the server.

[0870] Step 2:

[0871] The server analyzes the received image data using an AI model (e.g., TensorFlow or OpenCV). As a result of the analysis, it identifies destinations and areas that have not been visited by the user or robot. The input is the image data received in step 1, and the output is information on the identified destinations and areas that have not been visited.

[0872] Step 3:

[0873] The server generates individual travel plans or factory work plans based on the identified unvisited destinations or unworked areas. The travel plans include tourist spots, restaurants, and activities, while the work plans include work procedures and necessary tools. The input is the destination or area information identified in step 2, and the output is an automatically generated travel or work plan.

[0874] Step 4:

[0875] The server arranges accommodation and transportation based on the user's preferences and budget. It accesses a database and reserves accommodation and transportation that meets the requirements. The input is the user's preferences and budget information, and the output is information about the reserved accommodation and transportation.

[0876] Step 5:

[0877] A user or a robot records emotional data while traveling or working. This emotional data includes photographs, recorded voice, text data, and sensor data. This data is sent to a server in real time. The input is emotional data, and the output is the recorded emotional data.

[0878] Step 6:

[0879] The server analyzes the received emotional data using an emotion engine. The emotion engine analyzes the data using, for example, an NLP library or a voice analysis tool, to identify the emotional state of the user or robot. The input is the emotional data received in step 5, and the output is the analyzed emotional state information.

[0880] Step 7:

[0881] The server dynamically adjusts the travel or work plan based on the analysis of the emotion data. It changes the plan depending on whether the user or robot is satisfied. The input is the emotional state information obtained in step 6, and the output is the adjusted travel or work plan.

[0882] As a concrete example, a prompt sentence could be, "Please upload image data and identify areas that the robot has not yet worked on." By following this prompt, the system can collect the necessary data, analyze it, and dynamically provide the optimal plan.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] [Fourth embodiment]

[0887] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0888] 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.

[0889] 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).

[0890] 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.

[0891] 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.

[0892] 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).

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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."

[0900] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0901] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[0902] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[0903] The server then automatically generates a personalized travel plan based on the suggested destinations, taking into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, activities, etc. The user can then select the plan that best suits them.

[0904] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[0905] While traveling, users use their devices to record emotional data. While sending photos taken, audio recordings, and text input to a server, the user's current location information is also sent to the server using the GPS function. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0906] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip and moving moments, as well as music that matches the user's emotions. As a result, users can easily create moving travel video.

[0907] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[0908] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[0909] This system allows users to easily plan a personalized and exciting trip, record the experience, and share it.

[0910] The processing flow will be explained below.

[0911] Step 1:

[0912] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[0913] Step 2:

[0914] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[0915] Step 3:

[0916] The server loads an AI model to analyze the received image data, which uses image recognition technology to identify destinations the user has not yet visited.

[0917] Step 4:

[0918] The server uses an AI model to analyze the location where the image data was taken and suggests several unvisited destinations. These destination suggestions are then compared with a database to select the most suitable travel destination for the user.

[0919] Step 5:

[0920] Based on the proposed destinations, the server automatically generates a personalized travel plan that takes into account the user's preferences and budget. This travel plan includes destinations, activities, tourist spots, restaurants, etc.

[0921] Step 6:

[0922] The user uses the terminal to check the proposed travel plans and select the one that suits them best, and the selected plan is sent to the server.

[0923] Step 7:

[0924] The server will book accommodation and arrange transportation based on the user's selection. The server will book the best accommodation and transportation based on the user's budget and available offers.

[0925] Step 8:

[0926] The device records the user's emotional data while traveling. The user takes photos, records audio, and writes down their impressions in text. This data is then sent from the device to the server as needed.

[0927] Step 9:

[0928] The server analyzes the emotional data sent during the trip. The server combines photos, voice, text, and GPS data to identify the user's emotions. This data includes emotions such as joy, emotion, and excitement.

[0929] Step 10:

[0930] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[0931] Step 11:

[0932] After the trip, the server automatically generates a video recording of the trip based on the recorded emotional data and the selected music. This video includes photos of the places visited during the trip, moving moments, and the selected music.

[0933] Step 12:

[0934] The user uses the device to check the generated travel record video and selects an option to share it with the community. The device then sends a share request to the server.

[0935] Step 13:

[0936] The server receives the request and posts the generated travel video to the community, allowing users to share their moving experiences with other users.

[0937] By following the steps above, users can easily plan a personalized and exciting trip, record the experience, and share it.

[0938] Example 1

[0939] 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."

[0940] In recent years, there has been a demand for personalized travel plans, but there is no system that can automatically generate and manage the entire travel plan, suggesting unvisited destinations based on the user's past visits and preferences. As a result, users must spend a huge amount of time and effort researching and making arrangements themselves, and it is not easy to create memorable videos based on emotional records recorded during the trip. In addition, there is a lack of appropriate means to efficiently analyze emotional data during travel and share it after the trip.

[0941] 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.

[0942] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing photos from the user terminal using image recognition technology to identify destinations the user has not yet visited, and means for analyzing emotional data from photos and audio taken during the trip and adding music that matches the emotions to the travel record video after the trip. This enables users to easily create personalized travel plans, record emotional data during the trip, and create and share moving videos after the trip.

[0943] A "user terminal" is an information processing device that can be operated by a user, and includes a smartphone, a tablet, a computer, and the like.

[0944] "Image data" is digital data that includes visual information such as still images and videos.

[0945] A "server" is an information system that receives and transmits data from user terminals via a network and performs information processing.

[0946] "AI model" refers to an algorithm and its trained model that uses artificial intelligence technology to analyze and predict data.

[0947] A "Travel Plan" is a detailed plan that includes travel destinations, attractions, accommodations, transportation, and activities.

[0948] "Emotion data" is data that reflects the user's psychological state, and is extracted from photographs, recorded voice, text data, and the like.

[0949] "Travel recording video" is video generated based on photos taken and audio recorded by the user during their trip, as well as analyzed emotional data.

[0950] A "community" is a platform for sharing and interacting with user-generated content with other users.

[0951] "Image recognition technology" is a technology for analyzing digital images and recognizing specific objects or features.

[0952] "Music that matches emotions" is music selected based on the user's emotional data during the trip, and is played along with the video.

[0953] The present invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[0954] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. The device then sends this image data to the server.

[0955] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis uses image recognition technology. Specifically, it uses machine learning platforms such as TensorFlow to analyze the images. Based on the analysis results, the server presents potential destinations. At this time, it uses a database to identify places the user has not visited before.

[0956] The server uses this information to automatically generate a personalized travel plan that takes into account the user's preferences and budget. This plan includes recommended tourist spots, restaurants, and activities. The plan is generated using an automated process using algorithms. This information is then compiled in JSON format and sent to the user's device.

[0957] The user selects the travel plan that best suits their preferences from the multiple options displayed on the device. After the selection, the server arranges the optimal accommodation and transportation (flight or other means of transportation). Specifically, it accesses the hotel and flight reservation systems via API and executes the reservation procedure.

[0958] While traveling, users record emotional data using their smartphones or tablets. Specifically, they send photos they take, audio recordings, written text notes, and GPS location information to a server. The server analyzes the user's emotions from this data and records emotional data such as joy, emotion, and excitement.

[0959] After the trip is completed, the server selects music that matches the emotions based on the recorded emotion data and automatically generates a travel video. For this purpose, a program that combines music and video is executed using a video editing library (e.g., FFmpeg).

[0960] The generated travel video is shared with the community via the user's device. The user taps the "Share" button to make the video public within the community.

[0961] As a concrete example, a user may upload a photo of a city they have visited in the past (e.g., a photo of Tokyo Tower), and Nasu Highlands, which they have not yet visited, may be suggested as their next travel destination. Based on this suggestion, the server automatically generates a travel plan including tourist attractions, restaurants, and activities in Nasu Highlands and presents it to the user. During the trip, photos taken by the user and audio recordings made by the user in Nasu Highlands are sent to the server, and after the trip, a travel video is automatically generated accompanied by music that matches the user's emotions. Users can share this video in the community and share their impressions with other users.

[0962] An example of a prompt sentence is, "I uploaded a photo of Tokyo Tower. Can you recommend some places I haven't visited yet for my next trip?"

[0963] As described above, the system of the present invention enables users to easily create personalized travel plans, record emotional data during their trip, and create and share moving videos after their trip.

[0964] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0965] Step 1:

[0966] A user launches a travel planning application on their user device, such as a smartphone or tablet. Next, they select photos of places they have visited in the past and upload the image data. The device sends the selected image data to the server. The input is the photos of places they have visited in the past, and the output is the image data sent to the server. At this point, the user taps the "Upload Image" button and selects a photo from their photo library.

[0967] Step 2:

[0968] The server receives image data from the user's device and analyzes it using an AI model. In this process, image recognition technology is used to analyze the data. The input is the image data received from the user's device, and the output is the analysis results, which are potential unvisited destinations. Specifically, the server runs a Python script and uses TensorFlow to input the image data into the AI ​​model and obtain the analysis results.

[0969] Step 3:

[0970] The server identifies destinations that the user has not visited from the database based on the analysis results. The input is the image recognition analysis result, and the output is a list of candidate destinations that the user has not visited. At this time, the server searches the database using an SQL query to narrow down the list to places that the user has not visited before.

[0971] Step 4:

[0972] The server automatically generates a travel plan from a list of candidate destinations, taking into account the user's preferences and budget. The input is a list of candidate destinations that have not yet been visited, and the user's preferences and budget information, and the output is an automatically generated individual travel plan. The server executes the plan generation algorithm and generates travel plan information in JSON format.

[0973] Step 5:

[0974] The user selects the travel plan that best suits them from multiple plans displayed on the device. The input is the travel plan information displayed on the device, and the output is the selected travel plan. The user selects the desired plan through the application interface and taps the select button.

[0975] Step 6:

[0976] The server arranges accommodation and transportation based on the selected plan. The input is the selected travel plan, and the output is reservation information for accommodation and transportation. The server uses APIs to access hotel reservation systems and airline systems and automatically completes the reservation process.

[0977] Step 7:

[0978] While traveling, users record emotional data using smartphones or tablets. The inputs are photos taken, audio recordings, written text notes, and GPS data, and the output is emotional data sent to a server. The user uploads this data to the server in real time.

[0979] Step 8:

[0980] The server analyzes emotions such as joy, excitement, and so on based on the recorded emotional data. The input is the emotional data transmitted during the trip, and the output is the analyzed emotional data. The server processes the data using an analysis algorithm to determine the emotional state.

[0981] Step 9:

[0982] After the trip is over, the server automatically generates a travel video based on the emotion data. The input is the analyzed emotion data and the video data from the trip, and the output is the automatically generated travel video. To achieve this, the server uses a video editing library such as FFmpeg to run a program that combines music and video.

[0983] Step 10:

[0984] The generated travel record video is shared with the community via the user's device. The input is the automatically generated travel record video, and the output is the information to be shared with the community. The user taps the "Share" button on the application and sets the video to be made public within the community.

[0985] (Application example 1)

[0986] 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."

[0987] In recent years, the amount of information collected when planning a trip has increased, as has the time and effort required to create the plan. Therefore, users need a way to easily and efficiently create travel plans that fit their preferences and budget, and to record their emotions during the trip and preserve them as memories. Another issue is the lack of a system that provides a comprehensive service from planning to execution and recording the trip. The present invention aims to solve these issues and provide users with the ability to create personalized travel plans and create moving travel video records.

[0988] 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.

[0989] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating a personalized travel plan, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for analyzing image data from the user terminal and identifying potential destinations using an AI model and inputting prompt text using the generating AI model, and means for automatically suggesting and arranging activities, accommodations, and transportation according to the travel plan generated using the AI ​​model. This enables users to easily obtain personalized travel plans, generate travel record videos based on their emotions, and share them with a community.

[0990] A "user terminal" is an electronic device that can be operated by a user, and includes smartphones, tablets, personal computers, and the like.

[0991] "Image data" refers to data that includes visual information such as photographs and pictures uploaded from a user terminal.

[0992] "Analysis" is the process of extracting features from received image data and using AI models and other technologies to understand the content.

[0993] "Destination" refers to a place or location that the user plans to visit in the future.

[0994] A "travel plan" is a detailed visit plan for a specified destination, including tourist attractions, restaurants, activities, accommodations, transportation, etc.

[0995] An "AI model" is a mathematical algorithm or model that uses artificial intelligence to analyze data and derive appropriate actions or suggestions.

[0996] A "generative AI model" is an AI model that is trained to generate appropriate outputs for a specific purpose.

[0997] A "prompt" is a specific instruction input to a generative AI model that provides the context for deriving the desired output.

[0998] "Activities" are experiences or actions proposed in a travel plan, including sightseeing, activities, and event participation.

[0999] "Accommodation" refers to facilities such as hotels and guesthouses where users stay during their trip.

[1000] "Transportation" refers to the means of transportation used by the user during the trip, including flights, trains, buses, taxis, and the like.

[1001] "Emotion data" is data that represents the emotions felt by the user during the trip, and is analyzed from photographs, voice, text, etc.

[1002] "Travel footage" is footage that records events, places visited, and moving moments during a trip, and is accompanied by emotional music.

[1003] A "community" is an online gathering or platform where people can share travel plans and recorded footage.

[1004] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Specific embodiments of the system are described below.

[1005] Program processing

[1006] 1. First, the user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. The device then sends this image data to the server.

[1007] 2. The server analyzes the received image data using an AI model (e.g., ResNet-50) to identify destinations the user has not yet visited. Based on this, multiple destination candidates are suggested. A prompt sentence is input using the generative AI model to generate a specific travel plan.

[1008] 3. Based on the proposed destinations, the server automatically suggests and arranges suitable accommodations and transportation, taking into account the user's preferences and budget. This travel plan includes tourist spots to visit, restaurants, activities, etc. The user can select the plan that best suits them from these suggested plans.

[1009] 4. During the trip, the user uses the device to record emotional data. The photos taken, voice recordings, and text input by the user are sent to the server. The user's current location information is also sent to the server using the GPS function. The server analyzes this data and records the user's emotions.

[1010] 5. Once the trip is over, the server automatically selects music that matches the user's emotions based on the recorded emotional data and inserts it into the travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[1011] 6. The generated travel video is shared with the community via the user's device. Users can share the generated video with other users and share their impressions and experiences within the community.

[1012] Hardware and software used

[1013] The present invention uses the following hardware and software:

[1014] User devices: smartphones, tablets, computers, etc.

[1015] Server: Cloud server or dedicated server

[1016] AI models: Image analysis models such as ResNet-50 and generative AI models

[1017] GPS function: A smartphone function that obtains the user's location information

[1018] Software: Flask (supports Web API), PyTorch (runs AI models)

[1019] Specific examples

[1020] For example, consider a scenario where a user uploads a photo of a city they previously visited. The AI ​​model analyzes the photo and identifies it as a city. The next possible destination is suggested as a beach, and the generative AI model generates a detailed itinerary using the following prompt:

[1021] Prompt: Suggest a destination the user hasn't visited yet (mountain range, beach, city, etc.) and generate a detailed itinerary with activities available there (hiking, swimming, shopping, etc.), the best accommodations, and transportation options from origin to destination.

[1022] The proposed itinerary includes activities such as hiking and swimming, as well as suitable accommodation and flights. After the trip, an inspiring travel video is generated based on the photos taken by the user and the acquired location information, and shared with the community.

[1023] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1024] Step 1:

[1025] The server receives image data uploaded from the user's device. The user launches a travel planning application on their smartphone, tablet, or other device, selects photos of places they have visited, and sends them to the server. The input data in this case is an image file, which the server receives and stores.

[1026] Step 2:

[1027] The server analyzes the received image data and identifies destinations that the user has not yet visited. Specifically, the server uses an AI model (e.g., ResNet-50) to extract image features and analyze their content. The output is a list of destination candidates identified based on the image.

[1028] Step 3:

[1029] The server generates individual travel plans based on the identified destination candidates. Pre-created prompts are input into the generative AI model, which automatically generates detailed travel plans. The inputs are destination candidates and prompts, and the output is a travel plan that includes places to visit, activities, restaurants, accommodations, and transportation at each destination.

[1030] Step 4:

[1031] The server customizes the generated travel plan, taking into account the user's preferences and budget. Specifically, the AI ​​model arranges the optimal accommodation and transportation based on the user's past preference data and budget information. The input here is the user's preference data and budget information, and the output is a customized travel plan.

[1032] Step 5:

[1033] During the trip, the user's device records emotional data. The user uses the device to record photos taken, voice recordings, and input text data during the trip, and sends them to the server. The input data at this time includes photos, voice, text data, GPS location information, etc., and the server receives and analyzes these to determine the user's emotions.

[1034] Step 6:

[1035] When the trip ends, the server generates a travel video based on the recorded emotional data. Specifically, the server selects appropriate music based on the photos and videos the user took during the trip and the analyzed emotional data to create the video. The input here is emotional data, photos, and music information, and the output is an inspiring travel video.

[1036] Step 7:

[1037] The server shares the generated travel video with the community via the user's device. Users can share this video with other users and share their impressions within the community. The input here is the generated travel video, and the output is sharing with the community.

[1038] These steps enable users to easily obtain personalized travel plans, generate emotion-based travel video recordings, and share them with the community.

[1039] 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.

[1040] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates a personalized travel plan. The present invention also focuses on a system that combines an emotion engine that recognizes the user's emotions.

[1041] First, a user launches a travel planning application on their smartphone, tablet, or other user device and uploads image data. At this time, the user can select photos of places they have visited in the past. The device then sends this image data to the server.

[1042] The server analyzes the received image data and uses an AI model to identify destinations the user has not yet visited. This analysis results in multiple suggested destinations. The AI ​​model combines image recognition technology with a database to recommend attractive destinations that the user has not yet visited.

[1043] The server then automatically generates a personalized itinerary based on the suggested destinations, taking into account the user's preferences and budget. This itinerary includes recommended tourist spots, restaurants, activities, etc. The user can then select the itinerary that best suits them.

[1044] Furthermore, the server arranges suitable accommodation and transportation based on the user's selections and preferences, including booking the best accommodation within the user's budget range and arranging flights and other transportation from the origin to the destination.

[1045] While traveling, users use their devices to record emotional data. Photographs taken, voice recordings, and text input are sent to the server, and the user's current location information is also sent to the server using the GPS function. The emotion engine analyzes this data and identifies the user's emotions. The emotion engine integrates voice, text, and image data to recognize emotions in real time.

[1046] The server analyzes the emotion data transmitted during the trip and identifies the user's emotion based on the data. The server dynamically adjusts the travel plan based on the identified emotion data. For example, if the user feels very happy at a particular tourist spot, the server can suggest other fun places related to this place.

[1047] When the trip ends, the server automatically selects music that matches the user's emotions based on the recorded emotional data, and automatically generates a travel video. This video includes photos of the places visited during the trip, moving moments, and music that matches the user's emotions. As a result, users can easily create moving travel video.

[1048] This travel video can be shared with the community via the user's device. Users can share the video they have created with other users, sharing their impressions and experiences within the community.

[1049] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[1050] This system allows users to easily plan a personalized and inspiring trip, record and share the excitement. The emotion engine recognizes emotions in real time and adjusts the plan appropriately, providing an even more fulfilling travel experience.

[1051] The processing flow will be explained below.

[1052] Step 1:

[1053] The user uses the device to select image data stored on their smartphone or tablet, launches a travel planning application, and uploads the selected image data from the application.

[1054] Step 2:

[1055] The terminal sends the uploaded image data to the server. The image data sent from the terminal is received by the server.

[1056] Step 3:

[1057] The server analyzes the received image data. The server uses an AI model to recognize the image and identify destinations the user has not yet visited. The AI ​​model compares the image data with a database and suggests multiple potential destinations that the user has not yet visited.

[1058] Step 4:

[1059] The server automatically generates a personalized travel plan based on the proposed destinations, taking into account the user's preferences and budget. The travel plan includes recommended tourist spots, restaurants, activities, etc.

[1060] Step 5:

[1061] The user uses the terminal to check the proposed travel plans and select the plan that suits them best. The selected plan information is sent from the terminal to the server.

[1062] Step 6:

[1063] The server will then arrange the booking of accommodation and transport based on the user's selection. The server will ensure the best accommodation and transport options based on the user's budget and available offers.

[1064] Step 7:

[1065] When the trip begins, the user uses the device to record photos, audio, and text data during the trip, and emotional data is collected. Experiences and impressions at each point during the trip are recorded and sent from the device to the server.

[1066] Step 8:

[1067] The server analyzes the received emotion data using an emotion engine. It integrates photo, voice, and text data to recognize the user's emotions in real time. The emotion engine identifies emotions such as joy, emotion, and excitement.

[1068] Step 9:

[1069] Based on the results of the emotion engine's analysis, the server dynamically adjusts the travel plan. For example, if a user feels joy at a particular tourist spot, it will suggest additional similar places or experiences.

[1070] Step 10:

[1071] The server selects music that matches the emotion based on the recorded emotional data: upbeat music for moments of joy, and moving melodies for moments of emotion.

[1072] Step 11:

[1073] Once the trip is over, the server automatically generates a travel video based on the recorded emotional data and selected music. This video includes photos of the places visited and moving moments, as well as music.

[1074] Step 12:

[1075] The user uses the device to view the generated travel video and selects the option to share the video with the community.

[1076] Step 13:

[1077] The server posts the generated travel video to the community and shares it with other users, allowing users to share their travel experiences with other users through the video.

[1078] By following these steps, users can easily plan a personalized and exciting trip, record and share their impressions. In addition, by using an emotion engine, users' emotions can be recognized in real time, further enhancing the travel experience.

[1079] Example 2

[1080] 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."

[1081] When planning a trip, users face the challenge of efficiently identifying previously visited and unvisited locations and automatically generating personalized itineraries. It is also difficult to efficiently record emotional data during a trip and adjust itineraries in real time based on that information. Furthermore, there is a lack of a way to automatically generate recorded video footage after a trip and easily share moving experiences with other users. An integrated system that solves these problems is needed.

[1082] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving image data, means for analyzing the image data to identify destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for analyzing the emotional data and dynamically adjusting the travel plan, means for automatically inserting appropriate music into the travel record video based on the emotional data, means for automatically generating the travel record video, and means for sharing the video with a community. This allows the user to identify unvisited destinations based on past travel data and easily create an individual travel plan, adjust the plan in real time according to emotions even during the trip, and automatically generate and share moving record video after the trip.

[1083] A "user terminal" is a portable information processing device that can be operated by a user, such as a smartphone or tablet.

[1084] "Image data" refers to digital data of still images taken with a digital camera, smartphone, etc.

[1085] "Analysis" is the process of processing received data and extracting specific information.

[1086] A "destination" is a geographic location that a user plans to visit.

[1087] A "travel plan" is a detailed plan including the places the user will visit during the trip, the activities to be carried out, the accommodations and transportation to be used, etc.

[1088] "Accommodation" refers to a facility where a user stays during a trip.

[1089] "Transportation" refers to the means of transportation used by the user during a trip, including airplanes, trains, buses, etc.

[1090] "Emotional data" is digital data related to a user's emotions and moods, and includes information analyzed from text, audio, and images.

[1091] "Dynamic adjustment" means changing plans and settings in real time based on acquired data.

[1092] "Travel footage" refers to a digital video file that compiles travel memories, including photos and videos taken during the trip, and appropriate music.

[1093] "Automatic music insertion" means that a program selects music and incorporates it into video or other media based on specific criteria or data.

[1094] "Share with the community" means uploading the generated content to an online platform for public viewing and sharing with other users.

[1095] The present invention relates to a system that receives image data from a user terminal, identifies destinations that the user has not yet visited, and automatically generates an individual travel plan. Hereinafter, an embodiment of the system will be described in detail.

[1096] First, a user launches a travel planning application on their smartphone, tablet, or other user device, selects photos of places they have visited in the past, and uploads the image data. This image data is then sent from the device to the server.

[1097] The server stores the received image data in storage and analyzes it using an image recognition model (e.g., TensorFlow). Based on the analysis results, it identifies destinations that the user has not yet visited. This identification process is performed by combining image recognition technology and a database.

[1098] The server then automatically generates a personalized itinerary based on the identified destinations, using a user profiling system and recommendation algorithms (e.g., Scikit-Learn), including sightseeing spots, dining options, and activities.

[1099] The user selects the travel plan that best suits them from the presented options. The server then arranges appropriate accommodations and transportation based on the user's selection. A reservation system API (e.g., Booking.com API) is used here.

[1100] To record emotion data while traveling, users use their smartphones or tablets to take photos, record voice, input text, etc., and the devices send this data and GPS information to a server. The server then uses an emotion analysis engine (e.g., IBM Watson) to analyze this data and identify the user's emotion.

[1101] Furthermore, the server dynamically adjusts the itinerary based on the analysis of the emotional data during the trip. For example, if the user feels very happy at a particular tourist spot, it will add other enjoyable places related to this place to the itinerary.

[1102] Once the trip is over, the server aggregates all recorded data, selects music that matches the emotions based on the recorded emotional data, and automatically generates a travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server then uploads the generated video to cloud storage and provides it to the user.

[1103] Finally, users can view the travel video recorded on their own devices and then share it with the community, allowing them to share their impressions and experiences with other users.

[1104] For example, if a user uploads photos of a city they have visited in the past and is suggested a mountainous region they have not yet visited as their next travel destination, the system will automatically generate a travel plan that includes the area's beautiful scenery and tourist attractions. The system analyzes emotions and joy from photos taken and audio recorded during the trip, and after the trip, it automatically creates a travel video with music that perfectly matches those emotions. Furthermore, by sharing this video with the community, users can share their emotions with other users.

[1105] Examples of prompts to be input to a generative AI model include:

[1106] "I uploaded photos from my past trips. Please suggest the best destinations for my next trip and a travel plan that suits my preferences."

[1107] "Recommend fun places to visit in real time based on your location and sentiment data."

[1108] As described above, the present invention is a system that efficiently supports users in planning their travels, enriches their travel experiences, and enables them to share those experiences with other users.

[1109] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1110] Step 1:

[1111] The user launches a travel planning application from a smartphone or tablet. The application inputs photos from the user's past trips. The user can select photos of places they have visited and upload the image data. The image data is sent from the device to the server. The device then processes the selected image data and sends it to the server via the Internet. When the server receives the image data, it saves it in storage.

[1112] Step 2:

[1113] The server analyzes the received image data using an image recognition model (e.g., TensorFlow). The input is the received image data, and the output is a list of destinations that the user has not visited. Once the server analyzes the image data, it identifies destinations that the user has not visited based on the results. The process of identifying unvisited destinations is carried out by combining image recognition technology with a database.

[1114] Step 3:

[1115] The server generates a travel plan based on the identified destinations and taking into account user profile data (preferences, budget, etc.). The input is destination information and user profile data, and the output is a personalized travel plan. A generative AI model and recommendation algorithm (e.g., Scikit-Learn) are used here. The generated travel plan includes tourist attractions, restaurants, activities, etc. The server presents the generated travel plan to the user.

[1116] Step 4:

[1117] The user selects the travel plan that best suits their preferences from the presented plans. The input is the user's selection, and the output is the selected plan information. The server arranges accommodation and transportation based on the selected plan. It uses a reservation system API (e.g., Booking.com API) to make accommodation reservations and flight arrangements. Once the reservation is complete, the server provides confirmation information to the user.

[1118] Step 5:

[1119] While traveling, users use their smartphones or tablets to take photos, record audio, and input text data. These data become the input for emotion data. GPS information is also acquired. The device sends this data and location information to a server. The server analyzes the received emotion data using an emotion analysis engine (e.g., IBM Watson) to identify the user's emotion. The output is the emotion analysis results.

[1120] Step 6:

[1121] The server dynamically adjusts the travel plan based on the analysis results of the acquired emotion data. The input is the emotion analysis result, and the output is the adjusted plan. For example, if the user feels very happy at a particular tourist spot, the server adds other related enjoyable places to the plan. The server notifies the user of the adjusted plan and receives feedback.

[1122] Step 7:

[1123] When the trip ends, the server selects music that matches the emotion based on the recorded emotional data and generates a travel video. The input is the emotional data and photos and videos taken during the trip, and the output is the travel video. Video editing software (e.g., Adobe Premiere Pro) is used to generate the video. The server uploads the generated video file to cloud storage and provides the user with a download link.

[1124] Step 8:

[1125] The user can view the generated travel video on their own device. After viewing, the user can select the option to share the video with the community. To share the video, the device uploads the video to a social networking site or dedicated community platform via the server and generates a sharing URL. Other users can view the shared video and share their impressions by commenting and reacting.

[1126] (Application example 2)

[1127] 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."

[1128] There is a demand for greater efficiency in robotic work within factories, but with current systems, it is difficult to identify areas or procedures that robots have not yet been to, and work plans must be generated and adjusted manually. Furthermore, it is not possible to analyze the robot's work efficiency and satisfaction in real time and dynamically adjust work plans, making it difficult to maximize work efficiency.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1130] In this invention, the server includes means for receiving image data from a user terminal, means for analyzing the image data and identifying destinations the user has not yet visited, means for automatically generating an individual travel plan based on the destinations, means for arranging accommodations and transportation based on the user's preferences and budget, means for recording emotional data during the trip, means for automatically inserting appropriate music into a travel record video based on the emotional data, means for automatically generating the travel record video, means for sharing the video with a community, means for receiving image data within a factory and identifying unvisited areas, means for automatically generating an optimal work plan based on the areas, means for recording data during work and analyzing work efficiency, and means for dynamically adjusting the work plan based on the analysis results. This improves the efficiency of robot work within the factory and enables the generation and adjustment of optimal work plans in real time.

[1131] A "user terminal" refers to an information terminal used by a user, such as a mobile phone, tablet, or personal computer.

[1132] "Image data" refers to digital still image data captured by a camera or image sensor.

[1133] "Analysis" is the process of breaking down data using specific algorithms or programs to extract meaning and features.

[1134] An "unvisited destination" is a place or area that the user has no record of having visited before.

[1135] A "personalized itinerary" is a travel plan designed to meet the needs and preferences of a particular user.

[1136] "Accommodation" refers to the hotel or accommodation facility where the user stays during the trip.

[1137] "Transportation" refers to the means of transportation used during travel, such as airplanes, trains, and buses.

[1138] "Emotional data" refers to data such as voice, text, and images that represent the user's emotional state.

[1139] "Travel footage" refers to footage that records the places and events visited during a trip.

[1140] "Share with community" means sharing information with other users through a specific group or social network.

[1141] "In-factory image data" refers to image data obtained from cameras and image sensors installed within the factory.

[1142] An "unvisited area" is an area in the factory where the robot has not yet performed any work.

[1143] A "work plan" is a procedure or schedule for effectively carrying out a specific task.

[1144] "Data during work" refers to the motion data and environmental data recorded when the robot is working.

[1145] "Analyzing efficiency" means quantifying and analyzing data to evaluate the efficiency of work.

[1146] "Dynamic adjustment" means making changes and corrections automatically in real time based on the situation.

[1147] This invention relates to a system that receives image data from a user terminal, identifies unvisited destinations, and automatically generates an individual travel plan. Furthermore, this system also has the function of identifying unvisited areas and dynamically adjusting an optimal work plan to improve the efficiency of robotic work in factories.

[1148] The server first receives image data from the user's device. The user's device can be a smartphone, tablet, or PC, and the image data captured using the device's camera is sent to the server. The server then analyzes the image data using Python image recognition technology and libraries such as TensorFlow and OpenCV to identify destinations the user has not yet visited or areas within the factory where work has not yet been done.

[1149] The server then automatically generates personalized travel plans and optimized work plans based on the analyzed data. Travel plans include tourist spots, restaurants, and activities to visit, while factory work plans include the necessary procedures, tools, and work order. Database management systems and algorithms are used to tailor the plans based on the user's preferences and budget.

[1150] While traveling or working, the user or robot records emotional data. This data includes photos taken, voice recordings, input text data, and data from sensors. This data is sent to a server in real time and analyzed by an emotion engine. The emotion engine analyzes emotions using, for example, NLP libraries and voice analysis tools, and dynamically adjusts travel plans or work plans based on the results.

[1151] Once the trip is over, the server automatically selects music that matches the emotions based on the recorded emotional data and automatically generates a video recording of the trip. The video includes photos of the places visited during the trip, moving moments, and music that matches the emotions. Similarly, in factories, processes can be recorded to maximize work efficiency based on work data, and the data can be used to improve work in the future.

[1152] An example of a specific prompt might be, "Please upload image data to identify areas that the robot has not yet worked on." This allows the system to collect and analyze the necessary data as it goes along, dynamically providing the optimal plan.

[1153] This invention makes it possible to automatically generate individual travel plans and in-factory work plans and adjust them in real time, significantly improving the convenience and efficiency of users and robots.

[1154] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1155] Step 1:

[1156] The user terminal uses a camera to take images of the inside of a factory or a travel destination, and temporarily stores the image data in local storage. This image data is then sent to a server via a network. The input is the image data from the user terminal, and the output is the image data sent to the server.

[1157] Step 2:

[1158] The server analyzes the received image data using an AI model (e.g., TensorFlow or OpenCV). As a result of the analysis, it identifies destinations and areas that have not been visited by the user or robot. The input is the image data received in step 1, and the output is information on the identified destinations and areas that have not been visited.

[1159] Step 3:

[1160] The server generates individual travel plans or factory work plans based on the identified unvisited destinations or unworked areas. The travel plans include tourist spots, restaurants, and activities, while the work plans include work procedures and necessary tools. The input is the destination or area information identified in step 2, and the output is an automatically generated travel or work plan.

[1161] Step 4:

[1162] The server arranges accommodation and transportation based on the user's preferences and budget. It accesses a database and reserves accommodation and transportation that meets the requirements. The input is the user's preferences and budget information, and the output is information about the reserved accommodation and transportation.

[1163] Step 5:

[1164] A user or a robot records emotional data while traveling or working. This emotional data includes photographs, recorded voice, text data, and sensor data. This data is sent to a server in real time. The input is emotional data, and the output is the recorded emotional data.

[1165] Step 6:

[1166] The server analyzes the received emotional data using an emotion engine. The emotion engine analyzes the data using, for example, an NLP library or a voice analysis tool, to identify the emotional state of the user or robot. The input is the emotional data received in step 5, and the output is the analyzed emotional state information.

[1167] Step 7:

[1168] The server dynamically adjusts the travel or work plan based on the analysis of the emotion data. It changes the plan depending on whether the user or robot is satisfied. The input is the emotional state information obtained in step 6, and the output is the adjusted travel or work plan.

[1169] As a concrete example, a prompt sentence could be, "Please upload image data and identify areas that the robot has not yet worked on." By following this prompt, the system can collect the necessary data, analyze it, and dynamically provide the optimal plan.

[1170] 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.

[1171] 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.

[1172] 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.

[1173] 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.

[1174] 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.

[1175] 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.

[1176] 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).

[1177] 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.

[1178] 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."

[1179] 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.

[1180] 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).

[1181] 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.

[1182] 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.

[1183] 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.

[1184] 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.

[1185] 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.

[1186] 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.

[1187] 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.

[1188] 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.

[1189] 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.

[1190] 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.

[1191] The following is further disclosed regarding the above embodiment.

[1192] (Claim 1)

[1193] means for receiving image data from a user terminal;

[1194] means for analyzing the image data and identifying destinations that the user has not yet visited;

[1195] means for automatically generating an individualized travel plan based on the destination;

[1196] means for arranging accommodation and transportation based on the user's preferences and budget;

[1197] a means for recording emotional data during the trip;

[1198] means for automatically inserting appropriate music into the travel record video based on the emotion data;

[1199] means for automatically generating the travel record video;

[1200] a means for sharing said video with a community;

[1201] A system including:

[1202] (Claim 2)

[1203] 10. The system of claim 1, further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

[1204] (Claim 3)

[1205] 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data.

[1206] "Example 1"

[1207] (Claim 1)

[1208] means for receiving image data from a user terminal;

[1209] means for analyzing the image data and identifying destinations that the user has not yet visited;

[1210] means for automatically generating an individualized travel plan based on the destination;

[1211] means for arranging accommodation and transportation based on the user's preferences and budget;

[1212] a means for recording emotional data during the trip;

[1213] means for automatically inserting appropriate music into the travel record video based on the emotion data;

[1214] means for automatically generating the travel record video;

[1215] a means for sharing said video with a community;

[1216] A method to analyze photos from user devices using image recognition technology to identify unvisited destinations,

[1217] A method to analyze emotional data from photos and audio taken during a trip and add music that matches the emotion to the travel video after the trip.

[1218] A system including:

[1219] (Claim 2)

[1220] 10. The system of claim 1, further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

[1221] (Claim 3)

[1222] 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data.

[1223] "Application Example 1"

[1224] (Claim 1)

[1225] means for receiving image data from a user terminal;

[1226] means for analyzing the image data and identifying destinations that the user has not yet visited;

[1227] means for automatically generating an individualized travel plan based on the destination;

[1228] means for arranging accommodation and transportation based on the user's preferences and budget;

[1229] a means for recording emotional data during the trip;

[1230] means for automatically inserting appropriate music into the travel record video based on the emotion data;

[1231] means for automatically generating the travel record video;

[1232] a means for sharing said video with a community;

[1233] A means for analyzing image data from a user terminal, identifying potential destinations using an AI model, and inputting a prompt sentence using the generated AI model;

[1234] A means for generating a virtual trip planner application based on the potential destinations analyzed using the AI ​​model and providing the application to a user device;

[1235] A means to automatically suggest and arrange activities, accommodations, and transportation according to a travel plan generated using an AI model; and

[1236] A system including:

[1237] (Claim 2)

[1238] 10. The system of claim 1, further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

[1239] (Claim 3)

[1240] 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data.

[1241] "Example 2: Combining Emotion Engines"

[1242] (Claim 1)

[1243] means for receiving image data from a user terminal;

[1244] means for analyzing the image data and identifying destinations that the user has not yet visited;

[1245] means for automatically generating an individualized travel plan based on the destination;

[1246] means for arranging accommodation and transportation based on the user's preferences and budget;

[1247] a means for recording emotional data during the trip;

[1248] means for analyzing the emotion data and dynamically adjusting the travel plan;

[1249] means for automatically inserting appropriate music into the travel record video based on the emotion data;

[1250] means for automatically generating the travel record video;

[1251] a means for sharing said video with a community;

[1252] A system including:

[1253] (Claim 2)

[1254] 10. The system of claim 1, further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

[1255] (Claim 3)

[1256] 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data.

[1257] "Application example 2 when combining emotion engines"

[1258] (Claim 1)

[1259] means for receiving image data from a user terminal;

[1260] means for analyzing the image data and identifying destinations that the user has not yet visited;

[1261] means for automatically generating an individualized travel plan based on the destination;

[1262] means for arranging accommodation and transportation based on the user's preferences and budget;

[1263] a means for recording emotional data during the trip;

[1264] means for automatically inserting appropriate music into the travel record video based on the emotion data;

[1265] means for automatically generating the travel record video;

[1266] a means for sharing said video with a community;

[1267] means for receiving image data within the factory and identifying unvisited areas;

[1268] means for automatically generating an optimal work plan based on the area;

[1269] A means for recording data during work and analyzing work efficiency;

[1270] means for dynamically adjusting a work plan based on the analysis results;

[1271] A system including:

[1272] (Claim 2)

[1273] 10. The system of claim 1, further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

[1274] (Claim 3)

[1275] 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data. [Explanation of symbols]

[1276] 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 receiving image data from a user terminal; means for analyzing the image data and identifying destinations that the user has not yet visited; means for automatically generating an individualized travel plan based on the destination; means for arranging accommodation and transportation based on the user's preferences and budget; a means for recording emotional data during the trip; means for automatically inserting appropriate music into the travel record video based on the emotion data; means for automatically generating the travel record video; a means for sharing said video with a community; A system including:

2. The system of claim 1 , further comprising means for receiving voice data and text data from a user terminal and analyzing emotion data from the voice data and text data.

3. 2. The system according to claim 1, further comprising means for acquiring current location data from the user terminal and inserting location information into the travel record video based on the location data.

Images