System

Abstract

A system is provided.SOLUTION: Means for inputting a travel destination, a travel schedule, a budget, and a favorite activity by a user, terminal means for receiving the input information and transmitting the information to a server, server means for collecting data such as tourist spots, accommodation facilities, eating places, and activities from internal and external information sources on the basis of requirements of the user, and means for removing less relevant data and inaccurate information from the collected data, this system includes a filtering means for improving the accuracy of data, an analyzing means for analyzing the filtered data and generating a travel plan matched with the preference of a user, a cost calculating means for calculating the cost of each element and making the whole travel plan fit in a budget, and a means for transmitting the generated travel plan to a terminal and enabling the user to confirm and customize it.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

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

[0004] Conventional travel planning systems have the problem of being unable to adequately respond to the diverse requirements entered by users. Specifically, it is difficult to comprehensively process complex requirements such as travel destinations, itineraries, budgets, and activity preferences to propose optimal travel plans. Furthermore, due to the low accuracy and relevance of the collected data, the resulting plans often do not meet users' expectations. Furthermore, insufficient filtering of noise and irrelevant data generated during the collection and analysis process has also led to issues such as long processing times before useful information can be provided to users. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. First, a means for a user to input travel destinations, travel itineraries, budget, and preferred activities is provided. Then, a terminal means is provided for receiving the input information and transmitting the information to a server. Next, as a server means, a means is provided for collecting data such as tourist attractions, accommodations, places to eat, and activities from internal and external sources based on the user's requirements. Further, a filtering means is provided for removing irrelevant or inaccurate information from the collected data to improve data accuracy. Further, an analysis means is provided for analyzing the filtered data and generating a travel plan that matches the user's preferences. Furthermore, a cost calculation means is provided for calculating the cost of each element and ensuring that the overall travel plan fits within the budget. Finally, a means is provided for transmitting the generated travel plan to a terminal so that the user can review and customize it. This invention solves the problems of the past and makes it possible to quickly provide users with useful and accurate travel plans.

[0006] "User" means an individual or organization that utilizes the travel planning system to input travel requirements and receive suggestions.

[0007] A "destination" is a particular geographic area or location that a user wishes to visit.

[0008] "Travel itinerary" refers to the specific dates and periods for which a user plans to travel.

[0009] A "budget" is a monetary limit that a user wishes to spend on a trip.

[0010] "Favorite Activities" are specific activities or events that a user wants to experience during their trip.

[0011] A "means" is a device, facility, method, or system that is provided to perform a specific function or role.

[0012] A "terminal" is a device (e.g., a smartphone or computer) through which a user inputs information and communicates with a server.

[0013] A "server" is a remote computer system that receives, processes, analyzes, and optimizes user-submitted information to generate an optimal travel plan.

[0014] A "database" is a system that systematically stores travel information such as tourist attractions, accommodations, places to eat, and activities.

[0015] An "API" is a software interface that allows you to connect to external services and databases to obtain information.

[0016] "Filtering" is the process of removing unnecessary information or noise from collected data.

[0017] "Analysis" is the process of examining the data in detail to derive a travel plan that best suits the user's requirements.

[0018] "Costing" is the process of adding up the costs of each element of a travel plan to arrive at the total cost.

[0019] A "travel plan" is a plan generated based on the user's requirements, detailing the order in which tourist spots should be visited, the schedule, and the activities to be carried out within a budget.

[0020] "Confirmation" refers to the process in which the user confirms and evaluates the contents of the generated travel plan.

[0021] "Customization" refers to the process by which a user makes additional requests or changes to the travel plan provided. [Brief explanation of the drawings]

[0022] [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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] The present invention is a system that allows users to input their travel destinations, travel itineraries, budgets, and preferred activities, and is a technology for proposing optimal travel plans. Specific embodiments for implementing this system and the processing flow are described below.

[0044] System Overview

[0045] The system basically consists of a terminal where users input information, a server that receives and processes the input information, and a database that stores and manages the data.

[0046] User input

[0047] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0048] Data transmission by the terminal

[0049] The terminal receives the information entered by the user and transmits it to the server in real time, where the server begins processing immediately.

[0050] Data collection by the server

[0051] The server queries the database based on the received user requirements, for example, gathering information on attractions, accommodations, places to eat, activities, etc. from internal databases and external APIs.

[0052] Data Filtering and Noise Removal

[0053] The server analyzes the collected data and filters out irrelevant or inaccurate information, improving the accuracy of useful information and eliminating unnecessary data, such as hotels that are already fully booked or restaurants that are closed.

[0054] Data analysis

[0055] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate an optimal itinerary that matches the user's preferences, for example, predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0056] Cost Calculation

[0057] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[0058] Presenting your travel plan

[0059] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[0060] Specific examples

[0061] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[0062] Information collected

[0063] The server suggests tourist spots such as Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine, and collects information on long-established Kyoto inns as accommodations and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen.

[0064] Filtering and Analysis

[0065] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[0066] Plan Generation and Cost Calculation

[0067] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[0068] final offer

[0069] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[0070] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan their trips efficiently and accurately.

[0071] The processing flow will be explained below.

[0072] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities, such as "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[0073] Step 2: The terminal receives the information entered by the user, converts it into the specified format, and sends it to the server in real time.

[0074] Step 3: The server receives the user's input information and executes queries to gather relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[0075] Step 4: The server searches the database for data on attractions, accommodations, places to eat, and activities, and retrieves the relevant information. It also uses external APIs to gather real-time weather and event information.

[0076] Step 5: The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0077] Step 6: The server applies algorithms to the filtered data to generate an optimal itinerary that matches the user's preferences and requirements, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0078] Step 7: The server calculates the cost of each element of the generated itinerary (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[0079] Step 8: The server sends the final itinerary to the device, including details of the places to visit, the dates, and the budgeted costs.

[0080] Step 9: The terminal displays the travel plan received from the server to the user. The user can review the travel plan and customize it as needed (for example, add other tourist spots or change the budget).

[0081] Step 10: The user finalizes the travel plan and makes a reservation if necessary. This information is sent back to the server, and all data is saved as a finalized plan.

[0082] Example 1

[0083] 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."

[0084] Conventional travel planning systems have struggled to generate optimal travel plans based on users' individual requirements and preferences. Existing systems often provide only general tourist information and are unable to provide plans that reflect the user's specific needs. In addition, cost calculations are often insufficient, potentially resulting in plans that fall outside the user's budget, creating inconvenience for users. Furthermore, the accuracy and relevance of collected data can be low, resulting in the inclusion of inaccurate information, which can degrade the quality of travel plans.

[0085] 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.

[0086] In this invention, the server includes: means for collecting data on tourist attractions, accommodations, restaurants, activities, etc. from an internal database and external sources based on the user's requirements; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means including a generative AI model for analyzing the filtered data and generating a travel plan that matches the user's preferences; cost calculation means for calculating the cost of each element and ensuring the overall travel plan stays within budget; and means for transmitting the generated travel plan to a terminal so the user can review and customize it. This enables the generation of a precise travel plan based on the user's specific requirements and preferences. Furthermore, by planning within budget, user satisfaction can be increased.

[0087] "User" refers to a person or individual who inputs information such as travel destination, travel dates, budget, and preferred activities to create a travel plan.

[0088] "Terminal means" refers to a device or system that receives information entered by a user and transmits it to a server. Examples include smartphones and computers.

[0089] The term "server means" refers to a computer system that receives information sent from a user and performs a series of processes such as data collection, filtering, analysis, and plan generation.

[0090] "Tourist destinations" refer to places and attractions that tourists can visit in a travel destination, including historical sites and natural landscapes.

[0091] "Accommodation facilities" refer to facilities that provide a place for travelers to stay. Examples include hotels and inns.

[0092] "Food and beverage establishments" refers to establishments that provide meals during travel. Examples include restaurants and cafes.

[0093] "Activities" refers to interesting activities and experiences that you undertake while traveling, such as sightseeing tours and interactive programs.

[0094] "Database" means a system for systematically storing and managing collected information, including internal databases and data from external sources.

[0095] "Source" refers to external APIs and other information resources used in data collection.

[0096] "Generative AI model" refers to an artificial intelligence model used to automatically generate optimal travel plans based on user input.

[0097] "Filtering measures" refers to algorithms or processes used to remove irrelevant or inaccurate information from collected data.

[0098] "Analysis" refers to the processes and algorithms that utilize the filtered data to generate travel plans that match the user's preferences.

[0099] "Cost calculation means" refers to a process for calculating the cost of each element of a travel plan (e.g., accommodation, transportation, meals, admission fees, etc.) and ensuring that the overall plan stays within the user's budget.

[0100] The present invention is a system that provides an optimal travel plan by allowing a user to input travel destinations, travel dates, budget, and preferred activities. The system is configured as follows.

[0101] 1. User inputs information

[0102] Users enter their travel requirements through travel websites and mobile applications. This information includes destination, travel dates, budget, and preferred activities. For example, a user might enter a prompt like this:

[0103] Travel destination: Kyoto

[0104] Travel dates: November 1st to November 5th, 2023

[0105] Budget: 100,000 yen

[0106] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0107] 2. Sending data from the device to the server

[0108] The device receives the information entered by the user and transmits it to the server in real time using a network protocol such as an HTTP POST request.

[0109] 3. Data collection and filtering by the server

[0110] Based on the received user requirements, the server collects data using internal database queries and external APIs (e.g., Google Places API), including tourist destinations, accommodations, restaurants, activities, etc.

[0111] The collected data is then filtered through a specific algorithm to filter out irrelevant or inaccurate information, for example, removing hotels that are already fully booked or restaurants that are closed.

[0112] 4. Data analysis and generative AI models

[0113] The server then uses a generative AI model to perform advanced data analysis on the filtered data. This model generates an optimal travel plan that matches the user's preferences, for example, by predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0114] 5. Cost Calculation

[0115] The server calculates the cost of each element (accommodation, transportation, meals, admission fees, etc.) and adjusts the total to fit within the user's budget. For example, the server provides the optimal plan within a user-entered budget of 100,000 yen.

[0116] 6. Generating a travel plan and presenting it to the user

[0117] The server generates an optimal travel plan based on the analysis results and cost calculations, and the plan is sent back to the terminal for the user to review and customize.

[0118] Through these processes, the system can provide travel plans based on the user's specific requirements and preferences, and can also adjust the plans to fit within the user's budget, increasing user satisfaction.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] User input of information

[0122] Input: Information about travel destination, travel dates, budget, and preferred activities that users enter through travel sites and mobile applications.

[0123] How it works: A user manually enters information into an application form, such as:

[0124] Travel destination: Kyoto

[0125] Travel dates: November 1st to November 5th, 2023

[0126] Budget: 100,000 yen

[0127] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0128] Output: The entered information is stored within the application and passed to the next processing step.

[0129] Step 2:

[0130] Data transmission by the terminal

[0131] Input: Information entered by the user in step 1.

[0132] How it works: The device sends the information entered by the user to the server in real time using an HTTP POST request, and the server has an endpoint configured for this purpose.

[0133] Output: The server receives the user's input.

[0134] Step 3:

[0135] Data collection by the server

[0136] Input: User requirements information (destination, travel dates, budget, preferred activities).

[0137] How it works: The server queries an internal database and also sends requests to external sources (e.g., Google Places API) to gather the necessary data, including information about tourist attractions, accommodation, restaurants, and activities.

[0138] Output: The collected information on tourist attractions, accommodations, restaurants, and activities is stored on the server.

[0139] Step 4:

[0140] Server-based data filtering and noise reduction

[0141] Input: Data collected in Step 3.

[0142] How it works: The server applies filtering algorithms to remove irrelevant or inaccurate data, such as fully booked accommodations or closed restaurants.

[0143] Output: A filtered, reliable dataset is kept on the server.

[0144] Step 5:

[0145] Data analysis by server

[0146] Input: The filtered dataset.

[0147] How it works: The server uses the generative AI model to generate an optimal travel plan that matches the user's preferences, specifically predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0148] Output: A travel plan that best suits the user's requirements is generated and saved.

[0149] Step 6:

[0150] Server-based cost calculation

[0151] Input: Each element of the optimized itinerary (accommodation, transportation, places to eat, and each activity).

[0152] How it works: The server calculates the cost of each element and adjusts it to fit the overall plan within budget. For example, it adds up accommodation, travel, meals, admission fees, etc. and makes adjustments as needed.

[0153] Output: A completed itinerary within the adjusted costs.

[0154] Step 7:

[0155] Server generates and presents travel plans

[0156] Input: Cost-adjusted optimal travel plan.

[0157] Operation: The server sends the generated travel plan to the terminal again, returning the data as an HTTP response.

[0158] Output: The terminal receives the itinerary and presents it to the user.

[0159] Step 8:

[0160] User confirmation and modification of plans

[0161] Input: Travel plan provided by the device.

[0162] How it works: The user reviews the proposed itinerary and submits any necessary changes or additions through the application, for example, changing the order of visits or requesting additional attractions.

[0163] Output: The final customized itinerary is presented to the user.

[0164] (Application example 1)

[0165] 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."

[0166] Conventional travel planning systems have limitations in collecting and filtering information based on user input data, making it difficult to generate optimal plans in real time or provide users with intuitive and easy-to-understand information.In addition, advanced data analysis and AI technology are essential to provide travel plans that suit the diverse preferences of users, and no system has been able to meet these requirements.

[0167] 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.

[0168] In this invention, the server includes a means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements, a filtering means for removing irrelevant or inaccurate data from the collected data to improve data accuracy, an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences, and a means for generating and presenting an optimal travel plan using an external AI model in real time based on the data entered by the user. This makes it possible to respond to the diverse requirements of users and provide optimal and intuitive travel plans in real time.

[0169] "User" means a person or customer who inputs their preferences and requirements to create a travel plan.

[0170] "Destination" refers to a particular place or city that a User plans to visit.

[0171] "Travel itinerary" is information indicating the period from the start date to the end date of a trip.

[0172] "Budget" is the amount of money the user plans to spend on the trip.

[0173] "Preferred Activities" refers to the specific activities or experiences that a User is interested in while traveling.

[0174] "Terminal means" refers to a device or application that allows a user to input information and send it to a server.

[0175] "Server Means" means a computer system that receives user input information and collects and processes the necessary data.

[0176] A "database" is a structured data storage system for storing and managing collected information.

[0177] An "external API" is an interface for obtaining information from external data sources.

[0178] "Filtering measures" are techniques used to remove irrelevant or inaccurate information from collected data.

[0179] "Analysis means" refers to algorithms or software that generate travel plans based on the filtered data that match the user's preferences.

[0180] "Cost calculation means" is a technique for calculating the cost of each element and ensuring that the overall travel plan fits within the user's budget.

[0181] A "generative AI model" is an artificial intelligence technology used to generate optimal travel plans in real time based on user input information.

[0182] A "prompt sentence" is a guide sentence that uses a generative AI model to provide users with easy-to-understand information.

[0183] "Internal and External Sources" means the internal and external data sources used by the System to collect data.

[0184] This invention is a system that proposes optimal travel plans based on travel destinations, travel itineraries, budgets, and preferred activities input by a user. A specific method for realizing this system is described below.

[0185] System Overview

[0186] The system consists of the following main components:

[0187] Terminal means

[0188] Users input their travel requirements (destination, itinerary, budget, activities) using a smartphone application. The smartphone application was developed using React Native to provide a user-friendly interface.

[0189] Server Means

[0190] The entered data is sent to the server in real time. The server is built using Flask and receives the user's input data. The server collects data such as tourist attractions, accommodations, places to eat, and activities through internal database queries and external API calls (e.g., Google Places API, Amadeus API). The collected data is then stored in an internal database (e.g., PostgreSQL).

[0191] Filtering Methods

[0192] The server uses a specific algorithm to filter irrelevant or inaccurate information from the collected data, for example, by removing hotels that are already fully booked or restaurants that are closed.

[0193] Analysis means

[0194] The filtered data undergoes advanced analysis based on the user's requirements, using generative AI models such as GPT-4 and BERT to generate an optimal travel plan, which is then presented to the user in an easy-to-understand format using generated prompts.

[0195] Cost Calculation Method

[0196] The server calculates the cost of each element (e.g. accommodation, transportation, meals, entrance fees, etc.) and adjusts the overall itinerary to fit within the budget. This is done using the Python pandas library.

[0197] Presenting your travel plan

[0198] The generated itinerary is sent to the smartphone application user interface for the user to review and customize.

[0199] Specific examples

[0200] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[0201] 1. User input data:

[0202] Travel destination: Kyoto

[0203] Travel dates: November 1st to November 5th, 2023

[0204] Budget: 100,000 yen

[0205] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0206] 2. Data collection and filtering:

[0207] The server uses the Google Places API and Amadeus API to collect data on places such as Kinkaku-ji Temple, Kiyomizu-dera Temple, Fushimi Inari Taisha Shrine, long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen.

[0208] Eliminate irrelevant, duplicate, and inaccurate data.

[0209] 3. Data analysis and plan generation:

[0210] GPT-4 is used to generate prompts and suggest specific travel plans.

[0211] For example, a detailed itinerary suggestion such as "Visit Kinkakuji Temple on November 1st and check into a long-established inn" is presented.

[0212] Prompt Sentence Examples

[0213] "I'm planning a trip to Kyoto from November 1st to November 5th, 2023. My budget is 100,000 yen. My favorite activities are visiting historical sites, experiencing Japanese cuisine, and relaxing in hot springs. Please suggest a recommended itinerary."

[0214] In this way, specific processing is carried out to provide users with the most suitable travel plans. By linking the entire system, it becomes possible to provide high-quality travel plans that meet the user's requests in real time.

[0215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0216] Step 1:

[0217] A user uses a smartphone application to input their travel destination, travel dates, budget, and preferred activities. Specifically, the user fills out an input form in the application, and the information is saved in the application. The input information includes the travel destination (e.g., Kyoto), travel dates (e.g., November 1 to November 5, 2023), budget (e.g., 100,000 yen), and preferred activities (e.g., visiting historical sites, experiencing Japanese cuisine, hot springs).

[0218] Step 2:

[0219] The device sends the entered travel requirements to the server in real time. Specifically, when the user presses the "Submit" button, the application converts the input data into JSON format and sends it to the server using an HTTP request. The input includes travel destinations, travel dates, budget, and preferred activities. The server receives this data and stores it in an understandable format.

[0220] Step 3:

[0221] The server uses an internal database and external APIs (e.g., Google Places API or Amadeus API) to collect information on attractions, accommodation, places to eat, and activities based on user input data. The server uses the user input data to generate an API query and sends a request to the external API. It retrieves relevant information from the database and consolidates this information. The input is the user's travel requirements, and the output is information on attractions, accommodation, places to eat, and activities collected from the API and database.

[0222] Step 4:

[0223] The server filters irrelevant data and inaccurate information from the collected data. Specifically, the server uses a specific algorithm to remove duplicate data, establishments that can no longer be booked, restaurants that are no longer open, etc. The input is data collected from the API and database, and the output is filtered, highly accurate data.

[0224] Step 5:

[0225] The server performs analysis based on the filtered data and generates a travel plan that matches the user's preferences. This analysis uses a generative AI model such as GPT-4 or BERT. The server provides a prompt to the generative AI model, which then generates an optimal travel plan based on that. The input is the filtered data and the prompt, and the output is the generated travel plan.

[0226] Step 6:

[0227] The server calculates the cost of each element of the generated travel plan and adjusts it so that the overall plan fits within the user's budget. Specifically, the server calculates the cost of each tourist attraction, accommodation, place to eat, and activity, and fine-tunes the plan so that the total amount fits within the budget. The input is the cost information of each element, and the output is the adjusted travel plan.

[0228] Step 7:

[0229] The server sends the final adjusted itinerary to the device for the user to review and customize. Specifically, the server converts the generated plan into JSON format and sends it to the device using an HTTP response. The device displays the received plan on a user interface, allowing the user to review it and make fine adjustments if necessary. The input is the adjusted itinerary, and the output is the itinerary presented to the user.

[0230] In this way, each step works together to provide the user with the most suitable travel plan.

[0231] 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.

[0232] The present invention combines a system in which a user inputs their travel destination, itinerary, budget, and preferred activities with an emotion engine, and is a technology for providing optimal travel plans that take the user's emotions into consideration more than conventional travel planning systems. A specific embodiment of this system and its processing flow are described below.

[0233] System Overview

[0234] This system consists of a terminal where users input information, a server that receives and processes the input information and emotion data, a database that stores and manages the data, and an emotion engine that recognizes the user's emotions.

[0235] User input

[0236] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0237] Emotion Engine

[0238] The device's built-in emotion engine collects emotion data from the user's facial expressions and voice while they are typing. For example, if the user is smiling while typing, that emotion data is collected. It also uses voice recognition technology to recognize emotions from the tone of the user's voice.

[0239] Data transmission by the terminal

[0240] The terminal receives the travel information and collected emotion data entered by the user, converts them into a set format, and transmits them to the server in real time.

[0241] Data collection by the server

[0242] Based on the received user requirements and sentiment data, the server executes queries to collect relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[0243] Data Filtering and Noise Removal

[0244] The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0245] Data analysis

[0246] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate optimal travel plans that match the user's preferences and emotions, for example, predicting crowds at tourist spots and optimizing the order in which they are visited.

[0247] Cost Calculation

[0248] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[0249] Reflecting emotional data

[0250] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and spots that match the user's emotions. For example, if the user feels like relaxing, hot springs and relaxation facilities will be recommended.

[0251] Presenting your travel plan

[0252] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[0253] Specific examples

[0254] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and smiles while inputting the information and says, "I'd like a place that's relaxing," the system will operate as follows:

[0255] Collected information and emotional data

[0256] The server suggests Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist spots, collects Kyoto's long-established inns as accommodations, and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen, reflecting the user's desire to relax.

[0257] Filtering and Analysis

[0258] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[0259] Plan Generation and Cost Calculation

[0260] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[0261] final offer

[0262] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[0263] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan travel efficiently, accurately, and in line with their own preferences.

[0264] The processing flow will be explained below.

[0265] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities. For example, they might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[0266] Step 2: The device's built-in emotion engine analyzes the user's facial expressions and voice in real time as they type, collecting emotional data. For example, if the user smiles while typing, the emotion data is recorded as "relaxed."

[0267] Step 3: The device converts the input travel information and collected emotion data into a predefined format and transmits it to the server in real time. The transmitted data includes travel destination, itinerary, budget, activity preferences, and emotion data.

[0268] Step 4: The server executes queries to collect data on tourist attractions, accommodations, places to eat, and activities from the database and external APIs based on the received travel information and sentiment data. For example, it retrieves information on tourist attractions and accommodations in Kyoto.

[0269] Step 5: The server filters the collected data to remove irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0270] Step 6: The server applies algorithms to generate an optimal itinerary based on the filtered data, matching the user's preferences and requirements. Specifically, it predicts crowding at tourist spots and optimizes the order in which they are visited.

[0271] Step 7: The server analyzes the emotion data obtained from the emotion engine and identifies recommended activities and spots that match the user's emotions. For example, if the user expresses a desire to relax, the server will recommend hot springs and relaxation facilities.

[0272] Step 8: The server calculates the cost of each element of the generated travel plan (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[0273] Step 9: The server sends the final itinerary to the device, including details of the planned destinations, itinerary, budgeted costs, and recommended activities that take into account the sentiment data.

[0274] Step 10: The terminal displays the travel plan received from the server to the user, who can review the plan and further customize it if necessary (e.g., select additional tourist attractions or change the budget).

[0275] Step 11: The user finalizes the travel plan and completes the booking procedure if necessary. The final plan is sent to the server and all data is saved as the finalized plan.

[0276] Example 2

[0277] 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."

[0278] Conventional travel planning systems only considered the user's basic requirements, making it difficult to provide optimal travel plans that reflected the user's emotions and detailed preferences. Furthermore, data collection, filtering, and analysis often contained inaccurate or irrelevant information, making it difficult to generate travel plans that satisfied users. Furthermore, the ability to adjust travel plans to fit within a budget was often insufficient, requiring users to put in a great deal of effort to create a travel plan that fit their budget.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0280] In this invention, the server includes: means for collecting information on tourist destinations, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotions; filtering means for removing irrelevant or inaccurate data from the collected information to increase data accuracy; analysis means for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element to ensure that the overall travel plan stays within budget; and means for transmitting the generated travel plan to a user interface so that the user can review and customize it. This makes it possible to provide an optimal travel plan within budget, taking into account the user's emotions and detailed preferences and eliminating irrelevant data.

[0281] A "user" is an individual or organization that inputs travel destinations, travel itineraries, budget, and preferred activities.

[0282] A "user interface" is a means by which a user inputs information and transmits that information and emotion data to a server.

[0283] The "server" is a central processing unit that collects, analyzes, and filters information based on the user's requirements and feelings, generates an optimal travel plan, and transmits it to the terminal.

[0284] "Sources" are data suppliers that provide information on tourist destinations, accommodation, places to eat, activities, etc. through databases and external data acquisition means.

[0285] "Filtering measures" are processes used to remove irrelevant or inaccurate data from collected information and improve the accuracy of the data.

[0286] The "analysis means" is a process for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions.

[0287] "Cost calculation means" is a process for calculating the cost of each element and adjusting the overall travel plan to fit within the user's budget.

[0288] A "travel plan" is a proposal that integrates schedules and costs including sightseeing destinations, accommodations, places to eat, activities, etc. that meets the user's requirements and sentiments.

[0289] The present invention is a system that allows a user to input travel destinations, travel dates, budgets, and preferred activities, and provides an optimal travel plan based on the inputs, taking into consideration the user's feelings. Specific embodiments of the present invention are described below.

[0290] User data entry

[0291] A user uses a device to access a travel website or mobile application, and after logging in, enters the necessary information. The information entered includes travel destination, travel dates, budget, and preferred activities. For example, a user might enter the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This information is then recorded by the device.

[0292] Emotion recognition by emotion engine

[0293] The emotion engine installed on the device analyzes the user's facial expressions and voice. This is done through a camera and microphone, and emotional data is collected from the facial expressions and tone of voice shown when the user types. For example, if a user smiles and types "I like a place where I can relax," that emotion is collected as data.

[0294] Sending data

[0295] The device converts the travel information and collected emotion data entered by the user into a predetermined format and transmits it to the server in real time in a unified format such as JSON.

[0296] Data collection and analysis by the server

[0297] The server sends queries to databases and external APIs based on the received information to collect information on tourist destinations, accommodations, places to eat, and activities. For example, it obtains information on Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist attractions, long-established Kyoto inns as accommodations, Michelin-starred Japanese restaurants as places to eat, and Arashiyama Onsen as activities. The server then filters out unnecessary data and incorrect information from the collected information to improve its accuracy.

[0298] Filtering and Data Analysis

[0299] The server analyzes the filtered information and generates an optimal itinerary that matches the user's preferences and emotions. It uses a new algorithm to predict crowding at tourist spots and optimize the order in which the users visit. For example, the server can plan a trip to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon.

[0300] Cost Calculation

[0301] The server calculates the cost of each element and adjusts it so that the total fits within the user's budget. Specifically, it adds up the cost of accommodation, transportation, meals, admission fees, etc., so that the total comes in at 100,000 yen or less.

[0302] Reflecting emotional data

[0303] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and tourist spots based on the user's emotions. For example, hot springs and relaxation facilities can be recommended to users who prioritize relaxation.

[0304] Presenting your travel plan

[0305] The generated travel plan is sent to the terminal, where the user can review it. The user can review the presented plan and further customize it. Re-planning according to the user's request is performed by re-sending it from the terminal to the server.

[0306] Examples of concrete examples and prompts

[0307] For example, if a user enters "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and says with a smile, "I'd like a place to relax," the system will act as follows:

[0308] Collected information and emotional data

[0309] User request: "Kyoto" "November 1st to November 5th, 2023" "100,000 yen" "Visit historical sites, experience Japanese cuisine, and relax in hot springs"

[0310] User Sentiment: "Relaxed"

[0311] Server Processing

[0312] Collect information on tourist spots such as Kinkakuji Temple, Kiyomizudera Temple, and Fushimi Inari Taisha Shrine

[0313] Collect information on Kyoto's long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen

[0314] Calculate the cost and adjust the total amount to within 100,000 yen

[0315] Recommending hot springs and relaxation facilities based on user emotional data

[0316] Prompt Sentence Examples

[0317] Please enter your "travel destination," "travel dates," "budget," and "preferred activities."

[0318] Example: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0319] Example of emotional input: "I like a place where I can relax."

[0320] This allows users to get an efficient and personalized travel plan that reflects their emotions and detailed requests.

[0321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0322] Step 1: User Data Entry

[0323] A user logs into a travel website or mobile app using a device and enters their travel destination, travel dates, budget, and preferred activities. The entered information is stored in the device's database. For example, a user might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This input data is used for subsequent processing.

[0324] Step 2: Emotion recognition by the emotion engine

[0325] While the user is entering data, the device's built-in emotion engine uses the camera and microphone to collect the user's facial expressions and tone of voice. The data is analyzed in real time and stored in a database as the user's emotion information. For example, if a user smiles and says, "I like places where I can relax," the emotion data is saved as a tag called "relaxation."

[0326] Step 3: Sending data

[0327] The device combines the user input data and collected emotion data into a single packet and sends it to the server in a specified format (e.g., JSON format). The server receives this packet and parses it to extract each data element. For example, it may be sent in a format such as "Travel destination: Kyoto," "Date: November 1st to November 5th, 2023," "Budget: 100,000 yen," "Favorite activities: visiting historical sites, experiencing Japanese cuisine, relaxing hot springs," and "Emotion: Relaxation."

[0328] Step 4: Data collection by the server

[0329] The server analyzes the received user requirements and sentiment data and collects information such as tourist destinations, accommodations, dining places, and activities based on the analysis. It uses internal database queries and external APIs to collect the corresponding data. For example, the server might collect tourist spot information such as "Kinkaku-ji Temple," "Kiyomizu-dera Temple," and "Fushimi Inari Taisha Shrine," accommodation information such as "long-established Kyoto inns," and dining information such as "Michelin-starred Japanese restaurants."

[0330] Step 5: Data filtering and noise removal

[0331] The server analyzes the collected data and filters out unnecessary or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activity on days when bad weather is predicted. The filtered data is then stored as a newly organized dataset.

[0332] Step 6: Data analysis and plan generation

[0333] The server then applies the filtered information to advanced analytical algorithms to generate an optimal travel plan that matches the user's preferences and emotions. For example, it predicts how crowded tourist spots will be and calculates the optimal order in which to visit them. Specifically, it creates a schedule that visits Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and stores the resulting plan in a database.

[0334] Step 7: Cost calculation

[0335] The server aggregates the costs of each element and adjusts them so that the total fits within the user's budget. For example, it calculates the cost of accommodation, transportation, meals, and admission fees, and optimizes the items to keep the total within 100,000 yen. The cost calculation results are included in the generated travel plan.

[0336] Step 8: Reflecting emotional data

[0337] Emotional data can also influence the optimization of travel plans. For example, if a user indicates a desire to relax, the server will prioritize recommendations for hot springs and relaxation facilities. This information is incorporated as part of the travel plan.

[0338] Step 9: Present your travel plans

[0339] The final itinerary is then reformatted and sent to the device. The user can review the presented itinerary and customize it as needed. The user's feedback is then sent back to the server, and the plan is updated as needed. For example, a user may enter a request such as "I would like to change the time to visit Kinkaku-ji Temple."

[0340] (Application example 2)

[0341] 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."

[0342] Conventional systems were unable to provide optimal travel plans that took into account the user's emotions, simply by inputting the user's travel destination, travel dates, budget, and preferred activities. As a result, it was difficult to provide travel plans that met the user's expectations, and the user experience could not be improved. Furthermore, in physical stores, it was not possible to provide a shopping experience that took into account the customer's emotions, which did not lead to improved customer satisfaction.

[0343] 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.

[0344] In this invention, the server includes: means for a user to input travel destinations, itineraries, budget, and preferred activities; terminal means for receiving the input information and the user's emotional data and transmitting the information to the server; server means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotional data; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element and ensuring that the overall travel plan fits within the budget; means for transmitting the generated travel plan to the terminal so that the user can confirm and customize it; and means including an emotion engine that recognizes the user's emotional data and suggesting products and services that match the user's emotions in real time based on the emotional data. This makes it possible to provide optimal travel plans that take the user's emotions into consideration and to present recommended products and services in real time in physical stores.

[0345] The "travel destination input means" is a means by which the user inputs the travel destination.

[0346] The "travel itinerary input means" is a means by which the user inputs the duration of the trip.

[0347] The "budget input means" is a means for the user to input the amount of money that can be spent on travel.

[0348] The "means for inputting favorite activities" is a means for inputting activities and experiences that the user is interested in.

[0349] "Terminal means" refers to an electronic device that allows a user to input information and transmit that information to a server.

[0350] "Emotion data" is information about emotions collected from the user's facial expressions, tone of voice, and the like.

[0351] "Server means" is a computer system that collects and processes information based on user requirements and emotion data.

[0352] "Filtering means" refers to means for removing irrelevant or inaccurate information from collected data.

[0353] The "analysis means" is a means for analyzing the filtered data and generating a travel plan that matches the user's preferences and feelings.

[0354] A "cost calculation tool" is a tool that calculates the cost of each element of a travel plan and ensures that the overall plan stays within budget.

[0355] An "emotion engine" is an engine that analyzes a user's emotions and provides optimal information and services based on those emotions.

[0356] The "real-time suggestion means" is a means for suggesting products and services in real time based on the user's emotional data.

[0357] The present invention is a system that provides optimal travel plans and shopping experiences in brick-and-mortar stores that take into account the user's emotions. The system collects user input information and emotional data in real time, and performs analysis based on this information to provide recommended information that matches the user's emotions. A specific embodiment of this system and its processing flow are described below.

[0358] System Overview

[0359] This system consists of the following elements:

[0360] 1. Terminal means:

[0361] The device where a user enters information such as travel destination, itinerary, budget, and preferred activities. Specifically, this applies to mobile devices such as smartphones and tablets.

[0362] In addition, it has a built-in emotion engine that senses the user's facial expressions and tone of voice in real time.

[0363] 2. Server means:

[0364] A server that collects and analyzes relevant data such as tourist attractions, accommodations, places to eat, and activities from internal and external sources based on user requirements and sentiment data.

[0365] By using cloud servers, high data processing capacity and scalability are achieved.

[0366] 3. Filtering methods:

[0367] The server removes irrelevant or inaccurate information from the data collected, improving the accuracy of the data.

[0368] It uses specific algorithms to remove noise and unwanted data.

[0369] 4. Analysis method:

[0370] Based on the filtered data, optimal travel plans and product suggestions that match the user's preferences and emotions are generated.

[0371] Based on the data obtained from the emotion engine, the services desired by the user are identified.

[0372] 5. Cost calculation methods:

[0373] Calculate the cost of each element and adjust it so that the total fits within the user's budget.

[0374] 6. Real-time suggestion methods:

[0375] Based on the user's emotional data, products and services are suggested in real time.

[0376] Processing flow

[0377] Device data collection:

[0378] The user uses the terminal to input travel destination, travel dates, budget, and preferred activities.

[0379] The emotion engine collects emotional data from the user's facial expressions and tone of voice, for example, by detecting a smile on the user's face or a happy tone in the user's voice when the user is entering their travel plans.

[0380] Data transmission and collection:

[0381] The terminal transmits the travel information and emotion data entered by the user to the server in real time.

[0382] The server collects relevant information, such as tourist attractions, accommodations, and dining places, through an internal database and external APIs.

[0383] Data filtering and analysis:

[0384] The server analyzes the collected data and filters out data that is inaccurate or does not meet the user's requirements.

[0385] Based on the filtered data, the system generates an optimal travel plan tailored to the user's preferences and emotions. For example, if a user is looking for "Kyoto," "visiting historical sites," and "relaxing hot springs," the system will provide information on Kinkakuji Temple and Arashiyama Hot Springs.

[0386] Cost calculation and planning:

[0387] It calculates the cost of each element and adjusts the overall travel plan to fit within the user's budget.

[0388] The generated itinerary is sent to the terminal for the user to review and customize.

[0389] Examples of concrete examples and prompts

[0390] Examples:

[0391] While the user is wearing the smart glasses and walking around the store, products and services with a relaxing effect are displayed. Specifically, the text "Click here for relaxing aroma candles" appears on the smart glasses' display.

[0392] Example prompt sentence:

[0393] "Analyze the emotions of a customer when they visit the relaxation zone in a store, and generate a script to recommend products that have a relaxing effect based on that emotional data."

[0394] This will enable us to provide travel plans and shopping experiences that are tailored to the user's emotions in real time, thereby achieving higher customer satisfaction.

[0395] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0396] Step 1:

[0397] The user puts on the smart glasses and inputs their travel destination, itinerary, budget, and preferred activities using voice or gestures.

[0398] Input: User voice commands and gesture input

[0399] Output: Travel destination, travel dates, budget, and preferred activities

[0400] Step 2:

[0401] The device (smart glasses) uses a built-in camera and microphone to collect emotional data from the user's facial expressions and tone of voice.

[0402] Input: User's facial expression and voice tone

[0403] Output: User emotion data

[0404] Step 3:

[0405] The terminal transmits the collected travel information and emotion data to the server in a set format.

[0406] Input: Travel information and emotion data

[0407] Output: Formatted data sent to server

[0408] Step 4:

[0409] Based on the data received by the server, it uses an internal database and external APIs to collect relevant data such as tourist attractions, accommodation, places to eat, activities, etc.

[0410] Input: Travel information and emotion data

[0411] Output: Related data on attractions, accommodation, places to eat, activities, etc.

[0412] Step 5:

[0413] The server uses filtering means to remove irrelevant or inaccurate information from the collected data.

[0414] Input: Collected data

[0415] Output: Filtered data

[0416] Step 6:

[0417] The server analyzes the filtered data and the emotion data and generates an optimal travel plan that matches the user's preferences and emotions.

[0418] Input: Filtered data and sentiment data

[0419] Output: Generated itinerary

[0420] Step 7:

[0421] The server uses a cost calculation means to calculate the cost of each element of the travel plan and adjusts the overall travel plan so that it fits within the user's budget.

[0422] Input: Generated itinerary

[0423] Output: Costed itinerary

[0424] Step 8:

[0425] The server transmits the generated optimal travel plan to the terminal so that the user can check and customize it.

[0426] Input: Costed itinerary

[0427] Output: Trip plan sent to the device

[0428] Step 9:

[0429] The terminal presents the travel plan to the user and provides an interface that allows the user to review and customize the plan as needed.

[0430] Input: Travel plan sent from the server

[0431] Output: A travel plan that can be viewed by the user

[0432] Step 10:

[0433] Using the smart glasses' real-time suggestion means, optimal products and services are suggested in physical stores based on the user's emotional data.

[0434] Input: Real-time emotion data

[0435] Output: Product and service recommendations based on user sentiment

[0436] These are the specific processing steps of the system that realizes this application example. This makes it possible to provide optimal travel plans that take into account the user's emotions and to present recommended products and services in real time in physical stores.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Second embodiment]

[0441] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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."

[0453] The present invention is a system that allows users to input their travel destinations, travel itineraries, budgets, and preferred activities, and is a technology for proposing optimal travel plans. Specific embodiments for implementing this system and the processing flow are described below.

[0454] System Overview

[0455] The system basically consists of a terminal where users input information, a server that receives and processes the input information, and a database that stores and manages the data.

[0456] User input

[0457] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0458] Data transmission by the terminal

[0459] The terminal receives the information entered by the user and transmits it to the server in real time, where the server begins processing immediately.

[0460] Data collection by the server

[0461] The server queries the database based on the received user requirements, for example, gathering information on attractions, accommodations, places to eat, activities, etc. from internal databases and external APIs.

[0462] Data Filtering and Noise Removal

[0463] The server analyzes the collected data and filters out irrelevant or inaccurate information, improving the accuracy of useful information and eliminating unnecessary data, such as hotels that are already fully booked or restaurants that are closed.

[0464] Data analysis

[0465] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate an optimal itinerary that matches the user's preferences, for example, predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0466] Cost Calculation

[0467] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[0468] Presenting your travel plan

[0469] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[0470] Specific examples

[0471] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[0472] Information collected

[0473] The server suggests tourist spots such as Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine, and collects information on long-established Kyoto inns as accommodations and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen.

[0474] Filtering and Analysis

[0475] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[0476] Plan Generation and Cost Calculation

[0477] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[0478] final offer

[0479] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[0480] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan their trips efficiently and accurately.

[0481] The processing flow will be explained below.

[0482] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities, such as "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[0483] Step 2: The terminal receives the information entered by the user, converts it into the specified format, and sends it to the server in real time.

[0484] Step 3: The server receives the user's input information and executes queries to gather relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[0485] Step 4: The server searches the database for data on attractions, accommodations, places to eat, and activities, and retrieves the relevant information. It also uses external APIs to gather real-time weather and event information.

[0486] Step 5: The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0487] Step 6: The server applies algorithms to the filtered data to generate an optimal itinerary that matches the user's preferences and requirements, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0488] Step 7: The server calculates the cost of each element of the generated itinerary (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[0489] Step 8: The server sends the final itinerary to the device, including details of the places to visit, the dates, and the budgeted costs.

[0490] Step 9: The terminal displays the travel plan received from the server to the user. The user can review the travel plan and customize it as needed (for example, add other tourist spots or change the budget).

[0491] Step 10: The user finalizes the travel plan and makes a reservation if necessary. This information is sent back to the server, and all data is saved as a finalized plan.

[0492] Example 1

[0493] 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."

[0494] Conventional travel planning systems have struggled to generate optimal travel plans based on users' individual requirements and preferences. Existing systems often provide only general tourist information and are unable to provide plans that reflect the user's specific needs. In addition, cost calculations are often insufficient, potentially resulting in plans that fall outside the user's budget, creating inconvenience for users. Furthermore, the accuracy and relevance of collected data can be low, resulting in the inclusion of inaccurate information, which can degrade the quality of travel plans.

[0495] 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.

[0496] In this invention, the server includes: means for collecting data on tourist attractions, accommodations, restaurants, activities, etc. from an internal database and external sources based on the user's requirements; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means including a generative AI model for analyzing the filtered data and generating a travel plan that matches the user's preferences; cost calculation means for calculating the cost of each element and ensuring the overall travel plan stays within budget; and means for transmitting the generated travel plan to a terminal so the user can review and customize it. This enables the generation of a precise travel plan based on the user's specific requirements and preferences. Furthermore, by planning within budget, user satisfaction can be increased.

[0497] "User" refers to a person or individual who inputs information such as travel destination, travel dates, budget, and preferred activities to create a travel plan.

[0498] "Terminal means" refers to a device or system that receives information entered by a user and transmits it to a server. Examples include smartphones and computers.

[0499] The term "server means" refers to a computer system that receives information sent from a user and performs a series of processes such as data collection, filtering, analysis, and plan generation.

[0500] "Tourist destinations" refer to places and attractions that tourists can visit in a travel destination, including historical sites and natural landscapes.

[0501] "Accommodation facilities" refer to facilities that provide a place for travelers to stay. Examples include hotels and inns.

[0502] "Food and beverage establishments" refers to establishments that provide meals during travel. Examples include restaurants and cafes.

[0503] "Activities" refers to interesting activities and experiences that you undertake while traveling, such as sightseeing tours and interactive programs.

[0504] "Database" means a system for systematically storing and managing collected information, including internal databases and data from external sources.

[0505] "Source" refers to external APIs and other information resources used in data collection.

[0506] "Generative AI model" refers to an artificial intelligence model used to automatically generate optimal travel plans based on user input.

[0507] "Filtering measures" refers to algorithms or processes used to remove irrelevant or inaccurate information from collected data.

[0508] "Analysis" refers to the processes and algorithms that utilize the filtered data to generate travel plans that match the user's preferences.

[0509] "Cost calculation means" refers to a process for calculating the cost of each element of a travel plan (e.g., accommodation, transportation, meals, admission fees, etc.) and ensuring that the overall plan stays within the user's budget.

[0510] The present invention is a system that provides an optimal travel plan by allowing a user to input travel destinations, travel dates, budget, and preferred activities. The system is configured as follows.

[0511] 1. User inputs information

[0512] Users enter their travel requirements through travel websites and mobile applications. This information includes destination, travel dates, budget, and preferred activities. For example, a user might enter a prompt like this:

[0513] Travel destination: Kyoto

[0514] Travel dates: November 1st to November 5th, 2023

[0515] Budget: 100,000 yen

[0516] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0517] 2. Sending data from the device to the server

[0518] The device receives the information entered by the user and transmits it to the server in real time using a network protocol such as an HTTP POST request.

[0519] 3. Data collection and filtering by the server

[0520] Based on the received user requirements, the server collects data using internal database queries and external APIs (e.g., Google Places API), including tourist destinations, accommodations, restaurants, activities, etc.

[0521] The collected data is then filtered through a specific algorithm to filter out irrelevant or inaccurate information, for example, removing hotels that are already fully booked or restaurants that are closed.

[0522] 4. Data analysis and generative AI models

[0523] The server then uses a generative AI model to perform advanced data analysis on the filtered data. This model generates an optimal travel plan that matches the user's preferences, for example, by predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0524] 5. Cost Calculation

[0525] The server calculates the cost of each element (accommodation, transportation, meals, admission fees, etc.) and adjusts the total to fit within the user's budget. For example, the server provides the optimal plan within a user-entered budget of 100,000 yen.

[0526] 6. Generating a travel plan and presenting it to the user

[0527] The server generates an optimal travel plan based on the analysis results and cost calculations, and the plan is sent back to the terminal for the user to review and customize.

[0528] Through these processes, the system can provide travel plans based on the user's specific requirements and preferences, and can also adjust the plans to fit within the user's budget, increasing user satisfaction.

[0529] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0530] Step 1:

[0531] User input of information

[0532] Input: Information about travel destination, travel dates, budget, and preferred activities that users enter through travel sites and mobile applications.

[0533] How it works: A user manually enters information into an application form, such as:

[0534] Travel destination: Kyoto

[0535] Travel dates: November 1st to November 5th, 2023

[0536] Budget: 100,000 yen

[0537] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0538] Output: The entered information is stored within the application and passed to the next processing step.

[0539] Step 2:

[0540] Data transmission by the terminal

[0541] Input: Information entered by the user in step 1.

[0542] How it works: The device sends the information entered by the user to the server in real time using an HTTP POST request, and the server has an endpoint configured for this purpose.

[0543] Output: The server receives the user's input.

[0544] Step 3:

[0545] Data collection by the server

[0546] Input: User requirements information (destination, travel dates, budget, preferred activities).

[0547] How it works: The server queries an internal database and also sends requests to external sources (e.g., Google Places API) to gather the necessary data, including information about tourist attractions, accommodation, restaurants, and activities.

[0548] Output: The collected information on tourist attractions, accommodations, restaurants, and activities is stored on the server.

[0549] Step 4:

[0550] Server-based data filtering and noise reduction

[0551] Input: Data collected in Step 3.

[0552] How it works: The server applies filtering algorithms to remove irrelevant or inaccurate data, such as fully booked accommodations or closed restaurants.

[0553] Output: A filtered, reliable dataset is kept on the server.

[0554] Step 5:

[0555] Data analysis by server

[0556] Input: The filtered dataset.

[0557] How it works: The server uses the generative AI model to generate an optimal travel plan that matches the user's preferences, specifically predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0558] Output: A travel plan that best suits the user's requirements is generated and saved.

[0559] Step 6:

[0560] Server-based cost calculation

[0561] Input: Each element of the optimized itinerary (accommodation, transportation, places to eat, and each activity).

[0562] How it works: The server calculates the cost of each element and adjusts it to fit the overall plan within budget. For example, it adds up accommodation, travel, meals, admission fees, etc. and makes adjustments as needed.

[0563] Output: A completed itinerary within the adjusted costs.

[0564] Step 7:

[0565] Server generates and presents travel plans

[0566] Input: Cost-adjusted optimal travel plan.

[0567] Operation: The server sends the generated travel plan to the terminal again, returning the data as an HTTP response.

[0568] Output: The terminal receives the itinerary and presents it to the user.

[0569] Step 8:

[0570] User confirmation and modification of plans

[0571] Input: Travel plan provided by the device.

[0572] How it works: The user reviews the proposed itinerary and submits any necessary changes or additions through the application, for example, changing the order of visits or requesting additional attractions.

[0573] Output: The final customized itinerary is presented to the user.

[0574] (Application example 1)

[0575] 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."

[0576] Conventional travel planning systems have limitations in collecting and filtering information based on user input data, making it difficult to generate optimal plans in real time or provide users with intuitive and easy-to-understand information.In addition, advanced data analysis and AI technology are essential to provide travel plans that suit the diverse preferences of users, and no system has been able to meet these requirements.

[0577] 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.

[0578] In this invention, the server includes a means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements, a filtering means for removing irrelevant or inaccurate data from the collected data to improve data accuracy, an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences, and a means for generating and presenting an optimal travel plan using an external AI model in real time based on the data entered by the user. This makes it possible to respond to the diverse requirements of users and provide optimal and intuitive travel plans in real time.

[0579] "User" means a person or customer who inputs their preferences and requirements to create a travel plan.

[0580] "Destination" refers to a particular place or city that a User plans to visit.

[0581] "Travel itinerary" is information indicating the period from the start date to the end date of a trip.

[0582] "Budget" is the amount of money the user plans to spend on the trip.

[0583] "Preferred Activities" refers to the specific activities or experiences that a User is interested in while traveling.

[0584] "Terminal means" refers to a device or application that allows a user to input information and send it to a server.

[0585] "Server Means" means a computer system that receives user input information and collects and processes the necessary data.

[0586] A "database" is a structured data storage system for storing and managing collected information.

[0587] An "external API" is an interface for obtaining information from external data sources.

[0588] "Filtering measures" are techniques used to remove irrelevant or inaccurate information from collected data.

[0589] "Analysis means" refers to algorithms or software that generate travel plans based on the filtered data that match the user's preferences.

[0590] "Cost calculation means" is a technique for calculating the cost of each element and ensuring that the overall travel plan fits within the user's budget.

[0591] A "generative AI model" is an artificial intelligence technology used to generate optimal travel plans in real time based on user input information.

[0592] A "prompt sentence" is a guide sentence that uses a generative AI model to provide users with easy-to-understand information.

[0593] "Internal and External Sources" means the internal and external data sources used by the System to collect data.

[0594] This invention is a system that proposes optimal travel plans based on travel destinations, travel itineraries, budgets, and preferred activities input by a user. A specific method for realizing this system is described below.

[0595] System Overview

[0596] The system consists of the following main components:

[0597] Terminal means

[0598] Users input their travel requirements (destination, itinerary, budget, activities) using a smartphone application. The smartphone application was developed using React Native to provide a user-friendly interface.

[0599] Server Means

[0600] The entered data is sent to the server in real time. The server is built using Flask and receives the user's input data. The server collects data such as tourist attractions, accommodations, places to eat, and activities through internal database queries and external API calls (e.g., Google Places API, Amadeus API). The collected data is then stored in an internal database (e.g., PostgreSQL).

[0601] Filtering Methods

[0602] The server uses a specific algorithm to filter irrelevant or inaccurate information from the collected data, for example, by removing hotels that are already fully booked or restaurants that are closed.

[0603] Analysis means

[0604] The filtered data undergoes advanced analysis based on the user's requirements, using generative AI models such as GPT-4 and BERT to generate an optimal travel plan, which is then presented to the user in an easy-to-understand format using generated prompts.

[0605] Cost Calculation Method

[0606] The server calculates the cost of each element (e.g. accommodation, transportation, meals, entrance fees, etc.) and adjusts the overall itinerary to fit within the budget. This is done using the Python pandas library.

[0607] Presenting your travel plan

[0608] The generated itinerary is sent to the smartphone application user interface for the user to review and customize.

[0609] Specific examples

[0610] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[0611] 1. User input data:

[0612] Travel destination: Kyoto

[0613] Travel dates: November 1st to November 5th, 2023

[0614] Budget: 100,000 yen

[0615] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0616] 2. Data collection and filtering:

[0617] The server uses the Google Places API and Amadeus API to collect data on places such as Kinkaku-ji Temple, Kiyomizu-dera Temple, Fushimi Inari Taisha Shrine, long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen.

[0618] Eliminate irrelevant, duplicate, and inaccurate data.

[0619] 3. Data analysis and plan generation:

[0620] GPT-4 is used to generate prompts and suggest specific travel plans.

[0621] For example, a detailed itinerary suggestion such as "Visit Kinkakuji Temple on November 1st and check into a long-established inn" is presented.

[0622] Prompt Sentence Examples

[0623] "I'm planning a trip to Kyoto from November 1st to November 5th, 2023. My budget is 100,000 yen. My favorite activities are visiting historical sites, experiencing Japanese cuisine, and relaxing in hot springs. Please suggest a recommended itinerary."

[0624] In this way, specific processing is carried out to provide users with the most suitable travel plans. By linking the entire system, it becomes possible to provide high-quality travel plans that meet the user's requests in real time.

[0625] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0626] Step 1:

[0627] A user uses a smartphone application to input their travel destination, travel dates, budget, and preferred activities. Specifically, the user fills out an input form in the application, and the information is saved in the application. The input information includes the travel destination (e.g., Kyoto), travel dates (e.g., November 1 to November 5, 2023), budget (e.g., 100,000 yen), and preferred activities (e.g., visiting historical sites, experiencing Japanese cuisine, hot springs).

[0628] Step 2:

[0629] The device sends the entered travel requirements to the server in real time. Specifically, when the user presses the "Submit" button, the application converts the input data into JSON format and sends it to the server using an HTTP request. The input includes travel destinations, travel dates, budget, and preferred activities. The server receives this data and stores it in an understandable format.

[0630] Step 3:

[0631] The server uses an internal database and external APIs (e.g., Google Places API or Amadeus API) to collect information on attractions, accommodation, places to eat, and activities based on user input data. The server uses the user input data to generate an API query and sends a request to the external API. It retrieves relevant information from the database and consolidates this information. The input is the user's travel requirements, and the output is information on attractions, accommodation, places to eat, and activities collected from the API and database.

[0632] Step 4:

[0633] The server filters irrelevant data and inaccurate information from the collected data. Specifically, the server uses a specific algorithm to remove duplicate data, establishments that can no longer be booked, restaurants that are no longer open, etc. The input is data collected from the API and database, and the output is filtered, highly accurate data.

[0634] Step 5:

[0635] The server performs analysis based on the filtered data and generates a travel plan that matches the user's preferences. This analysis uses a generative AI model such as GPT-4 or BERT. The server provides a prompt to the generative AI model, which then generates an optimal travel plan based on that. The input is the filtered data and the prompt, and the output is the generated travel plan.

[0636] Step 6:

[0637] The server calculates the cost of each element of the generated travel plan and adjusts it so that the overall plan fits within the user's budget. Specifically, the server calculates the cost of each tourist attraction, accommodation, place to eat, and activity, and fine-tunes the plan so that the total amount fits within the budget. The input is the cost information of each element, and the output is the adjusted travel plan.

[0638] Step 7:

[0639] The server sends the final adjusted itinerary to the device for the user to review and customize. Specifically, the server converts the generated plan into JSON format and sends it to the device using an HTTP response. The device displays the received plan on a user interface, allowing the user to review it and make fine adjustments if necessary. The input is the adjusted itinerary, and the output is the itinerary presented to the user.

[0640] In this way, each step works together to provide the user with the most suitable travel plan.

[0641] 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.

[0642] The present invention combines a system in which a user inputs their travel destination, itinerary, budget, and preferred activities with an emotion engine, and is a technology for providing optimal travel plans that take the user's emotions into consideration more than conventional travel planning systems. A specific embodiment of this system and its processing flow are described below.

[0643] System Overview

[0644] This system consists of a terminal where users input information, a server that receives and processes the input information and emotion data, a database that stores and manages the data, and an emotion engine that recognizes the user's emotions.

[0645] User input

[0646] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0647] Emotion Engine

[0648] The device's built-in emotion engine collects emotion data from the user's facial expressions and voice while they are typing. For example, if the user is smiling while typing, that emotion data is collected. It also uses voice recognition technology to recognize emotions from the tone of the user's voice.

[0649] Data transmission by the terminal

[0650] The terminal receives the travel information and collected emotion data entered by the user, converts them into a set format, and transmits them to the server in real time.

[0651] Data collection by the server

[0652] Based on the received user requirements and sentiment data, the server executes queries to collect relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[0653] Data Filtering and Noise Removal

[0654] The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0655] Data analysis

[0656] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate optimal travel plans that match the user's preferences and emotions, for example, predicting crowds at tourist spots and optimizing the order in which they are visited.

[0657] Cost Calculation

[0658] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[0659] Reflecting emotional data

[0660] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and spots that match the user's emotions. For example, if the user feels like relaxing, hot springs and relaxation facilities will be recommended.

[0661] Presenting your travel plan

[0662] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[0663] Specific examples

[0664] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and smiles while inputting the information and says, "I'd like a place that's relaxing," the system will operate as follows:

[0665] Collected information and emotional data

[0666] The server suggests Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist spots, collects Kyoto's long-established inns as accommodations, and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen, reflecting the user's desire to relax.

[0667] Filtering and Analysis

[0668] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[0669] Plan Generation and Cost Calculation

[0670] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[0671] final offer

[0672] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[0673] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan travel efficiently, accurately, and in line with their own preferences.

[0674] The processing flow will be explained below.

[0675] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities. For example, they might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[0676] Step 2: The device's built-in emotion engine analyzes the user's facial expressions and voice in real time as they type, collecting emotional data. For example, if the user smiles while typing, the emotion data is recorded as "relaxed."

[0677] Step 3: The device converts the input travel information and collected emotion data into a predefined format and transmits it to the server in real time. The transmitted data includes travel destination, itinerary, budget, activity preferences, and emotion data.

[0678] Step 4: The server executes queries to collect data on tourist attractions, accommodations, places to eat, and activities from the database and external APIs based on the received travel information and sentiment data. For example, it retrieves information on tourist attractions and accommodations in Kyoto.

[0679] Step 5: The server filters the collected data to remove irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0680] Step 6: The server applies algorithms to generate an optimal itinerary based on the filtered data, matching the user's preferences and requirements. Specifically, it predicts crowding at tourist spots and optimizes the order in which they are visited.

[0681] Step 7: The server analyzes the emotion data obtained from the emotion engine and identifies recommended activities and spots that match the user's emotions. For example, if the user expresses a desire to relax, the server will recommend hot springs and relaxation facilities.

[0682] Step 8: The server calculates the cost of each element of the generated travel plan (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[0683] Step 9: The server sends the final itinerary to the device, including details of the planned destinations, itinerary, budgeted costs, and recommended activities that take into account the sentiment data.

[0684] Step 10: The terminal displays the travel plan received from the server to the user, who can review the plan and further customize it if necessary (e.g., select additional tourist attractions or change the budget).

[0685] Step 11: The user finalizes the travel plan and completes the booking procedure if necessary. The final plan is sent to the server and all data is saved as the finalized plan.

[0686] Example 2

[0687] 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."

[0688] Conventional travel planning systems only considered the user's basic requirements, making it difficult to provide optimal travel plans that reflected the user's emotions and detailed preferences. Furthermore, data collection, filtering, and analysis often contained inaccurate or irrelevant information, making it difficult to generate travel plans that satisfied users. Furthermore, the ability to adjust travel plans to fit within a budget was often insufficient, requiring users to put in a great deal of effort to create a travel plan that fit their budget.

[0689] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0690] In this invention, the server includes: means for collecting information on tourist destinations, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotions; filtering means for removing irrelevant or inaccurate data from the collected information to increase data accuracy; analysis means for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element to ensure that the overall travel plan stays within budget; and means for transmitting the generated travel plan to a user interface so that the user can review and customize it. This makes it possible to provide an optimal travel plan within budget, taking into account the user's emotions and detailed preferences and eliminating irrelevant data.

[0691] A "user" is an individual or organization that inputs travel destinations, travel itineraries, budget, and preferred activities.

[0692] A "user interface" is a means by which a user inputs information and transmits that information and emotion data to a server.

[0693] The "server" is a central processing unit that collects, analyzes, and filters information based on the user's requirements and feelings, generates an optimal travel plan, and transmits it to the terminal.

[0694] "Sources" are data suppliers that provide information on tourist destinations, accommodation, places to eat, activities, etc. through databases and external data acquisition means.

[0695] "Filtering measures" are processes used to remove irrelevant or inaccurate data from collected information and improve the accuracy of the data.

[0696] The "analysis means" is a process for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions.

[0697] "Cost calculation means" is a process for calculating the cost of each element and adjusting the overall travel plan to fit within the user's budget.

[0698] A "travel plan" is a proposal that integrates schedules and costs including sightseeing destinations, accommodations, places to eat, activities, etc. that meets the user's requirements and sentiments.

[0699] The present invention is a system that allows a user to input travel destinations, travel dates, budgets, and preferred activities, and provides an optimal travel plan based on the inputs, taking into consideration the user's feelings. Specific embodiments of the present invention are described below.

[0700] User data entry

[0701] A user uses a device to access a travel website or mobile application, and after logging in, enters the necessary information. The information entered includes travel destination, travel dates, budget, and preferred activities. For example, a user might enter the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This information is then recorded by the device.

[0702] Emotion recognition by emotion engine

[0703] The emotion engine installed on the device analyzes the user's facial expressions and voice. This is done through a camera and microphone, and emotional data is collected from the facial expressions and tone of voice shown when the user types. For example, if a user smiles and types "I like a place where I can relax," that emotion is collected as data.

[0704] Sending data

[0705] The device converts the travel information and collected emotion data entered by the user into a predetermined format and transmits it to the server in real time in a unified format such as JSON.

[0706] Data collection and analysis by the server

[0707] The server sends queries to databases and external APIs based on the received information to collect information on tourist destinations, accommodations, places to eat, and activities. For example, it obtains information on Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist attractions, long-established Kyoto inns as accommodations, Michelin-starred Japanese restaurants as places to eat, and Arashiyama Onsen as activities. The server then filters out unnecessary data and incorrect information from the collected information to improve its accuracy.

[0708] Filtering and Data Analysis

[0709] The server analyzes the filtered information and generates an optimal itinerary that matches the user's preferences and emotions. It uses a new algorithm to predict crowding at tourist spots and optimize the order in which the users visit. For example, the server can plan a trip to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon.

[0710] Cost Calculation

[0711] The server calculates the cost of each element and adjusts it so that the total fits within the user's budget. Specifically, it adds up the cost of accommodation, transportation, meals, admission fees, etc., so that the total comes in at 100,000 yen or less.

[0712] Reflecting emotional data

[0713] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and tourist spots based on the user's emotions. For example, hot springs and relaxation facilities can be recommended to users who prioritize relaxation.

[0714] Presenting your travel plan

[0715] The generated travel plan is sent to the terminal, where the user can review it. The user can review the presented plan and further customize it. Re-planning according to the user's request is performed by re-sending it from the terminal to the server.

[0716] Examples of concrete examples and prompts

[0717] For example, if a user enters "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and says with a smile, "I'd like a place to relax," the system will act as follows:

[0718] Collected information and emotional data

[0719] User request: "Kyoto" "November 1st to November 5th, 2023" "100,000 yen" "Visit historical sites, experience Japanese cuisine, and relax in hot springs"

[0720] User Sentiment: "Relaxed"

[0721] Server Processing

[0722] Collect information on tourist spots such as Kinkakuji Temple, Kiyomizudera Temple, and Fushimi Inari Taisha Shrine

[0723] Collect information on Kyoto's long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen

[0724] Calculate the cost and adjust the total amount to within 100,000 yen

[0725] Recommending hot springs and relaxation facilities based on user emotional data

[0726] Prompt Sentence Examples

[0727] Please enter your "travel destination," "travel dates," "budget," and "preferred activities."

[0728] Example: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0729] Example of emotional input: "I like a place where I can relax."

[0730] This allows users to get an efficient and personalized travel plan that reflects their emotions and detailed requests.

[0731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0732] Step 1: User Data Entry

[0733] A user logs into a travel website or mobile app using a device and enters their travel destination, travel dates, budget, and preferred activities. The entered information is stored in the device's database. For example, a user might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This input data is used for subsequent processing.

[0734] Step 2: Emotion recognition by the emotion engine

[0735] While the user is entering data, the device's built-in emotion engine uses the camera and microphone to collect the user's facial expressions and tone of voice. The data is analyzed in real time and stored in a database as the user's emotion information. For example, if a user smiles and says, "I like places where I can relax," the emotion data is saved as a tag called "relaxation."

[0736] Step 3: Sending data

[0737] The device combines the user input data and collected emotion data into a single packet and sends it to the server in a specified format (e.g., JSON format). The server receives this packet and parses it to extract each data element. For example, it may be sent in a format such as "Travel destination: Kyoto," "Date: November 1st to November 5th, 2023," "Budget: 100,000 yen," "Favorite activities: visiting historical sites, experiencing Japanese cuisine, relaxing hot springs," and "Emotion: Relaxation."

[0738] Step 4: Data collection by the server

[0739] The server analyzes the received user requirements and sentiment data and collects information such as tourist destinations, accommodations, dining places, and activities based on the analysis. It uses internal database queries and external APIs to collect the corresponding data. For example, the server might collect tourist spot information such as "Kinkaku-ji Temple," "Kiyomizu-dera Temple," and "Fushimi Inari Taisha Shrine," accommodation information such as "long-established Kyoto inns," and dining information such as "Michelin-starred Japanese restaurants."

[0740] Step 5: Data filtering and noise removal

[0741] The server analyzes the collected data and filters out unnecessary or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activity on days when bad weather is predicted. The filtered data is then stored as a newly organized dataset.

[0742] Step 6: Data analysis and plan generation

[0743] The server then applies the filtered information to advanced analytical algorithms to generate an optimal travel plan that matches the user's preferences and emotions. For example, it predicts how crowded tourist spots will be and calculates the optimal order in which to visit them. Specifically, it creates a schedule that visits Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and stores the resulting plan in a database.

[0744] Step 7: Cost calculation

[0745] The server aggregates the costs of each element and adjusts them so that the total fits within the user's budget. For example, it calculates the cost of accommodation, transportation, meals, and admission fees, and optimizes the items to keep the total within 100,000 yen. The cost calculation results are included in the generated travel plan.

[0746] Step 8: Reflecting emotional data

[0747] Emotional data can also influence the optimization of travel plans. For example, if a user indicates a desire to relax, the server will prioritize recommendations for hot springs and relaxation facilities. This information is incorporated as part of the travel plan.

[0748] Step 9: Present your travel plans

[0749] The final itinerary is then reformatted and sent to the device. The user can review the presented itinerary and customize it as needed. The user's feedback is then sent back to the server, and the plan is updated as needed. For example, a user may enter a request such as "I would like to change the time to visit Kinkaku-ji Temple."

[0750] (Application example 2)

[0751] 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."

[0752] Conventional systems were unable to provide optimal travel plans that took into account the user's emotions, simply by inputting the user's travel destination, travel dates, budget, and preferred activities. As a result, it was difficult to provide travel plans that met the user's expectations, and the user experience could not be improved. Furthermore, in physical stores, it was not possible to provide a shopping experience that took into account the customer's emotions, which did not lead to improved customer satisfaction.

[0753] 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.

[0754] In this invention, the server includes: means for a user to input travel destinations, itineraries, budget, and preferred activities; terminal means for receiving the input information and the user's emotional data and transmitting the information to the server; server means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotional data; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element and ensuring that the overall travel plan fits within the budget; means for transmitting the generated travel plan to the terminal so that the user can confirm and customize it; and means including an emotion engine that recognizes the user's emotional data and suggesting products and services that match the user's emotions in real time based on the emotional data. This makes it possible to provide optimal travel plans that take the user's emotions into consideration and to present recommended products and services in real time in physical stores.

[0755] The "travel destination input means" is a means by which the user inputs the travel destination.

[0756] The "travel itinerary input means" is a means by which the user inputs the duration of the trip.

[0757] The "budget input means" is a means for the user to input the amount of money that can be spent on travel.

[0758] The "means for inputting favorite activities" is a means for inputting activities and experiences that the user is interested in.

[0759] "Terminal means" refers to an electronic device that allows a user to input information and transmit that information to a server.

[0760] "Emotion data" is information about emotions collected from the user's facial expressions, tone of voice, and the like.

[0761] "Server means" is a computer system that collects and processes information based on user requirements and emotion data.

[0762] "Filtering means" refers to means for removing irrelevant or inaccurate information from collected data.

[0763] The "analysis means" is a means for analyzing the filtered data and generating a travel plan that matches the user's preferences and feelings.

[0764] A "cost calculation tool" is a tool that calculates the cost of each element of a travel plan and ensures that the overall plan stays within budget.

[0765] An "emotion engine" is an engine that analyzes a user's emotions and provides optimal information and services based on those emotions.

[0766] The "real-time suggestion means" is a means for suggesting products and services in real time based on the user's emotional data.

[0767] The present invention is a system that provides optimal travel plans and shopping experiences in brick-and-mortar stores that take into account the user's emotions. The system collects user input information and emotional data in real time, and performs analysis based on this information to provide recommended information that matches the user's emotions. A specific embodiment of this system and its processing flow are described below.

[0768] System Overview

[0769] This system consists of the following elements:

[0770] 1. Terminal means:

[0771] The device where a user enters information such as travel destination, itinerary, budget, and preferred activities. Specifically, this applies to mobile devices such as smartphones and tablets.

[0772] In addition, it has a built-in emotion engine that senses the user's facial expressions and tone of voice in real time.

[0773] 2. Server means:

[0774] A server that collects and analyzes relevant data such as tourist attractions, accommodations, places to eat, and activities from internal and external sources based on user requirements and sentiment data.

[0775] By using cloud servers, high data processing capacity and scalability are achieved.

[0776] 3. Filtering methods:

[0777] The server removes irrelevant or inaccurate information from the data collected, improving the accuracy of the data.

[0778] It uses specific algorithms to remove noise and unwanted data.

[0779] 4. Analysis method:

[0780] Based on the filtered data, optimal travel plans and product suggestions that match the user's preferences and emotions are generated.

[0781] Based on the data obtained from the emotion engine, the services desired by the user are identified.

[0782] 5. Cost calculation methods:

[0783] Calculate the cost of each element and adjust it so that the total fits within the user's budget.

[0784] 6. Real-time suggestion methods:

[0785] Based on the user's emotional data, products and services are suggested in real time.

[0786] Processing flow

[0787] Device data collection:

[0788] The user uses the terminal to input travel destination, travel dates, budget, and preferred activities.

[0789] The emotion engine collects emotional data from the user's facial expressions and tone of voice, for example, by detecting a smile on the user's face or a happy tone in the user's voice when the user is entering their travel plans.

[0790] Data transmission and collection:

[0791] The terminal transmits the travel information and emotion data entered by the user to the server in real time.

[0792] The server collects relevant information, such as tourist attractions, accommodations, and dining places, through an internal database and external APIs.

[0793] Data filtering and analysis:

[0794] The server analyzes the collected data and filters out data that is inaccurate or does not meet the user's requirements.

[0795] Based on the filtered data, the system generates an optimal travel plan tailored to the user's preferences and emotions. For example, if a user is looking for "Kyoto," "visiting historical sites," and "relaxing hot springs," the system will provide information on Kinkakuji Temple and Arashiyama Hot Springs.

[0796] Cost calculation and planning:

[0797] It calculates the cost of each element and adjusts the overall travel plan to fit within the user's budget.

[0798] The generated itinerary is sent to the terminal for the user to review and customize.

[0799] Examples of concrete examples and prompts

[0800] Examples:

[0801] While the user is wearing the smart glasses and walking around the store, products and services with a relaxing effect are displayed. Specifically, the text "Click here for relaxing aroma candles" appears on the smart glasses' display.

[0802] Example prompt sentence:

[0803] "Analyze the emotions of a customer when they visit the relaxation zone in a store, and generate a script to recommend products that have a relaxing effect based on that emotional data."

[0804] This will enable us to provide travel plans and shopping experiences that are tailored to the user's emotions in real time, thereby achieving higher customer satisfaction.

[0805] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0806] Step 1:

[0807] The user puts on the smart glasses and inputs their travel destination, itinerary, budget, and preferred activities using voice or gestures.

[0808] Input: User voice commands and gesture input

[0809] Output: Travel destination, travel dates, budget, and preferred activities

[0810] Step 2:

[0811] The device (smart glasses) uses a built-in camera and microphone to collect emotional data from the user's facial expressions and tone of voice.

[0812] Input: User's facial expression and voice tone

[0813] Output: User emotion data

[0814] Step 3:

[0815] The terminal transmits the collected travel information and emotion data to the server in a set format.

[0816] Input: Travel information and emotion data

[0817] Output: Formatted data sent to server

[0818] Step 4:

[0819] Based on the data received by the server, it uses an internal database and external APIs to collect relevant data such as tourist attractions, accommodation, places to eat, activities, etc.

[0820] Input: Travel information and emotion data

[0821] Output: Related data on attractions, accommodation, places to eat, activities, etc.

[0822] Step 5:

[0823] The server uses filtering means to remove irrelevant or inaccurate information from the collected data.

[0824] Input: Collected data

[0825] Output: Filtered data

[0826] Step 6:

[0827] The server analyzes the filtered data and the emotion data and generates an optimal travel plan that matches the user's preferences and emotions.

[0828] Input: Filtered data and sentiment data

[0829] Output: Generated itinerary

[0830] Step 7:

[0831] The server uses a cost calculation means to calculate the cost of each element of the travel plan and adjusts the overall travel plan so that it fits within the user's budget.

[0832] Input: Generated itinerary

[0833] Output: Costed itinerary

[0834] Step 8:

[0835] The server transmits the generated optimal travel plan to the terminal so that the user can check and customize it.

[0836] Input: Costed itinerary

[0837] Output: Trip plan sent to the device

[0838] Step 9:

[0839] The terminal presents the travel plan to the user and provides an interface that allows the user to review and customize the plan as needed.

[0840] Input: Travel plan sent from the server

[0841] Output: A travel plan that can be viewed by the user

[0842] Step 10:

[0843] Using the smart glasses' real-time suggestion means, optimal products and services are suggested in physical stores based on the user's emotional data.

[0844] Input: Real-time emotion data

[0845] Output: Product and service recommendations based on user sentiment

[0846] These are the specific processing steps of the system that realizes this application example. This makes it possible to provide optimal travel plans that take into account the user's emotions and to present recommended products and services in real time in physical stores.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] [Third embodiment]

[0851] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0852] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0853] 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).

[0854] 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.

[0855] 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.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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."

[0863] The present invention is a system that allows users to input their travel destinations, travel itineraries, budgets, and preferred activities, and is a technology for proposing optimal travel plans. Specific embodiments for implementing this system and the processing flow are described below.

[0864] System Overview

[0865] The system basically consists of a terminal where users input information, a server that receives and processes the input information, and a database that stores and manages the data.

[0866] User input

[0867] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[0868] Data transmission by the terminal

[0869] The terminal receives the information entered by the user and transmits it to the server in real time, where the server begins processing immediately.

[0870] Data collection by the server

[0871] The server queries the database based on the received user requirements, for example, gathering information on attractions, accommodations, places to eat, activities, etc. from internal databases and external APIs.

[0872] Data Filtering and Noise Removal

[0873] The server analyzes the collected data and filters out irrelevant or inaccurate information, improving the accuracy of useful information and eliminating unnecessary data, such as hotels that are already fully booked or restaurants that are closed.

[0874] Data analysis

[0875] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate an optimal itinerary that matches the user's preferences, for example, predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0876] Cost Calculation

[0877] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[0878] Presenting your travel plan

[0879] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[0880] Specific examples

[0881] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[0882] Information collected

[0883] The server suggests tourist spots such as Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine, and collects information on long-established Kyoto inns as accommodations and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen.

[0884] Filtering and Analysis

[0885] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[0886] Plan Generation and Cost Calculation

[0887] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[0888] final offer

[0889] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[0890] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan their trips efficiently and accurately.

[0891] The processing flow will be explained below.

[0892] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities, such as "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[0893] Step 2: The terminal receives the information entered by the user, converts it into the specified format, and sends it to the server in real time.

[0894] Step 3: The server receives the user's input information and executes queries to gather relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[0895] Step 4: The server searches the database for data on attractions, accommodations, places to eat, and activities, and retrieves the relevant information. It also uses external APIs to gather real-time weather and event information.

[0896] Step 5: The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[0897] Step 6: The server applies algorithms to the filtered data to generate an optimal itinerary that matches the user's preferences and requirements, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0898] Step 7: The server calculates the cost of each element of the generated itinerary (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[0899] Step 8: The server sends the final itinerary to the device, including details of the places to visit, the dates, and the budgeted costs.

[0900] Step 9: The terminal displays the travel plan received from the server to the user. The user can review the travel plan and customize it as needed (for example, add other tourist spots or change the budget).

[0901] Step 10: The user finalizes the travel plan and makes a reservation if necessary. This information is sent back to the server, and all data is saved as a finalized plan.

[0902] Example 1

[0903] 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."

[0904] Conventional travel planning systems have struggled to generate optimal travel plans based on users' individual requirements and preferences. Existing systems often provide only general tourist information and are unable to provide plans that reflect the user's specific needs. In addition, cost calculations are often insufficient, potentially resulting in plans that fall outside the user's budget, creating inconvenience for users. Furthermore, the accuracy and relevance of collected data can be low, resulting in the inclusion of inaccurate information, which can degrade the quality of travel plans.

[0905] 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.

[0906] In this invention, the server includes: means for collecting data on tourist attractions, accommodations, restaurants, activities, etc. from an internal database and external sources based on the user's requirements; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means including a generative AI model for analyzing the filtered data and generating a travel plan that matches the user's preferences; cost calculation means for calculating the cost of each element and ensuring the overall travel plan stays within budget; and means for transmitting the generated travel plan to a terminal so the user can review and customize it. This enables the generation of a precise travel plan based on the user's specific requirements and preferences. Furthermore, by planning within budget, user satisfaction can be increased.

[0907] "User" refers to a person or individual who inputs information such as travel destination, travel dates, budget, and preferred activities to create a travel plan.

[0908] "Terminal means" refers to a device or system that receives information entered by a user and transmits it to a server. Examples include smartphones and computers.

[0909] The term "server means" refers to a computer system that receives information sent from a user and performs a series of processes such as data collection, filtering, analysis, and plan generation.

[0910] "Tourist destinations" refer to places and attractions that tourists can visit in a travel destination, including historical sites and natural landscapes.

[0911] "Accommodation facilities" refer to facilities that provide a place for travelers to stay. Examples include hotels and inns.

[0912] "Food and beverage establishments" refers to establishments that provide meals during travel. Examples include restaurants and cafes.

[0913] "Activities" refers to interesting activities and experiences that you undertake while traveling, such as sightseeing tours and interactive programs.

[0914] "Database" means a system for systematically storing and managing collected information, including internal databases and data from external sources.

[0915] "Source" refers to external APIs and other information resources used in data collection.

[0916] "Generative AI model" refers to an artificial intelligence model used to automatically generate optimal travel plans based on user input.

[0917] "Filtering measures" refers to algorithms or processes used to remove irrelevant or inaccurate information from collected data.

[0918] "Analysis" refers to the processes and algorithms that utilize the filtered data to generate travel plans that match the user's preferences.

[0919] "Cost calculation means" refers to a process for calculating the cost of each element of a travel plan (e.g., accommodation, transportation, meals, admission fees, etc.) and ensuring that the overall plan stays within the user's budget.

[0920] The present invention is a system that provides an optimal travel plan by allowing a user to input travel destinations, travel dates, budget, and preferred activities. The system is configured as follows.

[0921] 1. User inputs information

[0922] Users enter their travel requirements through travel websites and mobile applications. This information includes travel destinations, travel dates, budget, and preferred activities. For example, a user might enter a prompt like this:

[0923] Travel destination: Kyoto

[0924] Travel dates: November 1st to November 5th, 2023

[0925] Budget: 100,000 yen

[0926] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0927] 2. Sending data from the device to the server

[0928] The device receives the information entered by the user and transmits it to the server in real time using a network protocol such as an HTTP POST request.

[0929] 3. Data collection and filtering by the server

[0930] Based on the received user requirements, the server collects data using internal database queries and external APIs (e.g., Google Places API), including tourist destinations, accommodations, restaurants, activities, etc.

[0931] The collected data is then filtered through a specific algorithm to filter out irrelevant or inaccurate information, for example, removing accommodations that are already fully booked or restaurants that are closed.

[0932] 4. Data analysis and generative AI models

[0933] The server then uses a generative AI model to perform advanced data analysis on the filtered data. This model generates an optimal travel plan that matches the user's preferences, for example, by predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0934] 5. Cost Calculation

[0935] The server calculates the cost of each element (accommodation, transportation, meals, admission fees, etc.) and adjusts the total to fit within the user's budget. For example, the server provides the optimal plan within a user-entered budget of 100,000 yen.

[0936] 6. Generating a travel plan and presenting it to the user

[0937] The server generates an optimal travel plan based on the analysis results and cost calculations, and the plan is sent back to the terminal for the user to review and customize.

[0938] Through these processes, the system can provide travel plans based on the user's specific requirements and preferences, and can also adjust the plans to fit within the user's budget, increasing user satisfaction.

[0939] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0940] Step 1:

[0941] User input of information

[0942] Input: Information about travel destination, travel dates, budget, and preferred activities that users enter through travel sites and mobile applications.

[0943] How it works: A user manually enters information into an application form, such as:

[0944] Travel destination: Kyoto

[0945] Travel dates: November 1st to November 5th, 2023

[0946] Budget: 100,000 yen

[0947] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[0948] Output: The entered information is stored within the application and passed to the next processing step.

[0949] Step 2:

[0950] Data transmission by the terminal

[0951] Input: Information entered by the user in step 1.

[0952] How it works: The device sends the information entered by the user to the server in real time using an HTTP POST request, and the server has an endpoint configured for this purpose.

[0953] Output: The server receives the user's input.

[0954] Step 3:

[0955] Data collection by the server

[0956] Input: User requirements information (destination, travel dates, budget, preferred activities).

[0957] How it works: The server queries an internal database and also sends requests to external sources (e.g., Google Places API) to gather the necessary data, including information about tourist attractions, accommodation, restaurants, and activities.

[0958] Output: The collected information on tourist attractions, accommodations, restaurants, and activities is stored on the server.

[0959] Step 4:

[0960] Server-based data filtering and noise reduction

[0961] Input: Data collected in Step 3.

[0962] How it works: The server applies filtering algorithms to remove irrelevant or inaccurate data, such as fully booked accommodations or closed restaurants.

[0963] Output: A filtered, reliable dataset is kept on the server.

[0964] Step 5:

[0965] Data analysis by server

[0966] Input: The filtered dataset.

[0967] How it works: The server uses the generative AI model to generate an optimal travel plan that matches the user's preferences, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[0968] Output: A travel plan that best suits the user's requirements is generated and saved.

[0969] Step 6:

[0970] Server-based cost calculation

[0971] Input: Each element of the optimized itinerary (accommodation, transportation, places to eat, and each activity).

[0972] How it works: The server calculates the cost of each element and adjusts it to fit the overall plan within budget. For example, it adds up accommodation, transportation, meals, admission fees, etc. and makes adjustments as needed.

[0973] Output: A completed itinerary within the adjusted costs.

[0974] Step 7:

[0975] Server generates and presents travel plans

[0976] Input: Cost-adjusted optimal travel plan.

[0977] Operation: The server sends the generated travel plan to the terminal again, returning the data as an HTTP response.

[0978] Output: The terminal receives the itinerary and presents it to the user.

[0979] Step 8:

[0980] User confirmation and modification of plans

[0981] Input: Travel plan provided by the device.

[0982] How it works: The user reviews the proposed itinerary and submits any necessary changes or additions through the application, for example, changing the order of visits or requesting additional attractions.

[0983] Output: The final customized itinerary is presented to the user.

[0984] (Application example 1)

[0985] 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."

[0986] Conventional travel planning systems have limitations in collecting and filtering information based on user input data, making it difficult to generate optimal plans in real time or provide users with intuitive and easy-to-understand information.In addition, advanced data analysis and AI technology are essential to provide travel plans that suit the diverse preferences of users, and no system has been able to meet these requirements.

[0987] 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.

[0988] In this invention, the server includes a means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements, a filtering means for removing irrelevant or inaccurate data from the collected data to improve data accuracy, an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences, and a means for generating and presenting an optimal travel plan using an external AI model in real time based on the data entered by the user. This makes it possible to respond to the diverse requirements of users and provide optimal and intuitive travel plans in real time.

[0989] "User" means a person or customer who inputs their preferences and requirements to create a travel plan.

[0990] "Destination" refers to a particular place or city that a User plans to visit.

[0991] "Travel itinerary" is information indicating the period from the start date to the end date of a trip.

[0992] "Budget" is the amount of money the user plans to spend on the trip.

[0993] "Preferred Activities" refers to the specific activities or experiences that a User is interested in while traveling.

[0994] "Terminal means" refers to a device or application that allows a user to input information and send it to a server.

[0995] "Server Means" means a computer system that receives user input information and collects and processes the necessary data.

[0996] A "database" is a structured data storage system for storing and managing collected information.

[0997] An "external API" is an interface for obtaining information from external data sources.

[0998] "Filtering measures" are techniques used to remove irrelevant or inaccurate information from collected data.

[0999] "Analysis means" refers to algorithms or software that generate travel plans based on the filtered data that match the user's preferences.

[1000] "Cost calculation means" is a technique for calculating the cost of each element and ensuring that the overall travel plan fits within the user's budget.

[1001] A "generative AI model" is an artificial intelligence technology used to generate optimal travel plans in real time based on user input information.

[1002] A "prompt sentence" is a guide sentence that uses a generative AI model to provide users with easy-to-understand information.

[1003] "Internal and External Sources" means the internal and external data sources used by the System to collect data.

[1004] This invention is a system that proposes optimal travel plans based on travel destinations, travel itineraries, budgets, and preferred activities input by a user. A specific method for realizing this system is described below.

[1005] System Overview

[1006] The system consists of the following main components:

[1007] Terminal means

[1008] Users input their travel requirements (destination, itinerary, budget, activities) using a smartphone application. The smartphone application was developed using React Native to provide a user-friendly interface.

[1009] Server Means

[1010] The entered data is sent to the server in real time. The server is built using Flask and receives the user's input data. The server collects data such as tourist attractions, accommodations, places to eat, and activities through internal database queries and external API calls (e.g., Google Places API, Amadeus API). The collected data is then stored in an internal database (e.g., PostgreSQL).

[1011] Filtering Methods

[1012] The server uses a specific algorithm to filter irrelevant or inaccurate information from the collected data, for example, by removing hotels that are already fully booked or restaurants that are closed.

[1013] Analysis means

[1014] The filtered data undergoes advanced analysis based on the user's requirements, using generative AI models such as GPT-4 and BERT to generate an optimal travel plan, which is then presented to the user in an easy-to-understand format using generated prompts.

[1015] Cost Calculation Method

[1016] The server calculates the cost of each element (e.g. accommodation, transportation, meals, entrance fees, etc.) and adjusts the overall itinerary to fit within the budget. This is done using the Python pandas library.

[1017] Presenting your travel plan

[1018] The generated itinerary is sent to the smartphone application user interface for the user to review and customize.

[1019] Specific examples

[1020] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[1021] 1. User input data:

[1022] Travel destination: Kyoto

[1023] Travel dates: November 1st to November 5th, 2023

[1024] Budget: 100,000 yen

[1025] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[1026] 2. Data collection and filtering:

[1027] The server uses the Google Places API and Amadeus API to collect data on places such as Kinkaku-ji Temple, Kiyomizu-dera Temple, Fushimi Inari Taisha Shrine, long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen.

[1028] Eliminate irrelevant, duplicate, and inaccurate data.

[1029] 3. Data analysis and plan generation:

[1030] GPT-4 is used to generate prompts and suggest specific travel plans.

[1031] For example, a detailed itinerary suggestion such as "Visit Kinkakuji Temple on November 1st and check into a long-established inn" is presented.

[1032] Prompt Sentence Examples

[1033] "I'm planning a trip to Kyoto from November 1st to November 5th, 2023. My budget is 100,000 yen. My favorite activities are visiting historical sites, experiencing Japanese cuisine, and relaxing in hot springs. Please suggest a recommended itinerary."

[1034] In this way, specific processing is carried out to provide the user with the optimal travel plan. By linking the entire system, it becomes possible to provide high-quality travel plans that meet the user's requests in real time.

[1035] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1036] Step 1:

[1037] A user uses a smartphone application to input their travel destination, travel dates, budget, and preferred activities. Specifically, the user fills out an input form in the application, and the information is saved in the application. The input information includes the travel destination (e.g., Kyoto), travel dates (e.g., November 1 to November 5, 2023), budget (e.g., 100,000 yen), and preferred activities (e.g., visiting historical sites, experiencing Japanese cuisine, hot springs).

[1038] Step 2:

[1039] The device sends the entered travel requirements to the server in real time. Specifically, when the user presses the "Submit" button, the application converts the input data into JSON format and sends it to the server using an HTTP request. The input includes travel destinations, travel dates, budget, and preferred activities. The server receives this data and stores it in an understandable format.

[1040] Step 3:

[1041] The server uses an internal database and external APIs (e.g., Google Places API or Amadeus API) to collect information on attractions, accommodation, places to eat, and activities based on user input data. The server uses the user input data to generate an API query and sends a request to the external API. It retrieves relevant information from the database and consolidates this information. The input is the user's travel requirements, and the output is information on attractions, accommodation, places to eat, and activities collected from the API and database.

[1042] Step 4:

[1043] The server filters irrelevant data and inaccurate information from the collected data. Specifically, the server uses a specific algorithm to remove duplicate data, establishments that can no longer be booked, restaurants that are no longer open, etc. The input is data collected from the API and database, and the output is filtered, highly accurate data.

[1044] Step 5:

[1045] The server performs analysis based on the filtered data and generates a travel plan that matches the user's preferences. This analysis uses a generative AI model such as GPT-4 or BERT. The server provides a prompt to the generative AI model, which then generates an optimal travel plan based on that. The input is the filtered data and the prompt, and the output is the generated travel plan.

[1046] Step 6:

[1047] The server calculates the cost of each element of the generated travel plan and adjusts it so that the overall plan fits within the user's budget. Specifically, the server calculates the cost of each tourist attraction, accommodation, place to eat, and activity, and fine-tunes the plan so that the total amount fits within the budget. The input is the cost information of each element, and the output is the adjusted travel plan.

[1048] Step 7:

[1049] The server sends the final adjusted itinerary to the device for the user to review and customize. Specifically, the server converts the generated plan into JSON format and sends it to the device using an HTTP response. The device displays the received plan on a user interface, allowing the user to review it and make fine adjustments if necessary. The input is the adjusted itinerary, and the output is the itinerary presented to the user.

[1050] In this way, each step works together to provide the user with the most suitable travel plan.

[1051] 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.

[1052] The present invention combines a system in which a user inputs their travel destination, itinerary, budget, and preferred activities with an emotion engine, and is a technology for providing optimal travel plans that take the user's emotions into consideration more than conventional travel planning systems. A specific embodiment of this system and its processing flow are described below.

[1053] System Overview

[1054] This system consists of a terminal where users input information, a server that receives and processes the input information and emotion data, a database that stores and manages the data, and an emotion engine that recognizes the user's emotions.

[1055] User input

[1056] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[1057] Emotion Engine

[1058] The device's built-in emotion engine collects emotion data from the user's facial expressions and voice while they are typing. For example, if the user is smiling while typing, that emotion data is collected. It also uses voice recognition technology to recognize emotions from the tone of the user's voice.

[1059] Data transmission by the terminal

[1060] The terminal receives the travel information and collected emotion data entered by the user, converts them into a set format, and transmits them to the server in real time.

[1061] Data collection by the server

[1062] Based on the received user requirements and sentiment data, the server executes queries to collect relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[1063] Data Filtering and Noise Removal

[1064] The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[1065] Data analysis

[1066] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate optimal travel plans that match the user's preferences and emotions, for example, predicting crowds at tourist spots and optimizing the order in which they are visited.

[1067] Cost Calculation

[1068] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[1069] Reflecting emotional data

[1070] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and spots that match the user's emotions. For example, if the user feels like relaxing, hot springs and relaxation facilities will be recommended.

[1071] Presenting your travel plan

[1072] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[1073] Specific examples

[1074] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and smiles while inputting the information and says, "I'd like a place that's relaxing," the system will operate as follows:

[1075] Collected information and emotional data

[1076] The server suggests Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist spots, collects Kyoto's long-established inns as accommodations, and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen, reflecting the user's desire to relax.

[1077] Filtering and Analysis

[1078] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[1079] Plan Generation and Cost Calculation

[1080] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[1081] final offer

[1082] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[1083] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan travel efficiently, accurately, and in line with their own preferences.

[1084] The processing flow will be explained below.

[1085] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities. For example, they might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[1086] Step 2: The device's built-in emotion engine analyzes the user's facial expressions and voice in real time as they type, collecting emotional data. For example, if the user smiles while typing, the emotion data is recorded as "relaxed."

[1087] Step 3: The device converts the input travel information and collected emotion data into a predefined format and transmits it to the server in real time. The transmitted data includes travel destination, itinerary, budget, activity preferences, and emotion data.

[1088] Step 4: The server executes queries to collect data on tourist attractions, accommodations, places to eat, and activities from the database and external APIs based on the received travel information and sentiment data. For example, it retrieves information on tourist attractions and accommodations in Kyoto.

[1089] Step 5: The server filters the collected data to remove irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[1090] Step 6: The server applies algorithms to generate an optimal itinerary based on the filtered data, matching the user's preferences and requirements. Specifically, it predicts crowding at tourist spots and optimizes the order in which they are visited.

[1091] Step 7: The server analyzes the emotion data obtained from the emotion engine and identifies recommended activities and spots that match the user's emotions. For example, if the user expresses an emotion of "wanting to relax," the server will recommend hot springs and relaxation facilities.

[1092] Step 8: The server calculates the cost of each element of the generated travel plan (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[1093] Step 9: The server sends the final itinerary to the device, including details of the planned destinations, itinerary, budgeted costs, and recommended activities that take into account the sentiment data.

[1094] Step 10: The terminal displays the travel plan received from the server to the user, who can review the travel plan and further customize it if necessary (e.g., select additional tourist attractions or change the budget).

[1095] Step 11: The user finalizes the travel plan and completes the booking procedure if necessary. The final plan is sent to the server and all data is saved as the finalized plan.

[1096] Example 2

[1097] 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."

[1098] Conventional travel planning systems only considered the user's basic requirements, making it difficult to provide optimal travel plans that reflected the user's emotions and detailed preferences. Furthermore, data collection, filtering, and analysis often contained inaccurate or irrelevant information, making it difficult to generate travel plans that satisfied users. Furthermore, the ability to adjust travel plans to fit within a budget was often insufficient, requiring users to put in a great deal of effort to create a travel plan that fit their budget.

[1099] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1100] In this invention, the server includes: means for collecting information on tourist destinations, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotions; filtering means for removing irrelevant or inaccurate data from the collected information to increase data accuracy; analysis means for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element to ensure that the overall travel plan stays within budget; and means for transmitting the generated travel plan to a user interface so that the user can review and customize it. This makes it possible to provide an optimal travel plan within budget, taking into account the user's emotions and detailed preferences and eliminating irrelevant data.

[1101] A "user" is an individual or organization that inputs travel destinations, travel itineraries, budget, and preferred activities.

[1102] A "user interface" is a means by which a user inputs information and transmits that information and emotion data to a server.

[1103] The "server" is a central processing unit that collects, analyzes, and filters information based on the user's requirements and feelings, generates an optimal travel plan, and transmits it to the terminal.

[1104] "Sources" are data suppliers that provide information on tourist destinations, accommodation, places to eat, activities, etc. through databases and external data acquisition means.

[1105] "Filtering measures" are processes used to remove irrelevant or inaccurate data from collected information and improve the accuracy of the data.

[1106] The "analysis means" is a process for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions.

[1107] "Cost calculation means" is a process for calculating the cost of each element and adjusting the overall travel plan to fit within the user's budget.

[1108] A "travel plan" is a proposal that integrates schedules and costs including sightseeing destinations, accommodations, places to eat, activities, etc. that meets the user's requirements and sentiments.

[1109] The present invention is a system that allows a user to input travel destinations, travel dates, budgets, and preferred activities, and provides an optimal travel plan based on the inputs, taking into consideration the user's feelings. Specific embodiments of the present invention are described below.

[1110] User data entry

[1111] A user uses a device to access a travel website or mobile application, and after logging in, enters the necessary information. The information entered includes travel destination, travel dates, budget, and preferred activities. For example, a user might enter the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This information is then recorded by the device.

[1112] Emotion recognition by emotion engine

[1113] The emotion engine installed on the device analyzes the user's facial expressions and voice. This is done through a camera and microphone, and emotional data is collected from the facial expressions and tone of voice shown when the user types. For example, if a user smiles and types "I like a place where I can relax," that emotion is collected as data.

[1114] Sending data

[1115] The device converts the travel information and collected emotion data entered by the user into a predetermined format and transmits it to the server in real time in a unified format such as JSON.

[1116] Data collection and analysis by the server

[1117] The server sends queries to databases and external APIs based on the received information to collect information on tourist destinations, accommodations, places to eat, and activities. For example, it obtains information on Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist attractions, long-established Kyoto inns as accommodations, Michelin-starred Japanese restaurants as places to eat, and Arashiyama Onsen as activities. The server then filters out unnecessary data and incorrect information from the collected information to improve its accuracy.

[1118] Filtering and Data Analysis

[1119] The server analyzes the filtered information and generates an optimal itinerary that matches the user's preferences and emotions. It uses a new algorithm to predict crowding at tourist spots and optimize the order in which the users visit. For example, the server can plan a trip to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon.

[1120] Cost Calculation

[1121] The server calculates the cost of each element and adjusts it so that the total fits within the user's budget. Specifically, it adds up the cost of accommodation, transportation, meals, admission fees, etc., so that the total comes in at 100,000 yen or less.

[1122] Reflecting emotional data

[1123] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and tourist spots based on the user's emotions. For example, hot springs and relaxation facilities can be recommended to users who prioritize relaxation.

[1124] Presenting your travel plan

[1125] The generated travel plan is sent to the terminal, where the user can review it. The user can review the presented plan and further customize it. Re-planning is performed according to the user's request through re-transmission from the terminal to the server.

[1126] Examples of specific examples and prompts

[1127] For example, if a user enters "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and says with a smile, "I'd like a place to relax," the system will act as follows:

[1128] Collected information and emotional data

[1129] User request: "Kyoto" "November 1st to November 5th, 2023" "100,000 yen" "Visit historical sites, experience Japanese cuisine, and relax in hot springs"

[1130] User Sentiment: "Relaxed"

[1131] Server Processing

[1132] Collect information on tourist spots such as Kinkakuji Temple, Kiyomizudera Temple, and Fushimi Inari Taisha Shrine

[1133] Collect information on Kyoto's long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen

[1134] Calculate the cost and adjust the total amount to within 100,000 yen

[1135] Recommending hot springs and relaxation facilities based on user emotional data

[1136] Prompt Sentence Examples

[1137] Please enter your "travel destination," "travel dates," "budget," and "preferred activities."

[1138] Example: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[1139] Example of emotional input: "I like a place where I can relax."

[1140] This allows users to get an efficient and personalized travel plan that reflects their emotions and detailed requests.

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1: User Data Entry

[1143] A user logs into a travel website or mobile app using a device and enters their travel destination, travel dates, budget, and preferred activities. The entered information is stored in the device's database. For example, a user might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This input data is used for subsequent processing.

[1144] Step 2: Emotion recognition by the emotion engine

[1145] While the user is entering data, the device's built-in emotion engine uses the camera and microphone to collect the user's facial expressions and tone of voice. The data is analyzed in real time and stored in a database as the user's emotion information. For example, if a user smiles and says, "I like places where I can relax," the emotion data is saved as a tag called "relaxation."

[1146] Step 3: Sending data

[1147] The device combines the user input data and collected emotion data into a single packet and sends it to the server in a specified format (e.g., JSON format). The server receives this packet and parses it to extract each data element. For example, it may be sent in a format such as "Travel destination: Kyoto," "Date: November 1st to November 5th, 2023," "Budget: 100,000 yen," "Favorite activities: visiting historical sites, experiencing Japanese cuisine, relaxing hot springs," and "Emotion: Relaxation."

[1148] Step 4: Data collection by the server

[1149] The server analyzes the received user requirements and sentiment data and collects information such as tourist destinations, accommodations, dining places, and activities based on the analysis. It uses internal database queries and external APIs to collect the corresponding data. For example, the server might collect tourist spot information such as "Kinkaku-ji Temple," "Kiyomizu-dera Temple," and "Fushimi Inari Taisha Shrine," accommodation information such as "long-established Kyoto inns," and dining information such as "Michelin-starred Japanese restaurants."

[1150] Step 5: Data filtering and noise removal

[1151] The server analyzes the collected data and filters out unnecessary or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activity on days when bad weather is predicted. The filtered data is then stored as a newly organized dataset.

[1152] Step 6: Data analysis and plan generation

[1153] The server then applies the filtered information to advanced analytical algorithms to generate an optimal travel plan that matches the user's preferences and emotions. For example, it predicts how crowded tourist spots will be and calculates the optimal order in which to visit them. Specifically, it creates a schedule that visits Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and stores the resulting plan in a database.

[1154] Step 7: Cost calculation

[1155] The server aggregates the costs of each element and adjusts them so that the total fits within the user's budget. For example, it calculates the cost of accommodation, transportation, meals, and admission fees, and optimizes the items to keep the total within 100,000 yen. The cost calculation results are included in the generated travel plan.

[1156] Step 8: Reflecting emotional data

[1157] Emotional data can also influence the optimization of travel plans. For example, if a user indicates a desire to relax, the server will prioritize recommendations for hot springs and relaxation facilities. This information is incorporated as part of the travel plan.

[1158] Step 9: Present your travel plans

[1159] The final itinerary is then reformatted and sent to the device. The user can review the presented itinerary and customize it as needed. The user's feedback is then sent back to the server, and the plan is updated as needed. For example, a user may enter a request such as "I would like to change the time to visit Kinkaku-ji Temple."

[1160] (Application example 2)

[1161] 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."

[1162] Conventional systems were unable to provide optimal travel plans that took into account the user's emotions, simply by inputting the user's travel destination, travel dates, budget, and preferred activities. As a result, it was difficult to provide travel plans that met the user's expectations, and the user experience could not be improved. Furthermore, in physical stores, it was not possible to provide a shopping experience that took into account the customer's emotions, which did not lead to improved customer satisfaction.

[1163] 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.

[1164] In this invention, the server includes: means for a user to input travel destinations, itineraries, budget, and preferred activities; terminal means for receiving the input information and the user's emotional data and transmitting the information to the server; server means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotional data; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element and ensuring that the overall travel plan fits within the budget; means for transmitting the generated travel plan to the terminal so that the user can confirm and customize it; and means including an emotion engine that recognizes the user's emotional data and suggesting products and services that match the user's emotions in real time based on the emotional data. This makes it possible to provide optimal travel plans that take the user's emotions into consideration and to present recommended products and services in real time in physical stores.

[1165] The "travel destination input means" is a means by which the user inputs the travel destination.

[1166] The "travel itinerary input means" is a means by which the user inputs the duration of the trip.

[1167] The "budget input means" is a means for the user to input the amount of money that can be spent on travel.

[1168] The "means for inputting favorite activities" is a means for inputting activities and experiences that the user is interested in.

[1169] "Terminal means" refers to an electronic device that allows a user to input information and transmit that information to a server.

[1170] "Emotion data" is information about emotions collected from the user's facial expressions, tone of voice, and the like.

[1171] "Server means" is a computer system that collects and processes information based on user requirements and emotion data.

[1172] "Filtering means" refers to means for removing irrelevant or inaccurate information from collected data.

[1173] The "analysis means" is a means for analyzing the filtered data and generating a travel plan that matches the user's preferences and feelings.

[1174] A "cost calculation tool" is a tool that calculates the cost of each element of a travel plan and ensures that the overall plan stays within budget.

[1175] An "emotion engine" is an engine that analyzes a user's emotions and provides optimal information and services based on those emotions.

[1176] The "real-time suggestion means" is a means for suggesting products and services in real time based on the user's emotional data.

[1177] The present invention is a system that provides optimal travel plans and shopping experiences in brick-and-mortar stores that take into account the user's emotions. The system collects user input information and emotional data in real time, and performs analysis based on this information to provide recommended information that matches the user's emotions. A specific embodiment of this system and its processing flow are described below.

[1178] System Overview

[1179] This system consists of the following elements:

[1180] 1. Terminal means:

[1181] The device where a user enters information such as travel destination, itinerary, budget, and preferred activities. Specifically, this applies to mobile devices such as smartphones and tablets.

[1182] In addition, it has a built-in emotion engine that senses the user's facial expressions and tone of voice in real time.

[1183] 2. Server means:

[1184] A server that collects and analyzes relevant data such as tourist attractions, accommodations, places to eat, and activities from internal and external sources based on user requirements and sentiment data.

[1185] By using cloud servers, high data processing capacity and scalability are achieved.

[1186] 3. Filtering methods:

[1187] The server removes irrelevant or inaccurate information from the data collected, improving the accuracy of the data.

[1188] It uses specific algorithms to remove noise and unwanted data.

[1189] 4. Analysis method:

[1190] Based on the filtered data, optimal travel plans and product suggestions that match the user's preferences and emotions are generated.

[1191] Based on the data obtained from the emotion engine, the services desired by the user are identified.

[1192] 5. Cost calculation methods:

[1193] Calculate the cost of each element and adjust it so that the total fits within the user's budget.

[1194] 6. Real-time suggestion methods:

[1195] Based on the user's emotional data, products and services are suggested in real time.

[1196] Processing flow

[1197] Device data collection:

[1198] The user uses the terminal to input travel destination, travel dates, budget, and preferred activities.

[1199] The emotion engine collects emotional data from the user's facial expressions and tone of voice, for example, by detecting a smile on the user's face or a happy tone in the user's voice when the user is entering their travel plans.

[1200] Data transmission and collection:

[1201] The terminal transmits the travel information and emotion data entered by the user to the server in real time.

[1202] The server collects relevant information, such as tourist attractions, accommodations, and dining places, through an internal database and external APIs.

[1203] Data filtering and analysis:

[1204] The server analyzes the collected data and filters out data that is inaccurate or does not meet the user's requirements.

[1205] Based on the filtered data, the system generates an optimal travel plan tailored to the user's preferences and emotions. For example, if a user is looking for "Kyoto," "visiting historical sites," and "relaxing hot springs," the system will provide information on Kinkakuji Temple and Arashiyama Hot Springs.

[1206] Cost calculation and planning:

[1207] It calculates the cost of each component and adjusts the overall travel plan to fit within the user's budget.

[1208] The generated itinerary is sent to the terminal for the user to review and customize.

[1209] Examples of specific examples and prompts

[1210] Examples:

[1211] While the user is wearing the smart glasses and walking around the store, products and services with a relaxing effect are displayed. Specifically, the text "Click here for relaxing aroma candles" appears on the smart glasses' display.

[1212] Example prompt sentence:

[1213] "Analyze the emotions of a customer when they visit the relaxation zone in a store, and generate a script to recommend products that have a relaxing effect based on that emotional data."

[1214] This will enable us to provide travel plans and shopping experiences that are tailored to the user's emotions in real time, thereby achieving higher customer satisfaction.

[1215] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1216] Step 1:

[1217] The user puts on the smart glasses and inputs their travel destination, itinerary, budget, and preferred activities using voice or gestures.

[1218] Input: User voice commands and gesture input

[1219] Output: Travel destination, travel dates, budget, and preferred activities

[1220] Step 2:

[1221] The device (smart glasses) uses a built-in camera and microphone to collect emotional data from the user's facial expressions and tone of voice.

[1222] Input: User's facial expression and voice tone

[1223] Output: User emotion data

[1224] Step 3:

[1225] The terminal transmits the collected travel information and emotion data to the server in a set format.

[1226] Input: Travel information and emotion data

[1227] Output: Formatted data sent to server

[1228] Step 4:

[1229] Based on the data received by the server, it uses an internal database and external APIs to collect relevant data such as tourist attractions, accommodation, places to eat, activities, etc.

[1230] Input: Travel information and emotion data

[1231] Output: Related data on attractions, accommodation, places to eat, activities, etc.

[1232] Step 5:

[1233] The server uses filtering means to remove irrelevant or inaccurate information from the collected data.

[1234] Input: Collected data

[1235] Output: Filtered data

[1236] Step 6:

[1237] The server analyzes the filtered data and the emotion data and generates an optimal travel plan that matches the user's preferences and emotions.

[1238] Input: Filtered data and sentiment data

[1239] Output: Generated itinerary

[1240] Step 7:

[1241] The server uses a cost calculation means to calculate the cost of each element of the travel plan and adjusts the overall travel plan so that it fits within the user's budget.

[1242] Input: Generated itinerary

[1243] Output: Costed itinerary

[1244] Step 8:

[1245] The server transmits the generated optimal travel plan to the terminal so that the user can check and customize it.

[1246] Input: Costed itinerary

[1247] Output: Trip plan sent to the device

[1248] Step 9:

[1249] The terminal presents the travel plan to the user and provides an interface that allows the user to review and customize the plan as needed.

[1250] Input: Travel plan sent from the server

[1251] Output: A travel plan that can be viewed by the user

[1252] Step 10:

[1253] Using the smart glasses' real-time suggestion means, optimal products and services are suggested in physical stores based on the user's emotional data.

[1254] Input: Real-time emotion data

[1255] Output: Product and service recommendations based on user sentiment

[1256] These are the specific processing steps of the system that realizes this application example. This makes it possible to provide optimal travel plans that take into account the user's emotions and to present recommended products and services in real time in physical stores.

[1257] 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.

[1258] 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.

[1259] 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.

[1260] [Fourth embodiment]

[1261] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1262] 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.

[1263] 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).

[1264] 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.

[1265] 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.

[1266] 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).

[1267] 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.

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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."

[1274] The present invention is a system that allows users to input their travel destinations, travel itineraries, budgets, and preferred activities, and is a technology for proposing optimal travel plans. Specific embodiments for implementing this system and the processing flow are described below.

[1275] System Overview

[1276] The system basically consists of a terminal where users input information, a server that receives and processes the input information, and a database that stores and manages the data.

[1277] User input

[1278] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[1279] Data transmission by the terminal

[1280] The terminal receives the information entered by the user and transmits it to the server in real time, where the server begins processing immediately.

[1281] Data collection by the server

[1282] The server queries the database based on the received user requirements, for example, gathering information on attractions, accommodations, places to eat, activities, etc. from internal databases and external APIs.

[1283] Data Filtering and Noise Removal

[1284] The server analyzes the collected data and filters out irrelevant or inaccurate information, improving the accuracy of useful information and eliminating unnecessary data, such as hotels that are already fully booked or restaurants that are closed.

[1285] Data analysis

[1286] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate an optimal itinerary that matches the user's preferences, for example, predicting crowds at tourist spots and optimizing the order in which they should be visited.

[1287] Cost Calculation

[1288] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[1289] Presenting your travel plan

[1290] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[1291] Specific examples

[1292] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[1293] Information collected

[1294] The server suggests tourist spots such as Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine, and collects information on long-established Kyoto inns as accommodations and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen.

[1295] Filtering and Analysis

[1296] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[1297] Plan Generation and Cost Calculation

[1298] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[1299] final offer

[1300] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[1301] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan their trips efficiently and accurately.

[1302] The processing flow will be explained below.

[1303] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities, such as "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[1304] Step 2: The terminal receives the information entered by the user, converts it into the specified format, and sends it to the server in real time.

[1305] Step 3: The server receives the user's input information and executes queries to gather relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[1306] Step 4: The server searches the database for data on attractions, accommodations, places to eat, and activities, and retrieves the relevant information. It also uses external APIs to gather real-time weather and event information.

[1307] Step 5: The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[1308] Step 6: The server applies algorithms to the filtered data to generate an optimal itinerary that matches the user's preferences and requirements, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[1309] Step 7: The server calculates the cost of each element of the generated itinerary (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[1310] Step 8: The server sends the final itinerary to the device, including details of the places to visit, the dates, and the budgeted costs.

[1311] Step 9: The terminal displays the travel plan received from the server to the user. The user can review the travel plan and customize it as needed (for example, add other tourist spots or change the budget).

[1312] Step 10: The user finalizes the travel plan and makes a reservation if necessary. This information is sent back to the server, and all data is saved as a finalized plan.

[1313] Example 1

[1314] 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."

[1315] Conventional travel planning systems have struggled to generate optimal travel plans based on users' individual requirements and preferences. Existing systems often provide only general tourist information and are unable to provide plans that reflect the user's specific needs. In addition, cost calculations are often insufficient, potentially resulting in plans that fall outside the user's budget, creating inconvenience for users. Furthermore, the accuracy and relevance of collected data can be low, resulting in the inclusion of inaccurate information, which can degrade the quality of travel plans.

[1316] 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.

[1317] In this invention, the server includes: means for collecting data on tourist attractions, accommodations, restaurants, activities, etc. from an internal database and external sources based on the user's requirements; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means including a generative AI model for analyzing the filtered data and generating a travel plan that matches the user's preferences; cost calculation means for calculating the cost of each element and ensuring the overall travel plan stays within budget; and means for transmitting the generated travel plan to a terminal so the user can review and customize it. This enables the generation of a precise travel plan based on the user's specific requirements and preferences. Furthermore, by planning within budget, user satisfaction can be increased.

[1318] "User" refers to a person or individual who inputs information such as travel destination, travel dates, budget, and preferred activities to create a travel plan.

[1319] "Terminal means" refers to a device or system that receives information entered by a user and transmits it to a server. Examples include smartphones and computers.

[1320] The term "server means" refers to a computer system that receives information sent from a user and performs a series of processes such as data collection, filtering, analysis, and plan generation.

[1321] "Tourist destinations" refer to places and attractions that tourists can visit in a travel destination, including historical sites and natural landscapes.

[1322] "Accommodation facilities" refer to facilities that provide a place for travelers to stay. Examples include hotels and inns.

[1323] "Food and beverage establishments" refers to establishments that provide meals during travel. Examples include restaurants and cafes.

[1324] "Activities" refers to interesting activities and experiences that you undertake while traveling, such as sightseeing tours and interactive programs.

[1325] "Database" means a system for systematically storing and managing collected information, including internal databases and data from external sources.

[1326] "Source" refers to external APIs and other information resources used in data collection.

[1327] "Generative AI model" refers to an artificial intelligence model used to automatically generate optimal travel plans based on user input.

[1328] "Filtering measures" refers to algorithms or processes used to remove irrelevant or inaccurate information from collected data.

[1329] "Analysis" refers to the processes and algorithms that utilize the filtered data to generate travel plans that match the user's preferences.

[1330] "Cost calculation means" refers to a process for calculating the cost of each element of a travel plan (e.g., accommodation, transportation, meals, admission fees, etc.) and ensuring that the overall plan stays within the user's budget.

[1331] The present invention is a system that provides an optimal travel plan by allowing a user to input travel destinations, travel dates, budget, and preferred activities. The system is configured as follows.

[1332] 1. User inputs information

[1333] Users enter their travel requirements through travel websites and mobile applications. This information includes travel destinations, travel dates, budget, and preferred activities. For example, a user might enter a prompt like this:

[1334] Travel destination: Kyoto

[1335] Travel dates: November 1st to November 5th, 2023

[1336] Budget: 100,000 yen

[1337] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[1338] 2. Sending data from the device to the server

[1339] The device receives the information entered by the user and transmits it to the server in real time using a network protocol such as an HTTP POST request.

[1340] 3. Data collection and filtering by the server

[1341] Based on the received user requirements, the server collects data using internal database queries and external APIs (e.g., Google Places API), including tourist destinations, accommodations, restaurants, activities, etc.

[1342] The collected data is then filtered through a specific algorithm to filter out irrelevant or inaccurate information, for example, removing accommodations that are already fully booked or restaurants that are closed.

[1343] 4. Data analysis and generative AI models

[1344] The server then uses a generative AI model to perform advanced data analysis on the filtered data. This model generates an optimal travel plan that matches the user's preferences, for example, by predicting crowds at tourist spots and optimizing the order in which they should be visited.

[1345] 5. Cost Calculation

[1346] The server calculates the cost of each element (accommodation, transportation, meals, admission fees, etc.) and adjusts the total to fit within the user's budget. For example, the server provides the optimal plan within a user-entered budget of 100,000 yen.

[1347] 6. Generating a travel plan and presenting it to the user

[1348] The server generates an optimal travel plan based on the analysis results and cost calculations, and the plan is sent back to the terminal for the user to review and customize.

[1349] Through these processes, the system can provide travel plans based on the user's specific requirements and preferences, and can also adjust the plans to fit within the user's budget, increasing user satisfaction.

[1350] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1351] Step 1:

[1352] User input of information

[1353] Input: Information about travel destination, travel dates, budget, and preferred activities that users enter through travel sites and mobile applications.

[1354] How it works: A user manually enters information into an application form, such as:

[1355] Travel destination: Kyoto

[1356] Travel dates: November 1st to November 5th, 2023

[1357] Budget: 100,000 yen

[1358] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[1359] Output: The entered information is stored within the application and passed to the next processing step.

[1360] Step 2:

[1361] Data transmission by the terminal

[1362] Input: Information entered by the user in step 1.

[1363] How it works: The device sends the information entered by the user to the server in real time using an HTTP POST request, and the server has an endpoint configured for this purpose.

[1364] Output: The server receives the user's input.

[1365] Step 3:

[1366] Data collection by the server

[1367] Input: User requirements information (destination, travel dates, budget, preferred activities).

[1368] How it works: The server queries an internal database and also sends requests to external sources (e.g., Google Places API) to gather the necessary data, including information about tourist attractions, accommodation, restaurants, and activities.

[1369] Output: The collected information on tourist attractions, accommodations, restaurants, and activities is stored on the server.

[1370] Step 4:

[1371] Server-based data filtering and noise reduction

[1372] Input: Data collected in Step 3.

[1373] How it works: The server applies filtering algorithms to remove irrelevant or inaccurate data, such as fully booked accommodations or closed restaurants.

[1374] Output: A filtered, reliable dataset is kept on the server.

[1375] Step 5:

[1376] Data analysis by server

[1377] Input: The filtered dataset.

[1378] How it works: The server uses the generative AI model to generate an optimal travel plan that matches the user's preferences, including predicting crowds at tourist spots and optimizing the order in which they should be visited.

[1379] Output: A travel plan that best suits the user's requirements is generated and saved.

[1380] Step 6:

[1381] Server-based cost calculation

[1382] Input: Each element of the optimized itinerary (accommodation, transportation, places to eat, and each activity).

[1383] How it works: The server calculates the cost of each element and adjusts it to fit the overall plan within budget. For example, it adds up accommodation, transportation, meals, admission fees, etc. and makes adjustments as needed.

[1384] Output: A completed itinerary within the adjusted costs.

[1385] Step 7:

[1386] Server generates and presents travel plans

[1387] Input: Cost-adjusted optimal travel plan.

[1388] Operation: The server sends the generated travel plan to the terminal again, returning the data as an HTTP response.

[1389] Output: The terminal receives the itinerary and presents it to the user.

[1390] Step 8:

[1391] User confirmation and modification of plans

[1392] Input: Travel plan provided by the device.

[1393] How it works: The user reviews the proposed itinerary and submits any necessary changes or additions through the application, for example, changing the order of visits or requesting additional attractions.

[1394] Output: The final customized itinerary is presented to the user.

[1395] (Application example 1)

[1396] 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."

[1397] Conventional travel planning systems have limitations in collecting and filtering information based on user input data, making it difficult to generate optimal plans in real time or provide users with intuitive and easy-to-understand information.In addition, advanced data analysis and AI technology are essential to provide travel plans that suit the diverse preferences of users, and no system has been able to meet these requirements.

[1398] 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.

[1399] In this invention, the server includes a means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements, a filtering means for removing irrelevant or inaccurate data from the collected data to improve data accuracy, an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences, and a means for generating and presenting an optimal travel plan using an external AI model in real time based on the data entered by the user. This makes it possible to respond to the diverse requirements of users and provide optimal and intuitive travel plans in real time.

[1400] "User" means a person or customer who inputs their preferences and requirements to create a travel plan.

[1401] "Destination" refers to a particular place or city that a User plans to visit.

[1402] "Travel itinerary" is information indicating the period from the start date to the end date of a trip.

[1403] "Budget" is the amount of money the user plans to spend on the trip.

[1404] "Preferred Activities" refers to the specific activities or experiences that a User is interested in while traveling.

[1405] "Terminal means" refers to a device or application that allows a user to input information and send it to a server.

[1406] "Server Means" means a computer system that receives user input information and collects and processes the necessary data.

[1407] A "database" is a structured data storage system for storing and managing collected information.

[1408] An "external API" is an interface for obtaining information from external data sources.

[1409] "Filtering measures" are techniques used to remove irrelevant or inaccurate information from collected data.

[1410] "Analysis means" refers to algorithms or software that generate travel plans based on the filtered data that match the user's preferences.

[1411] "Cost calculation means" is a technique for calculating the cost of each element and ensuring that the overall travel plan fits within the user's budget.

[1412] A "generative AI model" is an artificial intelligence technology used to generate optimal travel plans in real time based on user input information.

[1413] A "prompt sentence" is a guide sentence that uses a generative AI model to provide users with easy-to-understand information.

[1414] "Internal and External Sources" means the internal and external data sources used by the System to collect data.

[1415] This invention is a system that proposes optimal travel plans based on travel destinations, travel itineraries, budgets, and preferred activities input by a user. A specific method for realizing this system is described below.

[1416] System Overview

[1417] The system consists of the following main components:

[1418] Terminal means

[1419] Users input their travel requirements (destination, itinerary, budget, activities) using a smartphone application. The smartphone application was developed using React Native to provide a user-friendly interface.

[1420] Server Means

[1421] The entered data is sent to the server in real time. The server is built using Flask and receives the user's input data. The server collects data such as tourist attractions, accommodations, places to eat, and activities through internal database queries and external API calls (e.g., Google Places API, Amadeus API). The collected data is then stored in an internal database (e.g., PostgreSQL).

[1422] Filtering Methods

[1423] The server uses a specific algorithm to filter irrelevant or inaccurate information from the collected data, for example, by removing hotels that are already fully booked or restaurants that are closed.

[1424] Analysis means

[1425] The filtered data undergoes advanced analysis based on the user's requirements, using generative AI models such as GPT-4 and BERT to generate an optimal travel plan, which is then presented to the user in an easy-to-understand format using generated prompts.

[1426] Cost Calculation Method

[1427] The server calculates the cost of each element (e.g. accommodation, transportation, meals, entrance fees, etc.) and adjusts the overall itinerary to fit within the budget. This is done using the Python pandas library.

[1428] Presenting your travel plan

[1429] The generated itinerary is sent to the smartphone application user interface for the user to review and customize.

[1430] Specific examples

[1431] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," the system will operate as follows:

[1432] 1. User input data:

[1433] Travel destination: Kyoto

[1434] Travel dates: November 1st to November 5th, 2023

[1435] Budget: 100,000 yen

[1436] Favorite activities: Visiting historical sites, experiencing Japanese cuisine, relaxing in hot springs

[1437] 2. Data collection and filtering:

[1438] The server uses the Google Places API and Amadeus API to collect data on places such as Kinkaku-ji Temple, Kiyomizu-dera Temple, Fushimi Inari Taisha Shrine, long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen.

[1439] Eliminate irrelevant, duplicate, and inaccurate data.

[1440] 3. Data analysis and plan generation:

[1441] GPT-4 is used to generate prompts and suggest specific travel plans.

[1442] For example, a detailed itinerary suggestion such as "Visit Kinkakuji Temple on November 1st and check into a long-established inn" is presented.

[1443] Prompt Sentence Examples

[1444] "I'm planning a trip to Kyoto from November 1st to November 5th, 2023. My budget is 100,000 yen. My favorite activities are visiting historical sites, experiencing Japanese cuisine, and relaxing in hot springs. Please suggest a recommended itinerary."

[1445] In this way, specific processing is carried out to provide the user with the optimal travel plan. By linking the entire system, it becomes possible to provide high-quality travel plans that meet the user's requests in real time.

[1446] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1447] Step 1:

[1448] A user uses a smartphone application to input their travel destination, travel dates, budget, and preferred activities. Specifically, the user fills out an input form in the application, and the information is saved in the application. The input information includes the travel destination (e.g., Kyoto), travel dates (e.g., November 1 to November 5, 2023), budget (e.g., 100,000 yen), and preferred activities (e.g., visiting historical sites, experiencing Japanese cuisine, hot springs).

[1449] Step 2:

[1450] The device sends the entered travel requirements to the server in real time. Specifically, when the user presses the "Submit" button, the application converts the input data into JSON format and sends it to the server using an HTTP request. The input includes travel destinations, travel dates, budget, and preferred activities. The server receives this data and stores it in an understandable format.

[1451] Step 3:

[1452] The server uses an internal database and external APIs (e.g., Google Places API or Amadeus API) to collect information on attractions, accommodation, places to eat, and activities based on user input data. The server uses the user input data to generate an API query and sends a request to the external API. It retrieves relevant information from the database and consolidates this information. The input is the user's travel requirements, and the output is information on attractions, accommodation, places to eat, and activities collected from the API and database.

[1453] Step 4:

[1454] The server filters irrelevant data and inaccurate information from the collected data. Specifically, the server uses a specific algorithm to remove duplicate data, establishments that can no longer be booked, restaurants that are no longer open, etc. The input is data collected from the API and database, and the output is filtered, highly accurate data.

[1455] Step 5:

[1456] The server performs analysis based on the filtered data and generates a travel plan that matches the user's preferences. This analysis uses a generative AI model such as GPT-4 or BERT. The server provides a prompt to the generative AI model, which then generates an optimal travel plan based on that. The input is the filtered data and the prompt, and the output is the generated travel plan.

[1457] Step 6:

[1458] The server calculates the cost of each element of the generated travel plan and adjusts it so that the overall plan fits within the user's budget. Specifically, the server calculates the cost of each tourist attraction, accommodation, place to eat, and activity, and fine-tunes the plan so that the total amount fits within the budget. The input is the cost information of each element, and the output is the adjusted travel plan.

[1459] Step 7:

[1460] The server sends the final adjusted itinerary to the device for the user to review and customize. Specifically, the server converts the generated plan into JSON format and sends it to the device using an HTTP response. The device displays the received plan on a user interface, allowing the user to review it and make fine adjustments if necessary. The input is the adjusted itinerary, and the output is the itinerary presented to the user.

[1461] In this way, each step works together to provide the user with the most suitable travel plan.

[1462] 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.

[1463] The present invention combines a system in which a user inputs their travel destination, itinerary, budget, and preferred activities with an emotion engine, and is a technology for providing optimal travel plans that take the user's emotions into consideration more than conventional travel planning systems. A specific embodiment of this system and its processing flow are described below.

[1464] System Overview

[1465] This system consists of a terminal where users input information, a server that receives and processes the input information and emotion data, a database that stores and manages the data, and an emotion engine that recognizes the user's emotions.

[1466] User input

[1467] A user enters their travel requirements through a travel website or mobile application. The information they specify includes the travel destination, travel dates, budget, and preferred activities. For example, a user enters the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[1468] Emotion Engine

[1469] The device's built-in emotion engine collects emotion data from the user's facial expressions and voice while they are typing. For example, if the user is smiling while typing, that emotion data is collected. It also uses voice recognition technology to recognize emotions from the tone of the user's voice.

[1470] Data transmission by the terminal

[1471] The terminal receives the travel information and collected emotion data entered by the user, converts them into a set format, and transmits them to the server in real time.

[1472] Data collection by the server

[1473] Based on the received user requirements and sentiment data, the server executes queries to collect relevant data such as tourist attractions, accommodations, places to eat, activities, etc. from databases and external APIs.

[1474] Data Filtering and Noise Removal

[1475] The server analyzes the collected data and filters out irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[1476] Data analysis

[1477] Based on the refined data, the server performs advanced analysis and uses new algorithms to generate optimal travel plans that match the user's preferences and emotions, for example, predicting crowds at tourist spots and optimizing the order in which they are visited.

[1478] Cost Calculation

[1479] The server calculates the cost of each element and ensures that the total fits within the user's budget, for example, adding up the cost of accommodation, transportation, meals, admission fees, etc.

[1480] Reflecting emotional data

[1481] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and spots that match the user's emotions. For example, if the user feels like relaxing, hot springs and relaxation facilities will be recommended.

[1482] Presenting your travel plan

[1483] The generated travel plan is sent to the terminal for the user to review, and the user can review it and enter any changes or additions they require.

[1484] Specific examples

[1485] For example, if a user inputs the requirements "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and smiles while inputting the information and says, "I'd like a place that's relaxing," the system will operate as follows:

[1486] Collected information and emotional data

[1487] The server suggests Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist spots, collects Kyoto's long-established inns as accommodations, and Michelin-starred Japanese restaurants as dining options. It also collects information on Arashiyama Onsen, reflecting the user's desire to relax.

[1488] Filtering and Analysis

[1489] From the collected data, the system removes accommodations that are already fully booked and restaurants that are closed, and optimizes visit times and predicts congestion.

[1490] Plan Generation and Cost Calculation

[1491] For example, you could create a schedule to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and adjust the total cost for the entire trip to be less than 100,000 yen.

[1492] final offer

[1493] The generated travel plan is presented to the user, who can review the plan and further customize it if necessary.

[1494] The above is a concrete example of a travel planning system according to the present invention, which allows users to plan travel efficiently, accurately, and in line with their own preferences.

[1495] The processing flow will be explained below.

[1496] Step 1: A user visits a travel website or mobile application and enters their travel destination, travel dates, budget, and preferred activities. For example, they might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visit historical sites, experience Japanese cuisine, and relax in a hot spring."

[1497] Step 2: The device's built-in emotion engine analyzes the user's facial expressions and voice in real time as they type, collecting emotional data. For example, if the user smiles while typing, the emotion data is recorded as "relaxed."

[1498] Step 3: The device converts the input travel information and collected emotion data into a predefined format and transmits it to the server in real time. The transmitted data includes travel destination, itinerary, budget, activity preferences, and emotion data.

[1499] Step 4: The server executes queries to collect data on tourist attractions, accommodations, places to eat, and activities from the database and external APIs based on the received travel information and sentiment data. For example, it retrieves information on tourist attractions and accommodations in Kyoto.

[1500] Step 5: The server filters the collected data to remove irrelevant or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activities scheduled for dates when bad weather is predicted.

[1501] Step 6: The server applies algorithms to generate an optimal itinerary based on the filtered data, matching the user's preferences and requirements. Specifically, it predicts crowding at tourist spots and optimizes the order in which they are visited.

[1502] Step 7: The server analyzes the emotion data obtained from the emotion engine and identifies recommended activities and spots that match the user's emotions. For example, if the user expresses an emotion of "wanting to relax," the server will recommend hot springs and relaxation facilities.

[1503] Step 8: The server calculates the cost of each element of the generated travel plan (accommodation, transportation, meals, admission fees, etc.) and adjusts it so that the overall plan fits within the user's budget.

[1504] Step 9: The server sends the final itinerary to the device, including details of the planned destinations, itinerary, budgeted costs, and recommended activities that take into account the sentiment data.

[1505] Step 10: The terminal displays the travel plan received from the server to the user, who can review the travel plan and further customize it if necessary (e.g., select additional tourist attractions or change the budget).

[1506] Step 11: The user finalizes the travel plan and completes the booking procedure if necessary. The final plan is sent to the server and all data is saved as the finalized plan.

[1507] Example 2

[1508] 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."

[1509] Conventional travel planning systems only considered the user's basic requirements, making it difficult to provide optimal travel plans that reflected the user's emotions and detailed preferences. Furthermore, data collection, filtering, and analysis often contained inaccurate or irrelevant information, making it difficult to generate travel plans that satisfied users. Furthermore, the ability to adjust travel plans to fit within a budget was often insufficient, requiring users to put in a great deal of effort to create a travel plan that fit their budget.

[1510] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1511] In this invention, the server includes: means for collecting information on tourist destinations, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotions; filtering means for removing irrelevant or inaccurate data from the collected information to increase data accuracy; analysis means for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element to ensure that the overall travel plan stays within budget; and means for transmitting the generated travel plan to a user interface so that the user can review and customize it. This makes it possible to provide an optimal travel plan within budget, taking into account the user's emotions and detailed preferences and eliminating irrelevant data.

[1512] A "user" is an individual or organization that inputs travel destinations, travel itineraries, budget, and preferred activities.

[1513] A "user interface" is a means by which a user inputs information and transmits that information and emotion data to a server.

[1514] The "server" is a central processing unit that collects, analyzes, and filters information based on the user's requirements and feelings, generates an optimal travel plan, and transmits it to the terminal.

[1515] "Sources" are data suppliers that provide information on tourist destinations, accommodation, places to eat, activities, etc. through databases and external data acquisition means.

[1516] "Filtering measures" are processes used to remove irrelevant or inaccurate data from collected information and improve the accuracy of the data.

[1517] The "analysis means" is a process for analyzing the filtered information and emotion data to generate a travel plan that matches the user's preferences and emotions.

[1518] "Cost calculation means" is a process for calculating the cost of each element and adjusting the overall travel plan to fit within the user's budget.

[1519] A "travel plan" is a proposal that integrates schedules and costs including sightseeing destinations, accommodations, places to eat, activities, etc. that meets the user's requirements and sentiments.

[1520] The present invention is a system that allows a user to input travel destinations, travel dates, budgets, and preferred activities, and provides an optimal travel plan based on the inputs, taking into consideration the user's feelings. Specific embodiments of the present invention are described below.

[1521] User data entry

[1522] A user uses a device to access a travel website or mobile application, and after logging in, enters the necessary information. The information entered includes travel destination, travel dates, budget, and preferred activities. For example, a user might enter the following requirements: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This information is then recorded by the device.

[1523] Emotion recognition by emotion engine

[1524] The emotion engine installed on the device analyzes the user's facial expressions and voice. This is done through a camera and microphone, and emotional data is collected from the facial expressions and tone of voice shown when the user types. For example, if a user smiles and types "I like a place where I can relax," that emotion is collected as data.

[1525] Sending data

[1526] The device converts the travel information and collected emotion data entered by the user into a predetermined format and transmits it to the server in real time in a unified format such as JSON.

[1527] Data collection and analysis by the server

[1528] The server sends queries to databases and external APIs based on the received information to collect information on tourist destinations, accommodations, places to eat, and activities. For example, it obtains information on Kinkaku-ji Temple, Kiyomizu-dera Temple, and Fushimi Inari Taisha Shrine as tourist attractions, long-established Kyoto inns as accommodations, Michelin-starred Japanese restaurants as places to eat, and Arashiyama Onsen as activities. The server then filters out unnecessary data and incorrect information from the collected information to improve its accuracy.

[1529] Filtering and Data Analysis

[1530] The server analyzes the filtered information and generates an optimal itinerary that matches the user's preferences and emotions. It uses a new algorithm to predict crowding at tourist spots and optimize the order in which the users visit. For example, the server can plan a trip to visit Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon.

[1531] Cost Calculation

[1532] The server calculates the cost of each element and adjusts it so that the total fits within the user's budget. Specifically, it adds up the cost of accommodation, transportation, meals, admission fees, etc., so that the total comes in at 100,000 yen or less.

[1533] Reflecting emotional data

[1534] The emotional data obtained from the emotion engine is analyzed to identify recommended activities and tourist spots based on the user's emotions. For example, hot springs and relaxation facilities can be recommended to users who prioritize relaxation.

[1535] Presenting your travel plan

[1536] The generated travel plan is sent to the terminal, where the user can review it. The user can review the presented plan and further customize it. Re-planning is performed according to the user's request through re-transmission from the terminal to the server.

[1537] Examples of specific examples and prompts

[1538] For example, if a user enters "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs," and says with a smile, "I'd like a place to relax," the system will act as follows:

[1539] Collected information and emotional data

[1540] User request: "Kyoto" "November 1st to November 5th, 2023" "100,000 yen" "Visit historical sites, experience Japanese cuisine, and relax in hot springs"

[1541] User Sentiment: "Relaxed"

[1542] Server Processing

[1543] Collect information on tourist spots such as Kinkakuji Temple, Kiyomizudera Temple, and Fushimi Inari Taisha Shrine

[1544] Collect information on Kyoto's long-established inns, Michelin-starred Japanese restaurants, and Arashiyama Onsen

[1545] Calculate the cost and adjust the total amount to within 100,000 yen

[1546] Recommending hot springs and relaxation facilities based on user emotional data

[1547] Prompt Sentence Examples

[1548] Please enter your "travel destination," "travel dates," "budget," and "preferred activities."

[1549] Example: "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs."

[1550] Example of emotional input: "I like a place where I can relax."

[1551] This allows users to get an efficient and personalized travel plan that reflects their emotions and detailed requests.

[1552] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1553] Step 1: User Data Entry

[1554] A user logs into a travel website or mobile app using a device and enters their travel destination, travel dates, budget, and preferred activities. The entered information is stored in the device's database. For example, a user might enter "Kyoto," "November 1st to November 5th, 2023," "100,000 yen," "visiting historical sites, experiencing Japanese cuisine, and relaxing hot springs." This input data is used for subsequent processing.

[1555] Step 2: Emotion recognition by the emotion engine

[1556] While the user is entering data, the device's built-in emotion engine uses the camera and microphone to collect the user's facial expressions and tone of voice. The data is analyzed in real time and stored in a database as the user's emotion information. For example, if a user smiles and says, "I like places where I can relax," the emotion data is saved as a tag called "relaxation."

[1557] Step 3: Sending data

[1558] The device combines the user input data and collected emotion data into a single packet and sends it to the server in a specified format (e.g., JSON format). The server receives this packet and parses it to extract each data element. For example, it may be sent in a format such as "Travel destination: Kyoto," "Date: November 1st to November 5th, 2023," "Budget: 100,000 yen," "Favorite activities: visiting historical sites, experiencing Japanese cuisine, relaxing hot springs," and "Emotion: Relaxation."

[1559] Step 4: Data collection by the server

[1560] The server analyzes the received user requirements and sentiment data and collects information such as tourist destinations, accommodations, dining places, and activities based on the analysis. It uses internal database queries and external APIs to collect the corresponding data. For example, the server might collect tourist spot information such as "Kinkaku-ji Temple," "Kiyomizu-dera Temple," and "Fushimi Inari Taisha Shrine," accommodation information such as "long-established Kyoto inns," and dining information such as "Michelin-starred Japanese restaurants."

[1561] Step 5: Data filtering and noise removal

[1562] The server analyzes the collected data and filters out unnecessary or inaccurate information, such as hotels that are already fully booked, restaurants that are closed, or activity on days when bad weather is predicted. The filtered data is then stored as a newly organized dataset.

[1563] Step 6: Data analysis and plan generation

[1564] The server then applies the filtered information to advanced analytical algorithms to generate an optimal travel plan that matches the user's preferences and emotions. For example, it predicts how crowded tourist spots will be and calculates the optimal order in which to visit them. Specifically, it creates a schedule that visits Kinkaku-ji Temple in the morning and Kiyomizu-dera Temple in the afternoon, and stores the resulting plan in a database.

[1565] Step 7: Cost calculation

[1566] The server aggregates the costs of each element and adjusts them so that the total fits within the user's budget. For example, it calculates the cost of accommodation, transportation, meals, and admission fees, and optimizes the items to keep the total within 100,000 yen. The cost calculation results are included in the generated travel plan.

[1567] Step 8: Reflecting emotional data

[1568] Emotional data can also influence the optimization of travel plans. For example, if a user indicates a desire to relax, the server will prioritize recommendations for hot springs and relaxation facilities. This information is incorporated as part of the travel plan.

[1569] Step 9: Present your travel plans

[1570] The final itinerary is then reformatted and sent to the device. The user can review the presented itinerary and customize it as needed. The user's feedback is then sent back to the server, and the plan is updated as needed. For example, a user may enter a request such as "I would like to change the time to visit Kinkaku-ji Temple."

[1571] (Application example 2)

[1572] 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."

[1573] Conventional systems were unable to provide optimal travel plans that took into account the user's emotions, simply by inputting the user's travel destination, travel dates, budget, and preferred activities. As a result, it was difficult to provide travel plans that met the user's expectations, and the user experience could not be improved. Furthermore, in physical stores, it was not possible to provide a shopping experience that took into account the customer's emotions, which did not lead to improved customer satisfaction.

[1574] 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.

[1575] In this invention, the server includes: means for a user to input travel destinations, itineraries, budget, and preferred activities; terminal means for receiving the input information and the user's emotional data and transmitting the information to the server; server means for collecting data on tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and emotional data; filtering means for removing irrelevant or inaccurate information from the collected data to improve data accuracy; analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences and emotions; cost calculation means for calculating the cost of each element and ensuring that the overall travel plan fits within the budget; means for transmitting the generated travel plan to the terminal so that the user can confirm and customize it; and means including an emotion engine that recognizes the user's emotional data and suggesting products and services that match the user's emotions in real time based on the emotional data. This makes it possible to provide optimal travel plans that take the user's emotions into consideration and to present recommended products and services in real time in physical stores.

[1576] The "travel destination input means" is a means by which the user inputs the travel destination.

[1577] The "travel itinerary input means" is a means by which the user inputs the duration of the trip.

[1578] The "budget input means" is a means for the user to input the amount of money that can be spent on travel.

[1579] The "means for inputting favorite activities" is a means for inputting activities and experiences that the user is interested in.

[1580] "Terminal means" refers to an electronic device that allows a user to input information and transmit that information to a server.

[1581] "Emotion data" is information about emotions collected from the user's facial expressions, tone of voice, and the like.

[1582] "Server means" is a computer system that collects and processes information based on user requirements and emotion data.

[1583] "Filtering means" refers to means for removing irrelevant or inaccurate information from collected data.

[1584] The "analysis means" is a means for analyzing the filtered data and generating a travel plan that matches the user's preferences and feelings.

[1585] A "cost calculation tool" is a tool that calculates the cost of each element of a travel plan and ensures that the overall plan stays within budget.

[1586] An "emotion engine" is an engine that analyzes a user's emotions and provides optimal information and services based on those emotions.

[1587] The "real-time suggestion means" is a means for suggesting products and services in real time based on the user's emotional data.

[1588] The present invention is a system that provides optimal travel plans and shopping experiences in brick-and-mortar stores that take into account the user's emotions. The system collects user input information and emotional data in real time, and performs analysis based on this information to provide recommended information that matches the user's emotions. A specific embodiment of this system and its processing flow are described below.

[1589] System Overview

[1590] This system consists of the following elements:

[1591] 1. Terminal means:

[1592] The device where a user enters information such as travel destination, itinerary, budget, and preferred activities. Specifically, this applies to mobile devices such as smartphones and tablets.

[1593] In addition, it has a built-in emotion engine that senses the user's facial expressions and tone of voice in real time.

[1594] 2. Server means:

[1595] A server that collects and analyzes relevant data such as tourist attractions, accommodations, places to eat, and activities from internal and external sources based on user requirements and sentiment data.

[1596] By using cloud servers, high data processing capacity and scalability are achieved.

[1597] 3. Filtering methods:

[1598] The server removes irrelevant or inaccurate information from the data collected, improving the accuracy of the data.

[1599] It uses specific algorithms to remove noise and unwanted data.

[1600] 4. Analysis method:

[1601] Based on the filtered data, optimal travel plans and product suggestions that match the user's preferences and emotions are generated.

[1602] Based on the data obtained from the emotion engine, the services desired by the user are identified.

[1603] 5. Cost calculation methods:

[1604] Calculate the cost of each element and adjust it so that the total fits within the user's budget.

[1605] 6. Real-time suggestion methods:

[1606] Based on the user's emotional data, products and services are suggested in real time.

[1607] Processing flow

[1608] Device data collection:

[1609] The user uses the terminal to input travel destination, travel dates, budget, and preferred activities.

[1610] The emotion engine collects emotional data from the user's facial expressions and tone of voice, for example, by detecting a smile on the user's face or a happy tone in the user's voice when the user is entering their travel plans.

[1611] Data transmission and collection:

[1612] The terminal transmits the travel information and emotion data entered by the user to the server in real time.

[1613] The server collects relevant information, such as tourist attractions, accommodations, and dining places, through an internal database and external APIs.

[1614] Data filtering and analysis:

[1615] The server analyzes the collected data and filters out data that is inaccurate or does not meet the user's requirements.

[1616] Based on the filtered data, the system generates an optimal travel plan tailored to the user's preferences and emotions. For example, if a user is looking for "Kyoto," "visiting historical sites," and "relaxing hot springs," the system will provide information on Kinkakuji Temple and Arashiyama Hot Springs.

[1617] Cost calculation and planning:

[1618] It calculates the cost of each component and adjusts the overall travel plan to fit within the user's budget.

[1619] The generated itinerary is sent to the terminal for the user to review and customize.

[1620] Examples of specific examples and prompts

[1621] Examples:

[1622] While the user is wearing the smart glasses and walking around the store, products and services with a relaxing effect are displayed. Specifically, the text "Click here for relaxing aroma candles" appears on the smart glasses' display.

[1623] Example prompt sentence:

[1624] "Analyze the emotions of a customer when they visit the relaxation zone in a store, and generate a script to recommend products that have a relaxing effect based on that emotional data."

[1625] This will enable us to provide travel plans and shopping experiences that are tailored to the user's emotions in real time, thereby achieving higher customer satisfaction.

[1626] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1627] Step 1:

[1628] The user puts on the smart glasses and inputs their travel destination, itinerary, budget, and preferred activities using voice or gestures.

[1629] Input: User voice commands and gesture input

[1630] Output: Travel destination, travel dates, budget, and preferred activities

[1631] Step 2:

[1632] The device (smart glasses) uses a built-in camera and microphone to collect emotional data from the user's facial expressions and tone of voice.

[1633] Input: User's facial expression and voice tone

[1634] Output: User emotion data

[1635] Step 3:

[1636] The terminal transmits the collected travel information and emotion data to the server in a set format.

[1637] Input: Travel information and emotion data

[1638] Output: Formatted data sent to server

[1639] Step 4:

[1640] Based on the data received by the server, it uses an internal database and external APIs to collect relevant data such as tourist attractions, accommodation, places to eat, activities, etc.

[1641] Input: Travel information and emotion data

[1642] Output: Related data on attractions, accommodation, places to eat, activities, etc.

[1643] Step 5:

[1644] The server uses filtering means to remove irrelevant or inaccurate information from the collected data.

[1645] Input: Collected data

[1646] Output: Filtered data

[1647] Step 6:

[1648] The server analyzes the filtered data and the emotion data and generates an optimal travel plan that matches the user's preferences and emotions.

[1649] Input: Filtered data and sentiment data

[1650] Output: Generated itinerary

[1651] Step 7:

[1652] The server uses a cost calculation means to calculate the cost of each element of the travel plan and adjusts the overall travel plan so that it fits within the user's budget.

[1653] Input: Generated itinerary

[1654] Output: Costed itinerary

[1655] Step 8:

[1656] The server transmits the generated optimal travel plan to the terminal so that the user can check and customize it.

[1657] Input: Costed itinerary

[1658] Output: Trip plan sent to the device

[1659] Step 9:

[1660] The terminal presents the travel plan to the user and provides an interface that allows the user to review and customize the plan as needed.

[1661] Input: Travel plan sent from the server

[1662] Output: A travel plan that can be viewed by the user

[1663] Step 10:

[1664] Using the smart glasses' real-time suggestion means, optimal products and services are suggested in physical stores based on the user's emotional data.

[1665] Input: Real-time emotion data

[1666] Output: Product and service recommendations based on user sentiment

[1667] These are the specific processing steps of the system that realizes this application example. This makes it possible to provide optimal travel plans that take into account the user's emotions and to present recommended products and services in real time in physical stores.

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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).

[1675] 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.

[1676] 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."

[1677] 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.

[1678] 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).

[1679] 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.

[1680] 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.

[1681] 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.

[1682] 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.

[1683] 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.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] The following is further disclosed regarding the above embodiment.

[1690] (Claim 1)

[1691] a means for the user to input travel destination, travel dates, budget, and preferred activities;

[1692] a terminal means for receiving input information and transmitting the information to a server;

[1693] a server means for collecting data such as tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on user requirements;

[1694] filtering means to remove irrelevant or inaccurate data from the collected data and improve the accuracy of the data;

[1695] an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences;

[1696] A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget;

[1697] The system includes means for transmitting the generated travel plan to a terminal for user review and customization.

[1698] (Claim 2)

[1699] 10. The system of claim 1, wherein the server means comprises means for collecting data through internal database queries and external API calls.

[1700] (Claim 3)

[1701] 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

[1702] "Example 1"

[1703] (Claim 1)

[1704] a means for the user to input travel destination, travel dates, budget, and preferred activities;

[1705] a terminal means for receiving input information and transmitting the information to a server;

[1706] A server means for collecting data on tourist spots, accommodations, restaurants, activities, etc. from an internal database and external information sources based on user requirements;

[1707] filtering means to remove irrelevant or inaccurate data from the collected data and improve the accuracy of the data;

[1708] an analysis means including a generative AI model for analyzing the filtered data and generating a travel plan that matches the user's preferences;

[1709] A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget;

[1710] The system includes means for transmitting the generated travel plan to a terminal for user review and customization.

[1711] (Claim 2)

[1712] 10. The system of claim 1, wherein the server means comprises means for collecting data through internal database queries and external API calls.

[1713] (Claim 3)

[1714] 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

[1715] "Application Example 1"

[1716] (Claim 1)

[1717] a means for the user to input travel destination, travel dates, budget, and preferred activities;

[1718] a terminal means for receiving input information and transmitting the information to a server;

[1719] a server means for collecting data such as tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on user requirements;

[1720] filtering means to remove irrelevant or inaccurate data from the collected data and improve the accuracy of the data;

[1721] an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences;

[1722] A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget;

[1723] means for transmitting the generated travel plan to the terminal so that the user can review and customize it;

[1724] A means to generate and present optimal travel plans using external AI models in real time based on data entered by the user;

[1725] The system includes a means to present travel plans to users in an easy-to-understand format by using prompt sentences generated by a generative AI model.

[1726] (Claim 2)

[1727] 10. The system of claim 1, wherein the server means comprises means for collecting data through internal database queries and external API calls.

[1728] (Claim 3)

[1729] 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

[1730] "Example 2: Combining Emotion Engines"

[1731] (Claim 1)

[1732] a means for the user to input travel destination, travel dates, budget, and preferred activities;

[1733] a user interface means for receiving input information and transmitting the information and collected emotion data to a server;

[1734] A server means for collecting information such as tourist destinations, accommodations, places to eat, activities, etc. from internal and external sources based on the user's requirements and feelings;

[1735] filtering means to remove irrelevant or inaccurate data from the collected information and improve the accuracy of the data;

[1736] an analysis means for analyzing the filtered information and emotion data and generating a travel plan that matches the user's preferences and emotions;

[1737] A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget;

[1738] The system includes means for transmitting the generated itinerary to a user interface for user review and customization.

[1739] (Claim 2)

[1740] 10. The system of claim 1, wherein said server means comprises means for collecting information through internal database queries and external data acquisition means.

[1741] (Claim 3)

[1742] 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

[1743] "Application example 2 when combining emotion engines"

[1744] (Claim 1)

[1745] a means for the user to input travel destination, travel dates, budget, and preferred activities;

[1746] a terminal means for receiving input information and user emotion data and transmitting the information to a server;

[1747] A server means for collecting data such as tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on user requirements and emotion data;

[1748] filtering means to remove irrelevant or inaccurate data from the collected data and improve the accuracy of the data;

[1749] an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences and emotions;

[1750] A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget;

[1751] The system includes means for transmitting the generated travel plan to a terminal for user review and customization.

[1752] (Claim 2)

[1753] 10. The system of claim 1, wherein the server means comprises means for collecting data through internal database queries and external API calls.

[1754] (Claim 3)

[1755] 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

[1756] (Claim 4)

[1757] 2. The system according to claim 1, further comprising an emotion engine that recognizes emotion data of a user, and means for suggesting products and services that match the emotion of the user in real time based on the emotion data. [Explanation of symbols]

[1758] 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. a means for the user to input travel destination, travel dates, budget, and preferred activities; a terminal means for receiving input information and transmitting the information to a server; a server means for collecting data such as tourist attractions, accommodations, places to eat, activities, etc. from internal and external sources based on user requirements; filtering means to remove irrelevant or inaccurate data from the collected data and improve the accuracy of the data; an analysis means for analyzing the filtered data and generating a travel plan that matches the user's preferences; A cost calculator to calculate the cost of each element and ensure the overall itinerary stays within budget; The system includes means for transmitting the generated travel plan to a terminal for user review and customization.

2. 10. The system of claim 1, wherein said server means comprises means for collecting data through internal database queries and external API calls.

3. 2. The system of claim 1, wherein said filtering means comprises means for filtering out irrelevant data and noise using a specific algorithm.

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