system

Abstract

Provide a system. [Solution] a means for inputting user travel destination and activity interest information; means for receiving and storing the input information; means for analyzing the stored information and generating a travel plan based on the user's interests and budget; means for transmitting the generated travel plan to a user terminal; A means for acquiring the user's current location information and providing real-time information on nearby tourist spots and restaurants; means for receiving and analyzing feedback information from the user; and means for updating a travel plan generation algorithm based on the analyzed feedback information.

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 often offer only fixed itineraries, unable to flexibly adapt to users' interests and budgets. This makes it difficult to provide a travel experience that matches the user's interests. Furthermore, they lack the means to resolve inconveniences during travel, unable to provide real-time information or respond to changes in traffic conditions. Furthermore, it is difficult to incorporate post-trip feedback into next plans, so the system is often used only once. The present invention solves these problems by providing a system that offers users a consistent travel experience tailored to their individual needs. [Means for solving the problem]

[0005] The present invention provides a travel planning system including the following means: means for inputting information about a user's travel destination and activities of interest, means for receiving and saving the input information, means for analyzing the saved information and generating a travel plan based on the user's interests and budget, means for transmitting the generated travel plan to a user terminal, means for acquiring information about the user's current location and providing real-time information about nearby tourist attractions and restaurants, means for receiving and analyzing feedback information from the user, and means for updating a travel plan generation algorithm based on the analyzed feedback information. This makes it possible to provide flexible travel plans tailored to individual user needs, eliminate inconvenience during travel through real-time information updates, and realize continuous improvement of the plan based on the feedback.

[0006] "User" refers to an individual or group that utilizes the travel planning system to create and execute a travel plan.

[0007] "Travel destination" refers to the location or destination to which a user is planning to travel.

[0008] "Activity information" refers to information about activities and events that a user is interested in participating in during their trip.

[0009] "Input means" refers to the method or interface by which a user provides information to a system.

[0010] "Means for receiving" refers to the functions and processes by which the system receives information provided by the user.

[0011] "Means for storing" refers to the function for storing received information in a database or storage device.

[0012] "Analysis means" refers to the algorithms and methods used to process stored information and find relationships and patterns.

[0013] A "travel plan" refers to a detailed plan of travel schedules and destinations during a trip proposed to a user.

[0014] "Means for generating" refers to the algorithms and methods for generating a travel plan based on user input information.

[0015] "Transmission means" refers to a communication method or interface for delivering the generated travel plan to the user terminal.

[0016] "Current Location Information" refers to real-time geographic location data obtained from a User's Device.

[0017] "Means of providing" refers to a method for transmitting the information or services required by the user in real time.

[0018] "Feedback Information" refers to the ratings and opinions about the travel experience provided by the user to the system.

[0019] "Means of updating" refers to methods for improving the algorithms and planning logic within the system based on feedback information.

[0020] "Travel plan generation algorithm" refers to the calculation procedures and logic for creating optimal travel plans based on a user's interests and budget.

[0021] "Traffic conditions" refers to information regarding the operation status and congestion of the means of transportation used by the user during his / her trip.

[0022] "Weather information" refers to data regarding weather conditions at the user's travel destination. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2]1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0026] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0027] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0028] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0029] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0030] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0031] [First embodiment]

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

[0033] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0034] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0035] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0036] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0037] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0038] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0040] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0041] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0042] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] MODE FOR CARRYING OUT THE INVENTION

[0045] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[0046] System Overview

[0047] User Registration and Profiling

[0048] Device: The user installs the application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[0049] Server: Receives the input information and stores it in a database. It also obtains past travel history and rating information to generate a user profile.

[0050] Selecting a travel destination and registering interests

[0051] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[0052] Server: Receives the input travel destination and activity information, stores it in a database, and performs analysis to generate an appropriate travel plan based on it.

[0053] Generate and present a plan

[0054] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. At the same time, the server also references the user's past travel history and reviews to update the profile.

[0055] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0056] Real-time information provision

[0057] Terminal: The user launches the application while traveling.

[0058] Server: Obtains the user's current location in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[0059] Terminal: The user can adjust their plan based on the information provided.

[0060] Feedback and Improvements

[0061] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0062] Server: Receives and stores user feedback information, updates the travel plan generation algorithm based on this information, and reflects it in the next plan generation.

[0063] Specific examples

[0064] Example 1: A user plans a trip to Tokyo

[0065] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[0066] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[0067] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[0068] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[0069] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[0070] 6. User: Check the generated plan and start the trip.

[0071] 7. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[0072] 8. User: Enter feedback about the places and restaurants they visited.

[0073] 9. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[0074] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy travel plans that are flexible and respond in real time to their individual needs.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[0078] Step 2:

[0079] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[0080] Step 3:

[0081] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[0082] Step 4:

[0083] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[0084] Step 5:

[0085] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[0086] Step 6:

[0087] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0088] Step 7:

[0089] Server: Sends the generated travel plan to the user terminal.

[0090] Step 8:

[0091] Terminal: The user opens the application and checks the presented travel plan.

[0092] Step 9:

[0093] Device: The user launches the application while traveling and enables location information.

[0094] Step 10:

[0095] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[0096] Step 11:

[0097] Terminal: The user checks the notified information and adjusts the plan.

[0098] Step 12:

[0099] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0100] Step 13:

[0101] Server: Receives user feedback information and stores it in a database.

[0102] Step 14:

[0103] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[0104] Step 15:

[0105] Server: The updated algorithm is reflected in the generation of the next travel plan.

[0106] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that meets their individual needs.

[0107] Example 1

[0108] 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."

[0109] Conventional travel planning systems have difficulty generating individually customized travel plans based on users' interests and budgets, and do not adequately utilize real-time information and feedback. This has led to a demand for improved flexibility and accuracy in travel planning.

[0110] 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.

[0111] In this invention, the server includes means for inputting a user's personal information and information on activities of interest at the travel destination, means for receiving the input information and storing it in a database, means for generating and analyzing a user profile based on the stored information, means for using a generative AI model to generate a travel plan based on the user's interests and budget, means for transmitting the generated travel plan to a user terminal, means for acquiring the user's location information and providing real-time information on nearby tourist spots and restaurants, means for acquiring real-time traffic and weather information, means for receiving, storing, and analyzing feedback information from the user, and means for updating the travel plan generation algorithm based on the analyzed feedback information and reflecting it in the generation of the next travel plan. This enables the provision of travel plans customized to the user's needs and improves the flexibility and accuracy of travel plans by utilizing real-time information.

[0112] "User's personal information" refers to information including the user's name, age, gender, hobbies, budget, etc.

[0113] "Interesting activity information at a travel destination" refers to information about activities and events in which a user is interested at a travel destination.

[0114] "Database" refers to a system for efficiently storing and managing user information and travel destination data.

[0115] A "user profile" is a personalized set of information generated based on a user's personal information and past travel history and rating information.

[0116] "Generative AI model" refers to an artificial intelligence model used to generate travel plans based on a user's interests and budget.

[0117] "User terminal" means an electronic device (e.g., a smartphone, tablet, or laptop) on which a user installs and operates an application.

[0118] "Location information" refers to information about a user's current geographical location obtained using technology such as GPS.

[0119] "Tourist spots" refer to tourist destinations and famous places that users want to visit.

[0120] "Restaurant information" refers to detailed information about restaurants, cafes, etc. that the user plans to visit.

[0121] "Traffic conditions" refers to information about the real-time operation status of roads and public transportation.

[0122] "Weather information" refers to information about real-time weather forecasts and weather conditions.

[0123] "Feedback information" refers to evaluations and opinions about the places and services visited that a user provides after a trip.

[0124] A "travel plan generation algorithm" is a calculation method or procedure for analyzing input data and generating the optimal travel plan for the user.

[0125] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[0126] System Overview

[0127] User Registration and Profiling

[0128] Device: The user installs the travel planning system application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[0129] Server: Receives the entered user personal information and information on activities of interest at travel destinations and stores it in a database (e.g., MySQL (registered trademark) or PostgreSQL). Then, retrieves past travel history and rating information and generates a user profile using a Python script. The user profile includes information on previously visited tourist spots and restaurants, rating points, etc.

[0130] Selecting a travel destination and registering interests

[0131] User: Enter travel destinations and activities they are interested in. For example, enter "Travel destination: Tokyo" or "Activity: Eating out."

[0132] Terminal: Transmits the entered travel destination and activity information to the server.

[0133] Server: Stores the received travel destination and activity information in a database, then analyzes it using a generative AI model (e.g., TENSORFLOW® or PyTorch) to generate a travel plan based on the user's interests and budget.

[0134] Generate and present a plan

[0135] Server: Based on the user profile and the entered travel destination and activity information, the server analyzes the user's interests and budget and lists tourist spots and restaurants suitable for food tours. For example, the list includes "a long-established sushi restaurant in Ginza" and "a famous taiyaki shop in Asakusa."

[0136] Server: Based on the listed spots, the server generates an optimal travel schedule that takes into account travel time and rest times. This may involve using linear programming or genetic algorithms. The generated schedule includes specific timetables such as "10:00 AM: Taiyaki in Asakusa → 12:00 PM: Sushi lunch in Ginza."

[0137] Server: Sends the generated travel plan to the user terminal.

[0138] Terminal: The received travel plan is displayed on the user interface. The user can check the displayed plan and get ready to start the trip.

[0139] Real-time information provision

[0140] Device: During travel, the device uses GPS to obtain real-time information about the user's current location.

[0141] Server: Based on the user's current location, the server uses the Google (registered trademark) Maps API to provide information on nearby tourist spots and restaurants. Additionally, the server uses the OpenWeatherMap API to provide real-time weather and traffic information.

[0142] Terminal: The information provided in real time is displayed on the user interface, allowing users to adjust their travel plans based on this information.

[0143] Feedback and Improvements

[0144] User: After the trip, the user enters feedback about the places and restaurants they visited into the device. For example, they send feedback such as, "I was very satisfied with the sushi restaurant in Ginza."

[0145] Terminal: Sends the input feedback information to the server.

[0146] Server: Stores the received feedback information in a database. Then, retrains the generative AI model (e.g., TensorFlow or PyTorch) based on the collected feedback data and updates the itinerary generation algorithm.

[0147] Specific examples

[0148] Example: A user plans a trip to Tokyo

[0149] 1. The user installs the app and enters their name, age, gender, hobby (eating out), and budget (50,000 yen).

[0150] 2. The server receives the information, stores it in a database, and updates the user profile based on past travel history and ratings.

[0151] 3. The user selects Tokyo as their travel destination and registers "food tours" as an activity of interest.

[0152] 4. The server analyzes the information and creates a list of popular food spots in Tokyo and restaurants that fit within your budget.

[0153] 5. The server generates a schedule based on the listed spots, taking into account travel time and break times, and sends it to the device.

[0154] 6. The user confirms the generated plan and starts the trip.

[0155] 7. While traveling, the device will obtain real-time location information via GPS and provide information on nearby tourist attractions, restaurants, traffic conditions and weather.

[0156] 8. Users can provide feedback about the places and restaurants they visit.

[0157] 9. The server receives and stores the feedback information, retrains the generative AI model, and updates the itinerary generation algorithm.

[0158] Prompt Sentence Examples

[0159] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[0160] In this way, the present invention allows users to enjoy optimal travel plans tailored to their individual interests and budgets, and further enhances the quality of the travel experience by providing real-time information and continuous improvements based on user feedback.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Processing Steps

[0163] Step 1:

[0164] A user installs a travel planning app on a device such as a smartphone and enters personal information such as name, age, gender, hobbies, and budget on the account creation screen. The data entered is name, age, gender, hobbies, and budget. The device converts this information into JSON format and sends it to the server.

[0165] Input: Name, age, gender, hobbies, budget

[0166] Data processing: Convert personal information into JSON format

[0167] Output: Personal information data in JSON format

[0168] Step 2:

[0169] The server receives the personal information entered and stores it in a database. After saving, it runs a Python script to retrieve relevant information from the database (such as past trip history and ratings) and update the user profile.

[0170] Input: Personal information data in JSON format

[0171] Data processing: saving to database, updating user profile

[0172] Output: Updated user profile

[0173] Step 3:

[0174] The user enters information about their travel destination and the activity they are interested in into the app. For example, they enter "Travel destination: Tokyo" and "Activity: Eating out." The entered data is then sent back to the server.

[0175] Input: Travel destination, activity

[0176] Data processing: Converting destination and activity information into JSON format

[0177] Output: Destination and activity information in JSON format

[0178] Step 4:

[0179] The server stores the received destination and activity information in a database, and then uses a generative AI model (e.g., TensorFlow or PyTorch) to generate a trip plan based on the destination and activity information.

[0180] Input: Destination and activity information in JSON format

[0181] Data processing: Saving to database, analyzing using AI model and generating plan

[0182] Output: A list of travel itinerary suggestions

[0183] Step 5:

[0184] The server generates an optimal travel schedule that takes into account travel time and rest times based on the list of tourist spots and restaurants, using linear programming and genetic algorithms.

[0185] Input: Travel plan candidate list, user profile

[0186] Data processing: Execution of schedule generation algorithm

[0187] Output: Generated travel schedule

[0188] Step 6:

[0189] The server sends the generated travel schedule to the user's device. The data is converted to JSON format again.

[0190] Input: Generated travel schedule

[0191] Data processing: Conversion to JSON format

[0192] Output: JSON formatted travel schedule data

[0193] Step 7:

[0194] The terminal displays the received travel schedule on the user interface, and the user can review the displayed plan and make adjustments as necessary.

[0195] Input: JSON formatted travel schedule data

[0196] Data processing: Display on the user interface

[0197] Output: Final travel schedule

[0198] Step 8:

[0199] The user uses the device while traveling and obtains current location information in real time using the GPS function.

[0200] Input: Real-time location information

[0201] Data processing: GPS data collection

[0202] Output: Real-time location information

[0203] Step 9:

[0204] The server calls the Google Maps API to provide information about nearby tourist spots and restaurants based on the user's current location, and also uses the OpenWeatherMap API to obtain current weather and traffic information.

[0205] Input: Real-time location information

[0206] Data processing: API calls and data acquisition

[0207] Output: Nearby tourist spots, restaurant information, weather information, traffic conditions

[0208] Step 10:

[0209] The device displays the data sent from the server in real time, allowing users to adjust their travel plans based on this information.

[0210] Input: Nearby tourist spots, restaurant information, weather information, traffic conditions

[0211] Data processing: Display on the user interface

[0212] Output: Real-time information visualization

[0213] Step 11:

[0214] After the trip, the user inputs feedback about the spots and restaurants they visited into the terminal, and the input feedback information is sent to the server.

[0215] Input: Feedback information

[0216] Data processing: Convert to JSON format and send to server

[0217] Output: Feedback information in JSON format

[0218] Step 12:

[0219] The server stores the received feedback information in a database and retrains the generative AI model, which then reflects the itinerary generation algorithm in the next itinerary.

[0220] Input: Feedback information in JSON format

[0221] Data processing: saving to database, retraining AI models

[0222] Output: Updated itinerary generation algorithm

[0223] Example prompt sentence:

[0224] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[0225] (Application example 1)

[0226] 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."

[0227] Conventional food delivery systems have difficulty providing optimal delivery plans that match users' individual preferences and budgets. Furthermore, due to a lack of real-time information, users tend to spend a lot of time selecting the right restaurant and food. Furthermore, there is a lack of systems that effectively utilize user feedback to improve the next recommendation. These issues need to be addressed.

[0228] 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.

[0229] In this invention, the server includes means for inputting information on a user's food delivery destinations and favorite dishes, means for receiving and storing the input information, means for analyzing the stored information and generating a delivery plan based on the user's interests and budget, means for transmitting the generated delivery plan to a user terminal, means for acquiring the user's current location information and providing information on nearby restaurants and dishes in real time, means for receiving and analyzing feedback information from the user, and means for updating the delivery plan generation algorithm based on the analyzed feedback information. This makes it possible to provide an optimal delivery plan suited to each user's preferences and budget, and further enables the system's functions to be continuously improved through the provision of information and feedback in real time.

[0230] "Means for inputting user's food delivery destination and preferred dish information" refers to a user interface for inputting data such as the user's designated delivery location, preferred dish types, and allergy information through the application.

[0231] The "means for receiving and storing the input information" refers to a module for receiving data input by a user on the server side and recording it in a storage device such as a database.

[0232] "Means for analyzing the stored information and generating a delivery plan based on the user's interests and budget" refers to an algorithm that uses the stored data to create an optimal delivery plan based on the user's tastes, preferences, and budget.

[0233] "Means for transmitting the generated delivery plan to a user terminal" refers to a communication module for transmitting the generated delivery plan to a user device such as a smartphone or tablet.

[0234] "Means for obtaining the user's current location information and providing real-time information about nearby restaurants and cuisines" refers to a module that uses GPS, beacons, etc. to identify the user's current location and provides real-time information about nearby restaurants and cuisines based on that location.

[0235] "Means for receiving and analyzing feedback information from the user" refers to a function for receiving feedback data such as ratings and comments provided by the user, analyzing it, and improving the content of the next proposal.

[0236] "Means for updating the delivery plan generation algorithm based on the analyzed feedback information" refers to a function within the system for improving and updating the algorithm used to generate future delivery plans based on analyzed feedback data.

[0237] This invention relates to a system that provides optimal food delivery plans based on a user's individual preferences and budget. The system provides appropriate information in real time by linking user terminals and a server, enabling efficient, high-quality delivery services.

[0238] System Configuration

[0239] The system consists of the following elements:

[0240] 1. User Device

[0241] A smartphone or tablet is used as a user terminal, through which the user provides input data and receives information in real time.

[0242] 2. Server

[0243] The server acts as the backend for the application, generating user profiles, creating delivery plans, and providing real-time information. The server is built using Python / Django or Node.js / Express, and uses PostgreSQL or MongoDB as the database.

[0244] User Registration and Profiling

[0245] The server stores user information (e.g., name, age, favorite dishes, allergies, budget) received from the user's device in a database. This information, along with past order history and rating information, is analyzed to create a profile for each user. This profile is used when creating future delivery plans.

[0246] Restaurant and menu selection

[0247] The server lists appropriate restaurants and menus based on the type of meal and budget specified by the user, using specific algorithms (e.g., random forest or k-means clustering) to match the user's profile data and suggest the best options.

[0248] Generate and present a delivery plan

[0249] The generated delivery plan is optimized to take into account breaks and waiting times. Details of the specific restaurant, food, expected arrival time, and price are sent to the user's device. The user can then review the plan and order the selected menu.

[0250] Real-time information provision

[0251] The server uses GPS and beacons to obtain the user's current location in real time and immediately provides information about nearby restaurants and the dishes currently being served, as well as information about waiting times and estimated delivery times.

[0252] Feedback and Improvements

[0253] After the delivery is completed, the user provides feedback, which is sent to the server and stored. This data is reflected in the next delivery plan generation, improving the accuracy of the algorithm.

[0254] Specific examples

[0255] Example 1: User A orders sushi

[0256] User A installed the app, selected sushi as his / her favorite dish, and set his / her budget to 5,000 yen. User A was then suggested highly rated sushi restaurants based on his / her current location (e.g., within Tokyo). One example of a suggested plan included Sushi Restaurant B, which offers a sushi set (price: 3,000 yen). User A ordered sushi based on this suggestion, and after receiving the delivery, provided feedback rating his / her satisfaction as 5 stars.

[0257] Prompt Sentence Examples

[0258] User Profile:

[0259] Name: User A

[0260] Favorite food: Sushi

[0261] Budget: 5,000 yen

[0262] Current location: Tokyo

[0263] Rating history: Sushi Restaurant B (5 stars)

[0264] Next, please suggest a restaurant and dish you would recommend.

[0265] This concludes the "Mode for Carrying Out the Invention." This allows users to easily obtain delivery plans that suit their individual needs, and the system is continually improved based on feedback.

[0266] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0267] Step 1:

[0268] Users start the smartphone app and enter personal information such as their name, age, favorite dishes, allergies, budget, etc. on the account creation screen. The entered information is sent from the device to the server.

[0269] input:

[0270] Personal information such as name, age, favorite dishes, allergy information, budget, etc.

[0271] output:

[0272] User information sent to the server

[0273] Step 2:

[0274] The server stores the received user information in a database, which is then analyzed along with past order history and rating information to create a user profile.

[0275] input:

[0276] User information sent

[0277] output:

[0278] User profiles stored in a database

[0279] Operation:

[0280] The server analyzes the received data and generates a profile

[0281] Step 3:

[0282] The user selects a restaurant and menu based on the type of food they want to eat and their budget. The information entered into the terminal is sent to the server.

[0283] input:

[0284] What type of food do you want to eat and your budget?

[0285] output:

[0286] Cuisine and budget information sent to the server

[0287] Step 4:

[0288] The server lists suitable restaurants and menus based on the type of cuisine and budget entered by the user, matches it with the stored profile data, and suggests the best options using algorithms (e.g., random forest, k-means clustering).

[0289] input:

[0290] User profile, cuisine type, budget

[0291] output:

[0292] A list of restaurants and menus suggested to the user

[0293] Operation:

[0294] The server analyzes the profile data and applies algorithms to generate a list of suggestions

[0295] Step 5:

[0296] The generated delivery plan is sent to the user's terminal, where the user can confirm the proposed plan and order the selected menu.

[0297] input:

[0298] List of suggested restaurants and menus

[0299] output:

[0300] Delivery plan displayed on the user's device

[0301] Step 6:

[0302] The server uses GPS and beacons to obtain the user's current location in real time, and provides information about nearby restaurants and the dishes currently being served based on that location, as well as notifying the user of waiting times and estimated delivery times.

[0303] input:

[0304] User's current location

[0305] output:

[0306] Nearby restaurants and food information, waiting times, and estimated delivery times

[0307] Operation:

[0308] The server analyzes the location information and acquires and displays real-time data.

[0309] Step 7:

[0310] After receiving their delivery, users can enter their feedback on the food and service into the app, which then sends the feedback information from their device to the server.

[0311] input:

[0312] User feedback information (e.g., ratings, comments)

[0313] output:

[0314] Feedback information sent to the server

[0315] Step 8:

[0316] The server stores the feedback information received from users in a database and analyzes it. Based on the results of this analysis, it updates the algorithm for generating the next delivery plan and improves the system to make more appropriate proposals.

[0317] input:

[0318] User feedback information

[0319] output:

[0320] Next delivery plan with updated algorithm

[0321] Operation:

[0322] The server analyzes the feedback and updates the algorithm

[0323] The above are the specific processing steps of the system that realizes the application example based on the claims.

[0324] 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.

[0325] MODE FOR CARRYING OUT THE INVENTION

[0326] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[0327] System Overview

[0328] User Registration and Profiling

[0329] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[0330] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[0331] Selecting a travel destination and registering interests

[0332] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[0333] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[0334] Generate and present a plan

[0335] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. Updates the user's profile based on the user's past travel history and rating information.

[0336] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0337] Emotion Engine Operation

[0338] On-device: While a user is using an application, the emotion engine analyzes emotions based on the user's input and actions. For example, it determines emotions from the language and expressions used when a user enters comments or feedback.

[0339] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user has a low preference for the plan, it presents an alternative plan.

[0340] Real-time information provision

[0341] Device: The user launches the application while traveling and enables location information.

[0342] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[0343] Terminal: Monitors the user's emotional state in real time and dynamically adjusts the travel plan according to the user's emotions.

[0344] Feedback and Improvements

[0345] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0346] Server: Receives user feedback information and stores it in a database. Based on this, the travel plan generation algorithm is updated and reflected in the next plan generation.

[0347] Server: The server also analyzes feedback from the emotion engine and improves the plan generation algorithm by taking the user's emotions into account.

[0348] Specific examples

[0349] Example 1: A user plans a trip to Tokyo

[0350] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[0351] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[0352] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[0353] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[0354] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[0355] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[0356] 7. User: Check the generated plan and start the trip.

[0357] 8. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[0358] 9. Terminal: The emotion engine also monitors the user’s emotional state in real time and adjusts the plan when the user feels dissatisfied or tired.

[0359] 10. User: Enter feedback about the places and restaurants they visited.

[0360] 11. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[0361] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy flexible and real-time travel plans that meet their individual needs and emotions.

[0362] The processing flow will be explained below.

[0363] Step 1:

[0364] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[0365] Step 2:

[0366] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[0367] Step 3:

[0368] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[0369] Step 4:

[0370] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[0371] Step 5:

[0372] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[0373] Step 6:

[0374] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0375] Step 7:

[0376] Server: Sends the generated travel plan to the user terminal.

[0377] Step 8:

[0378] Terminal: The user opens the application and checks the presented travel plan.

[0379] Step 9:

[0380] Device: The user launches the application while traveling and enables location information.

[0381] Step 10:

[0382] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[0383] Step 11:

[0384] Terminal: The user checks the notified information and adjusts the plan.

[0385] Step 12:

[0386] On-device: During the journey, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments and feedback.

[0387] Step 13:

[0388] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user's emotion is negative, it presents an alternative plan.

[0389] Step 14:

[0390] Device: Monitors the user's emotional state in real time and adjusts the plan if the user feels frustrated or fatigued.

[0391] Step 15:

[0392] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0393] Step 16:

[0394] Server: Receives user feedback information and stores it in a database.

[0395] Step 17:

[0396] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[0397] Step 18:

[0398] Server: The updated algorithm is reflected in the generation of the next travel plan.

[0399] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that is tailored to their individual needs and emotions.

[0400] Example 2

[0401] 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."

[0402] Conventional travel planning systems have difficulty providing flexible and real-time travel plans that meet diverse user needs, and lack a means to effectively reflect user emotions and feedback.

[0403] 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.

[0404] In this invention, the server includes: means for a user to register account information; means for receiving the registered information and saving it in a database; means for inputting information about the user's travel destinations and activities of interest; means for receiving and saving the input information; means for analyzing the saved information and generating an itinerary based on the user's interests and budget; means for transmitting the generated itinerary to a user terminal; means for acquiring the user's current location information and providing real-time information about nearby tourist spots and restaurants; means including a sentiment analysis engine for acquiring feedback information; means for receiving and analyzing the feedback information and sentiment analysis results from the user; and means for updating the itinerary generation algorithm based on the analyzed feedback information. This enables the provision of flexible, real-time itineraries that reflect the diverse needs and emotions of users.

[0405] "Account information" refers to basic data required when using the system, such as the user's name, age, gender, hobbies, and budget.

[0406] A "database" is a system for efficiently storing, retrieving, and managing information, and is usually built on a server.

[0407] "Destination" refers to a geographical destination that a user wishes to visit.

[0408] "Activity information" is information about specific activities such as sightseeing, shopping, and dining that interest the user.

[0409] "Analysis" is the act of investigating and analyzing input data in detail to extract meaning and patterns.

[0410] A "travel plan" refers to a plan that combines places to visit, activities, a schedule, etc. based on the user's needs and interests.

[0411] A "user terminal" is a device that is directly operated by a user, and includes a smartphone, tablet, etc.

[0412] "Current location information" is geographic coordinate data of the user's current location, obtained from a device such as the user's smartphone.

[0413] A "tourist attraction" is a specific tourist destination that travelers want to visit.

[0414] "Eating and drinking establishment information" is information about establishments that provide meals, such as restaurants and cafes.

[0415] "Feedback" refers to information such as impressions, evaluations, and opinions that a user provides to the system during or after a trip.

[0416] An "emotion analysis engine" is a software component that determines a user's emotional state based on their input and behavior.

[0417] An "algorithm" refers to a set of steps or a computational method for solving a particular problem.

[0418] MODE FOR CARRYING OUT THE INVENTION

[0419] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[0420] System Overview

[0421] The system uses the following hardware and software:

[0422] Server hardware: General-purpose servers or cloud servers

[0423] Device hardware: smartphones, tablets

[0424] Server software: Django, Node.js, MySQL, PostgreSQL, ElasticSearch, GraphQL, Hugging Face Transformers, Google's BERT model

[0425] Device software: iOS app, ANDROID (registered trademark) app

[0426] API: HTTP, OpenWeatherMap API, Google Maps API

[0427] User Registration and Profiling

[0428] User: Download and install the application from the App Store or GOOGLE PLAY (registered trademark) on your smartphone.

[0429] User: Enter information such as name, age, gender, hobbies, budget, etc. on the account registration screen. The UI is designed to be simple and intuitive.

[0430] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[0431] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[0432] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[0433] Selecting a travel destination and registering interests

[0434] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[0435] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[0436] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[0437] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[0438] Generate and present a plan

[0439] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[0440] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[0441] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[0442] Emotion Engine Operation

[0443] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[0444] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[0445] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[0446] Real-time information provision

[0447] User: Enable location services for the app.

[0448] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[0449] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[0450] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[0451] Feedback and Improvements

[0452] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[0453] Terminal: Sends feedback information to the server.

[0454] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[0455] Specific examples

[0456] Example 1: A user plans a trip to Tokyo

[0457] 1. User: Install the app and enter their name, age, gender, hobby (eating out), and budget (50,000 yen).

[0458] 2. Terminal: Sends the entered information to the server.

[0459] 3. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[0460] 4. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[0461] 5. Terminal: Sends the entered information to the server.

[0462] 6. Server: Analyzes the information and creates a list of popular food spots in Tokyo and restaurants that are within your budget.

[0463] 7. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times, and sent to the device.

[0464] 8. Device: Display the received plan and analyze user comments and feedback through the sentiment engine. Adjust the plan as needed.

[0465] 9. User: Check the generated plan and start the trip.

[0466] 10. Device: Obtains real-time location information while traveling and displays nearby tourist attractions, restaurant information, traffic conditions, and weather information.

[0467] 11. Terminal: Monitors the user’s emotional state in real time and adjusts the plan as needed.

[0468] 12. User: Enter feedback about the places and restaurants visited after the trip.

[0469] 13. Device: Sends feedback to the server.

[0470] 14. Server: Receives and stores feedback information and reflects it in the next plan generation.

[0471] Prompt Sentence Examples

[0472] If a user types into the system, "I'm planning a trip to Tokyo, can you recommend some highly rated restaurants?", the system will take into account the user's emotional state and interests and respond as follows:

[0473] "We'd like to recommend some highly rated restaurants: Sushi place ABC, Ramen place XYZ, and Okonomiyaki place DEF. We also have great lunch menus. Which one do you prefer?"

[0474]

[0475] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0476] Step 1:

[0477] User: Download and install the application from the App Store or Google Play on their smartphone.

[0478] Step 2:

[0479] User: Enter information such as name, age, gender, hobbies, and budget on the account registration screen.

[0480] Input: User's basic information (name, age, gender, hobbies, budget).

[0481] Output: The input information is stored in the terminal and prepared for the next transmission step.

[0482] Step 3:

[0483] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[0484] Input: User basic information.

[0485] Output: User information sent to the server is saved.

[0486] Step 4:

[0487] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[0488] Input: User information.

[0489] Output: User information stored in the database and a status code to the terminal.

[0490] Step 5:

[0491] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[0492] Input: User information stored in the database, past travel history, and rating information.

[0493] Output: The generated user profile.

[0494] Step 6:

[0495] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[0496] Input: Travel destination (destination).

[0497] Output: The travel destination selection screen displayed.

[0498] Step 7:

[0499] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[0500] Input: Activities of interest.

[0501] Output: Selected activity information.

[0502] Step 8:

[0503] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[0504] Input: Travel destination, activity information of interest.

[0505] Output: Destination and activity information sent to the server.

[0506] Step 9:

[0507] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[0508] Input: Travel destination, activity information.

[0509] Output: Retrieved tourist spot and restaurant information.

[0510] Step 10:

[0511] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[0512] Input: User profile, travel destinations, and activity information.

[0513] Output: A list of tourist attractions and restaurants.

[0514] Step 11:

[0515] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[0516] Input: List of spots and restaurants, detailed information for each spot and restaurant.

[0517] Output: The generated travel schedule.

[0518] Step 12:

[0519] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[0520] Input: Travel schedule sent from the server.

[0521] Output: The schedule displayed in the user interface.

[0522] Step 13:

[0523] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[0524] Input: User feedback (comments and ratings).

[0525] Output: Feedback ready to send.

[0526] Step 14:

[0527] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[0528] Input: User feedback.

[0529] Output: Feedback sent to the emotion engine.

[0530] Step 15:

[0531] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[0532] Input: Analysis results from the emotion engine.

[0533] Output: Adjusted itinerary.

[0534] Step 16:

[0535] User: Enable location services for the app.

[0536] Enter: Enable location services.

[0537] Output: Enabled location services.

[0538] Step 17:

[0539] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[0540] Input: Current location information.

[0541] Output: The location information sent to the server.

[0542] Step 18:

[0543] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[0544] Input: Current location information.

[0545] Output: Provided real-time tourist attractions, restaurants, traffic and weather information.

[0546] Step 19:

[0547] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[0548] Input: The user's emotional state.

[0549] Output: Adjusted itinerary.

[0550] Step 20:

[0551] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[0552] Input: Feedback after the trip (impressions and ratings).

[0553] Output: Feedback ready to be sent.

[0554] Step 21:

[0555] Terminal: Sends feedback information to the server.

[0556] Input: Feedback information.

[0557] Output: Feedback information sent to the server.

[0558] Step 22:

[0559] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[0560] Input: Feedback information.

[0561] Output: An improved trip plan generation algorithm.

[0562] (Application example 2)

[0563] 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."

[0564] In conventional store visits and product selection, users face the challenge of efficiently finding the right store and product that matches their interests and budget. Furthermore, the provision of real-time store information and products is insufficient, and dynamic plan adjustments that take user emotions into account are not possible, resulting in an underoptimized user experience.

[0565] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about stores and products of interest to the user; means for receiving and saving the input information; means for analyzing the saved information and generating a store visit plan based on the user's interests and budget; means for transmitting the generated store visit plan to the user terminal; means for acquiring information about the user's current location and providing information about surrounding stores and products in real time; means for receiving and analyzing feedback information from the user; means for updating the store visit plan generation algorithm based on the analyzed feedback information; means for analyzing emotions from the user's input and behavior using an emotion engine; and means for dynamically adjusting the store visit plan in real time based on the analyzed emotion information. This allows the user to obtain an optimal store visit plan that suits their interests and budget, and the provision of information in real time and the dynamic adjustment of the plan based on emotions enable a more fulfilling store visit experience.

[0566] A "user" is an individual who installs the application, inputs information, and uses the store visit plan.

[0567] A "store" refers to a physical location that a user visits and that offers products or services of interest.

[0568] "Products" are goods and services offered at stores that are of interest to users.

[0569] "Information" refers to data entered by the user, including name, age, gender, hobbies, budget, stores and products of interest, etc.

[0570] A "plan" is a proposal of stores to visit and products to purchase, generated based on the user's interests and budget.

[0571] A "server" is a computer system that receives, stores, and analyzes information input by a user.

[0572] A "terminal" is a portable information processing terminal such as a mobile phone or smartphone used by a user.

[0573] "Feedback" refers to user impressions and evaluations of stores visited or products purchased.

[0574] An "emotion engine" is a software mechanism for analyzing emotions from user input and behavior.

[0575] "Real-time information provision" means providing the latest information about nearby stores and products immediately based on the user's current location information.

[0576] MODE FOR CARRYING OUT THE INVENTION

[0577] System Overview

[0578] This invention is a system for optimizing a user's store visit experience, and in particular, relates to an application that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[0579] User Registration and Profiling

[0580] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[0581] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[0582] Store and product selection and interest registration

[0583] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[0584] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[0585] Generate and present a plan

[0586] Server: Analyzes the above information and lists stores and products that match the user's interests and budget. Updates the user's profile based on the user's past store visit history and rating information.

[0587] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[0588] Emotion Engine Operation

[0589] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments or feedback.

[0590] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[0591] Real-time information provision

[0592] Device: The user launches the application and enables location while visiting the store.

[0593] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[0594] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[0595] Feedback and Improvements

[0596] Terminal: After the user has finished their visit, they enter feedback about the stores they visited and the products they purchased.

[0597] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[0598] Specific examples

[0599] Example: When a user visits a shopping mall

[0600] 1. User: Installs the app and enters their name, age, gender, hobby (fashion), and budget (30,000 yen).

[0601] 2. Server: Receives the information, stores it in a database, and updates the user profile based on past visits and reviews.

[0602] 3. User: Selects a specific shopping mall to visit and registers products (fashion items) that interest him / her.

[0603] 4. Server: Analyzes the entered information and lists recommended stores based on the user's interests and products that can be purchased within their budget.

[0604] 5. Server: Based on the listed stores and products, the server generates a plan that takes into account the route between stores and the length of stay, and sends it to the user's device.

[0605] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[0606] 7. User: Review the generated plan and start shopping.

[0607] 8. Device: While shopping, the device obtains your current location in real time and displays information about nearby stores and products. It also displays information about the store's congestion status and sales.

[0608] 9. Terminal: The emotion engine monitors the user's emotional state in real time and adjusts the plan when the user feels frustrated or fatigued.

[0609] 10. Users: Enter feedback about the stores they visit and the products they buy.

[0610] 11. Server: Receives feedback information, stores it in a database, and updates the algorithm based on it to generate the next plan.

[0611] Examples of prompt statements

[0612] Below are some example prompts for generative AI models:

[0613] Example prompt:

[0614] "Write code to implement a user registration feature for a mobile app. Implement an API endpoint on a Flask server that receives the following data and stores it in an SQLite database: Name, Age, Gender, Hobbies, Budget."

[0615] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0616] Step 1:

[0617] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[0618] Input: User information (name, age, gender, hobbies, budget)

[0619] Output: Send user registration information

[0620] Specific operation: When the user enters information into the application's input fields and presses the "Register" button, this information is sent to the server.

[0621] Step 2:

[0622] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[0623] Input: User registration information

[0624] Output: Updated user profile

[0625] Specific operation: The server connects to the database, saves the received user information, and compares it with past store visit history and evaluation information to update and generate a profile.

[0626] Step 3:

[0627] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[0628] Input: Store and product information

[0629] Output: Send store and product selection information

[0630] Specific operation: The user selects the store or product they are interested in from the list on the app's selection screen, presses the "Select" button, and sends the information to the server.

[0631] Step 4:

[0632] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[0633] Input: Store and product selection information

[0634] Output: Generate store visit plan

[0635] Specific operation: The server retrieves user information from the database and runs an algorithm to generate an optimal visit plan based on the entered store and product information.

[0636] Step 5:

[0637] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[0638] Input: Store and product information, user profile

[0639] Output: Send store visit plan

[0640] Specific operation: The generated visiting plan is sent to the user terminal and notified.

[0641] Step 6:

[0642] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions.

[0643] Input: User comments and feedback

[0644] Output: Analysis of the user's emotional state

[0645] Specific operation: The comments and feedback entered by users on the app are analyzed using text analysis and an emotion estimation algorithm is used to analyze emotions.

[0646] Step 7:

[0647] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[0648] Input: Sentiment analysis results

[0649] Output: Adjustment of plan or alternative proposals

[0650] Specific operation: The server receives the sentiment analysis results, dynamically adjusts the visit plan according to the user's satisfaction, and generates an alternative plan if necessary.

[0651] Step 8:

[0652] Device: The user launches the application and enables location while visiting the store.

[0653] Input: Current location request

[0654] Output: Send current location information

[0655] Specific operation: The user enables location services in the app, and the device obtains the current location using GPS and sends it to the server.

[0656] Step 9:

[0657] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[0658] Input: Current location

[0659] Output: Nearby stores and product information, crowd situation, sale information

[0660] Specific operation: Based on the current location information, the server searches a database of nearby stores and products, and obtains and provides the latest information on crowding and sales.

[0661] Step 10:

[0662] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[0663] Input: Real-time emotion data

[0664] Output: Adjusted visit plan

[0665] Specific operation: The obtained emotional data is analyzed, and if the user feels dissatisfied or tired, the plan is adjusted in real time, such as suggesting a new route or resting places.

[0666] Step 11:

[0667] Users: After completing their visit, they provide feedback about the stores they visited and the products they purchased.

[0668] Input: Feedback information

[0669] Output: Sending feedback information

[0670] Specific operation: The user enters their thoughts and ratings into the feedback form on the app and sends them to the server.

[0671] Step 12:

[0672] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[0673] Input: Feedback information

[0674] Output: Updated plan generation algorithm

[0675] Specific operation: The feedback data is analyzed and the algorithm parameters are adjusted to reflect the results in the next plan generation.

[0676] 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.

[0677] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0678] 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.

[0679] [Second embodiment]

[0680] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0681] 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.

[0682] 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).

[0683] 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.

[0684] 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.

[0685] 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).

[0686] 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.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0691] 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."

[0692] MODE FOR CARRYING OUT THE INVENTION

[0693] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[0694] System Overview

[0695] User Registration and Profiling

[0696] Device: The user installs the application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[0697] Server: Receives the input information and stores it in a database. It also obtains past travel history and rating information to generate a user profile.

[0698] Selecting a travel destination and registering interests

[0699] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[0700] Server: Receives the input travel destination and activity information, stores it in a database, and performs analysis to generate an appropriate travel plan based on it.

[0701] Generate and present a plan

[0702] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. At the same time, the server also references the user's past travel history and reviews to update the profile.

[0703] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0704] Real-time information provision

[0705] Terminal: The user launches the application while traveling.

[0706] Server: Obtains the user's current location in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[0707] Terminal: The user can adjust their plan based on the information provided.

[0708] Feedback and Improvements

[0709] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0710] Server: Receives and stores user feedback information, updates the travel plan generation algorithm based on this information, and reflects it in the next plan generation.

[0711] Specific examples

[0712] Example 1: A user plans a trip to Tokyo

[0713] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[0714] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[0715] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[0716] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[0717] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[0718] 6. User: Check the generated plan and start the trip.

[0719] 7. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[0720] 8. User: Enter feedback about the places and restaurants they visited.

[0721] 9. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[0722] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy travel plans that are flexible and respond in real time to their individual needs.

[0723] The processing flow will be explained below.

[0724] Step 1:

[0725] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[0726] Step 2:

[0727] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[0728] Step 3:

[0729] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[0730] Step 4:

[0731] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[0732] Step 5:

[0733] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[0734] Step 6:

[0735] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0736] Step 7:

[0737] Server: Sends the generated travel plan to the user terminal.

[0738] Step 8:

[0739] Terminal: The user opens the application and checks the presented travel plan.

[0740] Step 9:

[0741] Device: The user launches the application while traveling and enables location information.

[0742] Step 10:

[0743] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[0744] Step 11:

[0745] Terminal: The user checks the notified information and adjusts the plan.

[0746] Step 12:

[0747] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0748] Step 13:

[0749] Server: Receives user feedback information and stores it in a database.

[0750] Step 14:

[0751] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[0752] Step 15:

[0753] Server: The updated algorithm is reflected in the generation of the next travel plan.

[0754] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that meets their individual needs.

[0755] Example 1

[0756] 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."

[0757] Conventional travel planning systems have difficulty generating individually customized travel plans based on users' interests and budgets, and do not adequately utilize real-time information and feedback. This has led to a demand for improved flexibility and accuracy in travel planning.

[0758] 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.

[0759] In this invention, the server includes means for inputting a user's personal information and information on activities of interest at the travel destination, means for receiving the input information and storing it in a database, means for generating and analyzing a user profile based on the stored information, means for using a generative AI model to generate a travel plan based on the user's interests and budget, means for transmitting the generated travel plan to a user terminal, means for acquiring the user's location information and providing real-time information on nearby tourist spots and restaurants, means for acquiring real-time traffic and weather information, means for receiving, storing, and analyzing feedback information from the user, and means for updating the travel plan generation algorithm based on the analyzed feedback information and reflecting it in the generation of the next travel plan. This enables the provision of travel plans customized to the user's needs and improves the flexibility and accuracy of travel plans by utilizing real-time information.

[0760] "User's personal information" refers to information including the user's name, age, gender, hobbies, budget, etc.

[0761] "Interesting activity information at a travel destination" refers to information about activities and events in which a user is interested at a travel destination.

[0762] "Database" refers to a system for efficiently storing and managing user information and travel destination data.

[0763] A "user profile" is a personalized set of information generated based on a user's personal information and past travel history and rating information.

[0764] "Generative AI model" refers to an artificial intelligence model used to generate travel plans based on a user's interests and budget.

[0765] "User terminal" means an electronic device (e.g., a smartphone, tablet, or laptop) on which a user installs and operates an application.

[0766] "Location information" refers to information about a user's current geographical location obtained using technology such as GPS.

[0767] "Tourist spots" refer to tourist destinations and famous places that users want to visit.

[0768] "Restaurant information" refers to detailed information about restaurants, cafes, etc. that the user plans to visit.

[0769] "Traffic conditions" refers to information about the real-time operation status of roads and public transportation.

[0770] "Weather information" refers to information about real-time weather forecasts and weather conditions.

[0771] "Feedback information" refers to evaluations and opinions about the places and services visited that a user provides after a trip.

[0772] A "travel plan generation algorithm" is a calculation method or procedure for analyzing input data and generating the optimal travel plan for the user.

[0773] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[0774] System Overview

[0775] User Registration and Profiling

[0776] Device: The user installs the travel planning system application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[0777] Server: Receives the user's personal information and travel destination interest activity information and stores them in a database (e.g., MySQL or PostgreSQL). Then, retrieves past travel history and rating information and generates a user profile using a Python script. The user profile includes information on previously visited tourist spots and restaurants, rating points, etc.

[0778] Selecting a travel destination and registering interests

[0779] User: Enter travel destinations and activities they are interested in. For example, enter "Travel destination: Tokyo" or "Activity: Eating out."

[0780] Terminal: Transmits the entered travel destination and activity information to the server.

[0781] Server: Stores the received travel destination and activity information in a database, then analyzes it using a generative AI model (e.g., TensorFlow or PyTorch) to generate a travel plan based on the user's interests and budget.

[0782] Generate and present a plan

[0783] Server: Based on the user profile and the entered travel destination and activity information, the server analyzes the user's interests and budget and lists tourist spots and restaurants suitable for food tours. For example, the list includes "a long-established sushi restaurant in Ginza" and "a famous taiyaki shop in Asakusa."

[0784] Server: Based on the listed spots, the server generates an optimal travel schedule that takes into account travel time and rest times. This may involve using linear programming or genetic algorithms. The generated schedule includes specific timetables such as "10:00 AM: Taiyaki in Asakusa → 12:00 PM: Sushi lunch in Ginza."

[0785] Server: Sends the generated travel plan to the user terminal.

[0786] Terminal: The received travel plan is displayed on the user interface. The user can check the displayed plan and get ready to start the trip.

[0787] Real-time information provision

[0788] Device: During travel, the device uses GPS to obtain real-time information about the user's current location.

[0789] Server: Based on the user's current location, the server uses the Google Maps API to provide information on nearby tourist spots and restaurants. Additionally, the server uses the OpenWeatherMap API to provide real-time weather and traffic information.

[0790] Terminal: The information provided in real time is displayed on the user interface, allowing users to adjust their travel plans based on this information.

[0791] Feedback and Improvements

[0792] User: After the trip, the user enters feedback about the places and restaurants they visited into the device. For example, they send feedback such as, "I was very satisfied with the sushi restaurant in Ginza."

[0793] Terminal: Sends the input feedback information to the server.

[0794] Server: Stores the received feedback information in a database. Then, retrains the generative AI model (e.g., TensorFlow or PyTorch) based on the collected feedback data and updates the itinerary generation algorithm.

[0795] Specific examples

[0796] Example: A user plans a trip to Tokyo

[0797] 1. The user installs the app and enters their name, age, gender, hobby (eating out), and budget (50,000 yen).

[0798] 2. The server receives the information, stores it in a database, and updates the user profile based on past travel history and ratings.

[0799] 3. The user selects Tokyo as their travel destination and registers "food tours" as an activity of interest.

[0800] 4. The server analyzes the information and creates a list of popular food spots in Tokyo and restaurants that fit within your budget.

[0801] 5. The server generates a schedule based on the listed spots, taking into account travel time and break times, and sends it to the device.

[0802] 6. The user confirms the generated plan and starts the trip.

[0803] 7. While traveling, the device will obtain real-time location information via GPS and provide information on nearby tourist attractions, restaurants, traffic conditions and weather.

[0804] 8. Users can provide feedback about the places and restaurants they visit.

[0805] 9. The server receives and stores the feedback information, retrains the generative AI model, and updates the itinerary generation algorithm.

[0806] Prompt Sentence Examples

[0807] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[0808] In this way, the present invention allows users to enjoy optimal travel plans tailored to their individual interests and budgets, and further enhances the quality of the travel experience by providing real-time information and continuous improvements based on user feedback.

[0809] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0810] Processing Steps

[0811] Step 1:

[0812] A user installs a travel planning app on a device such as a smartphone and enters personal information such as name, age, gender, hobbies, and budget on the account creation screen. The data entered is name, age, gender, hobbies, and budget. The device converts this information into JSON format and sends it to the server.

[0813] Input: Name, age, gender, hobbies, budget

[0814] Data processing: Convert personal information into JSON format

[0815] Output: Personal information data in JSON format

[0816] Step 2:

[0817] The server receives the personal information entered and stores it in a database. After saving, it runs a Python script to retrieve relevant information from the database (such as past trip history and ratings) and update the user profile.

[0818] Input: Personal information data in JSON format

[0819] Data processing: saving to database, updating user profile

[0820] Output: Updated user profile

[0821] Step 3:

[0822] The user enters information about their travel destination and the activity they are interested in into the app. For example, they enter "Travel destination: Tokyo" and "Activity: Eating out." The entered data is then sent back to the server.

[0823] Input: Travel destination, activity

[0824] Data processing: Converting destination and activity information into JSON format

[0825] Output: Destination and activity information in JSON format

[0826] Step 4:

[0827] The server stores the received destination and activity information in a database, and then uses a generative AI model (e.g., TensorFlow or PyTorch) to generate a trip plan based on the destination and activity information.

[0828] Input: Destination and activity information in JSON format

[0829] Data processing: Saving to database, analyzing using AI model and generating plan

[0830] Output: A list of travel itinerary suggestions

[0831] Step 5:

[0832] The server generates an optimal travel schedule that takes into account travel time and rest times based on the list of tourist spots and restaurants, using linear programming and genetic algorithms.

[0833] Input: Travel plan candidate list, user profile

[0834] Data processing: Execution of schedule generation algorithm

[0835] Output: Generated travel schedule

[0836] Step 6:

[0837] The server sends the generated travel schedule to the user's device. The data is converted to JSON format again.

[0838] Input: Generated travel schedule

[0839] Data processing: Conversion to JSON format

[0840] Output: JSON formatted travel schedule data

[0841] Step 7:

[0842] The terminal displays the received travel schedule on the user interface, and the user can review the displayed plan and make adjustments as necessary.

[0843] Input: JSON formatted travel schedule data

[0844] Data processing: Display on the user interface

[0845] Output: Final travel schedule

[0846] Step 8:

[0847] The user uses the device while traveling and obtains current location information in real time using the GPS function.

[0848] Input: Real-time location information

[0849] Data processing: GPS data collection

[0850] Output: Real-time location information

[0851] Step 9:

[0852] The server calls the Google Maps API to provide information about nearby tourist spots and restaurants based on the user's current location, and also uses the OpenWeatherMap API to obtain current weather and traffic information.

[0853] Input: Real-time location information

[0854] Data processing: API calls and data acquisition

[0855] Output: Nearby tourist spots, restaurant information, weather information, traffic conditions

[0856] Step 10:

[0857] The device displays the data sent from the server in real time, allowing users to adjust their travel plans based on this information.

[0858] Input: Nearby tourist spots, restaurant information, weather information, traffic conditions

[0859] Data processing: Display on the user interface

[0860] Output: Real-time information visualization

[0861] Step 11:

[0862] After the trip, the user inputs feedback about the spots and restaurants they visited into the terminal, and the input feedback information is sent to the server.

[0863] Input: Feedback information

[0864] Data processing: Convert to JSON format and send to server

[0865] Output: Feedback information in JSON format

[0866] Step 12:

[0867] The server stores the received feedback information in a database and retrains the generative AI model, which then reflects the itinerary generation algorithm in the next itinerary.

[0868] Input: Feedback information in JSON format

[0869] Data processing: saving to database, retraining AI models

[0870] Output: Updated itinerary generation algorithm

[0871] Example prompt sentence:

[0872] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[0873] (Application example 1)

[0874] 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."

[0875] Conventional food delivery systems have difficulty providing optimal delivery plans that match users' individual preferences and budgets. Furthermore, due to a lack of real-time information, users tend to spend a lot of time selecting the right restaurant and food. Furthermore, there is a lack of systems that effectively utilize user feedback to improve the next recommendation. These issues need to be addressed.

[0876] 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.

[0877] In this invention, the server includes means for inputting information on a user's food delivery destinations and favorite dishes, means for receiving and storing the input information, means for analyzing the stored information and generating a delivery plan based on the user's interests and budget, means for transmitting the generated delivery plan to a user terminal, means for acquiring the user's current location information and providing information on nearby restaurants and dishes in real time, means for receiving and analyzing feedback information from the user, and means for updating the delivery plan generation algorithm based on the analyzed feedback information. This makes it possible to provide an optimal delivery plan suited to each user's preferences and budget, and further enables the system's functions to be continuously improved through the provision of information and feedback in real time.

[0878] "Means for inputting user's food delivery destination and preferred dish information" refers to a user interface for inputting data such as the user's designated delivery location, preferred dish types, and allergy information through the application.

[0879] The "means for receiving and storing the input information" refers to a module for receiving data input by a user on the server side and recording it in a storage device such as a database.

[0880] "Means for analyzing the stored information and generating a delivery plan based on the user's interests and budget" refers to an algorithm that uses the stored data to create an optimal delivery plan based on the user's tastes, preferences, and budget.

[0881] "Means for transmitting the generated delivery plan to a user terminal" refers to a communication module for transmitting the generated delivery plan to a user device such as a smartphone or tablet.

[0882] "Means for obtaining the user's current location information and providing real-time information about nearby restaurants and cuisines" refers to a module that uses GPS, beacons, etc. to identify the user's current location and provides real-time information about nearby restaurants and cuisines based on that location.

[0883] "Means for receiving and analyzing feedback information from the user" refers to a function for receiving feedback data such as ratings and comments provided by the user, analyzing it, and improving the content of the next proposal.

[0884] "Means for updating the delivery plan generation algorithm based on the analyzed feedback information" refers to a function within the system for improving and updating the algorithm used to generate future delivery plans based on analyzed feedback data.

[0885] This invention relates to a system that provides optimal food delivery plans based on a user's individual preferences and budget. The system provides appropriate information in real time by linking user terminals and a server, enabling efficient, high-quality delivery services.

[0886] System Configuration

[0887] The system consists of the following elements:

[0888] 1. User Device

[0889] A smartphone or tablet is used as a user terminal, through which the user provides input data and receives information in real time.

[0890] 2. Server

[0891] The server acts as the backend for the application, generating user profiles, creating delivery plans, and providing real-time information. The server is built using Python / Django or Node.js / Express, and uses PostgreSQL or MongoDB as the database.

[0892] User Registration and Profiling

[0893] The server stores user information (e.g., name, age, favorite dishes, allergies, budget) received from the user's device in a database. This information, along with past order history and rating information, is analyzed to create a profile for each user. This profile is used when creating future delivery plans.

[0894] Restaurant and menu selection

[0895] The server lists appropriate restaurants and menus based on the type of meal and budget specified by the user, using specific algorithms (e.g., random forest or k-means clustering) to match the user's profile data and suggest the best options.

[0896] Generate and present a delivery plan

[0897] The generated delivery plan is optimized to take into account breaks and waiting times. Details of the specific restaurant, food, expected arrival time, and price are sent to the user's device. The user can then review the plan and order the selected menu.

[0898] Real-time information provision

[0899] The server uses GPS and beacons to obtain the user's current location in real time and immediately provides information about nearby restaurants and the dishes currently being served, as well as information about waiting times and estimated delivery times.

[0900] Feedback and Improvements

[0901] After the delivery is completed, the user provides feedback, which is sent to the server and stored. This data is reflected in the next delivery plan generation, improving the accuracy of the algorithm.

[0902] Specific examples

[0903] Example 1: User A orders sushi

[0904] User A installed the app, selected sushi as his / her favorite dish, and set his / her budget to 5,000 yen. User A was then suggested highly rated sushi restaurants based on his / her current location (e.g., within Tokyo). One example of a suggested plan included Sushi Restaurant B, which offers a sushi set (price: 3,000 yen). User A ordered sushi based on this suggestion, and after receiving the delivery, provided feedback rating his / her satisfaction as 5 stars.

[0905] Prompt Sentence Examples

[0906] User Profile:

[0907] Name: User A

[0908] Favorite food: Sushi

[0909] Budget: 5,000 yen

[0910] Current location: Tokyo

[0911] Rating history: Sushi Restaurant B (5 stars)

[0912] Next, please suggest a restaurant and dish you would recommend.

[0913] This concludes the "Mode for Carrying Out the Invention." This allows users to easily obtain delivery plans that suit their individual needs, and the system is continually improved based on feedback.

[0914] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0915] Step 1:

[0916] Users start the smartphone app and enter personal information such as their name, age, favorite dishes, allergies, budget, etc. on the account creation screen. The entered information is sent from the device to the server.

[0917] input:

[0918] Personal information such as name, age, favorite dishes, allergy information, budget, etc.

[0919] output:

[0920] User information sent to the server

[0921] Step 2:

[0922] The server stores the received user information in a database, which is then analyzed along with past order history and rating information to create a user profile.

[0923] input:

[0924] User information sent

[0925] output:

[0926] User profiles stored in a database

[0927] Operation:

[0928] The server analyzes the received data and generates a profile

[0929] Step 3:

[0930] The user selects a restaurant and menu based on the type of food they want to eat and their budget. The information entered into the terminal is sent to the server.

[0931] input:

[0932] What type of food do you want to eat and your budget?

[0933] output:

[0934] Cuisine and budget information sent to the server

[0935] Step 4:

[0936] The server lists suitable restaurants and menus based on the type of cuisine and budget entered by the user, matches it with the stored profile data, and suggests the best options using algorithms (e.g., random forest, k-means clustering).

[0937] input:

[0938] User profile, cuisine type, budget

[0939] output:

[0940] A list of restaurants and menus suggested to the user

[0941] Operation:

[0942] The server analyzes the profile data and applies algorithms to generate a list of suggestions

[0943] Step 5:

[0944] The generated delivery plan is sent to the user's terminal, where the user can confirm the proposed plan and order the selected menu.

[0945] input:

[0946] List of suggested restaurants and menus

[0947] output:

[0948] Delivery plan displayed on the user's device

[0949] Step 6:

[0950] The server uses GPS and beacons to obtain the user's current location in real time, and provides information about nearby restaurants and the dishes currently being served based on that location, as well as notifying the user of waiting times and estimated delivery times.

[0951] input:

[0952] User's current location

[0953] output:

[0954] Nearby restaurants and food information, waiting times, and estimated delivery times

[0955] Operation:

[0956] The server analyzes the location information and acquires and displays real-time data.

[0957] Step 7:

[0958] After receiving their delivery, users can enter their feedback on the food and service into the app, which then sends the feedback information from their device to the server.

[0959] input:

[0960] User feedback information (e.g., ratings, comments)

[0961] output:

[0962] Feedback information sent to the server

[0963] Step 8:

[0964] The server stores the feedback information received from users in a database and analyzes it. Based on the results of this analysis, it updates the algorithm for generating the next delivery plan and improves the system to make more appropriate proposals.

[0965] input:

[0966] User feedback information

[0967] output:

[0968] Next delivery plan with updated algorithm

[0969] Operation:

[0970] The server analyzes the feedback and updates the algorithm

[0971] The above are the specific processing steps of the system that realizes the application example based on the claims.

[0972] 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.

[0973] MODE FOR CARRYING OUT THE INVENTION

[0974] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[0975] System Overview

[0976] User Registration and Profiling

[0977] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[0978] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[0979] Selecting a travel destination and registering interests

[0980] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[0981] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[0982] Generate and present a plan

[0983] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. Updates the user's profile based on the user's past travel history and rating information.

[0984] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[0985] Emotion Engine Operation

[0986] On-device: While a user is using an application, the emotion engine analyzes emotions based on the user's input and actions. For example, it determines emotions from the language and expressions used when a user enters comments or feedback.

[0987] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user has a low preference for the plan, it presents an alternative plan.

[0988] Real-time information provision

[0989] Device: The user launches the application while traveling and enables location information.

[0990] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[0991] Terminal: Monitors the user's emotional state in real time and dynamically adjusts the travel plan according to the user's emotions.

[0992] Feedback and Improvements

[0993] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[0994] Server: Receives user feedback information and stores it in a database. Based on this, the travel plan generation algorithm is updated and reflected in the next plan generation.

[0995] Server: The server also analyzes feedback from the emotion engine and improves the plan generation algorithm by taking the user's emotions into account.

[0996] Specific examples

[0997] Example 1: A user plans a trip to Tokyo

[0998] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[0999] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[1000] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[1001] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[1002] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[1003] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[1004] 7. User: Check the generated plan and start the trip.

[1005] 8. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[1006] 9. Terminal: The emotion engine also monitors the user’s emotional state in real time and adjusts the plan when the user feels dissatisfied or tired.

[1007] 10. User: Enter feedback about the places and restaurants they visited.

[1008] 11. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[1009] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy flexible and real-time travel plans that meet their individual needs and emotions.

[1010] The processing flow will be explained below.

[1011] Step 1:

[1012] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[1013] Step 2:

[1014] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[1015] Step 3:

[1016] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[1017] Step 4:

[1018] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[1019] Step 5:

[1020] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[1021] Step 6:

[1022] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[1023] Step 7:

[1024] Server: Sends the generated travel plan to the user terminal.

[1025] Step 8:

[1026] Terminal: The user opens the application and checks the presented travel plan.

[1027] Step 9:

[1028] Device: The user launches the application while traveling and enables location information.

[1029] Step 10:

[1030] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[1031] Step 11:

[1032] Terminal: The user checks the notified information and adjusts the plan.

[1033] Step 12:

[1034] On-device: During the journey, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments and feedback.

[1035] Step 13:

[1036] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user's emotion is negative, it presents an alternative plan.

[1037] Step 14:

[1038] Device: Monitors the user's emotional state in real time and adjusts the plan if the user feels frustrated or fatigued.

[1039] Step 15:

[1040] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[1041] Step 16:

[1042] Server: Receives user feedback information and stores it in a database.

[1043] Step 17:

[1044] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[1045] Step 18:

[1046] Server: The updated algorithm is reflected in the generation of the next travel plan.

[1047] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that is tailored to their individual needs and emotions.

[1048] Example 2

[1049] 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."

[1050] Conventional travel planning systems have difficulty providing flexible and real-time travel plans that meet diverse user needs, and lack a means to effectively reflect user emotions and feedback.

[1051] 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.

[1052] In this invention, the server includes: means for a user to register account information; means for receiving the registered information and saving it in a database; means for inputting information about the user's travel destinations and activities of interest; means for receiving and saving the input information; means for analyzing the saved information and generating an itinerary based on the user's interests and budget; means for transmitting the generated itinerary to a user terminal; means for acquiring the user's current location information and providing real-time information about nearby tourist spots and restaurants; means including a sentiment analysis engine for acquiring feedback information; means for receiving and analyzing the feedback information and sentiment analysis results from the user; and means for updating the itinerary generation algorithm based on the analyzed feedback information. This enables the provision of flexible, real-time itineraries that reflect the diverse needs and emotions of users.

[1053] "Account information" refers to basic data required when using the system, such as the user's name, age, gender, hobbies, and budget.

[1054] A "database" is a system for efficiently storing, retrieving, and managing information, and is usually built on a server.

[1055] "Destination" refers to a geographical destination that a user wishes to visit.

[1056] "Activity information" is information about specific activities such as sightseeing, shopping, and dining that interest the user.

[1057] "Analysis" is the act of investigating and analyzing input data in detail to extract meaning and patterns.

[1058] A "travel plan" refers to a plan that combines places to visit, activities, a schedule, etc. based on the user's needs and interests.

[1059] A "user terminal" is a device that is directly operated by a user, and includes a smartphone, tablet, etc.

[1060] "Current location information" is geographic coordinate data of the user's current location, obtained from a device such as the user's smartphone.

[1061] A "tourist attraction" is a specific tourist destination that travelers want to visit.

[1062] "Eating and drinking establishment information" is information about establishments that provide meals, such as restaurants and cafes.

[1063] "Feedback" refers to information such as impressions, evaluations, and opinions that a user provides to the system during or after a trip.

[1064] An "emotion analysis engine" is a software component that determines a user's emotional state based on their input and behavior.

[1065] An "algorithm" refers to a set of steps or a computational method for solving a particular problem.

[1066] MODE FOR CARRYING OUT THE INVENTION

[1067] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1068] System Overview

[1069] The system uses the following hardware and software:

[1070] Server hardware: General-purpose servers or cloud servers

[1071] Device hardware: smartphones, tablets

[1072] Server software: Django, Node.js, MySQL, PostgreSQL, Elasticsearch, GraphQL, Hugging Face Transformers, Google's BERT model

[1073] Device software: iOS app, Android app

[1074] API: HTTP, OpenWeatherMap API, Google Maps API

[1075] User Registration and Profiling

[1076] User: Download and install the application from the App Store or Google Play on their smartphone.

[1077] User: Enter information such as name, age, gender, hobbies, budget, etc. on the account registration screen. The UI is designed to be simple and intuitive.

[1078] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[1079] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[1080] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[1081] Selecting a travel destination and registering interests

[1082] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[1083] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[1084] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[1085] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[1086] Generate and present a plan

[1087] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[1088] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[1089] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[1090] Emotion Engine Operation

[1091] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[1092] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[1093] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[1094] Real-time information provision

[1095] User: Enable location services for the app.

[1096] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[1097] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[1098] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[1099] Feedback and Improvements

[1100] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[1101] Terminal: Sends feedback information to the server.

[1102] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[1103] Specific examples

[1104] Example 1: A user plans a trip to Tokyo

[1105] 1. User: Install the app and enter their name, age, gender, hobby (eating out), and budget (50,000 yen).

[1106] 2. Terminal: Sends the entered information to the server.

[1107] 3. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[1108] 4. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[1109] 5. Terminal: Sends the entered information to the server.

[1110] 6. Server: Analyzes the information and creates a list of popular food spots in Tokyo and restaurants that are within your budget.

[1111] 7. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times, and sent to the device.

[1112] 8. Device: Display the received plan and analyze user comments and feedback through the sentiment engine. Adjust the plan as needed.

[1113] 9. User: Check the generated plan and start the trip.

[1114] 10. Device: Obtains real-time location information while traveling and displays nearby tourist attractions, restaurant information, traffic conditions, and weather information.

[1115] 11. Terminal: Monitors the user’s emotional state in real time and adjusts the plan as needed.

[1116] 12. User: Enter feedback about the places and restaurants visited after the trip.

[1117] 13. Device: Sends feedback to the server.

[1118] 14. Server: Receives and stores feedback information and reflects it in the next plan generation.

[1119] Prompt Sentence Examples

[1120] If a user types into the system, "I'm planning a trip to Tokyo, can you recommend some highly rated restaurants?", the system will take into account the user's emotional state and interests and respond as follows:

[1121] "We'd like to recommend some highly rated restaurants: Sushi place ABC, Ramen place XYZ, and Okonomiyaki place DEF. We also have great lunch menus. Which one do you prefer?"

[1122]

[1123] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1124] Step 1:

[1125] User: Download and install the application from the App Store or Google Play on their smartphone.

[1126] Step 2:

[1127] User: Enter information such as name, age, gender, hobbies, and budget on the account registration screen.

[1128] Input: User's basic information (name, age, gender, hobbies, budget).

[1129] Output: The input information is stored in the terminal and prepared for the next transmission step.

[1130] Step 3:

[1131] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[1132] Input: User basic information.

[1133] Output: User information sent to the server is saved.

[1134] Step 4:

[1135] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[1136] Input: User information.

[1137] Output: User information stored in the database and a status code to the terminal.

[1138] Step 5:

[1139] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[1140] Input: User information stored in the database, past travel history, and rating information.

[1141] Output: The generated user profile.

[1142] Step 6:

[1143] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[1144] Input: Travel destination (destination).

[1145] Output: The travel destination selection screen displayed.

[1146] Step 7:

[1147] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[1148] Input: Activities of interest.

[1149] Output: Selected activity information.

[1150] Step 8:

[1151] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[1152] Input: Travel destination, activity information of interest.

[1153] Output: Destination and activity information sent to the server.

[1154] Step 9:

[1155] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[1156] Input: Travel destination, activity information.

[1157] Output: Retrieved tourist spot and restaurant information.

[1158] Step 10:

[1159] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[1160] Input: User profile, travel destinations, and activity information.

[1161] Output: A list of tourist attractions and restaurants.

[1162] Step 11:

[1163] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[1164] Input: List of spots and restaurants, detailed information for each spot and restaurant.

[1165] Output: The generated travel schedule.

[1166] Step 12:

[1167] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[1168] Input: Travel schedule sent from the server.

[1169] Output: The schedule displayed in the user interface.

[1170] Step 13:

[1171] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[1172] Input: User feedback (comments and ratings).

[1173] Output: Feedback ready to send.

[1174] Step 14:

[1175] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[1176] Input: User feedback.

[1177] Output: Feedback sent to the emotion engine.

[1178] Step 15:

[1179] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[1180] Input: Analysis results from the emotion engine.

[1181] Output: Adjusted itinerary.

[1182] Step 16:

[1183] User: Enable location services for the app.

[1184] Enter: Enable location services.

[1185] Output: Enabled location services.

[1186] Step 17:

[1187] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[1188] Input: Current location information.

[1189] Output: The location information sent to the server.

[1190] Step 18:

[1191] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[1192] Input: Current location information.

[1193] Output: Provided real-time tourist attractions, restaurants, traffic and weather information.

[1194] Step 19:

[1195] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[1196] Input: The user's emotional state.

[1197] Output: Adjusted itinerary.

[1198] Step 20:

[1199] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[1200] Input: Feedback after the trip (impressions and ratings).

[1201] Output: Feedback ready to be sent.

[1202] Step 21:

[1203] Terminal: Sends feedback information to the server.

[1204] Input: Feedback information.

[1205] Output: Feedback information sent to the server.

[1206] Step 22:

[1207] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[1208] Input: Feedback information.

[1209] Output: An improved trip plan generation algorithm.

[1210] (Application example 2)

[1211] 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."

[1212] In conventional store visits and product selection, users face the challenge of efficiently finding the right store and product that matches their interests and budget. Furthermore, the provision of real-time store information and products is insufficient, and dynamic plan adjustments that take user emotions into account are not possible, resulting in an underoptimized user experience.

[1213] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about stores and products of interest to the user; means for receiving and saving the input information; means for analyzing the saved information and generating a store visit plan based on the user's interests and budget; means for transmitting the generated store visit plan to the user terminal; means for acquiring information about the user's current location and providing information about surrounding stores and products in real time; means for receiving and analyzing feedback information from the user; means for updating the store visit plan generation algorithm based on the analyzed feedback information; means for analyzing emotions from the user's input and behavior using an emotion engine; and means for dynamically adjusting the store visit plan in real time based on the analyzed emotion information. This allows the user to obtain an optimal store visit plan that suits their interests and budget, and the provision of information in real time and the dynamic adjustment of the plan based on emotions enable a more fulfilling store visit experience.

[1214] A "user" is an individual who installs the application, inputs information, and uses the store visit plan.

[1215] A "store" refers to a physical location that a user visits and that offers products or services of interest.

[1216] "Products" are goods and services offered at stores that are of interest to users.

[1217] "Information" refers to data entered by the user, including name, age, gender, hobbies, budget, stores and products of interest, etc.

[1218] A "plan" is a proposal of stores to visit and products to purchase, generated based on the user's interests and budget.

[1219] A "server" is a computer system that receives, stores, and analyzes information input by a user.

[1220] A "terminal" is a portable information processing terminal such as a mobile phone or smartphone used by a user.

[1221] "Feedback" refers to user impressions and evaluations of stores visited or products purchased.

[1222] An "emotion engine" is a software mechanism for analyzing emotions from user input and behavior.

[1223] "Real-time information provision" means providing the latest information about nearby stores and products immediately based on the user's current location information.

[1224] MODE FOR CARRYING OUT THE INVENTION

[1225] System Overview

[1226] This invention is a system for optimizing a user's store visit experience, and in particular, relates to an application that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1227] User Registration and Profiling

[1228] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[1229] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[1230] Store and product selection and interest registration

[1231] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[1232] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[1233] Generate and present a plan

[1234] Server: Analyzes the above information and lists stores and products that match the user's interests and budget. Updates the user's profile based on the user's past store visit history and rating information.

[1235] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[1236] Emotion Engine Operation

[1237] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments or feedback.

[1238] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[1239] Real-time information provision

[1240] Device: The user launches the application and enables location while visiting the store.

[1241] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[1242] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[1243] Feedback and Improvements

[1244] Terminal: After the user has finished their visit, they enter feedback about the stores they visited and the products they purchased.

[1245] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[1246] Specific examples

[1247] Example: When a user visits a shopping mall

[1248] 1. User: Installs the app and enters their name, age, gender, hobby (fashion), and budget (30,000 yen).

[1249] 2. Server: Receives the information, stores it in a database, and updates the user profile based on past visits and reviews.

[1250] 3. User: Selects a specific shopping mall to visit and registers products (fashion items) that interest him / her.

[1251] 4. Server: Analyzes the entered information and lists recommended stores based on the user's interests and products that can be purchased within their budget.

[1252] 5. Server: Based on the listed stores and products, the server generates a plan that takes into account the route between stores and the length of stay, and sends it to the user's device.

[1253] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[1254] 7. User: Review the generated plan and start shopping.

[1255] 8. Device: While shopping, the device obtains your current location in real time and displays information about nearby stores and products. It also displays information about the store's congestion status and sales.

[1256] 9. Terminal: The emotion engine monitors the user's emotional state in real time and adjusts the plan when the user feels frustrated or fatigued.

[1257] 10. Users: Enter feedback about the stores they visit and the products they buy.

[1258] 11. Server: Receives feedback information, stores it in a database, and updates the algorithm based on it to generate the next plan.

[1259] Examples of prompt statements

[1260] Below are some example prompts for generative AI models:

[1261] Example prompt:

[1262] "Write code to implement a user registration feature for a mobile app. Implement an API endpoint on a Flask server that receives the following data and stores it in an SQLite database: Name, Age, Gender, Hobbies, Budget."

[1263] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1264] Step 1:

[1265] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[1266] Input: User information (name, age, gender, hobbies, budget)

[1267] Output: Send user registration information

[1268] Specific operation: When the user enters information into the application's input fields and presses the "Register" button, this information is sent to the server.

[1269] Step 2:

[1270] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[1271] Input: User registration information

[1272] Output: Updated user profile

[1273] Specific operation: The server connects to the database, saves the received user information, and compares it with past store visit history and evaluation information to update and generate a profile.

[1274] Step 3:

[1275] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[1276] Input: Store and product information

[1277] Output: Send store and product selection information

[1278] Specific operation: The user selects the store or product they are interested in from the list on the app's selection screen, presses the "Select" button, and sends the information to the server.

[1279] Step 4:

[1280] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[1281] Input: Store and product selection information

[1282] Output: Generate store visit plan

[1283] Specific operation: The server retrieves user information from the database and runs an algorithm to generate an optimal visit plan based on the entered store and product information.

[1284] Step 5:

[1285] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[1286] Input: Store and product information, user profile

[1287] Output: Send store visit plan

[1288] Specific operation: The generated visiting plan is sent to the user terminal and notified.

[1289] Step 6:

[1290] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions.

[1291] Input: User comments and feedback

[1292] Output: Analysis of the user's emotional state

[1293] Specific operation: The comments and feedback entered by users on the app are analyzed using text analysis and an emotion estimation algorithm is used to analyze emotions.

[1294] Step 7:

[1295] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[1296] Input: Sentiment analysis results

[1297] Output: Adjustment of plan or alternative proposals

[1298] Specific operation: The server receives the sentiment analysis results, dynamically adjusts the visit plan according to the user's satisfaction, and generates an alternative plan if necessary.

[1299] Step 8:

[1300] Device: The user launches the application and enables location while visiting the store.

[1301] Input: Current location request

[1302] Output: Send current location information

[1303] Specific operation: The user enables location services in the app, and the device obtains the current location using GPS and sends it to the server.

[1304] Step 9:

[1305] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[1306] Input: Current location

[1307] Output: Nearby stores and product information, crowd situation, sale information

[1308] Specific operation: Based on the current location information, the server searches a database of nearby stores and products, and obtains and provides the latest information on crowding and sales.

[1309] Step 10:

[1310] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[1311] Input: Real-time emotion data

[1312] Output: Adjusted visit plan

[1313] Specific operation: The obtained emotional data is analyzed, and if the user feels dissatisfied or tired, the plan is adjusted in real time, such as suggesting a new route or resting places.

[1314] Step 11:

[1315] Users: After completing their visit, they provide feedback about the stores they visited and the products they purchased.

[1316] Input: Feedback information

[1317] Output: Sending feedback information

[1318] Specific operation: The user enters their thoughts and ratings into the feedback form on the app and sends them to the server.

[1319] Step 12:

[1320] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[1321] Input: Feedback information

[1322] Output: Updated plan generation algorithm

[1323] Specific operation: The feedback data is analyzed and the algorithm parameters are adjusted to reflect the results in the next plan generation.

[1324] 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.

[1325] 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.

[1326] 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.

[1327] [Third embodiment]

[1328] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1329] 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.

[1330] 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).

[1331] 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.

[1332] 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.

[1333] 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).

[1334] 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.

[1335] 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.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] 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."

[1340] MODE FOR CARRYING OUT THE INVENTION

[1341] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[1342] System Overview

[1343] User Registration and Profiling

[1344] Device: The user installs the application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[1345] Server: Receives the input information and stores it in a database. It also obtains past travel history and rating information to generate a user profile.

[1346] Selecting a travel destination and registering interests

[1347] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[1348] Server: Receives the input travel destination and activity information, stores it in a database, and performs analysis to generate an appropriate travel plan based on it.

[1349] Generate and present a plan

[1350] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. At the same time, the server also references the user's past travel history and reviews to update the profile.

[1351] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[1352] Real-time information provision

[1353] Terminal: The user launches the application while traveling.

[1354] Server: Obtains the user's current location in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[1355] Terminal: The user can adjust their plan based on the information provided.

[1356] Feedback and Improvements

[1357] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[1358] Server: Receives and stores user feedback information, updates the travel plan generation algorithm based on this information, and reflects it in the next plan generation.

[1359] Specific examples

[1360] Example 1: A user plans a trip to Tokyo

[1361] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[1362] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[1363] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[1364] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[1365] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[1366] 6. User: Check the generated plan and start the trip.

[1367] 7. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[1368] 8. User: Enter feedback about the places and restaurants they visited.

[1369] 9. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[1370] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy travel plans that are flexible and respond in real time to their individual needs.

[1371] The processing flow will be explained below.

[1372] Step 1:

[1373] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[1374] Step 2:

[1375] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[1376] Step 3:

[1377] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[1378] Step 4:

[1379] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[1380] Step 5:

[1381] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[1382] Step 6:

[1383] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[1384] Step 7:

[1385] Server: Sends the generated travel plan to the user terminal.

[1386] Step 8:

[1387] Terminal: The user opens the application and checks the presented travel plan.

[1388] Step 9:

[1389] Device: The user launches the application while traveling and enables location information.

[1390] Step 10:

[1391] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[1392] Step 11:

[1393] Terminal: The user checks the notified information and adjusts the plan.

[1394] Step 12:

[1395] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[1396] Step 13:

[1397] Server: Receives user feedback information and stores it in a database.

[1398] Step 14:

[1399] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[1400] Step 15:

[1401] Server: The updated algorithm is reflected in the generation of the next travel plan.

[1402] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that meets their individual needs.

[1403] Example 1

[1404] 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."

[1405] Conventional travel planning systems have difficulty generating individually customized travel plans based on users' interests and budgets, and do not adequately utilize real-time information and feedback. This has led to a demand for improved flexibility and accuracy in travel planning.

[1406] 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.

[1407] In this invention, the server includes means for inputting a user's personal information and information on activities of interest at the travel destination, means for receiving the input information and storing it in a database, means for generating and analyzing a user profile based on the stored information, means for using a generative AI model to generate a travel plan based on the user's interests and budget, means for transmitting the generated travel plan to a user terminal, means for acquiring the user's location information and providing real-time information on nearby tourist spots and restaurants, means for acquiring real-time traffic and weather information, means for receiving, storing, and analyzing feedback information from the user, and means for updating the travel plan generation algorithm based on the analyzed feedback information and reflecting it in the generation of the next travel plan. This enables the provision of travel plans customized to the user's needs and improves the flexibility and accuracy of travel plans by utilizing real-time information.

[1408] "User's personal information" refers to information including the user's name, age, gender, hobbies, budget, etc.

[1409] "Interesting activity information at a travel destination" refers to information about activities and events in which a user is interested at a travel destination.

[1410] "Database" refers to a system for efficiently storing and managing user information and travel destination data.

[1411] A "user profile" is a personalized set of information generated based on a user's personal information and past travel history and rating information.

[1412] "Generative AI model" refers to an artificial intelligence model used to generate travel plans based on a user's interests and budget.

[1413] "User terminal" means an electronic device (e.g., a smartphone, tablet, or laptop) on which a user installs and operates an application.

[1414] "Location information" refers to information about a user's current geographical location obtained using technology such as GPS.

[1415] "Tourist spots" refer to tourist destinations and famous places that users want to visit.

[1416] "Restaurant information" refers to detailed information about restaurants, cafes, etc. that the user plans to visit.

[1417] "Traffic conditions" refers to information about the real-time operation status of roads and public transportation.

[1418] "Weather information" refers to information about real-time weather forecasts and weather conditions.

[1419] "Feedback information" refers to evaluations and opinions about the places and services visited that a user provides after a trip.

[1420] A "travel plan generation algorithm" is a calculation method or procedure for analyzing input data and generating the optimal travel plan for the user.

[1421] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[1422] System Overview

[1423] User Registration and Profiling

[1424] Device: The user installs the travel planning system application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[1425] Server: Receives the user's personal information and travel destination interest activity information and stores them in a database (e.g., MySQL or PostgreSQL). Then, retrieves past travel history and rating information and generates a user profile using a Python script. The user profile includes information on previously visited tourist spots and restaurants, rating points, etc.

[1426] Selecting a travel destination and registering interests

[1427] User: Enter travel destinations and activities they are interested in. For example, enter "Travel destination: Tokyo" or "Activity: Eating out."

[1428] Terminal: Transmits the entered travel destination and activity information to the server.

[1429] Server: Stores the received travel destination and activity information in a database, then analyzes it using a generative AI model (e.g., TensorFlow or PyTorch) to generate a travel plan based on the user's interests and budget.

[1430] Generate and present a plan

[1431] Server: Based on the user profile and the entered travel destination and activity information, the server analyzes the user's interests and budget and lists tourist spots and restaurants suitable for food tours. For example, the list includes "a long-established sushi restaurant in Ginza" and "a famous taiyaki shop in Asakusa."

[1432] Server: Based on the listed spots, the server generates an optimal travel schedule that takes into account travel time and rest times. This may involve using linear programming or genetic algorithms. The generated schedule includes specific timetables such as "10:00 AM: Taiyaki in Asakusa → 12:00 PM: Sushi lunch in Ginza."

[1433] Server: Sends the generated travel plan to the user terminal.

[1434] Terminal: The received travel plan is displayed on the user interface. The user can check the displayed plan and get ready to start the trip.

[1435] Real-time information provision

[1436] Device: During travel, the device uses GPS to obtain real-time information about the user's current location.

[1437] Server: Based on the user's current location, the server uses the Google Maps API to provide information on nearby tourist spots and restaurants. Additionally, the server uses the OpenWeatherMap API to provide real-time weather and traffic information.

[1438] Terminal: The information provided in real time is displayed on the user interface, allowing users to adjust their travel plans based on this information.

[1439] Feedback and Improvements

[1440] User: After the trip, the user enters feedback about the places and restaurants they visited into the device. For example, they send feedback such as, "I was very satisfied with the sushi restaurant in Ginza."

[1441] Terminal: Sends the input feedback information to the server.

[1442] Server: Stores the received feedback information in a database. Then, retrains the generative AI model (e.g., TensorFlow or PyTorch) based on the collected feedback data and updates the itinerary generation algorithm.

[1443] Specific examples

[1444] Example: A user plans a trip to Tokyo

[1445] 1. The user installs the app and enters their name, age, gender, hobby (eating out), and budget (50,000 yen).

[1446] 2. The server receives the information, stores it in a database, and updates the user profile based on past travel history and ratings.

[1447] 3. The user selects Tokyo as their travel destination and registers "food tours" as an activity of interest.

[1448] 4. The server analyzes the information and creates a list of popular food spots in Tokyo and restaurants that fit within your budget.

[1449] 5. The server generates a schedule based on the listed spots, taking into account travel time and break times, and sends it to the device.

[1450] 6. The user confirms the generated plan and starts the trip.

[1451] 7. While traveling, the device will obtain real-time location information via GPS and provide information on nearby tourist attractions, restaurants, traffic conditions and weather.

[1452] 8. Users can provide feedback about the places and restaurants they visit.

[1453] 9. The server receives and stores the feedback information, retrains the generative AI model, and updates the itinerary generation algorithm.

[1454] Prompt Sentence Examples

[1455] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[1456] In this way, the present invention allows users to enjoy optimal travel plans tailored to their individual interests and budgets, and further enhances the quality of the travel experience by providing real-time information and continuous improvements based on user feedback.

[1457] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1458] Processing Steps

[1459] Step 1:

[1460] A user installs a travel planning app on a device such as a smartphone and enters personal information such as name, age, gender, hobbies, and budget on the account creation screen. The data entered is name, age, gender, hobbies, and budget. The device converts this information into JSON format and sends it to the server.

[1461] Input: Name, age, gender, hobbies, budget

[1462] Data processing: Convert personal information into JSON format

[1463] Output: Personal information data in JSON format

[1464] Step 2:

[1465] The server receives the personal information entered and stores it in a database. After saving, it runs a Python script to retrieve relevant information from the database (such as past trip history and ratings) and update the user profile.

[1466] Input: Personal information data in JSON format

[1467] Data processing: saving to database, updating user profile

[1468] Output: Updated user profile

[1469] Step 3:

[1470] The user enters information about their travel destination and the activity they are interested in into the app. For example, they enter "Travel destination: Tokyo" and "Activity: Eating out." The entered data is then sent back to the server.

[1471] Input: Travel destination, activity

[1472] Data processing: Converting destination and activity information into JSON format

[1473] Output: Destination and activity information in JSON format

[1474] Step 4:

[1475] The server stores the received destination and activity information in a database, and then uses a generative AI model (e.g., TensorFlow or PyTorch) to generate a trip plan based on the destination and activity information.

[1476] Input: Destination and activity information in JSON format

[1477] Data processing: Saving to database, analyzing using AI model and generating plan

[1478] Output: A list of travel itinerary suggestions

[1479] Step 5:

[1480] The server generates an optimal travel schedule that takes into account travel time and rest times based on the list of tourist spots and restaurants, using linear programming and genetic algorithms.

[1481] Input: Travel plan candidate list, user profile

[1482] Data processing: Execution of schedule generation algorithm

[1483] Output: Generated travel schedule

[1484] Step 6:

[1485] The server sends the generated travel schedule to the user's device. The data is converted to JSON format again.

[1486] Input: Generated travel schedule

[1487] Data processing: Conversion to JSON format

[1488] Output: JSON formatted travel schedule data

[1489] Step 7:

[1490] The terminal displays the received travel schedule on the user interface, and the user can review the displayed plan and make adjustments as necessary.

[1491] Input: JSON formatted travel schedule data

[1492] Data processing: Display on the user interface

[1493] Output: Final travel schedule

[1494] Step 8:

[1495] The user uses the device while traveling and obtains current location information in real time using the GPS function.

[1496] Input: Real-time location information

[1497] Data processing: GPS data collection

[1498] Output: Real-time location information

[1499] Step 9:

[1500] The server calls the Google Maps API to provide information about nearby tourist spots and restaurants based on the user's current location, and also uses the OpenWeatherMap API to obtain current weather and traffic information.

[1501] Input: Real-time location information

[1502] Data processing: API calls and data acquisition

[1503] Output: Nearby tourist spots, restaurant information, weather information, traffic conditions

[1504] Step 10:

[1505] The device displays the data sent from the server in real time, allowing users to adjust their travel plans based on this information.

[1506] Input: Nearby tourist spots, restaurant information, weather information, traffic conditions

[1507] Data processing: Display on the user interface

[1508] Output: Real-time information visualization

[1509] Step 11:

[1510] After the trip, the user inputs feedback about the spots and restaurants they visited into the terminal, and the input feedback information is sent to the server.

[1511] Input: Feedback information

[1512] Data processing: Convert to JSON format and send to server

[1513] Output: Feedback information in JSON format

[1514] Step 12:

[1515] The server stores the received feedback information in a database and retrains the generative AI model, which then reflects the itinerary generation algorithm in the next itinerary.

[1516] Input: Feedback information in JSON format

[1517] Data processing: saving to database, retraining AI models

[1518] Output: Updated itinerary generation algorithm

[1519] Example prompt sentence:

[1520] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[1521] (Application example 1)

[1522] 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."

[1523] Conventional food delivery systems have difficulty providing optimal delivery plans that match users' individual preferences and budgets. Furthermore, due to a lack of real-time information, users tend to spend a lot of time selecting the right restaurant and food. Furthermore, there is a lack of systems that effectively utilize user feedback to improve the next recommendation. These issues need to be addressed.

[1524] 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.

[1525] In this invention, the server includes means for inputting information on a user's food delivery destinations and favorite dishes, means for receiving and storing the input information, means for analyzing the stored information and generating a delivery plan based on the user's interests and budget, means for transmitting the generated delivery plan to a user terminal, means for acquiring the user's current location information and providing information on nearby restaurants and dishes in real time, means for receiving and analyzing feedback information from the user, and means for updating the delivery plan generation algorithm based on the analyzed feedback information. This makes it possible to provide an optimal delivery plan suited to each user's preferences and budget, and further enables the system's functions to be continuously improved through the provision of information and feedback in real time.

[1526] "Means for inputting user's food delivery destination and preferred dish information" refers to a user interface for inputting data such as the user's designated delivery location, preferred dish types, and allergy information through the application.

[1527] The "means for receiving and storing the input information" refers to a module for receiving data input by a user on the server side and recording it in a storage device such as a database.

[1528] "Means for analyzing the stored information and generating a delivery plan based on the user's interests and budget" refers to an algorithm that uses the stored data to create an optimal delivery plan based on the user's tastes, preferences, and budget.

[1529] "Means for transmitting the generated delivery plan to a user terminal" refers to a communication module for transmitting the generated delivery plan to a user device such as a smartphone or tablet.

[1530] "Means for obtaining the user's current location information and providing real-time information about nearby restaurants and cuisines" refers to a module that uses GPS, beacons, etc. to identify the user's current location and provides real-time information about nearby restaurants and cuisines based on that location.

[1531] "Means for receiving and analyzing feedback information from the user" refers to a function for receiving feedback data such as ratings and comments provided by the user, analyzing it, and improving the content of the next proposal.

[1532] "Means for updating the delivery plan generation algorithm based on the analyzed feedback information" refers to a function within the system for improving and updating the algorithm used to generate future delivery plans based on analyzed feedback data.

[1533] This invention relates to a system that provides optimal food delivery plans based on a user's individual preferences and budget. The system provides appropriate information in real time by linking user terminals and a server, enabling efficient, high-quality delivery services.

[1534] System Configuration

[1535] The system consists of the following elements:

[1536] 1. User Device

[1537] A smartphone or tablet is used as a user terminal, through which the user provides input data and receives information in real time.

[1538] 2. Server

[1539] The server acts as the backend for the application, generating user profiles, creating delivery plans, and providing real-time information. The server is built using Python / Django or Node.js / Express, and uses PostgreSQL or MongoDB as the database.

[1540] User Registration and Profiling

[1541] The server stores user information (e.g., name, age, favorite dishes, allergies, budget) received from the user's device in a database. This information, along with past order history and rating information, is analyzed to create a profile for each user. This profile is used when creating future delivery plans.

[1542] Restaurant and menu selection

[1543] The server lists appropriate restaurants and menus based on the type of meal and budget specified by the user, using specific algorithms (e.g., random forest or k-means clustering) to match the user's profile data and suggest the best options.

[1544] Generate and present a delivery plan

[1545] The generated delivery plan is optimized to take into account breaks and waiting times. Details of the specific restaurant, food, expected arrival time, and price are sent to the user's device. The user can then review the plan and order the selected menu.

[1546] Real-time information provision

[1547] The server uses GPS and beacons to obtain the user's current location in real time and immediately provides information about nearby restaurants and the dishes currently being served, as well as information about waiting times and estimated delivery times.

[1548] Feedback and Improvements

[1549] After the delivery is completed, the user provides feedback, which is sent to the server and stored. This data is reflected in the next delivery plan generation, improving the accuracy of the algorithm.

[1550] Specific examples

[1551] Example 1: User A orders sushi

[1552] User A installed the app, selected sushi as his / her favorite dish, and set his / her budget to 5,000 yen. User A was then suggested highly rated sushi restaurants based on his / her current location (e.g., within Tokyo). One example of a suggested plan included Sushi Restaurant B, which offers a sushi set (price: 3,000 yen). User A ordered sushi based on this suggestion, and after receiving the delivery, provided feedback rating his / her satisfaction as 5 stars.

[1553] Prompt Sentence Examples

[1554] User Profile:

[1555] Name: User A

[1556] Favorite food: Sushi

[1557] Budget: 5,000 yen

[1558] Current location: Tokyo

[1559] Rating history: Sushi Restaurant B (5 stars)

[1560] Next, please suggest a restaurant and dish you would recommend.

[1561] This concludes the "Mode for Carrying Out the Invention." This allows users to easily obtain delivery plans that suit their individual needs, and the system is continually improved based on feedback.

[1562] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1563] Step 1:

[1564] Users start the smartphone app and enter personal information such as their name, age, favorite dishes, allergies, budget, etc. on the account creation screen. The entered information is sent from the device to the server.

[1565] input:

[1566] Personal information such as name, age, favorite dishes, allergy information, budget, etc.

[1567] output:

[1568] User information sent to the server

[1569] Step 2:

[1570] The server stores the received user information in a database, which is then analyzed along with past order history and rating information to create a user profile.

[1571] input:

[1572] User information sent

[1573] output:

[1574] User profiles stored in a database

[1575] Operation:

[1576] The server analyzes the received data and generates a profile

[1577] Step 3:

[1578] The user selects a restaurant and menu based on the type of food they want to eat and their budget. The information entered into the terminal is sent to the server.

[1579] input:

[1580] What type of food do you want to eat and your budget?

[1581] output:

[1582] Cuisine and budget information sent to the server

[1583] Step 4:

[1584] The server lists suitable restaurants and menus based on the type of cuisine and budget entered by the user, matches it with the stored profile data, and suggests the best options using algorithms (e.g., random forest, k-means clustering).

[1585] input:

[1586] User profile, cuisine type, budget

[1587] output:

[1588] A list of restaurants and menus suggested to the user

[1589] Operation:

[1590] The server analyzes the profile data and applies algorithms to generate a list of suggestions

[1591] Step 5:

[1592] The generated delivery plan is sent to the user's terminal, where the user can confirm the proposed plan and order the selected menu.

[1593] input:

[1594] List of suggested restaurants and menus

[1595] output:

[1596] Delivery plan displayed on the user's device

[1597] Step 6:

[1598] The server uses GPS and beacons to obtain the user's current location in real time, and provides information about nearby restaurants and the dishes currently being served based on that location, as well as notifying the user of waiting times and estimated delivery times.

[1599] input:

[1600] User's current location

[1601] output:

[1602] Nearby restaurants and food information, waiting times, and estimated delivery times

[1603] Operation:

[1604] The server analyzes the location information and acquires and displays real-time data.

[1605] Step 7:

[1606] After receiving their delivery, users can enter their feedback on the food and service into the app, which then sends the feedback information from their device to the server.

[1607] input:

[1608] User feedback information (e.g., ratings, comments)

[1609] output:

[1610] Feedback information sent to the server

[1611] Step 8:

[1612] The server stores the feedback information received from users in a database and analyzes it. Based on the results of this analysis, it updates the algorithm for generating the next delivery plan and improves the system to make more appropriate proposals.

[1613] input:

[1614] User feedback information

[1615] output:

[1616] Next delivery plan with updated algorithm

[1617] Operation:

[1618] The server analyzes the feedback and updates the algorithm

[1619] The above are the specific processing steps of the system that realizes the application example based on the claims.

[1620] 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.

[1621] MODE FOR CARRYING OUT THE INVENTION

[1622] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1623] System Overview

[1624] User Registration and Profiling

[1625] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[1626] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[1627] Selecting a travel destination and registering interests

[1628] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[1629] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[1630] Generate and present a plan

[1631] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. Updates the user's profile based on the user's past travel history and rating information.

[1632] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[1633] Emotion Engine Operation

[1634] On-device: While a user is using an application, the emotion engine analyzes emotions based on the user's input and actions. For example, it determines emotions from the language and expressions used when a user enters comments or feedback.

[1635] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user has a low preference for the plan, it presents an alternative plan.

[1636] Real-time information provision

[1637] Device: The user launches the application while traveling and enables location information.

[1638] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[1639] Terminal: Monitors the user's emotional state in real time and dynamically adjusts the travel plan according to the user's emotions.

[1640] Feedback and Improvements

[1641] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[1642] Server: Receives user feedback information and stores it in a database. Based on this, the travel plan generation algorithm is updated and reflected in the next plan generation.

[1643] Server: The server also analyzes feedback from the emotion engine and improves the plan generation algorithm by taking the user's emotions into account.

[1644] Specific examples

[1645] Example 1: A user plans a trip to Tokyo

[1646] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[1647] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[1648] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[1649] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[1650] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[1651] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[1652] 7. User: Check the generated plan and start the trip.

[1653] 8. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[1654] 9. Terminal: The emotion engine also monitors the user’s emotional state in real time and adjusts the plan when the user feels dissatisfied or tired.

[1655] 10. User: Enter feedback about the places and restaurants they visited.

[1656] 11. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[1657] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy flexible and real-time travel plans that meet their individual needs and emotions.

[1658] The processing flow will be explained below.

[1659] Step 1:

[1660] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[1661] Step 2:

[1662] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[1663] Step 3:

[1664] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[1665] Step 4:

[1666] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[1667] Step 5:

[1668] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[1669] Step 6:

[1670] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[1671] Step 7:

[1672] Server: Sends the generated travel plan to the user terminal.

[1673] Step 8:

[1674] Terminal: The user opens the application and checks the presented travel plan.

[1675] Step 9:

[1676] Device: The user launches the application while traveling and enables location information.

[1677] Step 10:

[1678] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[1679] Step 11:

[1680] Terminal: The user checks the notified information and adjusts the plan.

[1681] Step 12:

[1682] On-device: During the journey, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments and feedback.

[1683] Step 13:

[1684] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user's emotion is negative, it presents an alternative plan.

[1685] Step 14:

[1686] Device: Monitors the user's emotional state in real time and adjusts the plan if the user feels frustrated or fatigued.

[1687] Step 15:

[1688] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[1689] Step 16:

[1690] Server: Receives user feedback information and stores it in a database.

[1691] Step 17:

[1692] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[1693] Step 18:

[1694] Server: The updated algorithm is reflected in the generation of the next travel plan.

[1695] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that is tailored to their individual needs and emotions.

[1696] Example 2

[1697] 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."

[1698] Conventional travel planning systems have difficulty providing flexible and real-time travel plans that meet diverse user needs, and lack a means to effectively reflect user emotions and feedback.

[1699] 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.

[1700] In this invention, the server includes: means for a user to register account information; means for receiving the registered information and saving it in a database; means for inputting information about the user's travel destinations and activities of interest; means for receiving and saving the input information; means for analyzing the saved information and generating an itinerary based on the user's interests and budget; means for transmitting the generated itinerary to a user terminal; means for acquiring the user's current location information and providing real-time information about nearby tourist spots and restaurants; means including a sentiment analysis engine for acquiring feedback information; means for receiving and analyzing the feedback information and sentiment analysis results from the user; and means for updating the itinerary generation algorithm based on the analyzed feedback information. This enables the provision of flexible, real-time itineraries that reflect the diverse needs and emotions of users.

[1701] "Account information" refers to basic data required when using the system, such as the user's name, age, gender, hobbies, and budget.

[1702] A "database" is a system for efficiently storing, retrieving, and managing information, and is usually built on a server.

[1703] "Destination" refers to a geographical destination that a user wishes to visit.

[1704] "Activity information" is information about specific activities such as sightseeing, shopping, and dining that interest the user.

[1705] "Analysis" is the act of investigating and analyzing input data in detail to extract meaning and patterns.

[1706] A "travel plan" refers to a plan that combines places to visit, activities, a schedule, etc. based on the user's needs and interests.

[1707] A "user terminal" is a device that is directly operated by a user, and includes a smartphone, tablet, etc.

[1708] "Current location information" is geographic coordinate data of the user's current location, obtained from a device such as the user's smartphone.

[1709] A "tourist attraction" is a specific tourist destination that travelers want to visit.

[1710] "Eating and drinking establishment information" is information about establishments that provide meals, such as restaurants and cafes.

[1711] "Feedback" refers to information such as impressions, evaluations, and opinions that a user provides to the system during or after a trip.

[1712] An "emotion analysis engine" is a software component that determines a user's emotional state based on their input and behavior.

[1713] An "algorithm" refers to a set of steps or a computational method for solving a particular problem.

[1714] MODE FOR CARRYING OUT THE INVENTION

[1715] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1716] System Overview

[1717] The system uses the following hardware and software:

[1718] Server hardware: General-purpose servers or cloud servers

[1719] Device hardware: smartphones, tablets

[1720] Server software: Django, Node.js, MySQL, PostgreSQL, Elasticsearch, GraphQL, Hugging Face Transformers, Google's BERT model

[1721] Device software: iOS app, Android app

[1722] API: HTTP, OpenWeatherMap API, Google Maps API

[1723] User Registration and Profiling

[1724] User: Download and install the application from the App Store or Google Play on their smartphone.

[1725] User: Enter information such as name, age, gender, hobbies, budget, etc. on the account registration screen. The UI is designed to be simple and intuitive.

[1726] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[1727] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[1728] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[1729] Selecting a travel destination and registering interests

[1730] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[1731] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[1732] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[1733] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[1734] Generate and present a plan

[1735] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[1736] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[1737] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[1738] Emotion Engine Operation

[1739] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[1740] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[1741] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[1742] Real-time information provision

[1743] User: Enable location services for the app.

[1744] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[1745] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[1746] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[1747] Feedback and Improvements

[1748] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[1749] Terminal: Sends feedback information to the server.

[1750] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[1751] Specific examples

[1752] Example 1: A user plans a trip to Tokyo

[1753] 1. User: Install the app and enter their name, age, gender, hobby (eating out), and budget (50,000 yen).

[1754] 2. Terminal: Sends the entered information to the server.

[1755] 3. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[1756] 4. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[1757] 5. Terminal: Sends the entered information to the server.

[1758] 6. Server: Analyzes the information and creates a list of popular food spots in Tokyo and restaurants that are within your budget.

[1759] 7. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times, and sent to the device.

[1760] 8. Device: Display the received plan and analyze user comments and feedback through the sentiment engine. Adjust the plan as needed.

[1761] 9. User: Check the generated plan and start the trip.

[1762] 10. Device: Obtains real-time location information while traveling and displays nearby tourist attractions, restaurant information, traffic conditions, and weather information.

[1763] 11. Terminal: Monitors the user’s emotional state in real time and adjusts the plan as needed.

[1764] 12. User: Enter feedback about the places and restaurants visited after the trip.

[1765] 13. Device: Sends feedback to the server.

[1766] 14. Server: Receives and stores feedback information and reflects it in the next plan generation.

[1767] Prompt Sentence Examples

[1768] If a user types into the system, "I'm planning a trip to Tokyo, can you recommend some highly rated restaurants?", the system will take into account the user's emotional state and interests and respond as follows:

[1769] "We'd like to recommend some highly rated restaurants: Sushi place ABC, Ramen place XYZ, and Okonomiyaki place DEF. We also have great lunch menus. Which one do you prefer?"

[1770]

[1771] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1772] Step 1:

[1773] User: Download and install the application from the App Store or Google Play on their smartphone.

[1774] Step 2:

[1775] User: Enter information such as name, age, gender, hobbies, and budget on the account registration screen.

[1776] Input: User's basic information (name, age, gender, hobbies, budget).

[1777] Output: The input information is stored in the terminal and prepared for the next transmission step.

[1778] Step 3:

[1779] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[1780] Input: User basic information.

[1781] Output: User information sent to the server is saved.

[1782] Step 4:

[1783] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[1784] Input: User information.

[1785] Output: User information stored in the database and a status code to the terminal.

[1786] Step 5:

[1787] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[1788] Input: User information stored in the database, past travel history, and rating information.

[1789] Output: The generated user profile.

[1790] Step 6:

[1791] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[1792] Input: Travel destination (destination).

[1793] Output: The travel destination selection screen displayed.

[1794] Step 7:

[1795] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[1796] Input: Activities of interest.

[1797] Output: Selected activity information.

[1798] Step 8:

[1799] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[1800] Input: Travel destination, activity information of interest.

[1801] Output: Destination and activity information sent to the server.

[1802] Step 9:

[1803] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[1804] Input: Travel destination, activity information.

[1805] Output: Retrieved tourist spot and restaurant information.

[1806] Step 10:

[1807] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[1808] Input: User profile, travel destinations, and activity information.

[1809] Output: A list of tourist attractions and restaurants.

[1810] Step 11:

[1811] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[1812] Input: List of spots and restaurants, detailed information for each spot and restaurant.

[1813] Output: The generated travel schedule.

[1814] Step 12:

[1815] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[1816] Input: Travel schedule sent from the server.

[1817] Output: The schedule displayed in the user interface.

[1818] Step 13:

[1819] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[1820] Input: User feedback (comments and ratings).

[1821] Output: Feedback ready to send.

[1822] Step 14:

[1823] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[1824] Input: User feedback.

[1825] Output: Feedback sent to the emotion engine.

[1826] Step 15:

[1827] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[1828] Input: Analysis results from the emotion engine.

[1829] Output: Adjusted itinerary.

[1830] Step 16:

[1831] User: Enable location services for the app.

[1832] Enter: Enable location services.

[1833] Output: Enabled location services.

[1834] Step 17:

[1835] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[1836] Input: Current location information.

[1837] Output: The location information sent to the server.

[1838] Step 18:

[1839] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[1840] Input: Current location information.

[1841] Output: Provided real-time tourist attractions, restaurants, traffic and weather information.

[1842] Step 19:

[1843] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[1844] Input: The user's emotional state.

[1845] Output: Adjusted itinerary.

[1846] Step 20:

[1847] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[1848] Input: Feedback after the trip (impressions and ratings).

[1849] Output: Feedback ready to be sent.

[1850] Step 21:

[1851] Terminal: Sends feedback information to the server.

[1852] Input: Feedback information.

[1853] Output: Feedback information sent to the server.

[1854] Step 22:

[1855] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[1856] Input: Feedback information.

[1857] Output: An improved trip plan generation algorithm.

[1858] (Application example 2)

[1859] 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."

[1860] In conventional store visits and product selection, users face the challenge of efficiently finding the right store and product that matches their interests and budget. Furthermore, the provision of real-time store information and products is insufficient, and dynamic plan adjustments that take user emotions into account are not possible, resulting in an underoptimized user experience.

[1861] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about stores and products of interest to the user; means for receiving and saving the input information; means for analyzing the saved information and generating a store visit plan based on the user's interests and budget; means for transmitting the generated store visit plan to the user terminal; means for acquiring information about the user's current location and providing information about surrounding stores and products in real time; means for receiving and analyzing feedback information from the user; means for updating the store visit plan generation algorithm based on the analyzed feedback information; means for analyzing emotions from the user's input and behavior using an emotion engine; and means for dynamically adjusting the store visit plan in real time based on the analyzed emotion information. This allows the user to obtain an optimal store visit plan that suits their interests and budget, and the provision of information in real time and the dynamic adjustment of the plan based on emotions enable a more fulfilling store visit experience.

[1862] A "user" is an individual who installs the application, inputs information, and uses the store visit plan.

[1863] A "store" refers to a physical location that a user visits and that offers products or services of interest.

[1864] "Products" are goods and services offered at stores that are of interest to users.

[1865] "Information" refers to data entered by the user, including name, age, gender, hobbies, budget, stores and products of interest, etc.

[1866] A "plan" is a proposal of stores to visit and products to purchase, generated based on the user's interests and budget.

[1867] A "server" is a computer system that receives, stores, and analyzes information input by a user.

[1868] A "terminal" is a portable information processing terminal such as a mobile phone or smartphone used by a user.

[1869] "Feedback" refers to user impressions and evaluations of stores visited or products purchased.

[1870] An "emotion engine" is a software mechanism for analyzing emotions from user input and behavior.

[1871] "Real-time information provision" means providing the latest information about nearby stores and products immediately based on the user's current location information.

[1872] MODE FOR CARRYING OUT THE INVENTION

[1873] System Overview

[1874] This invention is a system for optimizing a user's store visit experience, and in particular, relates to an application that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1875] User Registration and Profiling

[1876] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[1877] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[1878] Store and product selection and interest registration

[1879] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[1880] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[1881] Generate and present a plan

[1882] Server: Analyzes the above information and lists stores and products that match the user's interests and budget. Updates the user's profile based on the user's past store visit history and rating information.

[1883] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[1884] Emotion Engine Operation

[1885] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments or feedback.

[1886] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[1887] Real-time information provision

[1888] Device: The user launches the application and enables location while visiting the store.

[1889] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[1890] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[1891] Feedback and Improvements

[1892] Terminal: After the user has finished their visit, they enter feedback about the stores they visited and the products they purchased.

[1893] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[1894] Specific examples

[1895] Example: When a user visits a shopping mall

[1896] 1. User: Installs the app and enters their name, age, gender, hobby (fashion), and budget (30,000 yen).

[1897] 2. Server: Receives the information, stores it in a database, and updates the user profile based on past visits and reviews.

[1898] 3. User: Selects a specific shopping mall to visit and registers products (fashion items) that interest him / her.

[1899] 4. Server: Analyzes the entered information and lists recommended stores based on the user's interests and products that can be purchased within their budget.

[1900] 5. Server: Based on the listed stores and products, the server generates a plan that takes into account the route between stores and the length of stay, and sends it to the user's device.

[1901] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[1902] 7. User: Review the generated plan and start shopping.

[1903] 8. Device: While shopping, the device obtains your current location in real time and displays information about nearby stores and products. It also displays information about the store's congestion status and sales.

[1904] 9. Terminal: The emotion engine monitors the user's emotional state in real time and adjusts the plan when the user feels frustrated or fatigued.

[1905] 10. Users: Enter feedback about the stores they visit and the products they buy.

[1906] 11. Server: Receives feedback information, stores it in a database, and updates the algorithm based on it to generate the next plan.

[1907] Examples of prompt statements

[1908] Below are some example prompts for generative AI models:

[1909] Example prompt:

[1910] "Write code to implement a user registration feature for a mobile app. Implement an API endpoint on a Flask server that receives the following data and stores it in an SQLite database: Name, Age, Gender, Hobbies, Budget."

[1911] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1912] Step 1:

[1913] User: Installs the application using a smartphone and enters information such as name, age, gender, hobbies, and budget on the registration screen.

[1914] Input: User information (name, age, gender, hobbies, budget)

[1915] Output: Send user registration information

[1916] Specific operation: When the user enters information into the application's input fields and presses the "Register" button, this information is sent to the server.

[1917] Step 2:

[1918] Server: Receives the information entered above and stores it in a database. It also obtains the user's past store visit history and rating information to generate a profile.

[1919] Input: User registration information

[1920] Output: Updated user profile

[1921] Specific operation: The server connects to the database, saves the received user information, and compares it with past store visit history and evaluation information to update and generate a profile.

[1922] Step 3:

[1923] User: Uses the application to select the stores they want to visit and the products they are interested in (e.g., fashion, gourmet, electronics, etc.).

[1924] Input: Store and product information

[1925] Output: Send store and product selection information

[1926] Specific operation: The user selects the store or product they are interested in from the list on the app's selection screen, presses the "Select" button, and sends the information to the server.

[1927] Step 4:

[1928] Server: Receives the entered store and product information and stores it in a database. It then analyzes the information entered by the user and generates an optimal store visit plan.

[1929] Input: Store and product selection information

[1930] Output: Generate store visit plan

[1931] Specific operation: The server retrieves user information from the database and runs an algorithm to generate an optimal visit plan based on the entered store and product information.

[1932] Step 5:

[1933] Server: Generates optimal visiting routes and schedules based on information on available stores and products, and sends them to the user's device.

[1934] Input: Store and product information, user profile

[1935] Output: Send store visit plan

[1936] Specific operation: The generated visiting plan is sent to the user terminal and notified.

[1937] Step 6:

[1938] On the device: While the user is using the application, the emotion engine analyzes emotions based on the user's input and actions.

[1939] Input: User comments and feedback

[1940] Output: Analysis of the user's emotional state

[1941] Specific operation: The comments and feedback entered by users on the app are analyzed using text analysis and an emotion estimation algorithm is used to analyze emotions.

[1942] Step 7:

[1943] Server: Receives feedback information from the emotion engine and reflects it in the store visit plan generation method. If the user has a low preference for the plan, it presents an alternative plan.

[1944] Input: Sentiment analysis results

[1945] Output: Adjustment of plan or alternative proposals

[1946] Specific operation: The server receives the sentiment analysis results, dynamically adjusts the visit plan according to the user's satisfaction, and generates an alternative plan if necessary.

[1947] Step 8:

[1948] Device: The user launches the application and enables location while visiting the store.

[1949] Input: Current location request

[1950] Output: Send current location information

[1951] Specific operation: The user enables location services in the app, and the device obtains the current location using GPS and sends it to the server.

[1952] Step 9:

[1953] Server: Obtains the user's current location information in real time and provides information about nearby stores and products, as well as real-time information about in-store congestion and sales.

[1954] Input: Current location

[1955] Output: Nearby stores and product information, crowd situation, sale information

[1956] Specific operation: Based on the current location information, the server searches a database of nearby stores and products, and obtains and provides the latest information on crowding and sales.

[1957] Step 10:

[1958] Terminal: Monitors the user's emotional state in real time and dynamically adjusts store visit plans according to the user's emotions.

[1959] Input: Real-time emotion data

[1960] Output: Adjusted visit plan

[1961] Specific operation: The obtained emotional data is analyzed, and if the user feels dissatisfied or tired, the plan is adjusted in real time, such as suggesting a new route or resting places.

[1962] Step 11:

[1963] Users: After completing their visit, they provide feedback about the stores they visited and the products they purchased.

[1964] Input: Feedback information

[1965] Output: Sending feedback information

[1966] Specific operation: The user enters their thoughts and ratings into the feedback form on the app and sends them to the server.

[1967] Step 12:

[1968] Server: Receives user feedback and stores it in a database. Based on this, the plan generation algorithm is updated and reflected in the next plan generation. Feedback from the emotion engine is also analyzed, and the plan generation algorithm is improved to take user emotions into account.

[1969] Input: Feedback information

[1970] Output: Updated plan generation algorithm

[1971] Specific operation: The feedback data is analyzed and the algorithm parameters are adjusted to reflect the results in the next plan generation.

[1972] 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.

[1973] 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.

[1974] 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.

[1975] [Fourth embodiment]

[1976] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1977] 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.

[1978] 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).

[1979] 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.

[1980] 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.

[1981] 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).

[1982] 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.

[1983] 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.

[1984] 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.

[1985] 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.

[1986] 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.

[1987] 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.

[1988] 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."

[1989] MODE FOR CARRYING OUT THE INVENTION

[1990] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[1991] System Overview

[1992] User Registration and Profiling

[1993] Device: The user installs the application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[1994] Server: Receives the input information and stores it in a database. It also obtains past travel history and rating information to generate a user profile.

[1995] Selecting a travel destination and registering interests

[1996] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[1997] Server: Receives the input travel destination and activity information, stores it in a database, and performs analysis to generate an appropriate travel plan based on it.

[1998] Generate and present a plan

[1999] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. At the same time, the server also references the user's past travel history and reviews to update the profile.

[2000] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[2001] Real-time information provision

[2002] Terminal: The user launches the application while traveling.

[2003] Server: Obtains the user's current location in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[2004] Terminal: The user can adjust their plan based on the information provided.

[2005] Feedback and Improvements

[2006] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[2007] Server: Receives and stores user feedback information, updates the travel plan generation algorithm based on this information, and reflects it in the next plan generation.

[2008] Specific examples

[2009] Example 1: A user plans a trip to Tokyo

[2010] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[2011] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[2012] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[2013] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[2014] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[2015] 6. User: Check the generated plan and start the trip.

[2016] 7. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[2017] 8. User: Enter feedback about the places and restaurants they visited.

[2018] 9. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[2019] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy travel plans that are flexible and respond in real time to their individual needs.

[2020] The processing flow will be explained below.

[2021] Step 1:

[2022] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[2023] Step 2:

[2024] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[2025] Step 3:

[2026] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[2027] Step 4:

[2028] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[2029] Step 5:

[2030] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[2031] Step 6:

[2032] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[2033] Step 7:

[2034] Server: Sends the generated travel plan to the user terminal.

[2035] Step 8:

[2036] Terminal: The user opens the application and checks the presented travel plan.

[2037] Step 9:

[2038] Device: The user launches the application while traveling and enables location information.

[2039] Step 10:

[2040] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[2041] Step 11:

[2042] Terminal: The user checks the notified information and adjusts the plan.

[2043] Step 12:

[2044] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[2045] Step 13:

[2046] Server: Receives user feedback information and stores it in a database.

[2047] Step 14:

[2048] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[2049] Step 15:

[2050] Server: The updated algorithm is reflected in the generation of the next travel plan.

[2051] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that meets their individual needs.

[2052] Example 1

[2053] 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."

[2054] Conventional travel planning systems have difficulty generating individually customized travel plans based on users' interests and budgets, and do not adequately utilize real-time information and feedback. This has led to a demand for improved flexibility and accuracy in travel planning.

[2055] 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.

[2056] In this invention, the server includes means for inputting a user's personal information and information on activities of interest at the travel destination, means for receiving the input information and storing it in a database, means for generating and analyzing a user profile based on the stored information, means for using a generative AI model to generate a travel plan based on the user's interests and budget, means for transmitting the generated travel plan to a user terminal, means for acquiring the user's location information and providing real-time information on nearby tourist spots and restaurants, means for acquiring real-time traffic and weather information, means for receiving, storing, and analyzing feedback information from the user, and means for updating the travel plan generation algorithm based on the analyzed feedback information and reflecting it in the generation of the next travel plan. This enables the provision of travel plans customized to the user's needs and improves the flexibility and accuracy of travel plans by utilizing real-time information.

[2057] "User's personal information" refers to information including the user's name, age, gender, hobbies, budget, etc.

[2058] "Interesting activity information at a travel destination" refers to information about activities and events in which a user is interested at a travel destination.

[2059] "Database" refers to a system for efficiently storing and managing user information and travel destination data.

[2060] A "user profile" is a personalized set of information generated based on a user's personal information and past travel history and rating information.

[2061] "Generative AI model" refers to an artificial intelligence model used to generate travel plans based on a user's interests and budget.

[2062] "User terminal" means an electronic device (e.g., a smartphone, tablet, or laptop) on which a user installs and operates an application.

[2063] "Location information" refers to information about a user's current geographical location obtained using technology such as GPS.

[2064] "Tourist spots" refer to tourist destinations and famous places that users want to visit.

[2065] "Restaurant information" refers to detailed information about restaurants, cafes, etc. that the user plans to visit.

[2066] "Traffic conditions" refers to information about the real-time operation status of roads and public transportation.

[2067] "Weather information" refers to information about real-time weather forecasts and weather conditions.

[2068] "Feedback information" refers to evaluations and opinions about the places and services visited that a user provides after a trip.

[2069] A "travel plan generation algorithm" is a calculation method or procedure for analyzing input data and generating the optimal travel plan for the user.

[2070] The present invention relates to a travel planning system for optimizing a user's travel experience. Specifically, it is a system that generates travel plans based on the user's interests and budget and provides information in real time. This system operates in cooperation with a server, a terminal, and a user.

[2071] System Overview

[2072] User Registration and Profiling

[2073] Device: The user installs the travel planning system application and enters information such as name, age, gender, hobbies, and budget on the account creation screen.

[2074] Server: Receives the user's personal information and travel destination interest activity information and stores them in a database (e.g., MySQL or PostgreSQL). Then, retrieves past travel history and rating information and generates a user profile using a Python script. The user profile includes information on previously visited tourist spots and restaurants, rating points, etc.

[2075] Selecting a travel destination and registering interests

[2076] User: Enter travel destinations and activities they are interested in. For example, enter "Travel destination: Tokyo" or "Activity: Eating out."

[2077] Terminal: Transmits the entered travel destination and activity information to the server.

[2078] Server: Stores the received travel destination and activity information in a database, then analyzes it using a generative AI model (e.g., TensorFlow or PyTorch) to generate a travel plan based on the user's interests and budget.

[2079] Generate and present a plan

[2080] Server: Based on the user profile and the entered travel destination and activity information, the server analyzes the user's interests and budget and lists tourist spots and restaurants suitable for food tours. For example, the list includes "a long-established sushi restaurant in Ginza" and "a famous taiyaki shop in Asakusa."

[2081] Server: Based on the listed spots, the server generates an optimal travel schedule that takes into account travel time and rest times. This may involve using linear programming or genetic algorithms. The generated schedule includes specific timetables such as "10:00 AM: Taiyaki in Asakusa → 12:00 PM: Sushi lunch in Ginza."

[2082] Server: Sends the generated travel plan to the user terminal.

[2083] Terminal: The received travel plan is displayed on the user interface. The user can check the displayed plan and get ready to start the trip.

[2084] Real-time information provision

[2085] Device: During travel, the device uses GPS to obtain real-time information about the user's current location.

[2086] Server: Based on the user's current location, the server uses the Google Maps API to provide information on nearby tourist spots and restaurants. Additionally, the server uses the OpenWeatherMap API to provide real-time weather and traffic information.

[2087] Terminal: The information provided in real time is displayed on the user interface, allowing users to adjust their travel plans based on this information.

[2088] Feedback and Improvements

[2089] User: After the trip, the user enters feedback about the spots and restaurants they visited into the device. For example, they send feedback such as, "I was very satisfied with the sushi restaurant in Ginza."

[2090] Terminal: Sends the input feedback information to the server.

[2091] Server: Stores the received feedback information in a database. Then, retrains the generative AI model (e.g., TensorFlow or PyTorch) based on the collected feedback data and updates the itinerary generation algorithm.

[2092] Specific examples

[2093] Example: A user plans a trip to Tokyo

[2094] 1. The user installs the app and enters their name, age, gender, hobby (eating out), and budget (50,000 yen).

[2095] 2. The server receives the information, stores it in a database, and updates the user profile based on past travel history and ratings.

[2096] 3. The user selects Tokyo as their travel destination and registers "food tours" as an activity of interest.

[2097] 4. The server analyzes the information and creates a list of popular food spots in Tokyo and restaurants that fit within your budget.

[2098] 5. The server generates a schedule based on the listed spots, taking into account travel time and break times, and sends it to the device.

[2099] 6. The user confirms the generated plan and starts the trip.

[2100] 7. While traveling, the device will obtain real-time location information via GPS and provide information on nearby tourist attractions, restaurants, traffic conditions and weather.

[2101] 8. Users can provide feedback about the places and restaurants they visit.

[2102] 9. The server receives and stores the feedback information, retrains the generative AI model, and updates the itinerary generation algorithm.

[2103] Prompt Sentence Examples

[2104] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[2105] In this way, the present invention allows users to enjoy optimal travel plans tailored to their individual interests and budgets, and further enhances the quality of the travel experience by providing real-time information and continuous improvements based on user feedback.

[2106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2107] Processing Steps

[2108] Step 1:

[2109] A user installs a travel planning app on a device such as a smartphone and enters personal information such as name, age, gender, hobbies, and budget on the account creation screen. The data entered is name, age, gender, hobbies, and budget. The device converts this information into JSON format and sends it to the server.

[2110] Input: Name, age, gender, hobbies, budget

[2111] Data processing: Convert personal information into JSON format

[2112] Output: Personal information data in JSON format

[2113] Step 2:

[2114] The server receives the personal information entered and stores it in a database. After saving, it runs a Python script to retrieve relevant information from the database (such as past trip history and ratings) and update the user profile.

[2115] Input: Personal information data in JSON format

[2116] Data processing: saving to database, updating user profile

[2117] Output: Updated user profile

[2118] Step 3:

[2119] The user enters information about their travel destination and the activity they are interested in into the app. For example, they enter "Travel destination: Tokyo" and "Activity: Eating out." The entered data is then sent back to the server.

[2120] Input: Travel destination, activity

[2121] Data processing: Converting destination and activity information into JSON format

[2122] Output: Destination and activity information in JSON format

[2123] Step 4:

[2124] The server stores the received destination and activity information in a database, and then uses a generative AI model (e.g., TensorFlow or PyTorch) to generate a trip plan based on the destination and activity information.

[2125] Input: Destination and activity information in JSON format

[2126] Data processing: Saving to database, analyzing using AI model and generating plan

[2127] Output: A list of travel itinerary suggestions

[2128] Step 5:

[2129] The server generates an optimal travel schedule that takes into account travel time and rest times based on the list of tourist spots and restaurants, using linear programming and genetic algorithms.

[2130] Input: Travel plan candidate list, user profile

[2131] Data processing: Execution of schedule generation algorithm

[2132] Output: Generated travel schedule

[2133] Step 6:

[2134] The server sends the generated travel schedule to the user's device. The data is converted to JSON format again.

[2135] Input: Generated travel schedule

[2136] Data processing: Conversion to JSON format

[2137] Output: JSON formatted travel schedule data

[2138] Step 7:

[2139] The terminal displays the received travel schedule on the user interface, and the user can review the displayed plan and make adjustments as necessary.

[2140] Input: JSON formatted travel schedule data

[2141] Data processing: Display on the user interface

[2142] Output: Final travel schedule

[2143] Step 8:

[2144] The user uses the device while traveling and obtains current location information in real time using the GPS function.

[2145] Input: Real-time location information

[2146] Data processing: GPS data collection

[2147] Output: Real-time location information

[2148] Step 9:

[2149] The server calls the Google Maps API to provide information about nearby tourist spots and restaurants based on the user's current location, and also uses the OpenWeatherMap API to obtain current weather and traffic information.

[2150] Input: Real-time location information

[2151] Data processing: API calls and data acquisition

[2152] Output: Nearby tourist spots, restaurant information, weather information, traffic conditions

[2153] Step 10:

[2154] The device displays the data sent from the server in real time, allowing users to adjust their travel plans based on this information.

[2155] Input: Nearby tourist spots, restaurant information, weather information, traffic conditions

[2156] Data processing: Display on the user interface

[2157] Output: Real-time information visualization

[2158] Step 11:

[2159] After the trip, the user inputs feedback about the spots and restaurants they visited into the terminal, and the input feedback information is sent to the server.

[2160] Input: Feedback information

[2161] Data processing: Convert to JSON format and send to server

[2162] Output: Feedback information in JSON format

[2163] Step 12:

[2164] The server stores the received feedback information in a database and retrains the generative AI model, which then reflects the itinerary generation algorithm in the next itinerary.

[2165] Input: Feedback information in JSON format

[2166] Data processing: saving to database, retraining AI models

[2167] Output: Updated itinerary generation algorithm

[2168] Example prompt sentence:

[2169] "I'd like to enjoy food tours of Tokyo. My budget is 50,000 yen. What travel plans do you recommend?"

[2170] (Application example 1)

[2171] 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."

[2172] Conventional food delivery systems have difficulty providing optimal delivery plans that match users' individual preferences and budgets. Furthermore, due to a lack of real-time information, users tend to spend a lot of time selecting the right restaurant and food. Furthermore, there is a lack of systems that effectively utilize user feedback to improve the next recommendation. These issues need to be addressed.

[2173] 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.

[2174] In this invention, the server includes means for inputting information on a user's food delivery destinations and favorite dishes, means for receiving and storing the input information, means for analyzing the stored information and generating a delivery plan based on the user's interests and budget, means for transmitting the generated delivery plan to a user terminal, means for acquiring the user's current location information and providing information on nearby restaurants and dishes in real time, means for receiving and analyzing feedback information from the user, and means for updating the delivery plan generation algorithm based on the analyzed feedback information. This makes it possible to provide an optimal delivery plan suited to each user's preferences and budget, and further enables the system's functions to be continuously improved through the provision of information and feedback in real time.

[2175] "Means for inputting user's food delivery destination and preferred dish information" refers to a user interface for inputting data such as the user's designated delivery location, preferred dish types, and allergy information through the application.

[2176] The "means for receiving and storing the input information" refers to a module for receiving data input by a user on the server side and recording it in a storage device such as a database.

[2177] "Means for analyzing the stored information and generating a delivery plan based on the user's interests and budget" refers to an algorithm that uses the stored data to create an optimal delivery plan based on the user's tastes, preferences, and budget.

[2178] "Means for transmitting the generated delivery plan to a user terminal" refers to a communication module for transmitting the generated delivery plan to a user device such as a smartphone or tablet.

[2179] "Means for obtaining the user's current location information and providing real-time information about nearby restaurants and cuisines" refers to a module that uses GPS, beacons, etc. to identify the user's current location and provides real-time information about nearby restaurants and cuisines based on that location.

[2180] "Means for receiving and analyzing feedback information from the user" refers to a function for receiving feedback data such as ratings and comments provided by the user, analyzing it, and improving the content of the next proposal.

[2181] "Means for updating the delivery plan generation algorithm based on the analyzed feedback information" refers to a function within the system for improving and updating the algorithm used to generate future delivery plans based on analyzed feedback data.

[2182] This invention relates to a system that provides optimal food delivery plans based on a user's individual preferences and budget. The system provides appropriate information in real time by linking user terminals and a server, enabling efficient, high-quality delivery services.

[2183] System Configuration

[2184] The system consists of the following elements:

[2185] 1. User Device

[2186] A smartphone or tablet is used as a user terminal, through which the user provides input data and receives information in real time.

[2187] 2. Server

[2188] The server acts as the backend for the application, generating user profiles, creating delivery plans, and providing real-time information. The server is built using Python / Django or Node.js / Express, and uses PostgreSQL or MongoDB as the database.

[2189] User Registration and Profiling

[2190] The server stores user information (e.g., name, age, favorite dishes, allergies, budget) received from the user's device in a database. This information, along with past order history and rating information, is analyzed to create a profile for each user. This profile is used when creating future delivery plans.

[2191] Restaurant and menu selection

[2192] The server lists appropriate restaurants and menus based on the type of meal and budget specified by the user, using specific algorithms (e.g., random forest or k-means clustering) to match the user's profile data and suggest the best options.

[2193] Generate and present a delivery plan

[2194] The generated delivery plan is optimized to take into account breaks and waiting times. Details of the specific restaurant, food, expected arrival time, and price are sent to the user's device. The user can then review the plan and order the selected menu.

[2195] Real-time information provision

[2196] The server uses GPS and beacons to obtain the user's current location in real time and immediately provides information about nearby restaurants and the dishes currently being served, as well as information about waiting times and estimated delivery times.

[2197] Feedback and Improvements

[2198] After the delivery is completed, the user provides feedback, which is sent to the server and stored. This data is reflected in the next delivery plan generation, improving the accuracy of the algorithm.

[2199] Specific examples

[2200] Example 1: User A orders sushi

[2201] User A installed the app, selected sushi as his / her favorite dish, and set his / her budget to 5,000 yen. User A was then suggested highly rated sushi restaurants based on his / her current location (e.g., within Tokyo). One example of a suggested plan included Sushi Restaurant B, which offers a sushi set (price: 3,000 yen). User A ordered sushi based on this suggestion, and after receiving the delivery, provided feedback rating his / her satisfaction as 5 stars.

[2202] Prompt Sentence Examples

[2203] User Profile:

[2204] Name: User A

[2205] Favorite food: Sushi

[2206] Budget: 5,000 yen

[2207] Current location: Tokyo

[2208] Rating history: Sushi Restaurant B (5 stars)

[2209] Next, please suggest a restaurant and dish you would recommend.

[2210] This concludes the "Mode for Carrying Out the Invention." This allows users to easily obtain delivery plans that suit their individual needs, and the system is continually improved based on feedback.

[2211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2212] Step 1:

[2213] Users start the smartphone app and enter personal information such as their name, age, favorite dishes, allergies, budget, etc. on the account creation screen. The entered information is sent from the device to the server.

[2214] input:

[2215] Personal information such as name, age, favorite dishes, allergy information, budget, etc.

[2216] output:

[2217] User information sent to the server

[2218] Step 2:

[2219] The server stores the received user information in a database, which is then analyzed along with past order history and rating information to create a user profile.

[2220] input:

[2221] User information sent

[2222] output:

[2223] User profiles stored in a database

[2224] Operation:

[2225] The server analyzes the received data and generates a profile

[2226] Step 3:

[2227] The user selects a restaurant and menu based on the type of food they want to eat and their budget. The information entered into the terminal is sent to the server.

[2228] input:

[2229] What type of food do you want to eat and your budget?

[2230] output:

[2231] Cuisine and budget information sent to the server

[2232] Step 4:

[2233] The server lists suitable restaurants and menus based on the type of cuisine and budget entered by the user, matches it with the stored profile data, and suggests the best options using algorithms (e.g., random forest, k-means clustering).

[2234] input:

[2235] User profile, cuisine type, budget

[2236] output:

[2237] A list of restaurants and menus suggested to the user

[2238] Operation:

[2239] The server analyzes the profile data and applies algorithms to generate a list of suggestions

[2240] Step 5:

[2241] The generated delivery plan is sent to the user's terminal, where the user can confirm the proposed plan and order the selected menu.

[2242] input:

[2243] List of suggested restaurants and menus

[2244] output:

[2245] Delivery plan displayed on the user's device

[2246] Step 6:

[2247] The server uses GPS and beacons to obtain the user's current location in real time, and provides information about nearby restaurants and the dishes currently being served based on that location, as well as notifying the user of waiting times and estimated delivery times.

[2248] input:

[2249] User's current location

[2250] output:

[2251] Nearby restaurants and food information, waiting times, and estimated delivery times

[2252] Operation:

[2253] The server analyzes the location information and acquires and displays real-time data.

[2254] Step 7:

[2255] After receiving their delivery, users can enter their feedback on the food and service into the app, which then sends the feedback information from their device to the server.

[2256] input:

[2257] User feedback information (e.g., ratings, comments)

[2258] output:

[2259] Feedback information sent to the server

[2260] Step 8:

[2261] The server stores the feedback information received from users in a database and analyzes it. Based on the results of this analysis, it updates the algorithm for generating the next delivery plan and improves the system to make more appropriate proposals.

[2262] input:

[2263] User feedback information

[2264] output:

[2265] Next delivery plan with updated algorithm

[2266] Operation:

[2267] The server analyzes the feedback and updates the algorithm

[2268] The above are the specific processing steps of the system that realizes the application example based on the claims.

[2269] 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.

[2270] MODE FOR CARRYING OUT THE INVENTION

[2271] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[2272] System Overview

[2273] User Registration and Profiling

[2274] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[2275] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[2276] Selecting a travel destination and registering interests

[2277] Terminal: The user inputs a specific location as a travel destination and selects activities of interest (e.g., eating out, sightseeing, shopping, etc.).

[2278] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[2279] Generate and present a plan

[2280] Server: Analyzes the received information and lists tourist spots and restaurants that match the user's interests and budget. Updates the user's profile based on the user's past travel history and rating information.

[2281] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[2282] Emotion Engine Operation

[2283] On-device: While a user is using an application, the emotion engine analyzes emotions based on the user's input and actions. For example, it determines emotions from the language and expressions used when a user enters comments or feedback.

[2284] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user has a low preference for the plan, it presents an alternative plan.

[2285] Real-time information provision

[2286] Device: The user launches the application while traveling and enables location information.

[2287] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants, as well as real-time traffic and weather information.

[2288] Terminal: Monitors the user's emotional state in real time and dynamically adjusts the travel plan according to the user's emotions.

[2289] Feedback and Improvements

[2290] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[2291] Server: Receives user feedback information and stores it in a database. Based on this, the travel plan generation algorithm is updated and reflected in the next plan generation.

[2292] Server: The server also analyzes feedback from the emotion engine and improves the plan generation algorithm by taking the user's emotions into account.

[2293] Specific examples

[2294] Example 1: A user plans a trip to Tokyo

[2295] 1. User: Install the app and enter your name, age, gender, hobby (eating out) and budget (50,000 yen).

[2296] 2. Server: Receives the information and stores it in a database. Updates the user profile based on past travel history and rating information.

[2297] 3. User: Selects Tokyo as a travel destination and registers "food tours" as an activity of interest.

[2298] 4. Server: Analyzes the information entered and lists popular food spots in Tokyo and restaurants that fit within your budget.

[2299] 5. Server: Based on the listed spots, a daily schedule is generated that takes into account travel time and rest times. The generated plan is sent to the user's device.

[2300] 6. Terminal: The user enters comments through the emotion engine, and the server analyzes the user's emotional state in real time and adjusts the plan as necessary.

[2301] 7. User: Check the generated plan and start the trip.

[2302] 8. Device: Obtains real-time location information while traveling and displays information on nearby tourist attractions and restaurants, as well as traffic and weather information.

[2303] 9. Terminal: The emotion engine also monitors the user’s emotional state in real time and adjusts the plan when the user feels dissatisfied or tired.

[2304] 10. User: Enter feedback about the places and restaurants they visited.

[2305] 11. Server: Receives and stores feedback information, updates the algorithm based on it, and reflects it in the next plan generation.

[2306] The above is a specific embodiment for carrying out the present invention. By using this system, users can enjoy flexible and real-time travel plans that meet their individual needs and emotions.

[2307] The processing flow will be explained below.

[2308] Step 1:

[2309] Device: The user installs the application and enters account information such as name, age, gender, hobbies, and budget on the registration screen.

[2310] Step 2:

[2311] Server: Receives the input information and stores it in a database. It also obtains the user's past travel history and rating information to generate a profile.

[2312] Step 3:

[2313] Terminal: The user selects their next travel destination, inputs the place they want to go (e.g., Tokyo), and selects the activity they are interested in (e.g., eating out).

[2314] Step 4:

[2315] Server: Receives the input travel destination and activity information and stores it in a database. It then analyzes the user's input information and generates travel plan suggestions.

[2316] Step 5:

[2317] Server: Lists tourist attractions and restaurants in the travel destination based on the user's interests and budget. Updates the profile based on the user's past travel history and rating information.

[2318] Step 6:

[2319] Server: Generates an optimal travel schedule based on the listed spots and restaurants, taking into account travel time and rest times.

[2320] Step 7:

[2321] Server: Sends the generated travel plan to the user terminal.

[2322] Step 8:

[2323] Terminal: The user opens the application and checks the presented travel plan.

[2324] Step 9:

[2325] Device: The user launches the application while traveling and enables location information.

[2326] Step 10:

[2327] Server: Obtains the user's current location information in real time and provides information on nearby tourist spots and restaurants. It also collects real-time traffic and weather information and provides it to the user.

[2328] Step 11:

[2329] Terminal: The user checks the notified information and adjusts the plan.

[2330] Step 12:

[2331] On-device: During the journey, the emotion engine analyzes emotions based on the user's input and actions, for example, determining emotions from the language and expressions used when entering comments and feedback.

[2332] Step 13:

[2333] Server: Receives feedback information from the emotion engine and reflects it in the travel plan generation means. If the user's emotion is negative, it presents an alternative plan.

[2334] Step 14:

[2335] Device: Monitors the user's emotional state in real time and adjusts the plan if the user feels frustrated or fatigued.

[2336] Step 15:

[2337] Terminal: After the trip is over, the user enters feedback about the places and restaurants they visited.

[2338] Step 16:

[2339] Server: Receives user feedback information and stores it in a database.

[2340] Step 17:

[2341] Server: Analyzes the stored feedback information and updates the travel plan generation algorithm.

[2342] Step 18:

[2343] Server: The updated algorithm is reflected in the generation of the next travel plan.

[2344] The above are the specific processing steps for implementing the present invention. This system allows users to enjoy a flexible and real-time travel experience that is tailored to their individual needs and emotions.

[2345] Example 2

[2346] 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."

[2347] Conventional travel planning systems have difficulty providing flexible and real-time travel plans that meet diverse user needs, and lack a means to effectively reflect user emotions and feedback.

[2348] 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.

[2349] In this invention, the server includes: means for a user to register account information; means for receiving the registered information and saving it in a database; means for inputting information about the user's travel destinations and activities of interest; means for receiving and saving the input information; means for analyzing the saved information and generating an itinerary based on the user's interests and budget; means for transmitting the generated itinerary to a user terminal; means for acquiring the user's current location information and providing real-time information about nearby tourist spots and restaurants; means including a sentiment analysis engine for acquiring feedback information; means for receiving and analyzing the feedback information and sentiment analysis results from the user; and means for updating the itinerary generation algorithm based on the analyzed feedback information. This enables the provision of flexible, real-time itineraries that reflect the diverse needs and emotions of users.

[2350] "Account information" refers to basic data required when using the system, such as the user's name, age, gender, hobbies, and budget.

[2351] A "database" is a system for efficiently storing, retrieving, and managing information, and is usually built on a server.

[2352] "Destination" refers to a geographical destination that a user wishes to visit.

[2353] "Activity information" is information about specific activities such as sightseeing, shopping, and dining that interest the user.

[2354] "Analysis" is the act of investigating and analyzing input data in detail to extract meaning and patterns.

[2355] A "travel plan" refers to a plan that combines places to visit, activities, a schedule, etc. based on the user's needs and interests.

[2356] A "user terminal" is a device that is directly operated by a user, and includes a smartphone, tablet, etc.

[2357] "Current location information" is geographic coordinate data of the user's current location, obtained from a device such as the user's smartphone.

[2358] A "tourist attraction" is a specific tourist destination that travelers want to visit.

[2359] "Eating and drinking establishment information" is information about establishments that provide meals, such as restaurants and cafes.

[2360] "Feedback" refers to information such as impressions, evaluations, and opinions that a user provides to the system during or after a trip.

[2361] An "emotion analysis engine" is a software component that determines a user's emotional state based on their input and behavior.

[2362] An "algorithm" refers to a set of steps or a computational method for solving a particular problem.

[2363] MODE FOR CARRYING OUT THE INVENTION

[2364] The present invention relates to a travel planning system for optimizing a user's travel experience, and in particular to a system that combines an emotion engine that recognizes the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[2365] System Overview

[2366] The system uses the following hardware and software:

[2367] Server hardware: General-purpose servers or cloud servers

[2368] Device hardware: smartphones, tablets

[2369] Server software: Django, Node.js, MySQL, PostgreSQL, Elasticsearch, GraphQL, Hugging Face Transformers, Google's BERT model

[2370] Device software: iOS app, Android app

[2371] API: HTTP, OpenWeatherMap API, Google Maps API

[2372] User Registration and Profiling

[2373] User: Download and install the application from the App Store or Google Play on their smartphone.

[2374] User: Enter information such as name, age, gender, hobbies, budget, etc. on the account registration screen. The UI is designed to be simple and intuitive.

[2375] Terminal: The information entered by the user is sent to the server via an HTTP POST request.

[2376] Server: Stores the received information in a database such as MySQL or PostgreSQL. Once storage is complete, returns a 200 OK status code.

[2377] Server: Retrieves user's past travel history and rating information from the database, analyzes it, and generates a user profile using Python libraries such as pandas and scikit-learn.

[2378] Selecting a travel destination and registering interests

[2379] User: Opens a travel destination search screen within the application and enters a destination, such as "Tokyo."

[2380] User: Select the activity of interest (e.g., eating out, sightseeing, shopping) from the displayed list.

[2381] Terminal: Sends the user's selection information to the server via an HTTP POST request.

[2382] Server: Executes queries against the database based on the received information to retrieve tourist attractions and restaurant information that match the travel destination and activity. Elasticsearch and GraphQL are used to retrieve data.

[2383] Generate and present a plan

[2384] Server: Combines user profile information with travel destination information to create a list of potential tourist spots and restaurants. Collaborative Filtering and Content-Based Filtering are used as recommendation algorithms.

[2385] Server: Generates an optimal travel schedule by taking into account the locations, business hours, break times, etc. of listed spots and restaurants. Scheduling is performed using the Python datetime library and Google Maps API.

[2386] Terminal: Receives the schedule generated by the server and displays it in a user interface. The UI is an intuitive timeline format, and clicking on each event displays more information.

[2387] Emotion Engine Operation

[2388] Users: Use the in-app feedback feature to leave comments and ratings while traveling. For example, they might say, "This restaurant was delicious."

[2389] Terminal: Converts the input feedback into an appropriate format and sends it to the emotion engine, which uses the Hugging Face Transformers library and Google's BERT model.

[2390] Server: Receives feedback from the emotion engine and adjusts the plan based on the results. For example, if there is a lot of negative feedback, remove the activity from the plan and add other candidates.

[2391] Real-time information provision

[2392] User: Enable location services for the app.

[2393] Device: The current location information is periodically sent to the server. The location information is obtained using the smartphone's built-in GPS.

[2394] Server: Based on the current location, it provides information on nearby tourist spots, restaurants, traffic conditions, and weather. It uses the OpenWeatherMap API and Google Maps API to obtain real-time data.

[2395] Terminal: Monitors the user's emotional state in real time and dynamically adjusts travel plans if the user feels dissatisfied or fatigued. Uses WebSockets, Faye, Socket.IO, etc. for real-time data streaming.

[2396] Feedback and Improvements

[2397] User: After completing the trip, users can enter their impressions and ratings of the places and restaurants they visited within the app.

[2398] Terminal: Sends feedback information to the server.

[2399] Server: The received feedback information is stored in a database and used to improve the next itinerary generation algorithm. Feedback analysis uses natural language processing (NLP) techniques and applies learning models to improve recommendation accuracy.

[2400] Specific examples

[2401] Example 1: A user plans a trip to Tokyo

[2402] 1. User: Install the app and enter their name, age, gender, hobby (eating out), and budget (50,000 yen).

[2403] 2. Terminal: Sends the entered information to the server.

[2404] 3. Server: Receives the information and stores it in...

Claims

1. a means for inputting user travel destination and activity interest information; means for receiving and storing the input information; means for analyzing the stored information and generating a travel plan based on the user's interests and budget; means for transmitting the generated travel plan to a user terminal; A means for acquiring the user's current location information and providing real-time information on nearby tourist spots and restaurants; means for receiving and analyzing feedback information from the user; and means for updating a travel plan generation algorithm based on the analyzed feedback information.

2. 2. The system according to claim 1, wherein said travel plan generating means generates a profile based on the user's past travel history and evaluation information, and generates an optimal travel plan.

3. 2. The system of claim 1, wherein the information provided in real time includes traffic and weather information.

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