System

Abstract

A system is provided.SOLUTION: Means for inputting current location information of a user, means for inputting preference information of the user, means for inputting behavior data of the user, means for transmitting the input information to a server, and means for receiving the transmitted information, A system comprising: means for acquiring geographical information, restaurant evaluations, tourist site reputations, and event information; means for generating a sightseeing plan based on the acquired information; means for transmitting the generated sightseeing plan to a user terminal; means for displaying the transmitted sightseeing plan to the user; means for inputting schedule changes and real-time information of the user; means for transmitting the input change information to a server; means for modifying the sightseeing plan based on the change information; and means for transmitting and displaying the modified plan to the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, it takes a lot of time and effort for travelers to create the perfect sightseeing plan for themselves. It is particularly difficult to plan a trip that takes into account one's preferences and current conditions (weather, traffic, etc.). It is also difficult to re-plan a trip if plans change during the trip or if new information becomes available in real time. There is a need to solve these problems. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for inputting a user's current location information, preference information, and behavioral data, and a means for transmitting this information to a server. The server also has a means for acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information based on the received information, and for generating a sightseeing plan based on the acquired information. The system further includes a means for transmitting the generated sightseeing plan to the user's terminal and displaying it. In addition, the system has a means for inputting changes to the user's schedule and real-time information, and a means for modifying the sightseeing plan based on the input changes. This allows the user to always obtain the optimal sightseeing plan and can flexibly respond to schedule changes during the trip.

[0006] "User's current location information" refers to geographical location data of the user's current location.

[0007] "Preference Information" is data about a user's preferred places and activities.

[0008] "Behavioral data" is information based on a user's past behavioral history and preferences.

[0009] A "server" is a computer system that receives, analyzes, and processes data.

[0010] "Geographic information" is location data about a particular place and information about its surroundings.

[0011] "Restaurant ratings" refers to reviews and rating data for a particular restaurant.

[0012] "Tourist destination reputation" refers to reviews and evaluation data for a particular tourist destination.

[0013] "Event information" is data about an event held at a specific location or time.

[0014] A "tourist plan" is a travel plan that includes the user's travel schedule and places to visit.

[0015] "User's device" refers to a mobile device such as a smartphone or tablet carried by the user.

[0016] "Change of Plan" refers to a user changing their plans during their trip.

[0017] "Real-time information" is the latest data on current conditions or situations.

[0018] "Input means" refers to the interface or device through which a user inputs information.

[0019] "Means for transmitting" refers to the functions and protocols for transmitting input data to other systems or devices.

[0020] "Means of receiving" refers to the functions and protocols for receiving data from outside.

[0021] "Means of acquisition" refers to the functions and protocols for collecting the necessary data from external databases and APIs.

[0022] "Generating means" refers to functions or algorithms that create new information or plans based on input and acquired data.

[0023] "Means for displaying" refers to an interface for visually presenting the generated data and plans to the user.

[0024] "Means of modification" refers to functions or algorithms that modify or update existing data or plans. [Brief explanation of the drawings]

[0025] [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

[0026] 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.

[0027] First, the terms used in the following description will be explained.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 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.

[0036] 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).

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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."

[0046] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data. This system is constructed by combining the user's terminal, a server, and multiple input / output means.

[0047] System configuration

[0048] 1. User Input Method:

[0049] It provides a user interface (UI) for users to input location, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0050] 2. Means of data transmission:

[0051] The terminal sends the data entered by the user to the server. Specifically, the input data is encoded and sent to the server via the Internet as an HTTPS request.

[0052] 3. Means of receiving and analyzing data:

[0053] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0054] 4. Tourist plan generation tool:

[0055] The server generates a sightseeing plan based on the acquired data, the user's preferences, and their current location, using machine learning algorithms and heuristic methods.

[0056] 5. Means of sending and displaying itineraries:

[0057] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[0058] 6. Real-time correction measures:

[0059] The user inputs changes in plans or new information (delays, weather changes, etc.) into the device, which then sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device.

[0060] Program processing flow (example)

[0061] 1. Enter your user information:

[0062] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 p.m. to 6:00 p.m.), and preferences (e.g., cafes and shopping) into the device.

[0063] 2. Data transmission:

[0064] The terminal transmits the input data to the server.

[0065] 3. Data analysis and external data acquisition:

[0066] The server analyzes the data entered by the user and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[0067] 4. Tourist plan generation:

[0068] Based on the acquired data and the user's preferences, the server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C."

[0069] 5. Submit and view your plan:

[0070] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[0071] 6. Real-time correction:

[0072] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[0073] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0074] The device will display the revised plan to the user.

[0075] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment during their trip.

[0076] The processing flow will be explained below.

[0077] Step 1:

[0078] Users input their current location, time of day, preferences, and behavioral data into the device application. Specifically, they use the in-app interface to select "Automatic Location Capture," select departure time and duration, and choose their preferred activities (e.g., cafes, shopping, events).

[0079] Step 2:

[0080] The device sends the entered user information to the server. Specifically, it encodes the input data into JSON format and sends an HTTPS POST request to the server.

[0081] Step 3:

[0082] The server analyzes the data it receives: when it receives a POST request, it decodes the data and updates the user profile (preferences, behavioral data).

[0083] Step 4:

[0084] The server obtains the necessary external data (geographical information, restaurant ratings, tourist attraction reviews, event information) from a database or API. Specifically, it sends requests using various APIs (e.g., geographical information API, review data API) to collect the relevant data.

[0085] Step 5:

[0086] The server generates a sightseeing plan based on the data acquired and user information. Specifically, it uses machine learning models and heuristic algorithms to generate a plan that suits the user's preferences.

[0087] Step 6:

[0088] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[0089] Step 7:

[0090] The device analyzes the received itinerary and presents it visually to the user, specifically by decoding the received data and displaying it in the application's UI components (maps, timetables, lists of detailed information, etc.).

[0091] Step 8:

[0092] The user inputs changes to their plans or new information in real time (e.g., delays, weather changes) into the device, typically using forms and options within the app to enter changes.

[0093] Step 9:

[0094] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[0095] Step 10:

[0096] The server modifies the existing tour plan based on the new information, receiving the changes and running them through a data analysis and optimization algorithm again to generate a new plan.

[0097] Step 11:

[0098] The server sends the revised itinerary to the user's device in JSON format.

[0099] Step 12:

[0100] The device receives the revised plan and displays it to the user by parsing the received data again and updating the UI components to display it.

[0101] Example 1

[0102] 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."

[0103] Current travel plan generation systems often lack the ability to immediately respond to real-time changes in users' circumstances (e.g., weather changes, traffic delays, etc.). As a result, the user experience can be marred by unexpected problems. It is also difficult to automatically generate plans that fully take into account individual users' preferences and behavioral patterns. These problems need to be solved.

[0104] 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.

[0105] In this invention, the server includes means for inputting user location information, means for inputting user preference information, means for inputting user behavior data, means for transmitting the input information to the server, means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist destination reviews, and event information, means for generating a sightseeing plan based on the acquired information, means for transmitting the generated sightseeing plan to the user's terminal, means for displaying the transmitted sightseeing plan to the user, means for inputting changes to the user's plans and real-time information, means for transmitting the input change information to the server, means for modifying the sightseeing plan based on the change information, and means for transmitting the modified plan to the terminal and displaying it. This makes it possible to generate and modify an optimal sightseeing plan that reflects real-time changes in the user's situation and individual preferences.

[0106] "Means for inputting user location information" refers to an interface for inputting information about the user's current location.

[0107] The "means for inputting user preference information" is an interface for inputting information about the user's tastes and preferences.

[0108] The "means for inputting user behavioral data" refers to an interface for inputting data regarding the user's past behavior and behavioral patterns.

[0109] The "means for transmitting input information to a server" refers to a communication means for transmitting information input by a user to a server.

[0110] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to the means by which the server obtains necessary information from external databases and APIs based on the user information received.

[0111] "Means for generating a sightseeing plan based on acquired information" refers to means for creating an optimal sightseeing plan based on acquired external information and user information.

[0112] The "means for transmitting the generated tour plan to the user's terminal" is a communication means for transmitting the tour plan generated by the server to the user's terminal.

[0113] The "means for displaying the transmitted tour plan to the user" refers to a means for visually displaying the tour plan received by the terminal to the user.

[0114] "Means for inputting user schedule changes and real-time information" refers to an interface that allows a user to input schedule changes and information that occurs in real time (e.g., traffic delays or weather changes).

[0115] The "means for transmitting input change information to the server" refers to a communication means for transmitting change information input by the user to the server.

[0116] The "means for amending a sightseeing plan based on change information" refers to a means for amending an existing sightseeing plan based on change information received by the server.

[0117] The "means for transmitting the revised tour plan to the terminal and displaying it" is a means for transmitting the revised tour plan from the server to the terminal and for the terminal to display it to the user.

[0118] This invention relates to a system that generates and modifies optimized sightseeing plans in real time using user location information, preferences, and behavioral data. This system is constructed by combining user terminals, a server, and multiple input / output means.

[0119] 1. User Input Method

[0120] Users input their location, preferences, and behavioral data through applications installed on mobile devices such as smartphones and tablets, specifically iOS or Android apps.

[0121] 2. Data transmission method

[0122] The terminal encodes the data entered by the user and sends it to the server via the Internet as an HTTPS request, which ensures secure transmission of the data. The specific communication method used is the HTTP library.

[0123] 3. Means of receiving and analyzing data

[0124] The server receives and analyzes the data sent from the device. It also retrieves necessary external data, such as geographic information, restaurant ratings, tourist attraction reviews, and event information, from databases and APIs. Specific software used includes MySQL and Google Maps API.

[0125] 4. Tourist plan generation tool

[0126] The server generates a sightseeing plan based on the acquired data and user input. Using machine learning algorithms (e.g., Scikit-learn) and heuristic methods, optimization calculations are performed based on the user's preferences and behavioral patterns. This generation process suggests the best combination of tourist spots for the user.

[0127] 5. Means of sending and displaying travel plans

[0128] The server sends the generated itinerary to the device, which receives it and displays it visually to the user. Display methods include map display, timetable, detailed information list, etc. Google Maps API is used as a specific visualization tool.

[0129] 6. Real-time correction methods

[0130] If the user changes plans or inputs new information (e.g., delays, weather changes) into the device, the device sends that information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device, ensuring that the user always gets the optimal plan.

[0131] Specific usage examples and prompt sentence examples

[0132] Usage example:

[0133] The user enters "Current location: Shibuya, Tokyo," "Time: 2:00 PM to 6:00 PM," and "Favorites: Cafes and shopping" into the dedicated app. The device sends this information to the server, which analyzes it to obtain geographic information for the Shibuya area, cafe ratings, shopping spot reputations, and event information. The server then generates a sightseeing plan based on this data and sends it to the device, such as "2:00 PM - Cafe A," "3:30 PM - Shopping Spot B," and "5:00 PM - Special Event C." The device then visually displays this information to the user.

[0134] Example prompt sentence:

[0135] "The user wants to enjoy cafes and shopping in Shibuya between 2pm and 6pm. Please generate the best sightseeing itinerary based on this."

[0136] This system allows users to have the best possible sightseeing experience according to the situation at hand, and by updating information in real time, it is possible to respond flexibly to unforeseen circumstances during travel.

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] A detailed explanation of the program divided into processing steps

[0139] Step 1: Enter your user information

[0140] Users use the mobile app to input their location information, preference information, and behavioral data. For example, users input "Current location: Shibuya, Tokyo," "Time period: 2:00 PM to 6:00 PM," and "Preferences: Cafes and shopping."

[0141] Input: Current location, time zone, preferences

[0142] Output: Encoded user information data

[0143] Specific behavior: The user enters the required information on the application screen and taps the input button.

[0144] Step 2: Send the data

[0145] The terminal encodes the data entered by the user and sends it to the server as an HTTPS request.

[0146] Input: Encoded user information data

[0147] Output: HTTPS request

[0148] Specific operation: The device is connected to the network and sends the data entered by the user to the server.

[0149] Step 3: Receiving data and acquiring external data

[0150] The server receives and analyzes the data sent from the device, then retrieves external data such as geographical information, restaurant ratings, tourist attraction reviews, and event information from databases and APIs.

[0151] Input: HTTPS request, encoded user information data

[0152] Output: Analyzed user information data, external data (geographical information, restaurant ratings, tourist destination reviews, event information)

[0153] Specific operation: The server analyzes the user information and, based on that information, sends a request to an external API (e.g., Google Maps API, Yelp API) to obtain the necessary data.

[0154] Step 4: Data analysis and tourism plan generation

[0155] The server generates a sightseeing plan based on the analyzed user information data and external data, and performs optimization calculations using machine learning algorithms (e.g., Scikit-learn) and heuristic methods.

[0156] Input: Parsed user information data, external data

[0157] Output: Generated itinerary

[0158] What it does: The server processes the data and runs an algorithm that generates a sightseeing itinerary based on the user's preferences and behavioral patterns.

[0159] Step 5: Submit and view your plan

[0160] The server encodes the generated travel plan and sends it to the terminal as an HTTPS request, and the terminal displays the received travel plan to the user.

[0161] Input: Generated itinerary

[0162] Output: HTTPS request, itinerary displayed

[0163] Specific operation: The server sends the sightseeing plan to the device, and the device displays the information visually in the application (e.g., map display, timetable, detailed list).

[0164] Step 6: Real-time correction

[0165] The user inputs changes in plans or new information (e.g., train delays, weather changes), and the device sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device for display.

[0166] Input: Schedule change information, real-time information

[0167] Output: Modified itinerary

[0168] What happens: The user enters new information into the app, the device sends it to the server, the server generates a revised plan and sends it back to the device, and the device displays the new plan to the user.

[0169] Through these steps, the system of the present invention provides the optimal sightseeing plan according to the user's situation and preferences, and can also update it in real time.

[0170] (Application example 1)

[0171] 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."

[0172] Conventional food delivery systems face the challenge of effectively utilizing individual information such as a user's current location, preferences, and past order history to propose optimal meal plans in real time. Furthermore, plans are not quickly adjusted to take into account real-time information such as delivery status and weather, resulting in a poor user experience. There is a need to solve these challenges and provide users with an efficient and satisfying food delivery experience.

[0173] 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.

[0174] In this invention, the server includes means for generating a meal plan based on the acquired information, means for transmitting the generated meal plan to the user's terminal, and means for integrating weather information, delivery status information, and real-time order data when generating and modifying the meal plan. This allows the server to propose an optimal meal plan in real time, taking into account the user's current location, preferences, past order history, etc., and to dynamically modify the plan based on the latest information on delivery, weather, etc.

[0175] "Means for inputting user's current location information" refers to means for obtaining the user's current physical location information. This information is obtained in real time using the GPS function of a smartphone or other mobile device.

[0176] "Means for inputting user preference information" refers to a means for inputting a user's preferences and tastes for food and services, allowing the user to select their preferred genres and specific menu items through the application interface.

[0177] "Means for inputting user behavior data" refers to means for collecting and inputting data related to a user's past order history and behavioral patterns, which will enable analysis based on the user's past trends.

[0178] "Means for transmitting input information to a server" refers to means for transmitting the location information, preference information, and behavioral data input by the user to a server via the Internet. The data is transmitted securely in an encoded format.

[0179] "Means for receiving transmitted information and acquiring geographic information, restaurant ratings, local reputation, and event information" refers to the means for acquiring related geographic information, restaurant ratings, local reputation, and event information based on the user information received by the server. Information is acquired using external APIs and databases.

[0180] The "means for generating a meal plan based on the acquired information" refers to a means for analyzing the acquired data and generating an optimal meal plan for the user based on that data. The plan is generated using machine learning algorithms or heuristic methods.

[0181] The "means for transmitting the generated meal plan to the user's device" refers to the means for transmitting the meal plan generated by the server to the user's device such as a smartphone or tablet. The data is encoded and transmitted securely.

[0182] "Means for displaying the transmitted meal plan to the user" means means for visually displaying the received meal plan on the user's device, including a map, list, timetable, etc.

[0183] "Means for users to input schedule changes and real-time information" refers to a means for users to input real-time information such as schedule changes, delivery delays, weather changes, etc. The information can be easily input using the app's interface.

[0184] The "means for transmitting the entered change information to the server" refers to a means for transmitting the change information entered by the user to the server. The data is encoded and transmitted securely over the Internet.

[0185] The "means for modifying the meal plan based on the change information" refers to a means for modifying the generated meal plan based on the change information received by the server. The modified plan is recalculated to adapt to the user's new needs.

[0186] The "means for transmitting the revised plan to the terminal and displaying it" refers to a means for transmitting the revised plan from the server back to the user's terminal and visually displaying it. The revised plan is displayed on the user's screen in the same way as the original plan.

[0187] This invention is a system that generates and modifies optimal meal plans in real time based on a user's current location, preferences, past ordering history, etc. This system is constructed by combining a user's terminal, a server, and multiple input / output means.

[0188] System configuration

[0189] 1. User Input Method:

[0190] An interface will be provided on a smartphone or tablet for users to input their current location, preferences, past order history, etc. Specifically, a UI will be implemented that allows users to obtain location information via GPS, select their preferred genre, and view and select past order history.

[0191] 2. Means of data transmission:

[0192] The input information is sent to the server using an HTTPS request. The input data is encoded in JSON format and sent via SSL / TLS for security reasons.

[0193] 3. Means of receiving and analyzing data:

[0194] The server receives and analyzes the data sent by users, using data analysis libraries such as Pandas, and obtains geographic information, restaurant ratings, local reputation, and event information through external APIs (e.g., Google Maps API, Yelp API).

[0195] 4. Meal plan generator:

[0196] Based on the acquired data, a meal plan is generated, using machine learning algorithms (e.g., k-means clustering, random forest) and heuristic methods to perform optimization calculations based on the user's preferences and constraints.

[0197] 5. Means of sending and displaying itineraries:

[0198] The meal plan generated by the server is then encoded into JSON format and sent to the user's device, where it is received and displayed visually, including timetables, maps, and detailed information lists.

[0199] 6. Real-time correction measures:

[0200] When the user enters new information (e.g., delivery delay, weather change) into the device, the device sends that information to the server, which then modifies the meal plan based on the new information and sends the modified plan back to the device for display.

[0201] Hardware and software used

[0202] Hardware:

[0203] Smartphone (iOS or Android)

[0204] Server (AWS, Google Cloud, etc.)

[0205] software:

[0206] Smartphone app (Swift or Kotlin)

[0207] Server side (Python, Node.js, etc.)

[0208] Databases and analytical libraries (Pandas, scikit-learn)

[0209] External API (Google Maps API, Yelp API)

[0210] Specific examples

[0211] For example, suppose a user is in Shinjuku and is looking for a Japanese lunch around 12:30. The user opens the smartphone app and types, "I'm looking for a Japanese lunch around 12:30 in the Shinjuku area. Are there any recommended restaurants?" This information is sent to the server in real time, and the server generates an optimal meal plan based on geographic information and restaurant reviews. As a result, the user might be offered a plan such as "Sushi at Restaurant A at 12:30" or "Matcha Latte at Cafe B at 1:15 PM." If the user reports issues such as delivery delays, the server dynamically modifies the plan and offers it again.

[0212] As described above, the present invention is a system that provides users with an efficient and satisfying food delivery experience.

[0213] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0214] Step 1:

[0215] A user opens the app on their smartphone and enters their current location (e.g., Shinjuku), time of day (e.g., lunch), preferences (e.g., Japanese food), and past ordering history. The input data is encoded in JSON format and sent to the server via an HTTPS request. This provides the server with specific information about the user.

[0216] Step 2:

[0217] The server receives the input JSON data and deserializes it. It then analyzes the user's current location, preferences, and past order history using a data analysis library such as Pandas. This allows the server to understand the user's basic needs.

[0218] Step 3:

[0219] The server uses external APIs (e.g., Google Maps API, Yelp API) to obtain geographic information, restaurant ratings, local reputation, event information, etc. based on the received data. The obtained data is stored in a database on the server. This allows the server to collect the latest information about services desired by users.

[0220] Step 4:

[0221] The server generates a meal plan based on the acquired data. It uses machine learning algorithms (e.g., k-means clustering, random forest) to perform optimization calculations based on the user's preferences and constraints. The generated meal plan is encoded in JSON format, allowing the server to propose a plan that best suits the user's needs.

[0222] Step 5:

[0223] The server sends the generated meal plan to the user's device. The plan received by the device is deserialized and displayed visually. For example, "12:30 - Sushi at Restaurant A" and "13:15 - Matcha Latte at Cafe B" are displayed to the user. This allows the user to easily check the proposed plan.

[0224] Step 6:

[0225] The user enters real-time information into the app, such as a change in schedule or a delivery delay. The new information is again encoded into JSON format and sent to the server via an HTTPS request, which reports the new status from the device to the server.

[0226] Step 7:

[0227] The server then modifies the generated meal plan based on the new information received, again using machine learning algorithms and heuristics to recalculate and adapt to the user's new needs. The modified plan is then encoded in JSON format and sent to the device, allowing the server to quickly adapt to user changes.

[0228] Step 8:

[0229] The device receives the revised plan, deserializes it, and displays it visually. The revised plan includes new time and location information, such as "13:00 - Sushi at Restaurant A" and "13:45 - Matcha Latte at Cafe B." This allows the user to always see the latest plan.

[0230] Through these steps, the system is able to provide users with an efficient and satisfying food delivery experience.

[0231] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0232] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also includes a function that recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[0233] System configuration

[0234] 1. User Input Method:

[0235] It provides a user interface (UI) for users to input their current location, time zone, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0236] 2. Means of data transmission:

[0237] The device sends the data entered by the user and the emotional data recognized by the emotion engine to the server. Specifically, the device encodes the input data and emotional data into JSON format and sends an HTTPS POST request to the server.

[0238] 3. Means of receiving and analyzing data:

[0239] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0240] 4. Emotion recognition means:

[0241] The device's built-in emotion engine recognizes the user's emotions through facial, voice, and text analysis, and this data is reflected in the creation of a travel plan.

[0242] 5. Tourist plan generation tool:

[0243] The server generates a sightseeing plan based on the acquired external data, user preferences, and emotional data, using machine learning algorithms and heuristic methods.

[0244] 6. Means of sending and displaying itineraries:

[0245] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[0246] 7. Real-time correction measures:

[0247] The user inputs changes in plans or new real-time information (e.g., delays, weather changes) into the device, which then sends the information to the server, which then modifies the sightseeing plan based on the new information and sends it back to the device.

[0248] Program processing flow (example)

[0249] 1. Enter your user information:

[0250] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 PM to 6:00 PM), and preferences (e.g., cafes and shopping) into the device. In addition, the emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and recognize their current emotion (e.g., happy, tired).

[0251] 2. Data transmission:

[0252] The terminal transmits the input user information and recognized emotion data to the server.

[0253] 3. Data analysis and external data acquisition:

[0254] The server analyzes the user's input data and emotional data, and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[0255] 4. Tourist plan generation:

[0256] The server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C" based on the acquired data, the user's preferences, and the recognized emotional data. For example, if the user is recognized as "tired," the plan will prioritize relaxing cafes and rest spots.

[0257] 5. Submit and view your plan:

[0258] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[0259] 6. Real-time correction:

[0260] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[0261] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0262] The device will display the revised plan to the user.

[0263] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment or emotions during their trip.

[0264] The processing flow will be explained below.

[0265] Step 1:

[0266] The user inputs their current location (e.g., Shibuya, Tokyo), time of day (e.g., 2 p.m. to 6 p.m.), preferences (e.g., cafes and shopping), and behavioral data into the device's application. Furthermore, the emotion engine analyzes the user's facial expressions and voice via the device's camera and microphone to recognize their current emotion (e.g., happy, tired).

[0267] Step 2:

[0268] The device sends the input user information and recognized emotion data to the server. Specifically, the input data and emotion data are encoded in JSON format and sent to the server as an HTTPS POST request.

[0269] Step 3:

[0270] The server receives and analyzes the transmitted data, for example, decoding the user's location, time zone, and preferences to update the user profile, and analyzing the emotional data to determine the user's current emotional state.

[0271] Step 4:

[0272] The server obtains the necessary external data (e.g., geographic information, restaurant ratings, tourist attraction reviews, and information about nearby events). Specifically, it sends requests using various APIs (e.g., geographic information API, review data API) to collect the relevant data.

[0273] Step 5:

[0274] The server generates a sightseeing plan based on the acquired data, user information, and emotional data. For example, if the user's emotional state is recognized as "tired," the plan will prioritize relaxing cafes and rest areas. The plan is optimized using machine learning and heuristic algorithms.

[0275] Step 6:

[0276] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[0277] Step 7:

[0278] The device analyzes the received travel plans and visually displays them to the user. Specifically, it decodes the received data and displays it in the application's UI components (maps, timetables, detailed information lists, etc.).

[0279] Step 8:

[0280] The user inputs changes to plans or new real-time information (e.g., train delays, weather changes) using in-app forms and options to enter changes.

[0281] Step 9:

[0282] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[0283] Step 10:

[0284] The server modifies the existing sightseeing plan based on the new information, for example, by analyzing and optimizing the data again based on the changed arrival time or new emotion data, and generates a new plan.

[0285] Step 11:

[0286] The server sends the revised itinerary to the user's device in JSON format.

[0287] Step 12:

[0288] The device receives the revised plan and displays it to the user. Specifically, it parses the received data again and updates the UI components to display it. For example, it displays "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0289] In this way, by using the emotion engine, users can obtain more personalized and adaptive sightseeing plans in real time that are tailored to their emotions.

[0290] Example 2

[0291] 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."

[0292] Conventional sightseeing plan generation systems only considered the user's current location, preferences, and behavioral data, which meant they lacked the ability to adapt to user emotions or real-time changes in location and situation. Furthermore, it was difficult to revise sightseeing plans in real time, which often meant they were unable to provide the optimal plan for the user.

[0293] 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.

[0294] In this invention, the server includes means for recognizing the user's emotions, means for transmitting input information and emotional data to the server, and means for receiving the transmitted information and emotional data and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information. This makes it possible to generate and modify a tour plan that flexibly responds to the user's emotions and real-time changes in the situation.

[0295] The "means for inputting user's current location information" refers to a device that has an interface or function that allows the user to input their current location.

[0296] The "means for inputting user preference information" refers to a device that has an interface or function that allows a user to input his or her preferences and activities of interest.

[0297] The "means for inputting user behavioral data" refers to a device that has an interface or function for inputting data regarding the user's past behavior and habits.

[0298] "Means for recognizing user emotions" refers to a device that has algorithms and functions for analyzing the user's facial expressions, voice, and text to detect and recognize the user's emotions.

[0299] "Means for transmitting input information and emotional data to a server" refers to a device that has the technology and functions to transmit data input by a user and recognized emotional data to a server via a network.

[0300] The "means for receiving transmitted information and emotion data" refers to a device that allows the server to receive data transmitted from the user terminal, and often uses a secure communication protocol.

[0301] "Means of obtaining geographic information, restaurant ratings, tourist destination reputation, and event information" refers to the functions and algorithms that allow the server to obtain the necessary geographic information and rating information from external databases and APIs.

[0302] The "means for generating a sightseeing plan based on acquired information and emotional data" is a device that has algorithms and models for integrating collected data and user emotional information to generate an optimal sightseeing plan.

[0303] The "means for transmitting the generated tour plan to the user's terminal" is a device having the technology and functions for transmitting the tour plan generated by the server to the user's terminal via the network.

[0304] The "means for displaying the transmitted tour plan to the user" refers to a device that has an interface or function for the user's terminal to visually display the received tour plan.

[0305] "Means for inputting user schedule changes and real-time information" means a device that has an interface or functionality that allows a user to change their original schedule or input real-time information (e.g., delays, weather changes) into the terminal.

[0306] The "means for transmitting input change information to the server" is a device having the technology and function for transmitting change information input by the user from the terminal to the server.

[0307] The "means for modifying a tour plan based on change information" is a device that has an algorithm or model for modifying and regenerating an existing tour plan based on change information received by the server.

[0308] The "means for transmitting the revised tour plan to the terminal and displaying it" refers to a device that has the technology and functions for the server to transmit the revised tour plan to the user's terminal and for the terminal to display it.

[0309] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preference information, and behavioral data, and also includes a function to recognize the user's emotions and reflect them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[0310] 1. Hardware and Software Configuration

[0311] This system includes a user interface (UI) installed on mobile devices such as smartphones and tablets, a server, and an emotion recognition engine. User data is encoded in JSON format and transmitted by sending an HTTPS POST request to the server. Specifically, the system uses the following hardware and software:

[0312] Devices: smartphones, tablets

[0313] Server: High performance server (e.g. AWS EC2)

[0314] Emotion recognition engine: AI models for facial expression analysis, speech analysis, and text analysis (e.g., Google Cloud AutoML, Amazon Rekognition)

[0315] Databases and APIs: External APIs and databases for retrieving geographic information, restaurant ratings, tourist attraction reviews, and event information (e.g., Google Places API, Yelp API)

[0316] 2. System processing flow

[0317] When a user uses their device to input their current location, preferences, and emotional data, the device sends this data to the server. The server analyzes the received data and obtains additional information from external APIs. The server uses a machine learning algorithm to generate an optimal sightseeing plan based on the obtained data and the user's preferences and emotions. The generated sightseeing plan is sent from the server to the user's device and displayed visually on the device. If the user changes their plans or enters real-time information, the device sends that information to the server, which then revises the plan.

[0318] 3. Examples of concrete examples and prompts

[0319] As a concrete example, consider a situation where a user is in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2pm and 6pm, but is a little tired. The following data is entered:

[0320] Current location: Shibuya

[0321] Time: 14:00 to 18:00

[0322] Likes: Cafes and shopping

[0323] Emotion: Tired

[0324] In this case, the system generates the following prompt for the itinerary:

[0325] Prompt Sentence Examples

[0326] "Currently, the user is located in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2 p.m. and 6 p.m. However, he feels a bit tired, so he would prefer a place where he can relax."

[0327] In this way, the system can generate and modify optimal sightseeing plans taking into account the user's emotions and real-time situations.

[0328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0329] Step 1:

[0330] Entering user information

[0331] The user uses the device's UI to input their current location, time zone, and preferences. For example, the user inputs "Shibuya," the time zone "14:00 to 18:00," and the preferences "cafes and shopping." At this time, the device's camera and microphone are used to analyze the user's facial expressions and voice and recognize their emotions. Based on the input, the device collects the user's input data and emotional data. The output is the user's current location, time zone, preferences, and emotional data.

[0332] Step 2:

[0333] Sending data

[0334] The device encodes the user's input data and recognized emotion data into JSON format. The encoded data is sent to the server as an HTTPS POST request. The input is the user's current location, time zone, preferences, and emotion data, and the output is the encoded JSON format data and a request to send it to the server. Specifically, the device sends the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired" to the server.

[0335] Step 3:

[0336] Receiving and analyzing data

[0337] The server receives JSON formatted data sent from the device. It analyzes the received data to understand the user's current location, time zone, preferences, and emotions. The input is the JSON formatted data sent from the device, and the output is the analysis results: current location, time zone, preferences, and emotions. Specifically, the server receives the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired," and analyzes and extracts each item.

[0338] Step 4:

[0339] Retrieving External Data

[0340] The server sends requests to the appropriate database or API to obtain external data such as geographic information, restaurant ratings, tourist attraction reviews, and event information. The input is the analyzed user's current location and time zone information, and the output is the data obtained from the external API. Specifically, the server sends requests to the Yelp API or Google Places API to obtain rating information for cafes and shopping spots in the "Shibuya" area.

[0341] Step 5:

[0342] Generate a sightseeing plan

[0343] The server combines the user's input data, recognized emotion data, and acquired external data to generate a sightseeing plan. It uses a machine learning algorithm to calculate the optimal plan. The input is the user's current location, time period, preferences, emotion data, and external data, and the output is the generated sightseeing plan. Specifically, the server creates a plan combining relaxing cafes and popular shopping spots based on the information "Shibuya," "14:00-18:00," "Cafe A, Shopping B, Event C," and "Tired."

[0344] Step 6:

[0345] Submitting and Viewing Plans

[0346] The server sends the generated sightseeing plan to the user's device. The device visually displays the received plan to the user. The input is the sightseeing plan generated by the server, and the output is the specific plan information displayed on the device. Specifically, the server sends the plan "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Event C" to the device, and the device displays it to the user in a map app or list format.

[0347] Step 7:

[0348] Real-time correction

[0349] The user inputs schedule changes or real-time information (e.g., train delays) into the device. The device sends this new information to the server. The server regenerates the sightseeing plan based on the new information and sends it back to the device. The input is the changed information the user input into the device and the information sent to the server, and the output is the revised sightseeing plan. Specifically, the user inputs "train delay," and the server generates a new plan "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Event C," which is sent to the device and displayed.

[0350] (Application example 2)

[0351] 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."

[0352] Conventional sightseeing plan generation systems create plans based on the user's current location, preferences, and behavioral data, but they do not fully consider the user's real-time emotions or environmental changes, which limits the optimization of the user experience. There is also the issue of ineffective personalized store guidance in physical stores.

[0353] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's current location; means for inputting information about the user's preferences; means for inputting data about the user's behavior; means for transmitting the input information to the server; means for receiving the transmitted information and acquiring geographic information, restaurant reviews, tourist destination reputations, and event information; means for generating a tour plan based on the acquired information; means for transmitting the generated tour plan to the user's terminal; means for displaying the transmitted tour plan to the user; means for inputting changes to the user's plans and real-time information; means for transmitting the input change information to the server; means for revising the tour plan based on the change information; means for transmitting and displaying the revised plan to the terminal; means for providing personalized store guidance based on the input preference information and behavior data; means for recognizing emotions using the user's camera and microphone; means for reflecting the recognized emotions in the tour plan; and means for modifying recommendations in real time based on the user's movement information and environmental changes. This enables more personalized tour plans and store guidance that take into account the user's emotions and environmental changes.

[0354] The "means for inputting user's current location information" refers to a device or software that provides an interface for obtaining and inputting the user's current location information.

[0355] "Means for inputting user preference information" refers to a device or software that provides an interface for inputting user preferences and interests.

[0356] "Means for inputting user behavioral data" refers to a device or software that provides an interface for inputting user behavior history and activity data.

[0357] The "means for transmitting input information to a server" refers to a device or software that transmits various data input by a user to a server via a communication means such as the Internet.

[0358] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to a device or software that obtains related external data based on the user data received by the server.

[0359] The "means for generating a sightseeing plan based on the acquired information" refers to a device or software that automatically generates an optimal sightseeing plan based on the received data and the acquired external data.

[0360] The "means for transmitting the generated tour plan to the user's terminal" is a device or software that transmits the tour plan generated by the server to the terminal used by the user.

[0361] The "means for displaying the transmitted travel itinerary to the user" refers to a device or software that provides an interface for visually displaying the received travel itinerary on the user's terminal.

[0362] "Means for inputting user schedule changes and real-time information" refers to a device or software that provides an interface for users to input schedule changes and real-time information about the current situation.

[0363] The "means for transmitting input change information to the server" refers to a device or software that transmits change information input by the user to the server.

[0364] The "means for modifying a tour plan based on change information" is a device or software that recalculates and modifies an existing tour plan based on received change information.

[0365] The "means for transmitting the revised itinerary to the terminal and displaying it" refers to a device or software that transmits the revised travel itinerary to the user's terminal and displays it.

[0366] "Means for providing personalized store guidance based on input preference information and behavioral data" refers to a device or software that automatically generates and provides optimal store guidance based on the user's past preferences and behavior.

[0367] "Means for recognizing emotions using the user's camera and microphone" refers to devices or software that use the camera and microphone installed on the device to analyze the user's facial expressions and voice and recognize emotions.

[0368] The "means for reflecting the recognized emotions in the sightseeing plan" is a device or software that adjusts the sightseeing plan based on the recognized emotional information of the user.

[0369] The "means for modifying recommendations in real time based on user movement information and environmental changes" refers to a device or software that dynamically modifies the current recommended plan based on user movement information and environmental change information received in real time.

[0370] This invention relates to a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user terminal, a server, and multiple input / output means.

[0371] 1. System Configuration

[0372] 1.1 User Device

[0373] It provides a user interface (UI) for inputting user location information, preferences, and behavioral data. The UI is installed on a mobile device such as a smartphone or tablet and also uses a camera and microphone. The user terminal also includes data transmission means, reception means, and display means.

[0374] 1.2 Server

[0375] The server analyzes the information received from the user's device (location information, preferences, behavioral data, and emotional data) and also acquires external data such as geographical information, restaurant reviews, tourist attraction reputations, and event information. It then generates an optimal sightseeing plan based on the received data and the acquired external data, and sends the results back to the user's device. The server performs these tasks using machine learning algorithms (e.g., Google Cloud Vision API, IBM Watson Tone Analyzer).

[0376] 2. Implementation form

[0377] 2.1 Data Collection and Transmission

[0378] A user uses a smartphone app to input their current location (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and behavioral data. The app also uses a camera and microphone to collect emotional data (e.g., tired, happy). These data are encoded into JSON format and sent to the server using an HTTPS POST request.

[0379] 2.2 Data Reception and Analysis

[0380] The server receives the data sent by the user and obtains additional data from geographic information systems (GIS) and review APIs (e.g., Google Places API, Yelp API). At the same time, it analyzes the emotional data using an emotion recognition engine, thereby generating a travel plan that best matches the user's current mood and preferences.

[0381] 2.3 Creating and Submitting a Plan

[0382] The server generates an optimal sightseeing plan using machine learning algorithms and heuristics based on the acquired data and analysis results. The generated plan is sent to the user's smartphone and displayed through a visually appealing UI. If the user provides feedback or inputs changes to the plan, this information is also sent to the server in real time, and the server regenerates the plan.

[0383] 3. Specific Examples

[0384] For example, if a user is in Shibuya and the emotion engine recognizes that they are "tired," the server will prioritize cafes and rest spots where they can relax based on the user's preferences (cafes and shopping). It will also provide recommended store information taking into account traffic conditions and weather information.

[0385] Prompt Sentence Examples

[0386] User is located in Shibuya, Tokyo, Japan. Time frame is 2:00 PM to 4:00 PM. Sentiment is tired. Preferences are cafes and shopping. Generate a list of recommended cafes and relaxing spots.

[0387] This invention allows users to always obtain the most suitable travel plan and quickly respond to various environmental and emotional changes during their trip. Furthermore, it also allows users to receive personalized guidance in physical stores, greatly improving the user experience.

[0388] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0389] Step 1:

[0390] The user launches the smartphone app and inputs their current location, preferences, and behavioral data. At this time, emotional data is also collected using the smartphone's camera and microphone. The input data is encoded in JSON format. Input includes current location information (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and emotional data (e.g., tired). The device collects this data, and the input data is output as a JSON-formatted string.

[0391] Step 2:

[0392] The data collected by the device is sent to the server using an HTTPS POST request. Data processing involves encoding the input data and creating a transmission request. The server receives this and stores the received data in a database for analysis. The input is the JSON-formatted string generated in step 1, and the output is a response code that confirms transmission to the server.

[0393] Step 3:

[0394] The server parses the received user information and retrieves additional data from geographic information systems (e.g., Google Maps API), review APIs (e.g., Yelp API), and other external data sources. This may include restaurant ratings near the current location, tourist attraction reputation, event information, etc. The input is the received data and response data from external data sources, and the output is the parsed dataset.

[0395] Step 4:

[0396] The server generates a sightseeing plan based on the analysis results and the user's preferences and emotion data. In this process, machine learning algorithms (e.g., heuristic methods, generative AI models) are used to create the optimal plan for the user. For data processing, the received data is incorporated into the algorithm, and the generated plan is output in JSON format. The input is the analysis result data and emotion data, and the output is the generated sightseeing plan data.

[0397] Step 5:

[0398] The server sends the generated itinerary to the user's device. Again, an HTTPS POST request is used for transmission. Data processing involves encoding the itinerary data and creating a transmission request. The input is the generated itinerary data, and the output is a response code sent to the user's device.

[0399] Step 6:

[0400] The terminal visually displays the received sightseeing plan to the user. The displayed content includes maps, timetables, and lists of recommended shops. The input is the sightseeing plan data received from the server, and the output is the visual information displayed on the user's screen.

[0401] Step 7:

[0402] While sightseeing, the user inputs schedule changes and real-time information (e.g., traffic delays, weather fluctuations). This information is sent back to the server from the terminal. As part of data processing, the change information is encoded and a transmission request is created. The input is the schedule change information, and the output is a response code that confirms transmission to the server.

[0403] Step 8:

[0404] The server modifies the current tour plan based on the received change information. In the modification process, an optimization recalculation is performed using the same algorithm as in step 4. The input is the change information and the existing tour plan data, and the output is the modified tour plan.

[0405] Step 9:

[0406] The server sends the modified itinerary to the user's terminal, which then displays it to the user again. The process is similar to steps 5 and 6. The input is the modified itinerary data, and the output is a response code and modified visual information to the user's terminal.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] [Second embodiment]

[0411] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0422] 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."

[0423] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data. This system is constructed by combining the user's terminal, a server, and multiple input / output means.

[0424] System configuration

[0425] 1. User Input Method:

[0426] It provides a user interface (UI) for users to input location, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0427] 2. Means of data transmission:

[0428] The terminal sends the data entered by the user to the server. Specifically, the input data is encoded and sent to the server via the Internet as an HTTPS request.

[0429] 3. Means of receiving and analyzing data:

[0430] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0431] 4. Tourist plan generation tool:

[0432] The server generates a sightseeing plan based on the acquired data, the user's preferences, and their current location, using machine learning algorithms and heuristic methods.

[0433] 5. Means of sending and displaying itineraries:

[0434] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[0435] 6. Real-time correction measures:

[0436] The user inputs changes in plans or new information (delays, weather changes, etc.) into the device, which then sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device.

[0437] Program processing flow (example)

[0438] 1. Enter your user information:

[0439] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 p.m. to 6:00 p.m.), and preferences (e.g., cafes and shopping) into the device.

[0440] 2. Data transmission:

[0441] The terminal transmits the input data to the server.

[0442] 3. Data analysis and external data acquisition:

[0443] The server analyzes the data entered by the user and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[0444] 4. Tourist plan generation:

[0445] Based on the acquired data and the user's preferences, the server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C."

[0446] 5. Submit and view your plan:

[0447] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[0448] 6. Real-time correction:

[0449] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[0450] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0451] The device will display the revised plan to the user.

[0452] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment during their trip.

[0453] The processing flow will be explained below.

[0454] Step 1:

[0455] Users input their current location, time of day, preferences, and behavioral data into the device application. Specifically, they use the in-app interface to select "Automatic Location Capture," select departure time and duration, and choose their preferred activities (e.g., cafes, shopping, events).

[0456] Step 2:

[0457] The device sends the entered user information to the server. Specifically, it encodes the input data into JSON format and sends an HTTPS POST request to the server.

[0458] Step 3:

[0459] The server analyzes the data it receives: when it receives a POST request, it decodes the data and updates the user profile (preferences, behavioral data).

[0460] Step 4:

[0461] The server obtains the necessary external data (geographical information, restaurant ratings, tourist attraction reviews, event information) from a database or API. Specifically, it sends requests using various APIs (e.g., geographical information API, review data API) to collect the relevant data.

[0462] Step 5:

[0463] The server generates a sightseeing plan based on the data acquired and user information. Specifically, it uses machine learning models and heuristic algorithms to generate a plan that suits the user's preferences.

[0464] Step 6:

[0465] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[0466] Step 7:

[0467] The device analyzes the received itinerary and presents it visually to the user, specifically by decoding the received data and displaying it in the application's UI components (maps, timetables, lists of detailed information, etc.).

[0468] Step 8:

[0469] The user inputs changes to their plans or new information in real time (e.g., delays, weather changes) into the device, typically using forms and options within the app to enter changes.

[0470] Step 9:

[0471] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[0472] Step 10:

[0473] The server modifies the existing tour plan based on the new information, receiving the changes and running them through a data analysis and optimization algorithm again to generate a new plan.

[0474] Step 11:

[0475] The server sends the revised itinerary to the user's device in JSON format.

[0476] Step 12:

[0477] The device receives the revised plan and displays it to the user by parsing the received data again and updating the UI components to display it.

[0478] Example 1

[0479] 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."

[0480] Current travel plan generation systems often lack the ability to immediately respond to real-time changes in users' circumstances (e.g., weather changes, traffic delays, etc.). As a result, the user experience can be marred by unexpected problems. It is also difficult to automatically generate plans that fully take into account individual users' preferences and behavioral patterns. These problems need to be solved.

[0481] 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.

[0482] In this invention, the server includes means for inputting user location information, means for inputting user preference information, means for inputting user behavior data, means for transmitting the input information to the server, means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist destination reviews, and event information, means for generating a sightseeing plan based on the acquired information, means for transmitting the generated sightseeing plan to the user's terminal, means for displaying the transmitted sightseeing plan to the user, means for inputting changes to the user's plans and real-time information, means for transmitting the input change information to the server, means for modifying the sightseeing plan based on the change information, and means for transmitting the modified plan to the terminal and displaying it. This makes it possible to generate and modify an optimal sightseeing plan that reflects real-time changes in the user's situation and individual preferences.

[0483] "Means for inputting user location information" refers to an interface for inputting information about the user's current location.

[0484] The "means for inputting user preference information" is an interface for inputting information about the user's tastes and preferences.

[0485] The "means for inputting user behavioral data" refers to an interface for inputting data regarding the user's past behavior and behavioral patterns.

[0486] The "means for transmitting input information to a server" refers to a communication means for transmitting information input by a user to a server.

[0487] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to the means by which the server obtains necessary information from external databases and APIs based on the user information received.

[0488] "Means for generating a sightseeing plan based on acquired information" refers to means for creating an optimal sightseeing plan based on acquired external information and user information.

[0489] The "means for transmitting the generated tour plan to the user's terminal" is a communication means for transmitting the tour plan generated by the server to the user's terminal.

[0490] The "means for displaying the transmitted tour plan to the user" refers to a means for visually displaying the tour plan received by the terminal to the user.

[0491] "Means for inputting user schedule changes and real-time information" refers to an interface that allows a user to input schedule changes and information that occurs in real time (e.g., traffic delays or weather changes).

[0492] The "means for transmitting input change information to the server" refers to a communication means for transmitting change information input by the user to the server.

[0493] The "means for amending a sightseeing plan based on change information" refers to a means for amending an existing sightseeing plan based on change information received by the server.

[0494] The "means for transmitting the revised tour plan to the terminal and displaying it" is a means for transmitting the revised tour plan from the server to the terminal and for the terminal to display it to the user.

[0495] This invention relates to a system that generates and modifies optimized sightseeing plans in real time using user location information, preferences, and behavioral data. This system is constructed by combining user terminals, a server, and multiple input / output means.

[0496] 1. User Input Method

[0497] Users input their location, preferences, and behavioral data through applications installed on mobile devices such as smartphones and tablets, specifically iOS or Android apps.

[0498] 2. Data transmission method

[0499] The terminal encodes the data entered by the user and sends it to the server via the Internet as an HTTPS request, which ensures secure transmission of the data. The specific communication method used is the HTTP library.

[0500] 3. Means of receiving and analyzing data

[0501] The server receives and analyzes the data sent from the device. It also retrieves necessary external data, such as geographic information, restaurant ratings, tourist attraction reviews, and event information, from databases and APIs. Specific software used includes MySQL and Google Maps API.

[0502] 4. Tourist plan generation tool

[0503] The server generates a sightseeing plan based on the acquired data and user input. Using machine learning algorithms (e.g., Scikit-learn) and heuristic methods, optimization calculations are performed based on the user's preferences and behavioral patterns. This generation process suggests the best combination of tourist spots for the user.

[0504] 5. Means of sending and displaying travel plans

[0505] The server sends the generated itinerary to the device, which receives it and displays it visually to the user. Display methods include map display, timetable, detailed information list, etc. Google Maps API is used as a specific visualization tool.

[0506] 6. Real-time correction methods

[0507] If the user changes plans or inputs new information (e.g., delays, weather changes) into the device, the device sends that information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device, ensuring that the user always gets the optimal plan.

[0508] Specific usage examples and prompt sentence examples

[0509] Usage example:

[0510] The user enters "Current location: Shibuya, Tokyo," "Time: 2:00 PM to 6:00 PM," and "Favorites: Cafes and shopping" into the dedicated app. The device sends this information to the server, which analyzes it to obtain geographic information for the Shibuya area, cafe ratings, shopping spot reputations, and event information. The server then generates a sightseeing plan based on this data and sends it to the device, such as "2:00 PM - Cafe A," "3:30 PM - Shopping Spot B," and "5:00 PM - Special Event C." The device then visually displays this information to the user.

[0511] Example prompt sentence:

[0512] "The user wants to enjoy cafes and shopping in Shibuya between 2pm and 6pm. Please generate the best sightseeing itinerary based on this."

[0513] This system allows users to have the best possible sightseeing experience according to the situation at hand, and by updating information in real time, it is possible to respond flexibly to unforeseen circumstances during travel.

[0514] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0515] A detailed explanation of the program divided into processing steps

[0516] Step 1: Enter your user information

[0517] Users use the mobile app to input their location information, preference information, and behavioral data. For example, users input "Current location: Shibuya, Tokyo," "Time period: 2:00 PM to 6:00 PM," and "Preferences: Cafes and shopping."

[0518] Input: Current location, time zone, preferences

[0519] Output: Encoded user information data

[0520] Specific behavior: The user enters the required information on the application screen and taps the input button.

[0521] Step 2: Send the data

[0522] The terminal encodes the data entered by the user and sends it to the server as an HTTPS request.

[0523] Input: Encoded user information data

[0524] Output: HTTPS request

[0525] Specific operation: The device is connected to the network and sends the data entered by the user to the server.

[0526] Step 3: Receiving data and acquiring external data

[0527] The server receives and analyzes the data sent from the device, then retrieves external data such as geographical information, restaurant ratings, tourist attraction reviews, and event information from databases and APIs.

[0528] Input: HTTPS request, encoded user information data

[0529] Output: Analyzed user information data, external data (geographical information, restaurant ratings, tourist destination reviews, event information)

[0530] Specific operation: The server analyzes the user information and, based on that information, sends a request to an external API (e.g., Google Maps API, Yelp API) to obtain the necessary data.

[0531] Step 4: Data analysis and tourism plan generation

[0532] The server generates a sightseeing plan based on the analyzed user information data and external data, and performs optimization calculations using machine learning algorithms (e.g., Scikit-learn) and heuristic methods.

[0533] Input: Parsed user information data, external data

[0534] Output: Generated itinerary

[0535] What it does: The server processes the data and runs an algorithm that generates a sightseeing itinerary based on the user's preferences and behavioral patterns.

[0536] Step 5: Submit and view your plan

[0537] The server encodes the generated travel plan and sends it to the terminal as an HTTPS request, and the terminal displays the received travel plan to the user.

[0538] Input: Generated itinerary

[0539] Output: HTTPS request, itinerary displayed

[0540] Specific operation: The server sends the sightseeing plan to the device, and the device displays the information visually in the application (e.g., map display, timetable, detailed list).

[0541] Step 6: Real-time correction

[0542] The user inputs changes in plans or new information (e.g., train delays, weather changes), and the device sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device for display.

[0543] Input: Schedule change information, real-time information

[0544] Output: Modified itinerary

[0545] What happens: The user enters new information into the app, the device sends it to the server, the server generates a revised plan and sends it back to the device, and the device displays the new plan to the user.

[0546] Through these steps, the system of the present invention provides the optimal sightseeing plan according to the user's situation and preferences, and can also update it in real time.

[0547] (Application example 1)

[0548] 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."

[0549] Conventional food delivery systems face the challenge of effectively utilizing individual information such as a user's current location, preferences, and past order history to propose optimal meal plans in real time. Furthermore, plans are not quickly adjusted to take into account real-time information such as delivery status and weather, resulting in a poor user experience. There is a need to solve these challenges and provide users with an efficient and satisfying food delivery experience.

[0550] 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.

[0551] In this invention, the server includes means for generating a meal plan based on the acquired information, means for transmitting the generated meal plan to the user's terminal, and means for integrating weather information, delivery status information, and real-time order data when generating and modifying the meal plan. This allows the server to propose an optimal meal plan in real time, taking into account the user's current location, preferences, past order history, etc., and to dynamically modify the plan based on the latest information on delivery, weather, etc.

[0552] "Means for inputting user's current location information" refers to means for obtaining the user's current physical location information. This information is obtained in real time using the GPS function of a smartphone or other mobile device.

[0553] "Means for inputting user preference information" refers to a means for inputting a user's preferences and tastes for food and services, allowing the user to select their preferred genres and specific menu items through the application interface.

[0554] "Means for inputting user behavior data" refers to means for collecting and inputting data related to a user's past order history and behavioral patterns, which will enable analysis based on the user's past trends.

[0555] "Means for transmitting input information to a server" refers to means for transmitting the location information, preference information, and behavioral data input by the user to a server via the Internet. The data is transmitted securely in an encoded format.

[0556] "Means for receiving transmitted information and acquiring geographic information, restaurant ratings, local reputation, and event information" refers to the means for acquiring related geographic information, restaurant ratings, local reputation, and event information based on the user information received by the server. Information is acquired using external APIs and databases.

[0557] The "means for generating a meal plan based on the acquired information" refers to a means for analyzing the acquired data and generating an optimal meal plan for the user based on that data. The plan is generated using machine learning algorithms or heuristic methods.

[0558] The "means for transmitting the generated meal plan to the user's device" refers to the means for transmitting the meal plan generated by the server to the user's device such as a smartphone or tablet. The data is encoded and transmitted securely.

[0559] "Means for displaying the transmitted meal plan to the user" means means for visually displaying the received meal plan on the user's device, including a map, list, timetable, etc.

[0560] "Means for users to input schedule changes and real-time information" refers to a means for users to input real-time information such as schedule changes, delivery delays, weather changes, etc. The information can be easily input using the app's interface.

[0561] The "means for transmitting the entered change information to the server" refers to a means for transmitting the change information entered by the user to the server. The data is encoded and transmitted securely over the Internet.

[0562] The "means for modifying the meal plan based on the change information" refers to a means for modifying the generated meal plan based on the change information received by the server. The modified plan is recalculated to adapt to the user's new needs.

[0563] The "means for transmitting the revised plan to the terminal and displaying it" refers to a means for transmitting the revised plan from the server back to the user's terminal and visually displaying it. The revised plan is displayed on the user's screen in the same way as the original plan.

[0564] This invention is a system that generates and modifies optimal meal plans in real time based on a user's current location, preferences, past ordering history, etc. This system is constructed by combining a user's terminal, a server, and multiple input / output means.

[0565] System configuration

[0566] 1. User Input Method:

[0567] An interface will be provided on a smartphone or tablet for users to input their current location, preferences, past order history, etc. Specifically, a UI will be implemented that allows users to obtain location information via GPS, select their preferred genre, and view and select past order history.

[0568] 2. Means of data transmission:

[0569] The input information is sent to the server using an HTTPS request. The input data is encoded in JSON format and sent via SSL / TLS for security reasons.

[0570] 3. Means of receiving and analyzing data:

[0571] The server receives and analyzes the data sent by users, using data analysis libraries such as Pandas, and obtains geographic information, restaurant ratings, local reputation, and event information through external APIs (e.g., Google Maps API, Yelp API).

[0572] 4. Meal plan generator:

[0573] Based on the acquired data, a meal plan is generated, using machine learning algorithms (e.g., k-means clustering, random forest) and heuristic methods to perform optimization calculations based on the user's preferences and constraints.

[0574] 5. Means of sending and displaying itineraries:

[0575] The meal plan generated by the server is then encoded into JSON format and sent to the user's device, where it is received and displayed visually, including timetables, maps, and detailed information lists.

[0576] 6. Real-time correction measures:

[0577] When the user enters new information (e.g., delivery delay, weather change) into the device, the device sends that information to the server, which then modifies the meal plan based on the new information and sends the modified plan back to the device for display.

[0578] Hardware and software used

[0579] Hardware:

[0580] Smartphone (iOS or Android)

[0581] Server (AWS, Google Cloud, etc.)

[0582] software:

[0583] Smartphone app (Swift or Kotlin)

[0584] Server side (Python, Node.js, etc.)

[0585] Databases and analytical libraries (Pandas, scikit-learn)

[0586] External API (Google Maps API, Yelp API)

[0587] Specific examples

[0588] For example, suppose a user is in Shinjuku and is looking for a Japanese lunch around 12:30. The user opens the smartphone app and types, "I'm looking for a Japanese lunch around 12:30 in the Shinjuku area. Are there any recommended restaurants?" This information is sent to the server in real time, and the server generates an optimal meal plan based on geographic information and restaurant reviews. As a result, the user might be offered a plan such as "Sushi at Restaurant A at 12:30" or "Matcha Latte at Cafe B at 1:15 PM." If the user reports issues such as delivery delays, the server dynamically modifies the plan and offers it again.

[0589] As described above, the present invention is a system that provides users with an efficient and satisfying food delivery experience.

[0590] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0591] Step 1:

[0592] A user opens the app on their smartphone and enters their current location (e.g., Shinjuku), time of day (e.g., lunch), preferences (e.g., Japanese food), and past ordering history. The input data is encoded in JSON format and sent to the server via an HTTPS request. This provides the server with specific information about the user.

[0593] Step 2:

[0594] The server receives the input JSON data and deserializes it. It then analyzes the user's current location, preferences, and past order history using a data analysis library such as Pandas. This allows the server to understand the user's basic needs.

[0595] Step 3:

[0596] The server uses external APIs (e.g., Google Maps API, Yelp API) to obtain geographic information, restaurant ratings, local reputation, event information, etc. based on the received data. The obtained data is stored in a database on the server. This allows the server to collect the latest information about services desired by users.

[0597] Step 4:

[0598] The server generates a meal plan based on the acquired data. It uses machine learning algorithms (e.g., k-means clustering, random forest) to perform optimization calculations based on the user's preferences and constraints. The generated meal plan is encoded in JSON format, allowing the server to propose a plan that best suits the user's needs.

[0599] Step 5:

[0600] The server sends the generated meal plan to the user's device. The plan received by the device is deserialized and displayed visually. For example, "12:30 - Sushi at Restaurant A" and "13:15 - Matcha Latte at Cafe B" are displayed to the user. This allows the user to easily check the proposed plan.

[0601] Step 6:

[0602] The user enters real-time information into the app, such as a change in schedule or a delivery delay. The new information is again encoded into JSON format and sent to the server via an HTTPS request, which reports the new status from the device to the server.

[0603] Step 7:

[0604] The server then modifies the generated meal plan based on the new information received, again using machine learning algorithms and heuristics to recalculate and adapt to the user's new needs. The modified plan is then encoded in JSON format and sent to the device, allowing the server to quickly adapt to user changes.

[0605] Step 8:

[0606] The device receives the revised plan, deserializes it, and displays it visually. The revised plan includes new time and location information, such as "13:00 - Sushi at Restaurant A" and "13:45 - Matcha Latte at Cafe B." This allows the user to always see the latest plan.

[0607] Through these steps, the system is able to provide users with an efficient and satisfying food delivery experience.

[0608] 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.

[0609] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also includes a function that recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[0610] System configuration

[0611] 1. User Input Method:

[0612] It provides a user interface (UI) for users to input their current location, time zone, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0613] 2. Means of data transmission:

[0614] The device sends the data entered by the user and the emotional data recognized by the emotion engine to the server. Specifically, the device encodes the input data and emotional data into JSON format and sends an HTTPS POST request to the server.

[0615] 3. Means of receiving and analyzing data:

[0616] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0617] 4. Emotion recognition means:

[0618] The device's built-in emotion engine recognizes the user's emotions through facial, voice, and text analysis, and this data is reflected in the creation of a travel plan.

[0619] 5. Tourist plan generation tool:

[0620] The server generates a sightseeing plan based on the acquired external data, user preferences, and emotional data, using machine learning algorithms and heuristic methods.

[0621] 6. Means of sending and displaying itineraries:

[0622] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[0623] 7. Real-time correction measures:

[0624] The user inputs changes in plans or new real-time information (e.g., delays, weather changes) into the device, which then sends the information to the server, which then modifies the sightseeing plan based on the new information and sends it back to the device.

[0625] Program processing flow (example)

[0626] 1. Enter your user information:

[0627] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 PM to 6:00 PM), and preferences (e.g., cafes and shopping) into the device. In addition, the emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and recognize their current emotion (e.g., happy, tired).

[0628] 2. Data transmission:

[0629] The terminal transmits the input user information and recognized emotion data to the server.

[0630] 3. Data analysis and external data acquisition:

[0631] The server analyzes the user's input data and emotional data, and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[0632] 4. Tourist plan generation:

[0633] The server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C" based on the acquired data, the user's preferences, and the recognized emotional data. For example, if the user is recognized as "tired," the plan will prioritize relaxing cafes and rest spots.

[0634] 5. Submit and view your plan:

[0635] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[0636] 6. Real-time correction:

[0637] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[0638] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0639] The device will display the revised plan to the user.

[0640] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment or emotions during their trip.

[0641] The processing flow will be explained below.

[0642] Step 1:

[0643] The user inputs their current location (e.g., Shibuya, Tokyo), time of day (e.g., 2 p.m. to 6 p.m.), preferences (e.g., cafes and shopping), and behavioral data into the device's application. Furthermore, the emotion engine analyzes the user's facial expressions and voice via the device's camera and microphone to recognize their current emotion (e.g., happy, tired).

[0644] Step 2:

[0645] The device sends the input user information and recognized emotion data to the server. Specifically, the input data and emotion data are encoded in JSON format and sent to the server as an HTTPS POST request.

[0646] Step 3:

[0647] The server receives and analyzes the transmitted data, for example, decoding the user's location, time zone, and preferences to update the user profile, and analyzing the emotional data to determine the user's current emotional state.

[0648] Step 4:

[0649] The server obtains the necessary external data (e.g., geographic information, restaurant ratings, tourist attraction reviews, and information about nearby events). Specifically, it sends requests using various APIs (e.g., geographic information API, review data API) to collect the relevant data.

[0650] Step 5:

[0651] The server generates a sightseeing plan based on the acquired data, user information, and emotional data. For example, if the user's emotional state is recognized as "tired," the plan will prioritize relaxing cafes and rest areas. The plan is optimized using machine learning and heuristic algorithms.

[0652] Step 6:

[0653] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[0654] Step 7:

[0655] The device analyzes the received travel plans and visually displays them to the user. Specifically, it decodes the received data and displays it in the application's UI components (maps, timetables, detailed information lists, etc.).

[0656] Step 8:

[0657] The user inputs changes to plans or new real-time information (e.g., train delays, weather changes) using in-app forms and options to enter changes.

[0658] Step 9:

[0659] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[0660] Step 10:

[0661] The server modifies the existing sightseeing plan based on the new information, for example, by analyzing and optimizing the data again based on the changed arrival time or new emotion data, and generates a new plan.

[0662] Step 11:

[0663] The server sends the revised itinerary to the user's device in JSON format.

[0664] Step 12:

[0665] The device receives the revised plan and displays it to the user. Specifically, it parses the received data again and updates the UI components to display it. For example, it displays "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0666] In this way, by using the emotion engine, users can obtain more personalized and adaptive sightseeing plans in real time that are tailored to their emotions.

[0667] Example 2

[0668] 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."

[0669] Conventional sightseeing plan generation systems only considered the user's current location, preferences, and behavioral data, which meant they lacked the ability to adapt to user emotions or real-time changes in location and situation. Furthermore, it was difficult to revise sightseeing plans in real time, which often meant they were unable to provide the optimal plan for the user.

[0670] 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.

[0671] In this invention, the server includes means for recognizing the user's emotions, means for transmitting input information and emotional data to the server, and means for receiving the transmitted information and emotional data and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information. This makes it possible to generate and modify a tour plan that flexibly responds to the user's emotions and real-time changes in the situation.

[0672] The "means for inputting user's current location information" refers to a device that has an interface or function that allows the user to input their current location.

[0673] The "means for inputting user preference information" refers to a device that has an interface or function that allows a user to input his or her preferences and activities of interest.

[0674] The "means for inputting user behavioral data" refers to a device that has an interface or function for inputting data regarding the user's past behavior and habits.

[0675] "Means for recognizing user emotions" refers to a device that has algorithms and functions for analyzing the user's facial expressions, voice, and text to detect and recognize the user's emotions.

[0676] "Means for transmitting input information and emotional data to a server" refers to a device that has the technology and functions to transmit data input by a user and recognized emotional data to a server via a network.

[0677] The "means for receiving transmitted information and emotion data" refers to a device that allows the server to receive data transmitted from the user terminal, and often uses a secure communication protocol.

[0678] "Means of obtaining geographic information, restaurant ratings, tourist destination reputation, and event information" refers to the functions and algorithms that allow the server to obtain the necessary geographic information and rating information from external databases and APIs.

[0679] The "means for generating a sightseeing plan based on acquired information and emotional data" is a device that has algorithms and models for integrating collected data and user emotional information to generate an optimal sightseeing plan.

[0680] The "means for transmitting the generated tour plan to the user's terminal" is a device having the technology and functions for transmitting the tour plan generated by the server to the user's terminal via the network.

[0681] The "means for displaying the transmitted tour plan to the user" refers to a device that has an interface or function for the user's terminal to visually display the received tour plan.

[0682] "Means for inputting user schedule changes and real-time information" means a device that has an interface or functionality that allows a user to change their original schedule or input real-time information (e.g., delays, weather changes) into the terminal.

[0683] The "means for transmitting input change information to the server" is a device having the technology and function for transmitting change information input by the user from the terminal to the server.

[0684] The "means for modifying a tour plan based on change information" is a device that has an algorithm or model for modifying and regenerating an existing tour plan based on change information received by the server.

[0685] The "means for transmitting the revised tour plan to the terminal and displaying it" refers to a device that has the technology and functions for the server to transmit the revised tour plan to the user's terminal and for the terminal to display it.

[0686] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preference information, and behavioral data, and also includes a function to recognize the user's emotions and reflect them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[0687] 1. Hardware and Software Configuration

[0688] This system includes a user interface (UI) installed on mobile devices such as smartphones and tablets, a server, and an emotion recognition engine. User data is encoded in JSON format and transmitted by sending an HTTPS POST request to the server. Specifically, the system uses the following hardware and software:

[0689] Devices: smartphones, tablets

[0690] Server: High performance server (e.g. AWS EC2)

[0691] Emotion recognition engine: AI models for facial expression analysis, speech analysis, and text analysis (e.g., Google Cloud AutoML, Amazon Rekognition)

[0692] Databases and APIs: External APIs and databases for retrieving geographic information, restaurant ratings, tourist attraction reviews, and event information (e.g., Google Places API, Yelp API)

[0693] 2. System processing flow

[0694] When a user uses their device to input their current location, preferences, and emotional data, the device sends this data to the server. The server analyzes the received data and obtains additional information from external APIs. The server uses a machine learning algorithm to generate an optimal sightseeing plan based on the obtained data and the user's preferences and emotions. The generated sightseeing plan is sent from the server to the user's device and displayed visually on the device. If the user changes their plans or enters real-time information, the device sends that information to the server, which then revises the plan.

[0695] 3. Examples of concrete examples and prompts

[0696] As a concrete example, consider a situation where a user is in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2pm and 6pm, but is a little tired. The following data is entered:

[0697] Current location: Shibuya

[0698] Time: 14:00 to 18:00

[0699] Likes: Cafes and shopping

[0700] Emotion: Tired

[0701] In this case, the system generates the following prompt for the itinerary:

[0702] Prompt Sentence Examples

[0703] "Currently, the user is located in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2 p.m. and 6 p.m. However, he feels a bit tired, so he would prefer a place where he can relax."

[0704] In this way, the system can generate and modify optimal sightseeing plans taking into account the user's emotions and real-time situations.

[0705] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0706] Step 1:

[0707] Entering user information

[0708] The user uses the device's UI to input their current location, time zone, and preferences. For example, the user inputs "Shibuya," the time zone "14:00 to 18:00," and the preferences "cafes and shopping." At this time, the device's camera and microphone are used to analyze the user's facial expressions and voice and recognize their emotions. Based on the input, the device collects the user's input data and emotional data. The output is the user's current location, time zone, preferences, and emotional data.

[0709] Step 2:

[0710] Sending data

[0711] The device encodes the user's input data and recognized emotion data into JSON format. The encoded data is sent to the server as an HTTPS POST request. The input is the user's current location, time zone, preferences, and emotion data, and the output is the encoded JSON format data and a request to send it to the server. Specifically, the device sends the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired" to the server.

[0712] Step 3:

[0713] Receiving and analyzing data

[0714] The server receives JSON formatted data sent from the device. It analyzes the received data to understand the user's current location, time zone, preferences, and emotions. The input is the JSON formatted data sent from the device, and the output is the analysis results: current location, time zone, preferences, and emotions. Specifically, the server receives the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired," and analyzes and extracts each item.

[0715] Step 4:

[0716] Retrieving External Data

[0717] The server sends requests to the appropriate database or API to obtain external data such as geographic information, restaurant ratings, tourist attraction reviews, and event information. The input is the analyzed user's current location and time zone information, and the output is the data obtained from the external API. Specifically, the server sends requests to the Yelp API or Google Places API to obtain rating information for cafes and shopping spots in the "Shibuya" area.

[0718] Step 5:

[0719] Generate a sightseeing plan

[0720] The server combines the user's input data, recognized emotion data, and acquired external data to generate a sightseeing plan. It uses a machine learning algorithm to calculate the optimal plan. The input is the user's current location, time period, preferences, emotion data, and external data, and the output is the generated sightseeing plan. Specifically, the server creates a plan combining relaxing cafes and popular shopping spots based on the information "Shibuya," "14:00-18:00," "Cafe A, Shopping B, Event C," and "Tired."

[0721] Step 6:

[0722] Submitting and Viewing Plans

[0723] The server sends the generated sightseeing plan to the user's device. The device visually displays the received plan to the user. The input is the sightseeing plan generated by the server, and the output is the specific plan information displayed on the device. Specifically, the server sends the plan "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Event C" to the device, and the device displays it to the user in a map app or list format.

[0724] Step 7:

[0725] Real-time correction

[0726] The user inputs schedule changes or real-time information (e.g., train delays) into the device. The device sends this new information to the server. The server regenerates the sightseeing plan based on the new information and sends it back to the device. The input is the changed information the user input into the device and the information sent to the server, and the output is the revised sightseeing plan. Specifically, the user inputs "train delay," and the server generates a new plan "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Event C," which is sent to the device and displayed.

[0727] (Application example 2)

[0728] 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."

[0729] Conventional sightseeing plan generation systems create plans based on the user's current location, preferences, and behavioral data, but they do not fully consider the user's real-time emotions or environmental changes, which limits the optimization of the user experience. There is also the issue of ineffective personalized store guidance in physical stores.

[0730] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's current location; means for inputting information about the user's preferences; means for inputting data about the user's behavior; means for transmitting the input information to the server; means for receiving the transmitted information and acquiring geographic information, restaurant reviews, tourist destination reputations, and event information; means for generating a tour plan based on the acquired information; means for transmitting the generated tour plan to the user's terminal; means for displaying the transmitted tour plan to the user; means for inputting changes to the user's plans and real-time information; means for transmitting the input change information to the server; means for revising the tour plan based on the change information; means for transmitting and displaying the revised plan to the terminal; means for providing personalized store guidance based on the input preference information and behavior data; means for recognizing emotions using the user's camera and microphone; means for reflecting the recognized emotions in the tour plan; and means for modifying recommendations in real time based on the user's movement information and environmental changes. This enables more personalized tour plans and store guidance that take into account the user's emotions and environmental changes.

[0731] The "means for inputting user's current location information" refers to a device or software that provides an interface for obtaining and inputting the user's current location information.

[0732] "Means for inputting user preference information" refers to a device or software that provides an interface for inputting user preferences and interests.

[0733] "Means for inputting user behavioral data" refers to a device or software that provides an interface for inputting user behavior history and activity data.

[0734] The "means for transmitting input information to a server" refers to a device or software that transmits various data input by a user to a server via a communication means such as the Internet.

[0735] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to a device or software that obtains related external data based on the user data received by the server.

[0736] The "means for generating a sightseeing plan based on the acquired information" refers to a device or software that automatically generates an optimal sightseeing plan based on the received data and the acquired external data.

[0737] The "means for transmitting the generated tour plan to the user's terminal" is a device or software that transmits the tour plan generated by the server to the terminal used by the user.

[0738] The "means for displaying the transmitted travel itinerary to the user" refers to a device or software that provides an interface for visually displaying the received travel itinerary on the user's terminal.

[0739] "Means for inputting user schedule changes and real-time information" refers to a device or software that provides an interface for users to input schedule changes and real-time information about the current situation.

[0740] The "means for transmitting input change information to the server" refers to a device or software that transmits change information input by the user to the server.

[0741] The "means for modifying a tour plan based on change information" is a device or software that recalculates and modifies an existing tour plan based on received change information.

[0742] The "means for transmitting the revised itinerary to the terminal and displaying it" refers to a device or software that transmits the revised travel itinerary to the user's terminal and displays it.

[0743] "Means for providing personalized store guidance based on input preference information and behavioral data" refers to a device or software that automatically generates and provides optimal store guidance based on the user's past preferences and behavior.

[0744] "Means for recognizing emotions using the user's camera and microphone" refers to devices or software that use the camera and microphone installed on the device to analyze the user's facial expressions and voice and recognize emotions.

[0745] The "means for reflecting the recognized emotions in the sightseeing plan" is a device or software that adjusts the sightseeing plan based on the recognized emotional information of the user.

[0746] The "means for modifying recommendations in real time based on user movement information and environmental changes" refers to a device or software that dynamically modifies the current recommended plan based on user movement information and environmental change information received in real time.

[0747] This invention relates to a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user terminal, a server, and multiple input / output means.

[0748] 1. System Configuration

[0749] 1.1 User Device

[0750] It provides a user interface (UI) for inputting user location information, preferences, and behavioral data. The UI is installed on a mobile device such as a smartphone or tablet and also uses a camera and microphone. The user terminal also includes data transmission means, reception means, and display means.

[0751] 1.2 Server

[0752] The server analyzes the information received from the user's device (location information, preferences, behavioral data, and emotional data) and also acquires external data such as geographical information, restaurant reviews, tourist attraction reputations, and event information. It then generates an optimal sightseeing plan based on the received data and the acquired external data, and sends the results back to the user's device. The server performs these tasks using machine learning algorithms (e.g., Google Cloud Vision API, IBM Watson Tone Analyzer).

[0753] 2. Implementation form

[0754] 2.1 Data Collection and Transmission

[0755] A user uses a smartphone app to input their current location (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and behavioral data. The app also uses a camera and microphone to collect emotional data (e.g., tired, happy). These data are encoded into JSON format and sent to the server using an HTTPS POST request.

[0756] 2.2 Data Reception and Analysis

[0757] The server receives the data sent by the user and obtains additional data from geographic information systems (GIS) and review APIs (e.g., Google Places API, Yelp API). At the same time, it analyzes the emotional data using an emotion recognition engine, thereby generating a travel plan that best matches the user's current mood and preferences.

[0758] 2.3 Creating and Submitting a Plan

[0759] The server generates an optimal sightseeing plan using machine learning algorithms and heuristics based on the acquired data and analysis results. The generated plan is sent to the user's smartphone and displayed through a visually appealing UI. If the user provides feedback or inputs changes to the plan, this information is also sent to the server in real time, and the server regenerates the plan.

[0760] 3. Specific Examples

[0761] For example, if a user is in Shibuya and the emotion engine recognizes that they are "tired," the server will prioritize cafes and rest spots where they can relax based on the user's preferences (cafes and shopping). It will also provide recommended store information taking into account traffic conditions and weather information.

[0762] Prompt Sentence Examples

[0763] User is located in Shibuya, Tokyo, Japan. Time frame is 2:00 PM to 4:00 PM. Sentiment is tired. Preferences are cafes and shopping. Generate a list of recommended cafes and relaxing spots.

[0764] This invention allows users to always obtain the most suitable travel plan and quickly respond to various environmental and emotional changes during their trip. Furthermore, it also allows users to receive personalized guidance in physical stores, greatly improving the user experience.

[0765] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0766] Step 1:

[0767] The user launches the smartphone app and inputs their current location, preferences, and behavioral data. At this time, emotional data is also collected using the smartphone's camera and microphone. The input data is encoded in JSON format. Input includes current location information (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and emotional data (e.g., tired). The device collects this data, and the input data is output as a JSON-formatted string.

[0768] Step 2:

[0769] The data collected by the device is sent to the server using an HTTPS POST request. Data processing involves encoding the input data and creating a transmission request. The server receives this and stores the received data in a database for analysis. The input is the JSON-formatted string generated in step 1, and the output is a response code that confirms transmission to the server.

[0770] Step 3:

[0771] The server parses the received user information and retrieves additional data from geographic information systems (e.g., Google Maps API), review APIs (e.g., Yelp API), and other external data sources. This may include restaurant ratings near the current location, tourist attraction reputation, event information, etc. The input is the received data and response data from external data sources, and the output is the parsed dataset.

[0772] Step 4:

[0773] The server generates a sightseeing plan based on the analysis results and the user's preferences and emotion data. In this process, machine learning algorithms (e.g., heuristic methods, generative AI models) are used to create the optimal plan for the user. For data processing, the received data is incorporated into the algorithm, and the generated plan is output in JSON format. The input is the analysis result data and emotion data, and the output is the generated sightseeing plan data.

[0774] Step 5:

[0775] The server sends the generated itinerary to the user's device. Again, an HTTPS POST request is used for transmission. Data processing involves encoding the itinerary data and creating a transmission request. The input is the generated itinerary data, and the output is a response code sent to the user's device.

[0776] Step 6:

[0777] The terminal visually displays the received sightseeing plan to the user. The displayed content includes maps, timetables, and lists of recommended shops. The input is the sightseeing plan data received from the server, and the output is the visual information displayed on the user's screen.

[0778] Step 7:

[0779] While sightseeing, the user inputs schedule changes and real-time information (e.g., traffic delays, weather fluctuations). This information is sent back to the server from the terminal. As part of data processing, the change information is encoded and a transmission request is created. The input is the schedule change information, and the output is a response code that confirms transmission to the server.

[0780] Step 8:

[0781] The server modifies the current tour plan based on the received change information. In the modification process, an optimization recalculation is performed using the same algorithm as in step 4. The input is the change information and the existing tour plan data, and the output is the modified tour plan.

[0782] Step 9:

[0783] The server sends the modified itinerary to the user's terminal, which then displays it to the user again. The process is similar to steps 5 and 6. The input is the modified itinerary data, and the output is a response code and modified visual information to the user's terminal.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] [Third embodiment]

[0788] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0789] 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.

[0790] 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).

[0791] 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.

[0792] 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.

[0793] 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).

[0794] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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."

[0800] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data. This system is constructed by combining the user's terminal, a server, and multiple input / output means.

[0801] System configuration

[0802] 1. User Input Method:

[0803] It provides a user interface (UI) for users to input location, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0804] 2. Means of data transmission:

[0805] The terminal sends the data entered by the user to the server. Specifically, the input data is encoded and sent to the server via the Internet as an HTTPS request.

[0806] 3. Means of receiving and analyzing data:

[0807] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0808] 4. Tourist plan generation tool:

[0809] The server generates a sightseeing plan based on the acquired data, the user's preferences, and their current location, using machine learning algorithms and heuristic methods.

[0810] 5. Means of sending and displaying itineraries:

[0811] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[0812] 6. Real-time correction measures:

[0813] The user inputs changes in plans or new information (delays, weather changes, etc.) into the device, which then sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device.

[0814] Program processing flow (example)

[0815] 1. Enter your user information:

[0816] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 p.m. to 6:00 p.m.), and preferences (e.g., cafes and shopping) into the device.

[0817] 2. Data transmission:

[0818] The terminal transmits the input data to the server.

[0819] 3. Data analysis and external data acquisition:

[0820] The server analyzes the data entered by the user and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[0821] 4. Tourist plan generation:

[0822] Based on the acquired data and the user's preferences, the server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C."

[0823] 5. Submit and view your plan:

[0824] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[0825] 6. Real-time correction:

[0826] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[0827] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[0828] The device will display the revised plan to the user.

[0829] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment during their trip.

[0830] The processing flow will be explained below.

[0831] Step 1:

[0832] Users input their current location, time of day, preferences, and behavioral data into the device application. Specifically, they use the in-app interface to select "Automatic Location Capture," select departure time and duration, and choose their preferred activities (e.g., cafes, shopping, events).

[0833] Step 2:

[0834] The device sends the entered user information to the server. Specifically, it encodes the input data into JSON format and sends an HTTPS POST request to the server.

[0835] Step 3:

[0836] The server analyzes the data it receives: when it receives a POST request, it decodes the data and updates the user profile (preferences, behavioral data).

[0837] Step 4:

[0838] The server obtains the necessary external data (geographical information, restaurant ratings, tourist attraction reviews, event information) from a database or API. Specifically, it sends requests using various APIs (e.g., geographical information API, review data API) to collect the relevant data.

[0839] Step 5:

[0840] The server generates a sightseeing plan based on the data acquired and user information. Specifically, it uses machine learning models and heuristic algorithms to generate a plan that suits the user's preferences.

[0841] Step 6:

[0842] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[0843] Step 7:

[0844] The device analyzes the received itinerary and presents it visually to the user, specifically by decoding the received data and displaying it in the application's UI components (maps, timetables, lists of detailed information, etc.).

[0845] Step 8:

[0846] The user inputs changes to their plans or new information in real time (e.g., delays, weather changes) into the device, typically using forms and options within the app to enter changes.

[0847] Step 9:

[0848] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[0849] Step 10:

[0850] The server modifies the existing tour plan based on the new information, receiving the changes and running them through a data analysis and optimization algorithm again to generate a new plan.

[0851] Step 11:

[0852] The server sends the revised itinerary to the user's device in JSON format.

[0853] Step 12:

[0854] The device receives the revised plan and displays it to the user by parsing the received data again and updating the UI components to display it.

[0855] Example 1

[0856] 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."

[0857] Current travel plan generation systems often lack the ability to immediately respond to real-time changes in users' circumstances (e.g., weather changes, traffic delays, etc.). As a result, the user experience can be marred by unexpected problems. It is also difficult to automatically generate plans that fully take into account individual users' preferences and behavioral patterns. These problems need to be solved.

[0858] 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.

[0859] In this invention, the server includes means for inputting user location information, means for inputting user preference information, means for inputting user behavior data, means for transmitting the input information to the server, means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist destination reviews, and event information, means for generating a sightseeing plan based on the acquired information, means for transmitting the generated sightseeing plan to the user's terminal, means for displaying the transmitted sightseeing plan to the user, means for inputting changes to the user's plans and real-time information, means for transmitting the input change information to the server, means for modifying the sightseeing plan based on the change information, and means for transmitting the modified plan to the terminal and displaying it. This makes it possible to generate and modify an optimal sightseeing plan that reflects real-time changes in the user's situation and individual preferences.

[0860] "Means for inputting user location information" refers to an interface for inputting information about the user's current location.

[0861] The "means for inputting user preference information" is an interface for inputting information about the user's tastes and preferences.

[0862] The "means for inputting user behavioral data" refers to an interface for inputting data regarding the user's past behavior and behavioral patterns.

[0863] The "means for transmitting input information to a server" refers to a communication means for transmitting information input by a user to a server.

[0864] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to the means by which the server obtains necessary information from external databases and APIs based on the user information received.

[0865] "Means for generating a sightseeing plan based on acquired information" refers to means for creating an optimal sightseeing plan based on acquired external information and user information.

[0866] The "means for transmitting the generated tour plan to the user's terminal" is a communication means for transmitting the tour plan generated by the server to the user's terminal.

[0867] The "means for displaying the transmitted tour plan to the user" refers to a means for visually displaying the tour plan received by the terminal to the user.

[0868] "Means for inputting user schedule changes and real-time information" refers to an interface that allows a user to input schedule changes and information that occurs in real time (e.g., traffic delays or weather changes).

[0869] The "means for transmitting input change information to the server" refers to a communication means for transmitting change information input by the user to the server.

[0870] The "means for amending a sightseeing plan based on change information" refers to a means for amending an existing sightseeing plan based on change information received by the server.

[0871] The "means for transmitting the revised tour plan to the terminal and displaying it" is a means for transmitting the revised tour plan from the server to the terminal and for the terminal to display it to the user.

[0872] This invention relates to a system that generates and modifies optimized sightseeing plans in real time using user location information, preferences, and behavioral data. This system is constructed by combining user terminals, a server, and multiple input / output means.

[0873] 1. User Input Method

[0874] Users input their location, preferences, and behavioral data through applications installed on mobile devices such as smartphones and tablets, specifically iOS or Android apps.

[0875] 2. Data transmission method

[0876] The terminal encodes the data entered by the user and sends it to the server via the Internet as an HTTPS request, which ensures secure transmission of the data. The specific communication method used is the HTTP library.

[0877] 3. Means of receiving and analyzing data

[0878] The server receives and analyzes the data sent from the device. It also retrieves necessary external data, such as geographic information, restaurant ratings, tourist attraction reviews, and event information, from databases and APIs. Specific software used includes MySQL and Google Maps API.

[0879] 4. Tourist plan generation tool

[0880] The server generates a sightseeing plan based on the acquired data and user input. Using machine learning algorithms (e.g., Scikit-learn) and heuristic methods, optimization calculations are performed based on the user's preferences and behavioral patterns. This generation process suggests the best combination of tourist spots for the user.

[0881] 5. Means of sending and displaying travel plans

[0882] The server sends the generated itinerary to the device, which receives it and displays it visually to the user. Display methods include map display, timetable, detailed information list, etc. Google Maps API is used as a specific visualization tool.

[0883] 6. Real-time correction methods

[0884] If the user changes plans or inputs new information (e.g., delays, weather changes) into the device, the device sends that information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device, ensuring that the user always gets the optimal plan.

[0885] Specific usage examples and prompt sentence examples

[0886] Usage example:

[0887] The user enters "Current location: Shibuya, Tokyo," "Time: 2:00 PM to 6:00 PM," and "Favorites: Cafes and shopping" into the dedicated app. The device sends this information to the server, which analyzes it to obtain geographic information for the Shibuya area, cafe ratings, shopping spot reputations, and event information. The server then generates a sightseeing plan based on this data and sends it to the device, such as "2:00 PM - Cafe A," "3:30 PM - Shopping Spot B," and "5:00 PM - Special Event C." The device then visually displays this information to the user.

[0888] Example prompt sentence:

[0889] "The user wants to enjoy cafes and shopping in Shibuya between 2pm and 6pm. Please generate the best sightseeing itinerary based on this."

[0890] This system allows users to have the best possible sightseeing experience according to the situation at hand, and by updating information in real time, it is possible to respond flexibly to unforeseen circumstances during travel.

[0891] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0892] A detailed explanation of the program divided into processing steps

[0893] Step 1: Enter your user information

[0894] Users use the mobile app to input their location information, preference information, and behavioral data. For example, users input "Current location: Shibuya, Tokyo," "Time period: 2:00 PM to 6:00 PM," and "Preferences: Cafes and shopping."

[0895] Input: Current location, time zone, preferences

[0896] Output: Encoded user information data

[0897] Specific behavior: The user enters the required information on the application screen and taps the input button.

[0898] Step 2: Send the data

[0899] The terminal encodes the data entered by the user and sends it to the server as an HTTPS request.

[0900] Input: Encoded user information data

[0901] Output: HTTPS request

[0902] Specific operation: The device is connected to the network and sends the data entered by the user to the server.

[0903] Step 3: Receiving data and acquiring external data

[0904] The server receives and analyzes the data sent from the device, then retrieves external data such as geographical information, restaurant ratings, tourist attraction reviews, and event information from databases and APIs.

[0905] Input: HTTPS request, encoded user information data

[0906] Output: Analyzed user information data, external data (geographical information, restaurant ratings, tourist destination reviews, event information)

[0907] Specific operation: The server analyzes the user information and, based on that information, sends a request to an external API (e.g., Google Maps API, Yelp API) to obtain the necessary data.

[0908] Step 4: Data analysis and tourism plan generation

[0909] The server generates a sightseeing plan based on the analyzed user information data and external data, and performs optimization calculations using machine learning algorithms (e.g., Scikit-learn) and heuristic methods.

[0910] Input: Parsed user information data, external data

[0911] Output: Generated itinerary

[0912] What it does: The server processes the data and runs an algorithm that generates a sightseeing itinerary based on the user's preferences and behavioral patterns.

[0913] Step 5: Submit and view your plan

[0914] The server encodes the generated travel plan and sends it to the terminal as an HTTPS request, and the terminal displays the received travel plan to the user.

[0915] Input: Generated itinerary

[0916] Output: HTTPS request, itinerary displayed

[0917] Specific operation: The server sends the sightseeing plan to the device, and the device displays the information visually in the application (e.g., map display, timetable, detailed list).

[0918] Step 6: Real-time correction

[0919] The user inputs changes in plans or new information (e.g., train delays, weather changes), and the device sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device for display.

[0920] Input: Schedule change information, real-time information

[0921] Output: Modified itinerary

[0922] What happens: The user enters new information into the app, the device sends it to the server, the server generates a revised plan and sends it back to the device, and the device displays the new plan to the user.

[0923] Through these steps, the system of the present invention provides the optimal sightseeing plan according to the user's situation and preferences, and can also update it in real time.

[0924] (Application example 1)

[0925] 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."

[0926] Conventional food delivery systems face the challenge of effectively utilizing individual information such as a user's current location, preferences, and past order history to propose optimal meal plans in real time. Furthermore, plans are not quickly adjusted to take into account real-time information such as delivery status and weather, resulting in a poor user experience. There is a need to solve these challenges and provide users with an efficient and satisfying food delivery experience.

[0927] 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.

[0928] In this invention, the server includes means for generating a meal plan based on the acquired information, means for transmitting the generated meal plan to the user's terminal, and means for integrating weather information, delivery status information, and real-time order data when generating and modifying the meal plan. This allows the server to propose an optimal meal plan in real time, taking into account the user's current location, preferences, past order history, etc., and to dynamically modify the plan based on the latest information on delivery, weather, etc.

[0929] "Means for inputting user's current location information" refers to means for obtaining the user's current physical location information. This information is obtained in real time using the GPS function of a smartphone or other mobile device.

[0930] "Means for inputting user preference information" refers to a means for inputting a user's preferences and tastes for food and services, allowing the user to select their preferred genres and specific menu items through the application interface.

[0931] "Means for inputting user behavior data" refers to means for collecting and inputting data related to a user's past order history and behavioral patterns, which will enable analysis based on the user's past trends.

[0932] "Means for transmitting input information to a server" refers to means for transmitting the location information, preference information, and behavioral data input by the user to a server via the Internet. The data is transmitted securely in an encoded format.

[0933] "Means for receiving transmitted information and acquiring geographic information, restaurant ratings, local reputation, and event information" refers to the means for acquiring related geographic information, restaurant ratings, local reputation, and event information based on the user information received by the server. Information is acquired using external APIs and databases.

[0934] The "means for generating a meal plan based on the acquired information" refers to a means for analyzing the acquired data and generating an optimal meal plan for the user based on that data. The plan is generated using machine learning algorithms or heuristic methods.

[0935] The "means for transmitting the generated meal plan to the user's device" refers to the means for transmitting the meal plan generated by the server to the user's device such as a smartphone or tablet. The data is encoded and transmitted securely.

[0936] "Means for displaying the transmitted meal plan to the user" means means for visually displaying the received meal plan on the user's device, including a map, list, timetable, etc.

[0937] "Means for users to input schedule changes and real-time information" refers to a means for users to input real-time information such as schedule changes, delivery delays, weather changes, etc. The information can be easily input using the app's interface.

[0938] The "means for transmitting the entered change information to the server" refers to a means for transmitting the change information entered by the user to the server. The data is encoded and transmitted securely over the Internet.

[0939] The "means for modifying the meal plan based on the change information" refers to a means for modifying the generated meal plan based on the change information received by the server. The modified plan is recalculated to adapt to the user's new needs.

[0940] The "means for transmitting the revised plan to the terminal and displaying it" refers to a means for transmitting the revised plan from the server back to the user's terminal and visually displaying it. The revised plan is displayed on the user's screen in the same way as the original plan.

[0941] This invention is a system that generates and modifies optimal meal plans in real time based on a user's current location, preferences, past ordering history, etc. This system is constructed by combining a user's terminal, a server, and multiple input / output means.

[0942] System configuration

[0943] 1. User Input Method:

[0944] An interface will be provided on a smartphone or tablet for users to input their current location, preferences, past order history, etc. Specifically, a UI will be implemented that allows users to obtain location information via GPS, select their preferred genre, and view and select past order history.

[0945] 2. Means of data transmission:

[0946] The input information is sent to the server using an HTTPS request. The input data is encoded in JSON format and sent via SSL / TLS for security reasons.

[0947] 3. Means of receiving and analyzing data:

[0948] The server receives and analyzes the data sent by users, using data analysis libraries such as Pandas, and obtains geographic information, restaurant ratings, local reputation, and event information through external APIs (e.g., Google Maps API, Yelp API).

[0949] 4. Meal plan generator:

[0950] Based on the acquired data, a meal plan is generated, using machine learning algorithms (e.g., k-means clustering, random forest) and heuristic methods to perform optimization calculations based on the user's preferences and constraints.

[0951] 5. Means of sending and displaying itineraries:

[0952] The meal plan generated by the server is then encoded into JSON format and sent to the user's device, where it is received and displayed visually, including timetables, maps, and detailed information lists.

[0953] 6. Real-time correction measures:

[0954] When the user enters new information (e.g., delivery delay, weather change) into the device, the device sends that information to the server, which then modifies the meal plan based on the new information and sends the modified plan back to the device for display.

[0955] Hardware and software used

[0956] Hardware:

[0957] Smartphone (iOS or Android)

[0958] Server (AWS, Google Cloud, etc.)

[0959] software:

[0960] Smartphone app (Swift or Kotlin)

[0961] Server side (Python, Node.js, etc.)

[0962] Databases and analytical libraries (Pandas, scikit-learn)

[0963] External API (Google Maps API, Yelp API)

[0964] Specific examples

[0965] For example, suppose a user is in Shinjuku and is looking for a Japanese lunch around 12:30. The user opens the smartphone app and types, "I'm looking for a Japanese lunch around 12:30 in the Shinjuku area. Are there any recommended restaurants?" This information is sent to the server in real time, and the server generates an optimal meal plan based on geographic information and restaurant reviews. As a result, the user might be offered a plan such as "Sushi at Restaurant A at 12:30" or "Matcha Latte at Cafe B at 1:15 PM." If the user reports issues such as delivery delays, the server dynamically modifies the plan and offers it again.

[0966] As described above, the present invention is a system that provides users with an efficient and satisfying food delivery experience.

[0967] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0968] Step 1:

[0969] A user opens the app on their smartphone and enters their current location (e.g., Shinjuku), time of day (e.g., lunch), preferences (e.g., Japanese food), and past ordering history. The input data is encoded in JSON format and sent to the server via an HTTPS request. This provides the server with specific information about the user.

[0970] Step 2:

[0971] The server receives the input JSON data and deserializes it. It then analyzes the user's current location, preferences, and past order history using a data analysis library such as Pandas. This allows the server to understand the user's basic needs.

[0972] Step 3:

[0973] The server uses external APIs (e.g., Google Maps API, Yelp API) to obtain geographic information, restaurant ratings, local reputation, event information, etc. based on the received data. The obtained data is stored in a database on the server. This allows the server to collect the latest information about services desired by users.

[0974] Step 4:

[0975] The server generates a meal plan based on the acquired data. It uses machine learning algorithms (e.g., k-means clustering, random forest) to perform optimization calculations based on the user's preferences and constraints. The generated meal plan is encoded in JSON format, allowing the server to propose a plan that best suits the user's needs.

[0976] Step 5:

[0977] The server sends the generated meal plan to the user's device. The plan received by the device is deserialized and displayed visually. For example, "12:30 - Sushi at Restaurant A" and "13:15 - Matcha Latte at Cafe B" are displayed to the user. This allows the user to easily check the proposed plan.

[0978] Step 6:

[0979] The user enters real-time information into the app, such as a change in schedule or a delivery delay. The new information is again encoded into JSON format and sent to the server via an HTTPS request, which reports the new status from the device to the server.

[0980] Step 7:

[0981] The server then modifies the generated meal plan based on the new information received, again using machine learning algorithms and heuristics to recalculate and adapt to the user's new needs. The modified plan is then encoded in JSON format and sent to the device, allowing the server to quickly adapt to user changes.

[0982] Step 8:

[0983] The device receives the revised plan, deserializes it, and displays it visually. The revised plan includes new time and location information, such as "13:00 - Sushi at Restaurant A" and "13:45 - Matcha Latte at Cafe B." This allows the user to always see the latest plan.

[0984] Through these steps, the system is able to provide users with an efficient and satisfying food delivery experience.

[0985] 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.

[0986] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also includes a function that recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[0987] System configuration

[0988] 1. User Input Method:

[0989] It provides a user interface (UI) for users to input their current location, time zone, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[0990] 2. Means of data transmission:

[0991] The device sends the data entered by the user and the emotional data recognized by the emotion engine to the server. Specifically, the device encodes the input data and emotional data into JSON format and sends an HTTPS POST request to the server.

[0992] 3. Means of receiving and analyzing data:

[0993] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[0994] 4. Emotion recognition means:

[0995] The device's built-in emotion engine recognizes the user's emotions through facial, voice, and text analysis, and this data is reflected in the creation of a travel plan.

[0996] 5. Tourist plan generation tool:

[0997] The server generates a sightseeing plan based on the acquired external data, user preferences, and emotional data, using machine learning algorithms and heuristic methods.

[0998] 6. Means of sending and displaying itineraries:

[0999] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[1000] 7. Real-time correction measures:

[1001] The user inputs changes in plans or new real-time information (e.g., delays, weather changes) into the device, which then sends the information to the server, which then modifies the sightseeing plan based on the new information and sends it back to the device.

[1002] Program processing flow (example)

[1003] 1. Enter your user information:

[1004] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 PM to 6:00 PM), and preferences (e.g., cafes and shopping) into the device. In addition, the emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and recognize their current emotion (e.g., happy, tired).

[1005] 2. Data transmission:

[1006] The terminal transmits the input user information and recognized emotion data to the server.

[1007] 3. Data analysis and external data acquisition:

[1008] The server analyzes the user's input data and emotional data, and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[1009] 4. Tourist plan generation:

[1010] The server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C" based on the acquired data, the user's preferences, and the recognized emotional data. For example, if the user is recognized as "tired," the plan will prioritize relaxing cafes and rest spots.

[1011] 5. Submit and view your plan:

[1012] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[1013] 6. Real-time correction:

[1014] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[1015] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[1016] The device will display the revised plan to the user.

[1017] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment or emotions during their trip.

[1018] The processing flow will be explained below.

[1019] Step 1:

[1020] The user inputs their current location (e.g., Shibuya, Tokyo), time of day (e.g., 2 p.m. to 6 p.m.), preferences (e.g., cafes and shopping), and behavioral data into the device's application. Furthermore, the emotion engine analyzes the user's facial expressions and voice via the device's camera and microphone to recognize their current emotion (e.g., happy, tired).

[1021] Step 2:

[1022] The device sends the input user information and recognized emotion data to the server. Specifically, the input data and emotion data are encoded in JSON format and sent to the server as an HTTPS POST request.

[1023] Step 3:

[1024] The server receives and analyzes the transmitted data, for example, decoding the user's location, time zone, and preferences to update the user profile, and analyzing the emotional data to determine the user's current emotional state.

[1025] Step 4:

[1026] The server obtains the necessary external data (e.g., geographic information, restaurant ratings, tourist attraction reviews, and information about nearby events). Specifically, it sends requests using various APIs (e.g., geographic information API, review data API) to collect the relevant data.

[1027] Step 5:

[1028] The server generates a sightseeing plan based on the acquired data, user information, and emotional data. For example, if the user's emotional state is recognized as "tired," the plan will prioritize relaxing cafes and rest areas. The plan is optimized using machine learning and heuristic algorithms.

[1029] Step 6:

[1030] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[1031] Step 7:

[1032] The device analyzes the received travel plans and visually displays them to the user. Specifically, it decodes the received data and displays it in the application's UI components (maps, timetables, detailed information lists, etc.).

[1033] Step 8:

[1034] The user inputs changes to plans or new real-time information (e.g., train delays, weather changes) using in-app forms and options to enter changes.

[1035] Step 9:

[1036] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[1037] Step 10:

[1038] The server modifies the existing sightseeing plan based on the new information, for example, by analyzing and optimizing the data again based on the changed arrival time or new emotion data, and generates a new plan.

[1039] Step 11:

[1040] The server sends the revised itinerary to the user's device in JSON format.

[1041] Step 12:

[1042] The device receives the revised plan and displays it to the user. Specifically, it parses the received data again and updates the UI components to display it. For example, it displays "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[1043] In this way, by using the emotion engine, users can obtain more personalized and adaptive sightseeing plans in real time that are tailored to their emotions.

[1044] Example 2

[1045] 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."

[1046] Conventional sightseeing plan generation systems only considered the user's current location, preferences, and behavioral data, which meant they lacked the ability to adapt to user emotions or real-time changes in location and situation. Furthermore, it was difficult to revise sightseeing plans in real time, which often meant they were unable to provide the optimal plan for the user.

[1047] 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.

[1048] In this invention, the server includes means for recognizing the user's emotions, means for transmitting input information and emotional data to the server, and means for receiving the transmitted information and emotional data and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information. This makes it possible to generate and modify a tour plan that flexibly responds to the user's emotions and real-time changes in the situation.

[1049] The "means for inputting user's current location information" refers to a device that has an interface or function that allows the user to input their current location.

[1050] The "means for inputting user preference information" refers to a device that has an interface or function that allows a user to input his or her preferences and activities of interest.

[1051] The "means for inputting user behavioral data" refers to a device that has an interface or function for inputting data regarding the user's past behavior and habits.

[1052] "Means for recognizing user emotions" refers to a device that has algorithms and functions for analyzing the user's facial expressions, voice, and text to detect and recognize the user's emotions.

[1053] "Means for transmitting input information and emotional data to a server" refers to a device that has the technology and functions to transmit data input by a user and recognized emotional data to a server via a network.

[1054] The "means for receiving transmitted information and emotion data" refers to a device that allows the server to receive data transmitted from the user terminal, and often uses a secure communication protocol.

[1055] "Means of obtaining geographic information, restaurant ratings, tourist destination reputation, and event information" refers to the functions and algorithms that allow the server to obtain the necessary geographic information and rating information from external databases and APIs.

[1056] The "means for generating a sightseeing plan based on acquired information and emotional data" is a device that has algorithms and models for integrating collected data and user emotional information to generate an optimal sightseeing plan.

[1057] The "means for transmitting the generated tour plan to the user's terminal" is a device having the technology and functions for transmitting the tour plan generated by the server to the user's terminal via the network.

[1058] The "means for displaying the transmitted tour plan to the user" refers to a device that has an interface or function for the user's terminal to visually display the received tour plan.

[1059] "Means for inputting user schedule changes and real-time information" means a device that has an interface or functionality that allows a user to change their original schedule or input real-time information (e.g., delays, weather changes) into the terminal.

[1060] The "means for transmitting input change information to the server" is a device having the technology and function for transmitting change information input by the user from the terminal to the server.

[1061] The "means for modifying a tour plan based on change information" is a device that has an algorithm or model for modifying and regenerating an existing tour plan based on change information received by the server.

[1062] The "means for transmitting the revised tour plan to the terminal and displaying it" refers to a device that has the technology and functions for the server to transmit the revised tour plan to the user's terminal and for the terminal to display it.

[1063] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preference information, and behavioral data, and also includes a function to recognize the user's emotions and reflect them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[1064] 1. Hardware and Software Configuration

[1065] This system includes a user interface (UI) installed on mobile devices such as smartphones and tablets, a server, and an emotion recognition engine. User data is encoded in JSON format and transmitted by sending an HTTPS POST request to the server. Specifically, the system uses the following hardware and software:

[1066] Devices: smartphones, tablets

[1067] Server: High performance server (e.g. AWS EC2)

[1068] Emotion recognition engine: AI models for facial expression analysis, speech analysis, and text analysis (e.g., Google Cloud AutoML, Amazon Rekognition)

[1069] Databases and APIs: External APIs and databases for retrieving geographic information, restaurant ratings, tourist attraction reviews, and event information (e.g., Google Places API, Yelp API)

[1070] 2. System processing flow

[1071] When a user uses their device to input their current location, preferences, and emotional data, the device sends this data to the server. The server analyzes the received data and obtains additional information from external APIs. The server uses a machine learning algorithm to generate an optimal sightseeing plan based on the obtained data and the user's preferences and emotions. The generated sightseeing plan is sent from the server to the user's device and displayed visually on the device. If the user changes their plans or enters real-time information, the device sends that information to the server, which then revises the plan.

[1072] 3. Examples of concrete examples and prompts

[1073] As a concrete example, consider a situation where a user is in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2pm and 6pm, but is a little tired. The following data is entered:

[1074] Current location: Shibuya

[1075] Time: 14:00 to 18:00

[1076] Likes: Cafes and shopping

[1077] Emotion: Tired

[1078] In this case, the system generates the following prompt for the itinerary:

[1079] Prompt Sentence Examples

[1080] "Currently, the user is located in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2 p.m. and 6 p.m. However, he feels a bit tired, so he would prefer a place where he can relax."

[1081] In this way, the system can generate and modify optimal sightseeing plans taking into account the user's emotions and real-time situations.

[1082] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1083] Step 1:

[1084] Entering user information

[1085] The user uses the device's UI to input their current location, time zone, and preferences. For example, the user inputs "Shibuya," the time zone "14:00 to 18:00," and the preferences "cafes and shopping." At this time, the device's camera and microphone are used to analyze the user's facial expressions and voice and recognize their emotions. Based on the input, the device collects the user's input data and emotional data. The output is the user's current location, time zone, preferences, and emotional data.

[1086] Step 2:

[1087] Sending data

[1088] The device encodes the user's input data and recognized emotion data into JSON format. The encoded data is sent to the server as an HTTPS POST request. The input is the user's current location, time zone, preferences, and emotion data, and the output is the encoded JSON format data and a request to send it to the server. Specifically, the device sends the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired" to the server.

[1089] Step 3:

[1090] Receiving and analyzing data

[1091] The server receives JSON formatted data sent from the device. It analyzes the received data to understand the user's current location, time zone, preferences, and emotions. The input is the JSON formatted data sent from the device, and the output is the analysis results: current location, time zone, preferences, and emotions. Specifically, the server receives the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired," and analyzes and extracts each item.

[1092] Step 4:

[1093] Retrieving External Data

[1094] The server sends requests to the appropriate database or API to obtain external data such as geographic information, restaurant ratings, tourist attraction reviews, and event information. The input is the analyzed user's current location and time zone information, and the output is the data obtained from the external API. Specifically, the server sends requests to the Yelp API or Google Places API to obtain rating information for cafes and shopping spots in the "Shibuya" area.

[1095] Step 5:

[1096] Generate a sightseeing plan

[1097] The server combines the user's input data, recognized emotion data, and acquired external data to generate a sightseeing plan. It uses a machine learning algorithm to calculate the optimal plan. The input is the user's current location, time period, preferences, emotion data, and external data, and the output is the generated sightseeing plan. Specifically, the server creates a plan combining relaxing cafes and popular shopping spots based on the information "Shibuya," "14:00-18:00," "Cafe A, Shopping B, Event C," and "Tired."

[1098] Step 6:

[1099] Submitting and Viewing Plans

[1100] The server sends the generated sightseeing plan to the user's device. The device visually displays the received plan to the user. The input is the sightseeing plan generated by the server, and the output is the specific plan information displayed on the device. Specifically, the server sends the plan "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Event C" to the device, and the device displays it to the user in a map app or list format.

[1101] Step 7:

[1102] Real-time correction

[1103] The user inputs schedule changes or real-time information (e.g., train delays) into the device. The device sends this new information to the server. The server regenerates the sightseeing plan based on the new information and sends it back to the device. The input is the changed information the user input into the device and the information sent to the server, and the output is the revised sightseeing plan. Specifically, the user inputs "train delay," and the server generates a new plan "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Event C," which is sent to the device and displayed.

[1104] (Application example 2)

[1105] 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."

[1106] Conventional sightseeing plan generation systems create plans based on the user's current location, preferences, and behavioral data, but they do not fully consider the user's real-time emotions or environmental changes, which limits the optimization of the user experience. There is also the issue of ineffective personalized store guidance in physical stores.

[1107] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's current location; means for inputting information about the user's preferences; means for inputting data about the user's behavior; means for transmitting the input information to the server; means for receiving the transmitted information and acquiring geographic information, restaurant reviews, tourist destination reputations, and event information; means for generating a tour plan based on the acquired information; means for transmitting the generated tour plan to the user's terminal; means for displaying the transmitted tour plan to the user; means for inputting changes to the user's plans and real-time information; means for transmitting the input change information to the server; means for revising the tour plan based on the change information; means for transmitting and displaying the revised plan to the terminal; means for providing personalized store guidance based on the input preference information and behavior data; means for recognizing emotions using the user's camera and microphone; means for reflecting the recognized emotions in the tour plan; and means for modifying recommendations in real time based on the user's movement information and environmental changes. This enables more personalized tour plans and store guidance that take into account the user's emotions and environmental changes.

[1108] The "means for inputting user's current location information" refers to a device or software that provides an interface for obtaining and inputting the user's current location information.

[1109] "Means for inputting user preference information" refers to a device or software that provides an interface for inputting user preferences and interests.

[1110] "Means for inputting user behavioral data" refers to a device or software that provides an interface for inputting user behavior history and activity data.

[1111] The "means for transmitting input information to a server" refers to a device or software that transmits various data input by a user to a server via a communication means such as the Internet.

[1112] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to a device or software that obtains related external data based on the user data received by the server.

[1113] The "means for generating a sightseeing plan based on the acquired information" refers to a device or software that automatically generates an optimal sightseeing plan based on the received data and the acquired external data.

[1114] The "means for transmitting the generated tour plan to the user's terminal" is a device or software that transmits the tour plan generated by the server to the terminal used by the user.

[1115] The "means for displaying the transmitted travel itinerary to the user" refers to a device or software that provides an interface for visually displaying the received travel itinerary on the user's terminal.

[1116] "Means for inputting user schedule changes and real-time information" refers to a device or software that provides an interface for users to input schedule changes and real-time information about the current situation.

[1117] The "means for transmitting input change information to the server" refers to a device or software that transmits change information input by the user to the server.

[1118] The "means for modifying a tour plan based on change information" is a device or software that recalculates and modifies an existing tour plan based on received change information.

[1119] The "means for transmitting the revised itinerary to the terminal and displaying it" refers to a device or software that transmits the revised travel itinerary to the user's terminal and displays it.

[1120] "Means for providing personalized store guidance based on input preference information and behavioral data" refers to a device or software that automatically generates and provides optimal store guidance based on the user's past preferences and behavior.

[1121] "Means for recognizing emotions using the user's camera and microphone" refers to devices or software that use the camera and microphone installed on the device to analyze the user's facial expressions and voice and recognize emotions.

[1122] The "means for reflecting the recognized emotions in the sightseeing plan" is a device or software that adjusts the sightseeing plan based on the recognized emotional information of the user.

[1123] The "means for modifying recommendations in real time based on user movement information and environmental changes" refers to a device or software that dynamically modifies the current recommended plan based on user movement information and environmental change information received in real time.

[1124] This invention relates to a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user terminal, a server, and multiple input / output means.

[1125] 1. System Configuration

[1126] 1.1 User Device

[1127] It provides a user interface (UI) for inputting user location information, preferences, and behavioral data. The UI is installed on a mobile device such as a smartphone or tablet and also uses a camera and microphone. The user terminal also includes data transmission means, reception means, and display means.

[1128] 1.2 Server

[1129] The server analyzes the information received from the user's device (location information, preferences, behavioral data, and emotional data) and also acquires external data such as geographical information, restaurant reviews, tourist attraction reputations, and event information. It then generates an optimal sightseeing plan based on the received data and the acquired external data, and sends the results back to the user's device. The server performs these tasks using machine learning algorithms (e.g., Google Cloud Vision API, IBM Watson Tone Analyzer).

[1130] 2. Implementation form

[1131] 2.1 Data Collection and Transmission

[1132] A user uses a smartphone app to input their current location (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and behavioral data. The app also uses a camera and microphone to collect emotional data (e.g., tired, happy). These data are encoded into JSON format and sent to the server using an HTTPS POST request.

[1133] 2.2 Data Reception and Analysis

[1134] The server receives the data sent by the user and obtains additional data from geographic information systems (GIS) and review APIs (e.g., Google Places API, Yelp API). At the same time, it analyzes the emotional data using an emotion recognition engine, thereby generating a travel plan that best matches the user's current mood and preferences.

[1135] 2.3 Creating and Submitting a Plan

[1136] The server generates an optimal sightseeing plan using machine learning algorithms and heuristics based on the acquired data and analysis results. The generated plan is sent to the user's smartphone and displayed through a visually appealing UI. If the user provides feedback or inputs changes to the plan, this information is also sent to the server in real time, and the server regenerates the plan.

[1137] 3. Specific Examples

[1138] For example, if a user is in Shibuya and the emotion engine recognizes that they are "tired," the server will prioritize cafes and rest spots where they can relax based on the user's preferences (cafes and shopping). It will also provide recommended store information taking into account traffic conditions and weather information.

[1139] Prompt Sentence Examples

[1140] User is located in Shibuya, Tokyo, Japan. Time frame is 2:00 PM to 4:00 PM. Sentiment is tired. Preferences are cafes and shopping. Generate a list of recommended cafes and relaxing spots.

[1141] This invention allows users to always obtain the most suitable travel plan and quickly respond to various environmental and emotional changes during their trip. Furthermore, it also allows users to receive personalized guidance in physical stores, greatly improving the user experience.

[1142] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1143] Step 1:

[1144] The user launches the smartphone app and inputs their current location, preferences, and behavioral data. At this time, emotional data is also collected using the smartphone's camera and microphone. The input data is encoded in JSON format. Input includes current location information (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and emotional data (e.g., tired). The device collects this data, and the input data is output as a JSON-formatted string.

[1145] Step 2:

[1146] The data collected by the device is sent to the server using an HTTPS POST request. Data processing involves encoding the input data and creating a transmission request. The server receives this and stores the received data in a database for analysis. The input is the JSON-formatted string generated in step 1, and the output is a response code that confirms transmission to the server.

[1147] Step 3:

[1148] The server parses the received user information and retrieves additional data from geographic information systems (e.g., Google Maps API), review APIs (e.g., Yelp API), and other external data sources. This may include restaurant ratings near the current location, tourist attraction reputation, event information, etc. The input is the received data and response data from external data sources, and the output is the parsed dataset.

[1149] Step 4:

[1150] The server generates a sightseeing plan based on the analysis results and the user's preferences and emotion data. In this process, machine learning algorithms (e.g., heuristic methods, generative AI models) are used to create the optimal plan for the user. For data processing, the received data is incorporated into the algorithm, and the generated plan is output in JSON format. The input is the analysis result data and emotion data, and the output is the generated sightseeing plan data.

[1151] Step 5:

[1152] The server sends the generated itinerary to the user's device. Again, an HTTPS POST request is used for transmission. Data processing involves encoding the itinerary data and creating a transmission request. The input is the generated itinerary data, and the output is a response code sent to the user's device.

[1153] Step 6:

[1154] The terminal visually displays the received sightseeing plan to the user. The displayed content includes maps, timetables, and lists of recommended shops. The input is the sightseeing plan data received from the server, and the output is the visual information displayed on the user's screen.

[1155] Step 7:

[1156] While sightseeing, the user inputs schedule changes and real-time information (e.g., traffic delays, weather fluctuations). This information is sent back to the server from the terminal. As part of data processing, the change information is encoded and a transmission request is created. The input is the schedule change information, and the output is a response code that confirms transmission to the server.

[1157] Step 8:

[1158] The server modifies the current tour plan based on the received change information. In the modification process, an optimization recalculation is performed using the same algorithm as in step 4. The input is the change information and the existing tour plan data, and the output is the modified tour plan.

[1159] Step 9:

[1160] The server sends the modified itinerary to the user's terminal, which then displays it to the user again. The process is similar to steps 5 and 6. The input is the modified itinerary data, and the output is a response code and modified visual information to the user's terminal.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] [Fourth embodiment]

[1165] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1166] 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.

[1167] 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).

[1168] 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.

[1169] 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.

[1170] 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).

[1171] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1172] 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.

[1173] 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.

[1174] 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.

[1175] 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.

[1176] 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.

[1177] 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."

[1178] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data. This system is constructed by combining the user's terminal, a server, and multiple input / output means.

[1179] System configuration

[1180] 1. User Input Method:

[1181] It provides a user interface (UI) for users to input location, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[1182] 2. Means of data transmission:

[1183] The terminal sends the data entered by the user to the server. Specifically, the input data is encoded and sent to the server via the Internet as an HTTPS request.

[1184] 3. Means of receiving and analyzing data:

[1185] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[1186] 4. Tourist plan generation tool:

[1187] The server generates a sightseeing plan based on the acquired data, the user's preferences, and their current location, using machine learning algorithms and heuristic methods.

[1188] 5. Means of sending and displaying itineraries:

[1189] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[1190] 6. Real-time correction measures:

[1191] The user inputs changes in plans or new information (delays, weather changes, etc.) into the device, which then sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device.

[1192] Program processing flow (example)

[1193] 1. Enter your user information:

[1194] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 p.m. to 6:00 p.m.), and preferences (e.g., cafes and shopping) into the device.

[1195] 2. Data transmission:

[1196] The terminal transmits the input data to the server.

[1197] 3. Data analysis and external data acquisition:

[1198] The server analyzes the data entered by the user and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[1199] 4. Tourist plan generation:

[1200] Based on the acquired data and the user's preferences, the server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C."

[1201] 5. Submit and view your plan:

[1202] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[1203] 6. Real-time correction:

[1204] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[1205] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[1206] The device will display the revised plan to the user.

[1207] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment during their trip.

[1208] The processing flow will be explained below.

[1209] Step 1:

[1210] Users input their current location, time of day, preferences, and behavioral data into the device application. Specifically, they use the in-app interface to select "Automatic Location Capture," select departure time and duration, and choose their preferred activities (e.g., cafes, shopping, events).

[1211] Step 2:

[1212] The device sends the entered user information to the server. Specifically, it encodes the input data into JSON format and sends an HTTPS POST request to the server.

[1213] Step 3:

[1214] The server analyzes the data it receives: when it receives a POST request, it decodes the data and updates the user profile (preferences, behavioral data).

[1215] Step 4:

[1216] The server obtains the necessary external data (geographical information, restaurant ratings, tourist attraction reviews, event information) from a database or API. Specifically, it sends requests using various APIs (e.g., geographical information API, review data API) to collect the relevant data.

[1217] Step 5:

[1218] The server generates a sightseeing plan based on the data acquired and user information. Specifically, it uses machine learning models and heuristic algorithms to generate a plan that suits the user's preferences.

[1219] Step 6:

[1220] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[1221] Step 7:

[1222] The device analyzes the received itinerary and presents it visually to the user, specifically by decoding the received data and displaying it in the application's UI components (maps, timetables, lists of detailed information, etc.).

[1223] Step 8:

[1224] The user inputs changes to their plans or new information in real time (e.g., delays, weather changes) into the device, typically using forms and options within the app to enter changes.

[1225] Step 9:

[1226] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[1227] Step 10:

[1228] The server modifies the existing tour plan based on the new information, receiving the changes and running them through a data analysis and optimization algorithm again to generate a new plan.

[1229] Step 11:

[1230] The server sends the revised itinerary to the user's device in JSON format.

[1231] Step 12:

[1232] The device receives the revised plan and displays it to the user by parsing the received data again and updating the UI components to display it.

[1233] Example 1

[1234] 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."

[1235] Current travel plan generation systems often lack the ability to immediately respond to real-time changes in users' circumstances (e.g., weather changes, traffic delays, etc.). As a result, the user experience can be marred by unexpected problems. It is also difficult to automatically generate plans that fully take into account individual users' preferences and behavioral patterns. These problems need to be solved.

[1236] 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.

[1237] In this invention, the server includes means for inputting user location information, means for inputting user preference information, means for inputting user behavior data, means for transmitting the input information to the server, means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist destination reviews, and event information, means for generating a sightseeing plan based on the acquired information, means for transmitting the generated sightseeing plan to the user's terminal, means for displaying the transmitted sightseeing plan to the user, means for inputting changes to the user's plans and real-time information, means for transmitting the input change information to the server, means for modifying the sightseeing plan based on the change information, and means for transmitting the modified plan to the terminal and displaying it. This makes it possible to generate and modify an optimal sightseeing plan that reflects real-time changes in the user's situation and individual preferences.

[1238] "Means for inputting user location information" refers to an interface for inputting information about the user's current location.

[1239] The "means for inputting user preference information" is an interface for inputting information about the user's tastes and preferences.

[1240] The "means for inputting user behavioral data" refers to an interface for inputting data regarding the user's past behavior and behavioral patterns.

[1241] The "means for transmitting input information to a server" refers to a communication means for transmitting information input by a user to a server.

[1242] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to the means by which the server obtains necessary information from external databases and APIs based on the user information received.

[1243] "Means for generating a sightseeing plan based on acquired information" refers to means for creating an optimal sightseeing plan based on acquired external information and user information.

[1244] The "means for transmitting the generated tour plan to the user's terminal" is a communication means for transmitting the tour plan generated by the server to the user's terminal.

[1245] The "means for displaying the transmitted tour plan to the user" refers to a means for visually displaying the tour plan received by the terminal to the user.

[1246] "Means for inputting user schedule changes and real-time information" refers to an interface that allows a user to input schedule changes and information that occurs in real time (e.g., traffic delays or weather changes).

[1247] The "means for transmitting input change information to the server" refers to a communication means for transmitting change information input by the user to the server.

[1248] The "means for amending a sightseeing plan based on change information" refers to a means for amending an existing sightseeing plan based on change information received by the server.

[1249] The "means for transmitting the revised tour plan to the terminal and displaying it" is a means for transmitting the revised tour plan from the server to the terminal and for the terminal to display it to the user.

[1250] This invention relates to a system that generates and modifies optimized sightseeing plans in real time using user location information, preferences, and behavioral data. This system is constructed by combining user terminals, a server, and multiple input / output means.

[1251] 1. User Input Method

[1252] Users input their location, preferences, and behavioral data through applications installed on mobile devices such as smartphones and tablets, specifically iOS or Android apps.

[1253] 2. Data transmission method

[1254] The terminal encodes the data entered by the user and sends it to the server via the Internet as an HTTPS request, which ensures secure transmission of the data. The specific communication method used is the HTTP library.

[1255] 3. Means of receiving and analyzing data

[1256] The server receives and analyzes the data sent from the device. It also retrieves necessary external data, such as geographic information, restaurant ratings, tourist attraction reviews, and event information, from databases and APIs. Specific software used includes MySQL and Google Maps API.

[1257] 4. Tourist plan generation tool

[1258] The server generates a sightseeing plan based on the acquired data and user input. Using machine learning algorithms (e.g., Scikit-learn) and heuristic methods, optimization calculations are performed based on the user's preferences and behavioral patterns. This generation process suggests the best combination of tourist spots for the user.

[1259] 5. Means of sending and displaying travel plans

[1260] The server sends the generated itinerary to the device, which receives it and displays it visually to the user. Display methods include map display, timetable, detailed information list, etc. Google Maps API is used as a specific visualization tool.

[1261] 6. Real-time correction methods

[1262] If the user changes plans or inputs new information (e.g., delays, weather changes) into the device, the device sends that information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device, ensuring that the user always gets the optimal plan.

[1263] Specific usage examples and prompt sentence examples

[1264] Usage example:

[1265] The user enters "Current location: Shibuya, Tokyo," "Time: 2:00 PM to 6:00 PM," and "Favorites: Cafes and shopping" into the dedicated app. The device sends this information to the server, which analyzes it to obtain geographic information for the Shibuya area, cafe ratings, shopping spot reputations, and event information. The server then generates a sightseeing plan based on this data and sends it to the device, such as "2:00 PM - Cafe A," "3:30 PM - Shopping Spot B," and "5:00 PM - Special Event C." The device then visually displays this information to the user.

[1266] Example prompt sentence:

[1267] "The user wants to enjoy cafes and shopping in Shibuya between 2pm and 6pm. Please generate the best sightseeing itinerary based on this."

[1268] This system allows users to have the best possible sightseeing experience according to the situation at hand, and by updating information in real time, it is possible to respond flexibly to unforeseen circumstances during travel.

[1269] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1270] A detailed explanation of the program divided into processing steps

[1271] Step 1: Enter your user information

[1272] Users use the mobile app to input their location information, preference information, and behavioral data. For example, users input "Current location: Shibuya, Tokyo," "Time period: 2:00 PM to 6:00 PM," and "Preferences: Cafes and shopping."

[1273] Input: Current location, time zone, preferences

[1274] Output: Encoded user information data

[1275] Specific behavior: The user enters the required information on the application screen and taps the input button.

[1276] Step 2: Send the data

[1277] The terminal encodes the data entered by the user and sends it to the server as an HTTPS request.

[1278] Input: Encoded user information data

[1279] Output: HTTPS request

[1280] Specific operation: The device is connected to the network and sends the data entered by the user to the server.

[1281] Step 3: Receiving data and acquiring external data

[1282] The server receives and analyzes the data sent from the device, then retrieves external data such as geographical information, restaurant ratings, tourist attraction reviews, and event information from databases and APIs.

[1283] Input: HTTPS request, encoded user information data

[1284] Output: Analyzed user information data, external data (geographical information, restaurant ratings, tourist destination reviews, event information)

[1285] Specific operation: The server analyzes the user information and, based on that information, sends a request to an external API (e.g., Google Maps API, Yelp API) to obtain the necessary data.

[1286] Step 4: Data analysis and tourism plan generation

[1287] The server generates a sightseeing plan based on the analyzed user information data and external data, and performs optimization calculations using machine learning algorithms (e.g., Scikit-learn) and heuristic methods.

[1288] Input: Parsed user information data, external data

[1289] Output: Generated itinerary

[1290] What it does: The server processes the data and runs an algorithm that generates a sightseeing itinerary based on the user's preferences and behavioral patterns.

[1291] Step 5: Submit and view your plan

[1292] The server encodes the generated travel plan and sends it to the terminal as an HTTPS request, and the terminal displays the received travel plan to the user.

[1293] Input: Generated itinerary

[1294] Output: HTTPS request, itinerary displayed

[1295] Specific operation: The server sends the sightseeing plan to the device, and the device displays the information visually in the application (e.g., map display, timetable, detailed list).

[1296] Step 6: Real-time correction

[1297] The user inputs changes in plans or new information (e.g., train delays, weather changes), and the device sends the information to the server. The server then modifies the sightseeing plan based on the new information and sends it back to the device for display.

[1298] Input: Schedule change information, real-time information

[1299] Output: Modified itinerary

[1300] What happens: The user enters new information into the app, the device sends it to the server, the server generates a revised plan and sends it back to the device, and the device displays the new plan to the user.

[1301] Through these steps, the system of the present invention provides the optimal sightseeing plan according to the user's situation and preferences, and can also update it in real time.

[1302] (Application example 1)

[1303] 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."

[1304] Conventional food delivery systems face the challenge of effectively utilizing individual information such as a user's current location, preferences, and past order history to propose optimal meal plans in real time. Furthermore, plans are not quickly adjusted to take into account real-time information such as delivery status and weather, resulting in a poor user experience. There is a need to solve these challenges and provide users with an efficient and satisfying food delivery experience.

[1305] 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.

[1306] In this invention, the server includes means for generating a meal plan based on the acquired information, means for transmitting the generated meal plan to the user's terminal, and means for integrating weather information, delivery status information, and real-time order data when generating and modifying the meal plan. This allows the server to propose an optimal meal plan in real time, taking into account the user's current location, preferences, past order history, etc., and to dynamically modify the plan based on the latest information on delivery, weather, etc.

[1307] "Means for inputting user's current location information" refers to means for obtaining the user's current physical location information. This information is obtained in real time using the GPS function of a smartphone or other mobile device.

[1308] "Means for inputting user preference information" refers to a means for inputting a user's preferences and tastes for food and services, allowing the user to select their preferred genres and specific menu items through the application interface.

[1309] "Means for inputting user behavior data" refers to means for collecting and inputting data related to a user's past order history and behavioral patterns, which will enable analysis based on the user's past trends.

[1310] "Means for transmitting input information to a server" refers to means for transmitting the location information, preference information, and behavioral data input by the user to a server via the Internet. The data is transmitted securely in an encoded format.

[1311] "Means for receiving transmitted information and acquiring geographic information, restaurant ratings, local reputation, and event information" refers to the means for acquiring related geographic information, restaurant ratings, local reputation, and event information based on the user information received by the server. Information is acquired using external APIs and databases.

[1312] The "means for generating a meal plan based on the acquired information" refers to a means for analyzing the acquired data and generating an optimal meal plan for the user based on that data. The plan is generated using machine learning algorithms or heuristic methods.

[1313] The "means for transmitting the generated meal plan to the user's device" refers to the means for transmitting the meal plan generated by the server to the user's device such as a smartphone or tablet. The data is encoded and transmitted securely.

[1314] "Means for displaying the transmitted meal plan to the user" means means for visually displaying the received meal plan on the user's device, including a map, list, timetable, etc.

[1315] "Means for users to input schedule changes and real-time information" refers to a means for users to input real-time information such as schedule changes, delivery delays, weather changes, etc. The information can be easily input using the app's interface.

[1316] The "means for transmitting the entered change information to the server" refers to a means for transmitting the change information entered by the user to the server. The data is encoded and transmitted securely over the Internet.

[1317] The "means for modifying the meal plan based on the change information" refers to a means for modifying the generated meal plan based on the change information received by the server. The modified plan is recalculated to adapt to the user's new needs.

[1318] The "means for transmitting the revised plan to the terminal and displaying it" refers to a means for transmitting the revised plan from the server back to the user's terminal and visually displaying it. The revised plan is displayed on the user's screen in the same way as the original plan.

[1319] This invention is a system that generates and modifies optimal meal plans in real time based on a user's current location, preferences, past ordering history, etc. This system is constructed by combining a user's terminal, a server, and multiple input / output means.

[1320] System configuration

[1321] 1. User Input Method:

[1322] An interface will be provided on a smartphone or tablet for users to input their current location, preferences, past order history, etc. Specifically, a UI will be implemented that allows users to obtain location information via GPS, select their preferred genre, and view and select past order history.

[1323] 2. Means of data transmission:

[1324] The input information is sent to the server using an HTTPS request. The input data is encoded in JSON format and sent via SSL / TLS for security reasons.

[1325] 3. Means of receiving and analyzing data:

[1326] The server receives and analyzes the data sent by users, using data analysis libraries such as Pandas, and obtains geographic information, restaurant ratings, local reputation, and event information through external APIs (e.g., Google Maps API, Yelp API).

[1327] 4. Meal plan generator:

[1328] Based on the acquired data, a meal plan is generated, using machine learning algorithms (e.g., k-means clustering, random forest) and heuristic methods to perform optimization calculations based on the user's preferences and constraints.

[1329] 5. Means of sending and displaying itineraries:

[1330] The meal plan generated by the server is then encoded into JSON format and sent to the user's device, where it is received and displayed visually, including timetables, maps, and detailed information lists.

[1331] 6. Real-time correction measures:

[1332] When the user enters new information (e.g., delivery delay, weather change) into the device, the device sends that information to the server, which then modifies the meal plan based on the new information and sends the modified plan back to the device for display.

[1333] Hardware and software used

[1334] Hardware:

[1335] Smartphone (iOS or Android)

[1336] Server (AWS, Google Cloud, etc.)

[1337] software:

[1338] Smartphone app (Swift or Kotlin)

[1339] Server side (Python, Node.js, etc.)

[1340] Databases and analytical libraries (Pandas, scikit-learn)

[1341] External API (Google Maps API, Yelp API)

[1342] Specific examples

[1343] For example, suppose a user is in Shinjuku and is looking for a Japanese lunch around 12:30. The user opens the smartphone app and types, "I'm looking for a Japanese lunch around 12:30 in the Shinjuku area. Are there any recommended restaurants?" This information is sent to the server in real time, and the server generates an optimal meal plan based on geographic information and restaurant reviews. As a result, the user might be offered a plan such as "Sushi at Restaurant A at 12:30" or "Matcha Latte at Cafe B at 1:15 PM." If the user reports issues such as delivery delays, the server dynamically modifies the plan and offers it again.

[1344] As described above, the present invention is a system that provides users with an efficient and satisfying food delivery experience.

[1345] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1346] Step 1:

[1347] A user opens the app on their smartphone and enters their current location (e.g., Shinjuku), time of day (e.g., lunch), preferences (e.g., Japanese food), and past ordering history. The input data is encoded in JSON format and sent to the server via an HTTPS request. This provides the server with specific information about the user.

[1348] Step 2:

[1349] The server receives the input JSON data and deserializes it. It then analyzes the user's current location, preferences, and past order history using a data analysis library such as Pandas. This allows the server to understand the user's basic needs.

[1350] Step 3:

[1351] The server uses external APIs (e.g., Google Maps API, Yelp API) to obtain geographic information, restaurant ratings, local reputation, event information, etc. based on the received data. The obtained data is stored in a database on the server. This allows the server to collect the latest information about services desired by users.

[1352] Step 4:

[1353] The server generates a meal plan based on the acquired data. It uses machine learning algorithms (e.g., k-means clustering, random forest) to perform optimization calculations based on the user's preferences and constraints. The generated meal plan is encoded in JSON format, allowing the server to propose a plan that best suits the user's needs.

[1354] Step 5:

[1355] The server sends the generated meal plan to the user's device. The plan received by the device is deserialized and displayed visually. For example, "12:30 - Sushi at Restaurant A" and "13:15 - Matcha Latte at Cafe B" are displayed to the user. This allows the user to easily check the proposed plan.

[1356] Step 6:

[1357] The user enters real-time information into the app, such as a change in schedule or a delivery delay. The new information is again encoded into JSON format and sent to the server via an HTTPS request, which reports the new status from the device to the server.

[1358] Step 7:

[1359] The server then modifies the generated meal plan based on the new information received, again using machine learning algorithms and heuristics to recalculate and adapt to the user's new needs. The modified plan is then encoded in JSON format and sent to the device, allowing the server to quickly adapt to user changes.

[1360] Step 8:

[1361] The device receives the revised plan, deserializes it, and displays it visually. The revised plan includes new time and location information, such as "13:00 - Sushi at Restaurant A" and "13:45 - Matcha Latte at Cafe B." This allows the user to always see the latest plan.

[1362] Through these steps, the system is able to provide users with an efficient and satisfying food delivery experience.

[1363] 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.

[1364] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also includes a function that recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[1365] System configuration

[1366] 1. User Input Method:

[1367] It provides a user interface (UI) for users to input their current location, time zone, preferences, and behavioral data. The UI is installed on mobile devices such as smartphones and tablets.

[1368] 2. Means of data transmission:

[1369] The device sends the data entered by the user and the emotional data recognized by the emotion engine to the server. Specifically, the device encodes the input data and emotional data into JSON format and sends an HTTPS POST request to the server.

[1370] 3. Means of receiving and analyzing data:

[1371] The server receives and analyzes the data sent from the device, and also acquires external data such as geographic information, restaurant ratings, tourist attraction reputations, and event information.

[1372] 4. Emotion recognition means:

[1373] The device's built-in emotion engine recognizes the user's emotions through facial, voice, and text analysis, and this data is reflected in the creation of a travel plan.

[1374] 5. Tourist plan generation tool:

[1375] The server generates a sightseeing plan based on the acquired external data, user preferences, and emotional data, using machine learning algorithms and heuristic methods.

[1376] 6. Means of sending and displaying itineraries:

[1377] The server sends the generated itinerary to the user's device, which receives it and displays it to the user in a visual format that includes maps, timetables, detailed information lists, etc.

[1378] 7. Real-time correction measures:

[1379] The user inputs changes in plans or new real-time information (e.g., delays, weather changes) into the device, which then sends the information to the server, which then modifies the sightseeing plan based on the new information and sends it back to the device.

[1380] Program processing flow (example)

[1381] 1. Enter your user information:

[1382] The user inputs their current location (e.g., Shibuya, Tokyo), time period (e.g., 2:00 PM to 6:00 PM), and preferences (e.g., cafes and shopping) into the device. In addition, the emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and recognize their current emotion (e.g., happy, tired).

[1383] 2. Data transmission:

[1384] The terminal transmits the input user information and recognized emotion data to the server.

[1385] 3. Data analysis and external data acquisition:

[1386] The server analyzes the user's input data and emotional data, and retrieves geographical information about the Shibuya area, ratings of cafes during opening hours, reputations of shopping spots, and information about nearby events from databases and APIs.

[1387] 4. Tourist plan generation:

[1388] The server generates a sightseeing plan that includes cafe "A," shopping spot "B," and special event "C" based on the acquired data, the user's preferences, and the recognized emotional data. For example, if the user is recognized as "tired," the plan will prioritize relaxing cafes and rest spots.

[1389] 5. Submit and view your plan:

[1390] The server sends the generated sightseeing plan to the user's device, which displays "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Special Event C."

[1391] 6. Real-time correction:

[1392] When a user inputs train delay information into a terminal, the terminal transmits the information to a server.

[1393] The server generates a new plan taking into account the delay information, for example, "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[1394] The device will display the revised plan to the user.

[1395] This system allows users to always obtain the most optimal sightseeing plan and quickly respond to changes in the environment or emotions during their trip.

[1396] The processing flow will be explained below.

[1397] Step 1:

[1398] The user inputs their current location (e.g., Shibuya, Tokyo), time of day (e.g., 2 p.m. to 6 p.m.), preferences (e.g., cafes and shopping), and behavioral data into the device's application. Furthermore, the emotion engine analyzes the user's facial expressions and voice via the device's camera and microphone to recognize their current emotion (e.g., happy, tired).

[1399] Step 2:

[1400] The device sends the input user information and recognized emotion data to the server. Specifically, the input data and emotion data are encoded in JSON format and sent to the server as an HTTPS POST request.

[1401] Step 3:

[1402] The server receives and analyzes the transmitted data, for example, decoding the user's location, time zone, and preferences to update the user profile, and analyzing the emotional data to determine the user's current emotional state.

[1403] Step 4:

[1404] The server obtains the necessary external data (e.g., geographic information, restaurant ratings, tourist attraction reviews, and information about nearby events). Specifically, it sends requests using various APIs (e.g., geographic information API, review data API) to collect the relevant data.

[1405] Step 5:

[1406] The server generates a sightseeing plan based on the acquired data, user information, and emotional data. For example, if the user's emotional state is recognized as "tired," the plan will prioritize relaxing cafes and rest areas. The plan is optimized using machine learning and heuristic algorithms.

[1407] Step 6:

[1408] The server sends the generated travel plan to the user's device. Specifically, it converts the generated plan into JSON format and sends it as an HTTPS response.

[1409] Step 7:

[1410] The device analyzes the received travel plans and visually displays them to the user. Specifically, it decodes the received data and displays it in the application's UI components (maps, timetables, detailed information lists, etc.).

[1411] Step 8:

[1412] The user inputs changes to plans or new real-time information (e.g., train delays, weather changes) using in-app forms and options to enter changes.

[1413] Step 9:

[1414] The device sends the change information to the server by encoding the change information in JSON format and sending it again via HTTPS POST request.

[1415] Step 10:

[1416] The server modifies the existing sightseeing plan based on the new information, for example, by analyzing and optimizing the data again based on the changed arrival time or new emotion data, and generates a new plan.

[1417] Step 11:

[1418] The server sends the revised itinerary to the user's device in JSON format.

[1419] Step 12:

[1420] The device receives the revised plan and displays it to the user. Specifically, it parses the received data again and updates the UI components to display it. For example, it displays "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Special Event C."

[1421] In this way, by using the emotion engine, users can obtain more personalized and adaptive sightseeing plans in real time that are tailored to their emotions.

[1422] Example 2

[1423] 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."

[1424] Conventional sightseeing plan generation systems only considered the user's current location, preferences, and behavioral data, which meant they lacked the ability to adapt to user emotions or real-time changes in location and situation. Furthermore, it was difficult to revise sightseeing plans in real time, which often meant they were unable to provide the optimal plan for the user.

[1425] 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.

[1426] In this invention, the server includes means for recognizing the user's emotions, means for transmitting input information and emotional data to the server, and means for receiving the transmitted information and emotional data and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information. This makes it possible to generate and modify a tour plan that flexibly responds to the user's emotions and real-time changes in the situation.

[1427] The "means for inputting user's current location information" refers to a device that has an interface or function that allows the user to input their current location.

[1428] The "means for inputting user preference information" refers to a device that has an interface or function that allows a user to input his or her preferences and activities of interest.

[1429] The "means for inputting user behavioral data" refers to a device that has an interface or function for inputting data regarding the user's past behavior and habits.

[1430] "Means for recognizing user emotions" refers to a device that has algorithms and functions for analyzing the user's facial expressions, voice, and text to detect and recognize the user's emotions.

[1431] "Means for transmitting input information and emotional data to a server" refers to a device that has the technology and functions to transmit data input by a user and recognized emotional data to a server via a network.

[1432] The "means for receiving transmitted information and emotion data" refers to a device that allows the server to receive data transmitted from the user terminal, and often uses a secure communication protocol.

[1433] "Means of obtaining geographic information, restaurant ratings, tourist destination reputation, and event information" refers to the functions and algorithms that allow the server to obtain the necessary geographic information and rating information from external databases and APIs.

[1434] The "means for generating a sightseeing plan based on acquired information and emotional data" is a device that has algorithms and models for integrating collected data and user emotional information to generate an optimal sightseeing plan.

[1435] The "means for transmitting the generated tour plan to the user's terminal" is a device having the technology and functions for transmitting the tour plan generated by the server to the user's terminal via the network.

[1436] The "means for displaying the transmitted tour plan to the user" refers to a device that has an interface or function for the user's terminal to visually display the received tour plan.

[1437] "Means for inputting user schedule changes and real-time information" means a device that has an interface or functionality that allows a user to change their original schedule or input real-time information (e.g., delays, weather changes) into the terminal.

[1438] The "means for transmitting input change information to the server" is a device having the technology and function for transmitting change information input by the user from the terminal to the server.

[1439] The "means for modifying a tour plan based on change information" is a device that has an algorithm or model for modifying and regenerating an existing tour plan based on change information received by the server.

[1440] The "means for transmitting the revised tour plan to the terminal and displaying it" refers to a device that has the technology and functions for the server to transmit the revised tour plan to the user's terminal and for the terminal to display it.

[1441] This invention is a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preference information, and behavioral data, and also includes a function to recognize the user's emotions and reflect them in the sightseeing plans. This system is composed of a user's terminal, a server, and multiple input and output means.

[1442] 1. Hardware and Software Configuration

[1443] This system includes a user interface (UI) installed on mobile devices such as smartphones and tablets, a server, and an emotion recognition engine. User data is encoded in JSON format and transmitted by sending an HTTPS POST request to the server. Specifically, the system uses the following hardware and software:

[1444] Devices: smartphones, tablets

[1445] Server: High performance server (e.g. AWS EC2)

[1446] Emotion recognition engine: AI models for facial expression analysis, speech analysis, and text analysis (e.g., Google Cloud AutoML, Amazon Rekognition)

[1447] Databases and APIs: External APIs and databases for retrieving geographic information, restaurant ratings, tourist attraction reviews, and event information (e.g., Google Places API, Yelp API)

[1448] 2. System processing flow

[1449] When a user uses their device to input their current location, preferences, and emotional data, the device sends this data to the server. The server analyzes the received data and obtains additional information from external APIs. The server uses a machine learning algorithm to generate an optimal sightseeing plan based on the obtained data and the user's preferences and emotions. The generated sightseeing plan is sent from the server to the user's device and displayed visually on the device. If the user changes their plans or enters real-time information, the device sends that information to the server, which then revises the plan.

[1450] 3. Examples of concrete examples and prompts

[1451] As a concrete example, consider a situation where a user is in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2pm and 6pm, but is a little tired. The following data is entered:

[1452] Current location: Shibuya

[1453] Time: 14:00 to 18:00

[1454] Likes: Cafes and shopping

[1455] Emotion: Tired

[1456] In this case, the system generates the following prompt for the itinerary:

[1457] Prompt Sentence Examples

[1458] "Currently, the user is located in Shibuya, Tokyo, and wants to enjoy a cafe and shopping between 2 p.m. and 6 p.m. However, he feels a bit tired, so he would prefer a place where he can relax."

[1459] In this way, the system can generate and modify optimal sightseeing plans taking into account the user's emotions and real-time situations.

[1460] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1461] Step 1:

[1462] Entering user information

[1463] The user uses the device's UI to input their current location, time zone, and preferences. For example, the user inputs "Shibuya," the time zone "14:00 to 18:00," and the preferences "cafes and shopping." At this time, the device's camera and microphone are used to analyze the user's facial expressions and voice and recognize their emotions. Based on the input, the device collects the user's input data and emotional data. The output is the user's current location, time zone, preferences, and emotional data.

[1464] Step 2:

[1465] Sending data

[1466] The device encodes the user's input data and recognized emotion data into JSON format. The encoded data is sent to the server as an HTTPS POST request. The input is the user's current location, time zone, preferences, and emotion data, and the output is the encoded JSON format data and a request to send it to the server. Specifically, the device sends the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired" to the server.

[1467] Step 3:

[1468] Receiving and analyzing data

[1469] The server receives JSON formatted data sent from the device. It analyzes the received data to understand the user's current location, time zone, preferences, and emotions. The input is the JSON formatted data sent from the device, and the output is the analysis results: current location, time zone, preferences, and emotions. Specifically, the server receives the data "Shibuya," "14:00-18:00," "cafe, shopping," and "tired," and analyzes and extracts each item.

[1470] Step 4:

[1471] Retrieving External Data

[1472] The server sends requests to the appropriate database or API to obtain external data such as geographic information, restaurant ratings, tourist attraction reviews, and event information. The input is the analyzed user's current location and time zone information, and the output is the data obtained from the external API. Specifically, the server sends requests to the Yelp API or Google Places API to obtain rating information for cafes and shopping spots in the "Shibuya" area.

[1473] Step 5:

[1474] Generate a sightseeing plan

[1475] The server combines the user's input data, recognized emotion data, and acquired external data to generate a sightseeing plan. It uses a machine learning algorithm to calculate the optimal plan. The input is the user's current location, time period, preferences, emotion data, and external data, and the output is the generated sightseeing plan. Specifically, the server creates a plan combining relaxing cafes and popular shopping spots based on the information "Shibuya," "14:00-18:00," "Cafe A, Shopping B, Event C," and "Tired."

[1476] Step 6:

[1477] Submitting and Viewing Plans

[1478] The server sends the generated sightseeing plan to the user's device. The device visually displays the received plan to the user. The input is the sightseeing plan generated by the server, and the output is the specific plan information displayed on the device. Specifically, the server sends the plan "14:00 - Cafe A, 15:30 - Shopping B, 17:00 - Event C" to the device, and the device displays it to the user in a map app or list format.

[1479] Step 7:

[1480] Real-time correction

[1481] The user inputs schedule changes or real-time information (e.g., train delays) into the device. The device sends this new information to the server. The server regenerates the sightseeing plan based on the new information and sends it back to the device. The input is the changed information the user input into the device and the information sent to the server, and the output is the revised sightseeing plan. Specifically, the user inputs "train delay," and the server generates a new plan "14:30 - Cafe A, 16:00 - Shopping B, 17:30 - Event C," which is sent to the device and displayed.

[1482] (Application example 2)

[1483] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1484] Conventional sightseeing plan generation systems create plans based on the user's current location, preferences, and behavioral data, but they do not fully consider the user's real-time emotions or environmental changes, which limits the optimization of the user experience. There is also the issue of ineffective personalized store guidance in physical stores.

[1485] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's current location; means for inputting information about the user's preferences; means for inputting data about the user's behavior; means for transmitting the input information to the server; means for receiving the transmitted information and acquiring geographic information, restaurant reviews, tourist destination reputations, and event information; means for generating a tour plan based on the acquired information; means for transmitting the generated tour plan to the user's terminal; means for displaying the transmitted tour plan to the user; means for inputting changes to the user's plans and real-time information; means for transmitting the input change information to the server; means for revising the tour plan based on the change information; means for transmitting and displaying the revised plan to the terminal; means for providing personalized store guidance based on the input preference information and behavior data; means for recognizing emotions using the user's camera and microphone; means for reflecting the recognized emotions in the tour plan; and means for modifying recommendations in real time based on the user's movement information and environmental changes. This enables more personalized tour plans and store guidance that take into account the user's emotions and environmental changes.

[1486] The "means for inputting user's current location information" refers to a device or software that provides an interface for obtaining and inputting the user's current location information.

[1487] "Means for inputting user preference information" refers to a device or software that provides an interface for inputting user preferences and interests.

[1488] "Means for inputting user behavioral data" refers to a device or software that provides an interface for inputting user behavior history and activity data.

[1489] The "means for transmitting input information to a server" refers to a device or software that transmits various data input by a user to a server via a communication means such as the Internet.

[1490] "Means for receiving transmitted information and obtaining geographical information, restaurant ratings, tourist attraction reputations, and event information" refers to a device or software that obtains related external data based on the user data received by the server.

[1491] The "means for generating a sightseeing plan based on the acquired information" refers to a device or software that automatically generates an optimal sightseeing plan based on the received data and the acquired external data.

[1492] The "means for transmitting the generated tour plan to the user's terminal" is a device or software that transmits the tour plan generated by the server to the terminal used by the user.

[1493] The "means for displaying the transmitted travel itinerary to the user" refers to a device or software that provides an interface for visually displaying the received travel itinerary on the user's terminal.

[1494] "Means for inputting user schedule changes and real-time information" refers to a device or software that provides an interface for users to input schedule changes and real-time information about the current situation.

[1495] The "means for transmitting input change information to the server" refers to a device or software that transmits change information input by the user to the server.

[1496] The "means for modifying a tour plan based on change information" is a device or software that recalculates and modifies an existing tour plan based on received change information.

[1497] The "means for transmitting the revised itinerary to the terminal and displaying it" refers to a device or software that transmits the revised travel itinerary to the user's terminal and displays it.

[1498] "Means for providing personalized store guidance based on input preference information and behavioral data" refers to a device or software that automatically generates and provides optimal store guidance based on the user's past preferences and behavior.

[1499] "Means for recognizing emotions using the user's camera and microphone" refers to devices or software that use the camera and microphone installed on the device to analyze the user's facial expressions and voice and recognize emotions.

[1500] The "means for reflecting the recognized emotions in the sightseeing plan" is a device or software that adjusts the sightseeing plan based on the recognized emotional information of the user.

[1501] The "means for modifying recommendations in real time based on user movement information and environmental changes" refers to a device or software that dynamically modifies the current recommended plan based on user movement information and environmental change information received in real time.

[1502] This invention relates to a system that generates and modifies optimal sightseeing plans in real time based on the user's current location, preferences, and behavioral data, and also recognizes the user's emotions and reflects them in the sightseeing plans. This system is composed of a user terminal, a server, and multiple input / output means.

[1503] 1. System Configuration

[1504] 1.1 User Device

[1505] It provides a user interface (UI) for inputting user location information, preferences, and behavioral data. The UI is installed on a mobile device such as a smartphone or tablet and also uses a camera and microphone. The user terminal also includes data transmission means, reception means, and display means.

[1506] 1.2 Server

[1507] The server analyzes the information received from the user's device (location information, preferences, behavioral data, and emotional data) and also acquires external data such as geographical information, restaurant reviews, tourist attraction reputations, and event information. It then generates an optimal sightseeing plan based on the received data and the acquired external data, and sends the results back to the user's device. The server performs these tasks using machine learning algorithms (e.g., Google Cloud Vision API, IBM Watson Tone Analyzer).

[1508] 2. Implementation form

[1509] 2.1 Data Collection and Transmission

[1510] A user uses a smartphone app to input their current location (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and behavioral data. The app also uses a camera and microphone to collect emotional data (e.g., tired, happy). These data are encoded into JSON format and sent to the server using an HTTPS POST request.

[1511] 2.2 Data Reception and Analysis

[1512] The server receives the data sent by the user and obtains additional data from geographic information systems (GIS) and review APIs (e.g., Google Places API, Yelp API). At the same time, it analyzes the emotional data using an emotion recognition engine, thereby generating a travel plan that best matches the user's current mood and preferences.

[1513] 2.3 Creating and Submitting a Plan

[1514] The server generates an optimal sightseeing plan using machine learning algorithms and heuristics based on the acquired data and analysis results. The generated plan is sent to the user's smartphone and displayed through a visually appealing UI. If the user provides feedback or inputs changes to the plan, this information is also sent to the server in real time, and the server regenerates the plan.

[1515] 3. Specific Examples

[1516] For example, if a user is in Shibuya and the emotion engine recognizes that they are "tired," the server will prioritize cafes and rest spots where they can relax based on the user's preferences (cafes and shopping). It will also provide recommended store information taking into account traffic conditions and weather information.

[1517] Prompt Sentence Examples

[1518] User is located in Shibuya, Tokyo, Japan. Time frame is 2:00 PM to 4:00 PM. Sentiment is tired. Preferences are cafes and shopping. Generate a list of recommended cafes and relaxing spots.

[1519] This invention allows users to always obtain the most suitable travel plan and quickly respond to various environmental and emotional changes during their trip. Furthermore, it also allows users to receive personalized guidance in physical stores, greatly improving the user experience.

[1520] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1521] Step 1:

[1522] The user launches the smartphone app and inputs their current location, preferences, and behavioral data. At this time, emotional data is also collected using the smartphone's camera and microphone. The input data is encoded in JSON format. Input includes current location information (e.g., Shibuya, Tokyo), preferences (e.g., cafes and shopping), and emotional data (e.g., tired). The device collects this data, and the input data is output as a JSON-formatted string.

[1523] Step 2:

[1524] The data collected by the device is sent to the server using an HTTPS POST request. Data processing involves encoding the input data and creating a transmission request. The server receives this and stores the received data in a database for analysis. The input is the JSON-formatted string generated in step 1, and the output is a response code that confirms transmission to the server.

[1525] Step 3:

[1526] The server parses the received user information and retrieves additional data from geographic information systems (e.g., Google Maps API), review APIs (e.g., Yelp API), and other external data sources. This may include restaurant ratings near the current location, tourist attraction reputation, event information, etc. The input is the received data and response data from external data sources, and the output is the parsed dataset.

[1527] Step 4:

[1528] The server generates a sightseeing plan based on the analysis results and the user's preferences and emotion data. In this process, machine learning algorithms (e.g., heuristic methods, generative AI models) are used to create the optimal plan for the user. For data processing, the received data is incorporated into the algorithm, and the generated plan is output in JSON format. The input is the analysis result data and emotion data, and the output is the generated sightseeing plan data.

[1529] Step 5:

[1530] The server sends the generated itinerary to the user's device. Again, an HTTPS POST request is used for transmission. Data processing involves encoding the itinerary data and creating a transmission request. The input is the generated itinerary data, and the output is a response code sent to the user's device.

[1531] Step 6:

[1532] The terminal visually displays the received sightseeing plan to the user. The displayed content includes maps, timetables, and lists of recommended shops. The input is the sightseeing plan data received from the server, and the output is the visual information displayed on the user's screen.

[1533] Step 7:

[1534] While sightseeing, the user inputs schedule changes and real-time information (e.g., traffic delays, weather fluctuations). This information is sent back to the server from the terminal. As part of data processing, the change information is encoded and a transmission request is created. The input is the schedule change information, and the output is a response code that confirms transmission to the server.

[1535] Step 8:

[1536] The server modifies the current tour plan based on the received change information. In the modification process, an optimization recalculation is performed using the same algorithm as in step 4. The input is the change information and the existing tour plan data, and the output is the modified tour plan.

[1537] Step 9:

[1538] The server sends the modified itinerary to the user's terminal, which then displays it to the user again. The process is similar to steps 5 and 6. The input is the modified itinerary data, and the output is a response code and modified visual information to the user's terminal.

[1539] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1540] 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.

[1541] 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 robot 414.

[1542] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1543] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1544] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1545] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1546] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, motorcycles, and other devices, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1547] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1548] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1549] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1550] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1551] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1552] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1553] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1554] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1555] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1556] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1557] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1558] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1559] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1560] The following is further disclosed regarding the above embodiment.

[1561] (Claim 1)

[1562] a means for inputting the user's current location information;

[1563] a means for inputting user preference information;

[1564] a means for inputting user behavior data;

[1565] means for transmitting the input information to a server;

[1566] A means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information;

[1567] A means for generating a sightseeing plan based on the acquired information;

[1568] A means for transmitting the generated sightseeing plan to a user's terminal;

[1569] means for displaying the submitted itinerary to the user;

[1570] A means for users to input schedule changes and real-time information;

[1571] means for transmitting the input change information to a server;

[1572] A means to modify sightseeing plans based on the change information,

[1573] means for transmitting and displaying the modified plan to the terminal;

[1574] A system including:

[1575] (Claim 2)

[1576] 2. The system according to claim 1, wherein the means for generating a sightseeing plan uses a machine learning algorithm to perform optimization calculations based on preferences and constraints.

[1577] (Claim 3)

[1578] 10. The system of claim 1, further comprising means for integrating real-time data of weather information, traffic information, and events in generating and modifying sightseeing plans.

[1579] "Example 1" (Claim 1)

[1580] a means for inputting the user's location information;

[1581] a means for inputting user preferences;

[1582] a means for inputting user behavior data;

[1583] means for transmitting the input information to a server;

[1584] A means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information;

[1585] A means for generating a sightseeing plan based on the acquired information;

[1586] A means for transmitting the generated sightseeing plan to a user's terminal;

[1587] means for displaying the submitted itinerary to the user;

[1588] A means for users to input schedule changes and real-time information;

[1589] means for transmitting the input change information to a server;

[1590] A means to modify sightseeing plans based on the change information,

[1591] means for transmitting and displaying the modified plan to the terminal;

[1592] A system including:

[1593] (Claim 2)

[1594] 2. The system according to claim 1, wherein the means for generating a sightseeing plan uses an artificial intelligence algorithm to perform optimization calculations based on preferences and constraints.

[1595] (Claim 3)

[1596] 10. The system of claim 1, further comprising means for integrating real-time weather, traffic and event data in generating and modifying the tourism plan.

[1597] This claim details how the system generates and modifies optimal sightseeing plans in real time based on user location, preferences, and behavioral data.

[1598] "Application Example 1"

[1599] (Claim 1)

[1600] a means for inputting the user's current location information;

[1601] a means for inputting user preference information;

[1602] a means for inputting user behavior data;

[1603] means for transmitting the input information to a server;

[1604] A means for receiving the transmitted information and acquiring geographic information, restaurant ratings, local reputation, and event information;

[1605] a means for generating a meal plan based on the acquired information;

[1606] a means for transmitting the generated meal plan to the user's device;

[1607] a means for displaying the submitted meal plan to the user;

[1608] A means for users to input schedule changes and real-time information;

[1609] means for transmitting the input change information to a server;

[1610] A way to modify your meal plan based on changes, and

[1611] means for transmitting and displaying the modified plan to the terminal;

[1612] A system including:

[1613] (Claim 2)

[1614] 2. The system of claim 1, wherein the means for generating a meal plan uses a machine learning algorithm to perform optimization calculations based on preferences and constraints.

[1615] (Claim 3)

[1616] 10. The system of claim 1, further comprising means for integrating weather information, delivery status information, and real-time order data in generating and modifying meal plans.

[1617] "Example 2: Combining Emotion Engines"

[1618] (Claim 1)

[1619] a means for inputting the user's current location information;

[1620] a means for inputting user preference information;

[1621] a means for inputting user behavior data;

[1622] a means of recognizing a user's emotions;

[1623] means for transmitting the input information and emotion data to a server;

[1624] A means for receiving the transmitted information and emotion data and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information;

[1625] A means for generating a sightseeing plan based on the acquired information and emotion data;

[1626] A means for transmitting the generated sightseeing plan to a user's terminal;

[1627] means for displaying the submitted itinerary to the user;

[1628] A means for users to input schedule changes and real-time information;

[1629] means for transmitting the input change information to a server;

[1630] A means to modify sightseeing plans based on the change information,

[1631] means for transmitting and displaying the modified plan to the terminal;

[1632] A system including:

[1633] (Claim 2)

[1634] 2. The system of claim 1, wherein the means for generating a sightseeing plan uses a machine learning algorithm to perform optimization calculations based on preferences, sentiment data, and constraints.

[1635] (Claim 3)

[1636] 10. The system of claim 1, further comprising means for integrating weather information, traffic information, real-time event data, and sentiment data in generating and modifying the sightseeing plan.

[1637] "Application example 2 when combining emotion engines"

[1638] (Claim 1)

[1639] a means for inputting the user's current location information;

[1640] a means for inputting user preference information;

[1641] a means for inputting user behavior data;

[1642] means for transmitting the input information to a server;

[1643] A means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information;

[1644] A means for generating a sightseeing plan based on the acquired information;

[1645] A means for transmitting the generated sightseeing plan to a user's terminal;

[1646] means for displaying the submitted itinerary to the user;

[1647] A means for users to input schedule changes and real-time information;

[1648] means for transmitting the input change information to a server;

[1649] A means to modify sightseeing plans based on the change information,

[1650] means for transmitting and displaying the modified plan to the terminal;

[1651] A means for providing personalized store guidance based on input preference information and behavioral data;

[1652] a means for recognizing emotions using the user's camera and microphone;

[1653] A means of incorporating the perceived emotions into tourism plans;

[1654] a means for modifying recommendations in real time based on user movement information and environmental variations;

[1655] A system including:

[1656] (Claim 2)

[1657] The system according to claim 1, wherein the means for generating a sightseeing plan uses a machine learning algorithm to perform optimization calculations based on preferences and constraints, and further utilizes user emotional data.

[1658] (Claim 3)

[1659] 10. The system of claim 1, further comprising means for integrating real-time data of weather information, traffic information, and events in generating and modifying sightseeing plans. [Explanation of symbols]

[1660] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting the user's current location information; a means for inputting user preference information; a means for inputting user behavior data; means for transmitting the input information to a server; A means for receiving the transmitted information and acquiring geographic information, restaurant ratings, tourist attraction reputations, and event information; A means for generating a sightseeing plan based on the acquired information; A means for transmitting the generated sightseeing plan to a user's terminal; means for displaying the submitted itinerary to the user; A means for users to input schedule changes and real-time information; means for transmitting the input change information to a server; A means to modify sightseeing plans based on the change information, means for transmitting and displaying the modified plan to the terminal; A system including:

2. The system according to claim 1 , wherein the means for generating a sightseeing plan uses a machine learning algorithm to perform optimization calculations based on preferences and constraints.

3. 10. The system of claim 1, further comprising means for integrating real-time data of weather, traffic and events in generating and modifying sightseeing plans.

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