System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining user information; means for obtaining weather information; means for generating a travel plan based on user preferences and the weather information; means for notifying a user of the generated travel plan; means for modifying the travel plan based on user feedback; and means for finalizing the modified travel plan and making an associated reservation.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional methods for creating travel plans require users to research destination information and create an appropriate schedule, which requires time and effort. It is also difficult to quickly create a travel plan that suits the weather and the user's mood. As a result, many people find planning a trip too tedious and end up abandoning the trip altogether. The present invention aims to solve these problems and provide a system that allows users to easily and quickly create travel plans. [Means for solving the problem]

[0005] The present invention is a system including means for acquiring user information, means for acquiring weather information, means for generating a travel plan based on the user's preferences and weather information, means for notifying the user of the generated travel plan, means for modifying the travel plan based on the user's feedback, means for finalizing the modified travel plan and making related reservations, and means for selecting tourist attractions and restaurants, calculating an efficient route, and suggesting the optimal means of transportation from the user's current location to the destination, thereby significantly reducing the effort required for the user to create a travel plan and providing a comfortable travel experience.

[0006] "User information" refers to data including a user's past travel history, preferences, budget, current mood and physical condition, etc.

[0007] "Weather Information" means data about current and forecast weather obtained through a weather API or otherwise.

[0008] A "travel plan" is a detailed schedule of tourist attractions, restaurants, transportation, order of visits, duration of stay, etc., generated based on the user's preferences and weather information.

[0009] "Means of generation" refers to the system's function of creating travel plans using algorithms and machine learning models based on user information and weather information.

[0010] "Means of notification" refers to the system's functions of displaying the generated travel plan to the user or notifying them via push notification or email.

[0011] "Feedback" refers to any requests for corrections or comments made by a User regarding a proposed travel plan.

[0012] "Finalization" refers to completing the final travel plan by incorporating user feedback.

[0013] "Means of making reservations" refers to the system's functions that automatically make reservations for accommodation, transportation, tickets to tourist attractions, etc. based on the finalized travel plan.

[0014] A "tourist destination database" is a source of information that collects and stores information on many tourist destinations.

[0015] A "restaurant database" is a source of information that collects and stores information about a large number of restaurants.

[0016] An "efficient route" is the result of calculating the optimal order of visits and means of transportation to selected tourist spots and restaurants.

[0017] "Transportation" refers to the means of transportation used during a trip, such as a car, train, or plane. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a system that saves users the trouble of making travel plans and quickly provides optimal travel plans. The system of the present invention operates by combining multiple means and generates travel plans based on data such as user information, weather information, and databases of tourist spots and restaurants.

[0040] This system is configured as follows:

[0041] 1. Collection of User Information

[0042] server

[0043] When a user logs in to the system, the server automatically retrieves the user's past travel history and preference data from the database, such as tourist spots the user has visited in the past, food preferences, and travel budget.

[0044] The server uses a specific API (e.g., an application or wearable device that manages health data) to obtain the user's current mood and physical condition.

[0045] 2. Integration of user information and weather information

[0046] server

[0047] The server uses a weather API to retrieve current and near-future weather information, including temperature, precipitation, wind speed, etc.

[0048] The server compares the acquired user information with weather information and selects a travel destination that suits the user's preferences and physical condition.

[0049] 3. Generate the initial plan

[0050] server

[0051] The server searches a tourist spot database and a restaurant database to select the tourist spot and restaurant that best suit the user's preferences and weather conditions.

[0052] The server calculates an efficient route based on the selected tourist spots and restaurants.

[0053] 4. Creating and notifying detailed plans

[0054] server

[0055] Based on the initial plan, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[0056] The generated schedule is sent to the user's device.

[0057] Terminal

[0058] The terminal notifies the user of the detailed schedule sent from the server and displays it on the screen.

[0059] User

[0060] Users can review the proposed itinerary and make any necessary modifications, for example, adding or removing specific tourist attractions.

[0061] 5. Finalize the plan and make a reservation

[0062] server

[0063] The server creates a final itinerary based on the modifications made by the user.

[0064] Based on the final plan created, accommodation reservations, transportation arrangements, and ticket purchases for sightseeing spots are automatically made. For example, hotel reservation APIs and plane ticket reservation APIs are used to quickly make the necessary reservations.

[0065] Specific examples

[0066] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[0067] 1. Information gathering

[0068] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0069] Get weather information from the weather API and check that the weather is good for the day.

[0070] 2. Initial plan generation

[0071] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0072] 3. Creating a detailed plan

[0073] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0074] The terminal notifies the user of the schedule and displays it on the screen.

[0075] 4. User Feedback

[0076] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0077] 5. Final planning and booking

[0078] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[0079] In this way, users can eliminate the need for tedious planning and quickly obtain optimal travel plans. This system allows users to enjoy their trips with ease and improves their satisfaction.

[0080] The processing flow will be explained below.

[0081] Step 1:

[0082] A user logs in to the system.

[0083] Step 2:

[0084] The server retrieves the user's past travel history and preference data from a database.

[0085] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[0086] Step 3:

[0087] The server sends a request to the weather API to obtain current and near-future weather information.

[0088] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[0089] Step 4:

[0090] The server obtains the user's current mood and physical condition from various sensors and input forms.

[0091] How it works: Collects health data from smartphone APIs and medical interview data from users.

[0092] Step 5:

[0093] The server integrates the user information and weather information and searches a database of tourist attractions and restaurants.

[0094] How it works: It runs a search query against each database based on the user's preferences and weather conditions to generate a list of candidates.

[0095] Step 6:

[0096] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[0097] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[0098] Step 7:

[0099] The server generates the initial itinerary and creates a detailed schedule.

[0100] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[0101] Step 8:

[0102] The server sends the generated schedule to the user's terminal.

[0103] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[0104] Step 9:

[0105] The terminal notifies the user of the detailed schedule received from the server.

[0106] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[0107] Step 10:

[0108] The user reviews the proposed itinerary and makes any necessary modifications.

[0109] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[0110] Step 11:

[0111] The server receives the user's modification requests and creates the final itinerary.

[0112] How it works: The algorithm re-optimizes the plan based on user feedback.

[0113] Step 12:

[0114] The server automatically makes related reservations based on the finalized plan.

[0115] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[0116] In this way, it is possible to provide the user with an optimal travel plan that meets their needs.

[0117] Example 1

[0118] 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."

[0119] Conventional travel planning systems require users to individually search for travel plans and manually plan them, which is time-consuming and laborious. It is also difficult to provide optimal travel plans that take into account weather and the user's health condition. It is also difficult to immediately reflect user feedback and revise travel plans in real time. To solve these issues, there is a need for a fast and flexible travel plan generation and booking automation system that takes into account user preferences, health condition, and weather information.

[0120] 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.

[0121] In this invention, the server includes means for acquiring user information, means for acquiring health status data, means for acquiring weather information, means for generating a travel plan based on the user's preferences, health status, and weather information, means for notifying the user of the generated travel plan, means for modifying the travel plan based on the user's feedback, and means for finalizing the modified travel plan and making related reservations. This allows users to quickly obtain an optimal travel plan based on their health status and weather conditions, eliminating the need for individual searches and manual planning. Furthermore, real-time plan modifications based on user feedback improve travel satisfaction.

[0122] "User information" is a general term for data such as a user's past travel history, preferences, budget, etc.

[0123] "Health data" refers to information about a user's current physical condition or mood, obtained from wearable devices or health management applications.

[0124] "Weather information" refers to data about current and near-future weather conditions obtained through weather APIs, including temperature, precipitation, wind speed, etc.

[0125] A "travel plan" is a detailed schedule that includes planned visits to tourist attractions and restaurants, generated based on the user's preferences, health status, and weather information.

[0126] "Device" is a general term for electronic devices used by users, including smartphones and tablets.

[0127] "Feedback" refers to any corrections or additional instructions given by the user to the proposed travel plan, which are sent to the server via the terminal.

[0128] "Reservation" refers to procedures such as purchasing accommodation, transportation, and tickets to tourist attractions based on a confirmed travel plan.

[0129] "Database" refers to an information accumulation system that stores user information, tourist destination data, restaurant data, etc., and can be searched and retrieved as needed.

[0130] An "API" is an interface that allows different software applications to communicate with each other, and is used to obtain weather information, health status data, etc.

[0131] "Route" refers to a calculated route for efficiently visiting tourist attractions and restaurants, and is used to optimize the user's travel.

[0132] A "schedule" is a plan detailing the order of visits, means of transportation, and duration of stay at each location.

[0133] This invention is a system for efficiently planning travel plans for users, in which the server, terminal, and user each play specific roles. Specifically, the system uses user information, health status data, and weather information to generate travel plans tailored to the user's needs and even automatically makes the necessary reservations.

[0134] Hardware and software used

[0135] server:

[0136] The server uses a database management system (DBMS) to manage user information, tourist destination data, and restaurant data.

[0137] Use APIs to retrieve external weather and health data, for example, use the OpenWeatherMap API to retrieve weather information and health data from the Google Fit API or other health management applications.

[0138] It uses generative AI models to generate optimal travel plans based on user preferences and current conditions.

[0139] Device:

[0140] The user's mobile device, such as a smartphone or tablet, is used. These devices receive the information sent from the server and notify and display it to the user.

[0141] user:

[0142] Users log in to the system and provide information about their preferences and physical condition, and feedback is also sent to the server via their device.

[0143] Data processing and calculation

[0144] server

[0145] The server automatically retrieves past travel history and preference data from the database when a user logs in, for example using SQL queries to find the required data.

[0146] The server utilizes specific APIs to collect data about the user's current mood and physical condition. Data obtained from the health status API includes, for example, sleep duration and activity level.

[0147] The server retrieves weather information through a weather API, including current and near-future weather, temperature, precipitation, and wind speed.

[0148] The server comprehensively analyzes the acquired data and generates a travel plan that best suits the user's preferences and health status. This analysis and plan generation is performed using a generative AI model.

[0149] After generating the plan, the server sends a detailed schedule to the user's smartphone or tablet.

[0150] The server receives feedback from the user, adjusts the final plan, and automatically makes all necessary reservations, for example using accommodation booking APIs and transportation booking APIs.

[0151] Terminal

[0152] The device notifies the user of the travel plan received from the server and displays it on the screen, allowing the user to review the proposed plan and enter any changes or additions.

[0153] Users can send feedback to the server via their devices, including changes to selected tourist spots and restaurants, or changes to the order of visits.

[0154] Specific examples

[0155] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[0156] 1. Information gathering

[0157] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0158] Get weather information from the weather API and check that the weather is good for the day.

[0159] 2. Initial plan generation

[0160] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0161] 3. Creating a detailed plan

[0162] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0163] The terminal notifies the user of the schedule and displays it on the screen.

[0164] 4. User Feedback

[0165] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0166] 5. Final planning and booking

[0167] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[0168] In this way, users are freed from the tedious task of planning trips and can quickly obtain the best travel plans, thereby enriching users' travel experience and increasing their satisfaction.

[0169] Prompt Sentence Examples

[0170] "Today I want to enjoy nature."

[0171] "Looking for tourist spots that can be enjoyed even in the rain"

[0172] "I want you to plan a gourmet tour."

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] Step 1: User login and information gathering

[0175] server

[0176] When a user logs into the system, the server authenticates the entered username and password and starts a session.

[0177] Input: Username, Password

[0178] Data processing: Performs the authentication process and generates session information if successful.

[0179] Output: Session information, user ID

[0180] server

[0181] The server retrieves the user's past travel history and preferences from a database using SQL queries to find the required data based on the user ID.

[0182] Input: User ID

[0183] Data processing: Search and extract data on past travel history and preferences.

[0184] Output: Travel history data, preference data

[0185] server

[0186] The server uses the health management API to obtain the user's current health status data, for example, to collect activity data and physical condition data for a specific date.

[0187] Input: Health management API token, user ID

[0188] Data processing: Send a request to the health management API and analyze the response data.

[0189] Output: Health status data

[0190] Step 2: Get weather information

[0191] server

[0192] The server uses the weather API to obtain current and near-future weather information (e.g., temperature, precipitation, wind speed, etc.).

[0193] Input: Location, Weather API token

[0194] Data processing: Send a request to the weather API and analyze the response data.

[0195] Output: Weather information data

[0196] Step 3: Generate an initial plan

[0197] server

[0198] The server refers to the tourist destination database and restaurant database to select the tourist destination and restaurant that best suits the user's preferences, health condition, and weather conditions, thereby providing the user with the best options for their current situation.

[0199] Input: Travel history data, preference data, health data, weather information data

[0200] Data processing: Use generative AI models to perform integrated analysis of user information and external data.

[0201] Output: Initial plan data

[0202] server

[0203] The server calculates an efficient route based on the selected tourist spots and restaurants, using Google Maps API and other tools to calculate the optimal travel route.

[0204] Input: Initial plan data, location data

[0205] Data processing: Calculate the optimal route using Google Maps API.

[0206] Output: Route information data

[0207] Step 4: Create and communicate a detailed plan

[0208] server

[0209] Based on the initial plan and route information, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[0210] Input: Initial plan data, route information data

[0211] Data processing: Apply a schedule generation algorithm to create a detailed schedule.

[0212] Output: Detailed schedule data

[0213] server

[0214] The server transmits the generated detailed schedule to the user's terminal.

[0215] Input: Detailed schedule data, user terminal information

[0216] Data processing: Convert detailed schedule data into a format suitable for the device.

[0217] Output: Schedule notification data

[0218] Terminal

[0219] The terminal receives the detailed schedule sent from the server, notifies the user, and displays it on the screen.

[0220] Input: Schedule notification data

[0221] Data processing: Converting schedule notification data into a format for display in the user interface.

[0222] Output: Screen display data

[0223] Step 5: Incorporating user feedback

[0224] user

[0225] Users can review the proposed itinerary and make any necessary modifications, including adding or removing attractions or restaurants, or changing the order in which they are visited.

[0226] Input: Proposed itinerary

[0227] Data processing: Accepts user corrections as input.

[0228] Output: Corrective feedback data

[0229] server

[0230] The server receives feedback from the user and creates the final itinerary, which includes recalculation to reflect the user's changes.

[0231] Input: Corrective feedback data, initial plan data

[0232] Data processing: Recalculate the plan based on the modifications and generate the final plan.

[0233] Output: Final plan data

[0234] Step 6: Finalize your plan and book

[0235] server

[0236] Based on the final plan, the server automatically reserves accommodation, secures transportation, purchases tickets to tourist attractions, etc. This is done using a reservation API.

[0237] Input: Final plan data, Reservation API token

[0238] Data processing: Send a request to the booking API to retrieve booking information.

[0239] Output: Confirmed reservation data

[0240] server

[0241] The server sends the confirmed reservation details to the user's terminal and notifies them for confirmation.

[0242] Input: Reservation confirmation data, user terminal information

[0243] Data processing: Converts reservation confirmation data into a format suitable for the device.

[0244] Output: Booking notification data

[0245] Terminal

[0246] The terminal receives the reservation details sent from the server, notifies the user, and displays them on the screen.

[0247] Input: Booking notification data

[0248] Data processing: Converting booking notification data into a format for display in the user interface.

[0249] Output: Screen display data

[0250] (Application example 1)

[0251] 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."

[0252] Conventional food delivery services require users to search and select menus themselves, making it difficult to provide appropriate suggestions based on their physical condition or weather conditions. This makes it difficult for some users to choose meals that take their physical condition and weather into consideration, which can lead to lower satisfaction. Furthermore, if an appropriate dish is not selected, there is a risk of harming their health. Furthermore, personalized suggestions are lacking because the service does not fully utilize users' preferences and past ordering history.

[0253] 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.

[0254] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for generating a food delivery plan based on the user's preferences and weather information, means for notifying the user of the generated food delivery plan, means for modifying the food delivery plan based on the user's feedback, and means for finalizing the modified food delivery plan and placing an associated order. This makes it possible to suggest optimal dishes based on the user's individual preferences, physical condition, and weather conditions, and to automatically confirm the order.

[0255] "Means for obtaining user information" refers to means for collecting a user's past order history, preference data, health status, etc.

[0256] "Means for obtaining weather information" refers to means for obtaining current and near-future weather information such as temperature, precipitation, and wind speed.

[0257] The "means for generating a food delivery plan" is a means for selecting dishes that suit the user's preferences and physical condition based on user information and weather information.

[0258] The "means for notifying the user of the food delivery plan" is a means for sending the generated food delivery plan to the user's terminal and notifying the user.

[0259] The "means for modifying the food delivery plan based on user feedback" refers to a means for modifying the selected food delivery plan based on feedback information from users.

[0260] "Means for finalizing the food delivery plan and placing the related orders" means the means for finalizing the optimal food order based on the revised food delivery plan and placing the order with the restaurant.

[0261] "Means for searching menu information of affiliated restaurants and delivery services" refers to means for searching a database for menu information of affiliated restaurants and delivery services.

[0262] "Means for selecting dishes that best suit the user's preferences and weather conditions" refers to means for selecting the most suitable dishes based on user information and weather information.

[0263] "A means for suggesting the optimal delivery method from the user's current location to the restaurant" is a means for suggesting the optimal delivery method based on the user's current location and the restaurant's location information.

[0264] The present invention is a system that collects user information, weather information, and restaurant menu information, and provides an optimal food delivery plan based on the user's preferences and physical condition. Specific examples are presented below to explain the detailed configuration and operation of the present invention.

[0265] 1. Collection of User Information

[0266] When a user logs in to the system, the server automatically retrieves the user's past order history and preference data from the database. Specifically, it collects data on the user's favorite dishes, favorite restaurants, past order history, and health status. It also retrieves the user's current physical condition data from healthcare applications and wearable devices. This provides the basic data needed to generate a personalized food delivery plan.

[0267] 2. Obtaining weather information

[0268] The server uses a weather API to obtain current and near-future weather information, including temperature, precipitation, wind speed, etc. For example, the server uses the Weather API to obtain real-time weather information for the user's location.

[0269] 3. Generate a food delivery plan

[0270] The server integrates user information and weather information to suggest the best dishes to suit the user's preferences and physical condition. It searches menu information from affiliated restaurants and delivery services to select dishes that meet the user's requirements. Since it also takes weather conditions into account, it can, for example, suggest cold dishes on hot days and hot dishes on cold days.

[0271] 4. Plan Notification and Feedback

[0272] The generated food delivery plan is sent from the server to the user's device and notified. The user can then review the proposed plan via their smartphone or smart glasses. If the user provides feedback, the server will modify the plan based on that feedback and finalize the plan. For example, modifications can be made to accommodate the user's requests, such as allergies to certain ingredients or requests for other dishes.

[0273] 5. Order confirmation and execution

[0274] The server automatically places an order with partner restaurants based on the finalized food delivery plan, allowing users to enjoy the best food without any hassle. Order information is sent via the restaurant or delivery service's API.

[0275] Hardware and software used

[0276] The hardware used includes a server, smartphone, and smart glasses, while the software uses Weather API, restaurant APIs, and a user information management system to obtain data via APIs.

[0277] Examples of specific examples and prompts

[0278] For example, if a user types, "It's hot today, I want to eat something light," the server will suggest cold Chinese noodles based on the weather information indicating the high temperature and the user's request.

[0279] Example prompt sentence:

[0280] "It's hot today, I want to eat something refreshing."

[0281] By entering this prompt, the system will suggest the most suitable dish and automatically confirm the order.

[0282] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0283] Step 1:

[0284] When a user logs in to the system, the server obtains user information, including the user's past order history, preference data, and health status data. The input is the user's login information, and the output is the user's detailed information. Specifically, based on the user ID, the server collects past order history, preference food, and health status data from the database. This data is used in the next step.

[0285] Step 2:

[0286] The server uses a weather API to obtain weather information for the user's location. The input is the user's location information, and the output is current and near-future weather data. Specifically, the server calls the Weather API to obtain information such as temperature, precipitation, and wind speed. This data is then used to generate the plan.

[0287] Step 3:

[0288] The server integrates user information and weather information to generate a food delivery plan based on the user's preferences, physical condition, and weather conditions. The input is the user information and weather information obtained in the previous step, and the output is a list of suggested dishes. Specifically, it searches a database of affiliated restaurants and selects the dish that best suits the user's requirements. For example, it suggests cold dishes on hot days and hot dishes on cold days.

[0289] Step 4:

[0290] The server sends the generated food delivery plan to the user's device and notifies them. The input is the generated list of dishes, and the output is a notification displayed on the user's device. Specifically, a notification is sent to the user's smartphone or smart glasses, displaying detailed information about the proposed dishes.

[0291] Step 5:

[0292] The user submits feedback on the proposed food delivery plan. The input is the user's feedback information, and the output is the requested corrections. Specifically, the user enters information about allergies to specific ingredients and other desired dishes on the app and sends it to the server.

[0293] Step 6:

[0294] The server modifies the food delivery plan based on the user's feedback. The input is the user's feedback information, and the output is the final modified plan. Specifically, it searches the database again and reselects dishes that match the user's preferences.

[0295] Step 7:

[0296] The server places an order with the partner restaurant based on the finalized food delivery plan. The input is the finalized dish information, and the output is a notification of order confirmation to the restaurant. Specifically, the server calls the restaurant's API to automatically send the order information and receive confirmation.

[0297] Step 8:

[0298] The restaurant prepares the food based on the received order and delivers it to the user through a delivery service. The input is the order information from the server, and the output is a notification that the food has been delivered. Specifically, after cooking is complete, the food is handed over to a delivery person who then delivers it to the user.

[0299] 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.

[0300] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[0301] System configuration

[0302] The system consists of the following main components:

[0303] 1. How we collect user information

[0304] 2. How to obtain weather information

[0305] 3. Emotion Engine

[0306] 4. Travel plan generation method

[0307] 5. Means of notification

[0308] 6. Feedback channels

[0309] 7. Final confirmation method

[0310] 8. Reservation Methods

[0311] 9. How to select tourist spots and restaurants

[0312] 10. Means of transportation suggestion

[0313] Obtaining user information and weather information

[0314] server

[0315] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[0316] The server obtains current and future weather information in real time via a weather API.

[0317] Emotion recognition by emotion engine

[0318] server

[0319] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[0320] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[0321] Travel plan generation and notification

[0322] server

[0323] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[0324] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[0325] The generated travel plan is sent to the user's device.

[0326] Terminal

[0327] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[0328] User feedback and plan revisions

[0329] User

[0330] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[0331] server

[0332] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[0333] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[0334] Specific examples

[0335] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[0336] 1. Information gathering

[0337] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0338] Get weather information from the weather API and check that the weather is good for the day.

[0339] 2. Emotion recognition

[0340] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[0341] 3. Initial plan generation

[0342] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0343] 4. Creating a detailed plan

[0344] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0345] The terminal notifies the user of the schedule and displays it on the screen.

[0346] 5. User Feedback

[0347] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0348] 6. Final planning and booking

[0349] The server incorporates user feedback and creates the final plan.

[0350] The server automatically issues park admission tickets and reserves cafe seats.

[0351] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[0352] The processing flow will be explained below.

[0353] Step 1:

[0354] A user logs in to the system.

[0355] Step 2:

[0356] The server retrieves the user's past travel history and preference data from a database.

[0357] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[0358] Step 3:

[0359] The server sends a request to the weather API to obtain current and near-future weather information.

[0360] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[0361] Step 4:

[0362] The server uses an emotion engine to analyze voice input and facial recognition data to recognize the user's emotions.

[0363] How it works: Audio and video data captured through a microphone and camera is sent to the emotion engine, where it performs text analysis, audio analysis, image analysis, etc.

[0364] Example: When a user says, "I'm a little tired, but I want to go somewhere," the emotion engine analyzes the voice data and recognizes it as, "I'm tired, but I'm looking for a new experience."

[0365] Step 5:

[0366] The server integrates the above acquired data (user information, weather information, emotion data) and selects appropriate candidates from a tourist destination database and a restaurant database.

[0367] How it works: Extracts and filters a list of tourist attractions and restaurants from a database that match the user's preferences and current sentiment.

[0368] Step 6:

[0369] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[0370] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[0371] Step 7:

[0372] The server generates the initial itinerary and creates a detailed schedule.

[0373] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[0374] Example: Create a schedule that involves visiting a nature park in the morning and relaxing at a cafe in the afternoon.

[0375] Step 8:

[0376] The server sends the generated schedule to the user's terminal.

[0377] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[0378] Step 9:

[0379] The terminal notifies the user of the detailed schedule received from the server.

[0380] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[0381] Step 10:

[0382] The user reviews the proposed itinerary and makes any necessary modifications.

[0383] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[0384] Example: When a user says, "I want to add another tourist spot after the cafe," that information is sent to the server.

[0385] Step 11:

[0386] The server receives the user's modification requests and creates the final itinerary.

[0387] How it works: The algorithm re-applies the plan and optimizes it based on the corrections received from the user.

[0388] Step 12:

[0389] The server automatically makes related reservations based on the finalized plan.

[0390] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[0391] Example: Buying tickets online to selected tourist attractions and confirming cafe reservations.

[0392] In this way, an optimal travel plan that takes the user's emotions into account can be automatically generated and flexibly revised based on feedback.

[0393] Example 2

[0394] 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."

[0395] Conventional travel planning systems have difficulty generating plans that take into account the user's emotions and moods. Furthermore, the travel plans proposed to users are not always appropriate for the user's mood or real-time weather information, resulting in a decrease in user satisfaction. Therefore, there is a need for a system that can automatically generate more personalized travel plans based on the user's emotions and weather information, as well as flexible feedback and revisions based on those plans.

[0396] 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.

[0397] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for recognizing and analyzing user emotion data, means for generating a travel plan based on the user's preferences, weather information, and emotion data, means for notifying the user of the generated travel plan, means for modifying the travel plan based on user feedback, and means for finalizing the modified travel plan and making related reservations. This enables the generation of an optimal travel plan that takes into account the user's emotions, preferences, and real-time weather information, and the flexible modification of the plan based on user feedback.

[0398] "User Information" means data including a user's past travel history, preferences, budget, etc.

[0399] "Weather Information" means data about current and future weather conditions obtained through the Weather API.

[0400] "Emotional Data" refers to information about a user's emotional state based on tone, speed, facial expression, etc., obtained from their voice and facial expressions.

[0401] A "travel plan" is a plan that includes the selection of tourist spots and restaurants, as well as route planning, and is generated based on the user's emotions, preferences, and weather information.

[0402] "Feedback" refers to opinions and requests received by users when they input corrections or requests regarding the proposed travel plan.

[0403] "Notification" refers to the process of sending the travel plan generated by the server to the user's terminal and informing the user.

[0404] "Reservation" is the process of securing necessary accommodation, transportation, tickets to tourist attractions, etc. based on the final travel plan generated.

[0405] "Tourist destinations" refer to places and facilities that users would like to visit while traveling.

[0406] "Food and Beverage" refers to the restaurants and cafes that you choose to eat at during your trip.

[0407] "Transportation" refers to suggestions for transportation and routes that users can use to travel from their current location to their destination.

[0408] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[0409] System configuration

[0410] The system consists of the following main components:

[0411] 1. How we collect user information

[0412] 2. How to obtain weather information

[0413] 3. Emotion Engine

[0414] 4. Travel plan generation method

[0415] 5. Means of notification

[0416] 6. Feedback channels

[0417] 7. Final confirmation method

[0418] 8. Reservation Methods

[0419] 9. How to select tourist spots and restaurants

[0420] 10. Means of transportation suggestion

[0421] Obtaining user information and weather information

[0422] server

[0423] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[0424] The server obtains current and future weather information in real time via a weather API.

[0425] Emotion recognition by emotion engine

[0426] server

[0427] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[0428] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[0429] Travel plan generation and notification

[0430] server

[0431] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[0432] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[0433] The generated travel plan is sent to the user's device.

[0434] Terminal

[0435] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[0436] User feedback and plan revisions

[0437] User

[0438] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[0439] server

[0440] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[0441] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[0442] Specific examples

[0443] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[0444] 1. Information gathering

[0445] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0446] Get weather information from the weather API and check that the weather is good for the day.

[0447] 2. Emotion recognition

[0448] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[0449] 3. Initial plan generation

[0450] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0451] 4. Creating a detailed plan

[0452] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0453] The terminal notifies the user of the schedule and displays it on the screen.

[0454] 5. User Feedback

[0455] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0456] 6. Final planning and booking

[0457] The server incorporates user feedback and creates the final plan.

[0458] The server automatically issues park admission tickets and reserves cafe seats.

[0459] Example prompt: "I want to go somewhere for a change today. I'm tired, but I want to find a new place."

[0460] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[0461] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0462] Step 1: Get user information

[0463] When a user logs in to the system, the server reads the user's past travel history and preference data from the database. Specifically, it executes an SQL query such as SELECT FROM user_preferences WHERE user_id = :user_id;. The input data includes the user's ID, and the output is information about the user's past travel history and preferences. This obtains the user's individual information and serves as the basis for generating a customized travel plan.

[0464] Step 2: Get weather information

[0465] The server uses a weather API (for example, a general weather API service) to obtain current and future weather information. Specifically, it sends an API request such as curl -X GET "http: / / api.openweathermap.org / data / 2.5 / weather?q=City&appid=YOUR_API_KEY". This input data includes geographic location data, and the output is weather information for that location. This allows it to generate travel plans that take current and forecast weather into account.

[0466] Step 3: Emotion Recognition

[0467] The server uses an emotion engine to analyze the emotional data entered by the user through voice input or facial recognition. Emotions are recognized based on tone and speed in the voice data, and facial expressions in the facial recognition data. Specifically, the server sends audio and images as a POST request to an emotion engine API (such as a general emotion analysis API). This input data includes audio and image data, and the user's emotional state is obtained as output. This makes it possible to propose travel plans that take into account the user's current emotions.

[0468] Step 4: Generate your travel plan

[0469] The server generates a travel plan by integrating the user's preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it selects tourist spots where they can enjoy nature. Specifically, to extract travel destinations based on preferences, weather, and emotional information, it executes an SQL query such as SELECT FROM locations WHERE category = 'nature' AND suitability_score > 7;. The input data includes the user's emotional state and weather information, and the output is a list of candidate tourist spots and restaurants.

[0470] Step 5: Plan Notification

[0471] The server sends the generated itinerary to the user's device. Specifically, it sends the itinerary data via an HTTP request. The input includes the information about the generated itinerary, and the output is the data received by the user's device. The device receives the itinerary sent from the server and notifies the user using push notifications or in-app notifications.

[0472] Step 6: Gather user feedback

[0473] The user reviews the proposed travel plan and makes any necessary modifications. Specifically, the user enters and submits the modified data on the device. The device then sends a POST request using JSON-formatted data to send the user's feedback to the server. The input data includes the user's modification request, and the feedback data is sent to the server as output.

[0474] Step 7: Generate the final plan

[0475] The server generates a final itinerary based on the user's feedback. Specifically, it generates a new itinerary that reflects the user's modifications and queries the database again to update the optimal route and tourist destination information. The input data includes the user's feedback, and the revised itinerary is obtained as the output.

[0476] Step 8: Making a reservation

[0477] The server automatically makes the necessary reservations based on the final travel plan. Specifically, it uses a reservation API (for example, a general reservation service API) to reserve accommodations, tickets to tourist attractions, and restaurants. The input data includes details of the final travel plan, and the output is reservation confirmation data.

[0478] (Application example 2)

[0479] 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."

[0480] Conventional factory work schedule management is based primarily on work procedures and the efficiency of each process, but it is difficult to consider individual worker conditions such as the emotional state and fatigue level of workers. This has led to problems such as reduced production efficiency, increased work errors, and concerns about worker safety and health. The present invention aims to solve these problems by recognizing workers' emotional states in real time and managing work schedules flexibly based on this information.

[0481] The specific processing by the specific 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 acquiring user (worker) information, means for acquiring weather information, means for recognizing the emotional state of the user (worker), means for generating a work schedule based on the user's (worker's) preferences, weather information, and emotional information, means for notifying the user (worker) of the generated work schedule, means for modifying the work schedule based on user (worker) feedback, and means for finalizing the modified work schedule and allocating related tasks. This enables the generation of flexible and efficient work schedules that take into account the emotional state of workers.

[0482] "Means for obtaining user information" refers to the function by which the system collects personal information about users (workers), past work history, preferred tasks, etc.

[0483] "Means for obtaining weather information" refers to the function by which the system obtains data on weather and climate from external information services and reflects this in work schedules.

[0484] "Means for recognizing the user's emotional state" refers to the system's ability to detect the emotions and psychological state of workers in real time and analyze this as data.

[0485] The "means for generating a work schedule" is a function that automatically creates an optimal work schedule based on the user's preferences, weather information, and emotional information.

[0486] The "means for notifying the user of the generated work schedule" is a function that notifies the created work schedule to the worker in real time and provides the information.

[0487] "Means for modifying work schedules based on user feedback" is a function that receives the opinions and requests of workers and flexibly modifies the work schedule accordingly.

[0488] The "means for finalizing the revised work schedule and allocating related tasks" is a function for appropriately allocating various related work tasks based on the finalized work schedule.

[0489] "Means for selecting the optimal task according to the conditions of the work site and equipment and calculating the efficient work route" is a function that selects the optimal work task and calculates the efficient work sequence, taking into account the conditions of the work site and the operating status of the machines.

[0490] "A means for proposing the optimal means of transportation from the worker's current location to the target work location" is a function that suggests the optimal route and means of transportation from the worker's current location to the designated work location.

[0491] This system is a factory robot management system that optimizes work schedules based on the emotional state of the user (worker). The system consists of the following main components:

[0492] System configuration

[0493] 1. How we collect user information

[0494] The server retrieves the user's activity history, preferences, and past feedback from a database, including the tasks they have performed in the past, their preferred tasks, and their work pace.

[0495] 2. How to obtain weather information

[0496] The server uses external weather APIs to obtain real-time current and future weather information, which helps to adjust the environment within the factory and maximize work efficiency.

[0497] 3. Emotional state recognition method

[0498] The server uses an emotion engine to analyze the user's voice input, facial recognition, and vital sign data. The emotion engine determines the user's emotional state by analyzing tone and speed from the voice data and facial expressions from the facial data. This emotion engine uses voice recognition software and facial recognition libraries (e.g., OpenCV, Dlib).

[0499] 4. Work Schedule Generation Method

[0500] The server generates a work schedule by integrating user preferences, weather information, and emotional information, assigning lighter tasks when the user is tired and more complex tasks when the user is less stressed.

[0501] 5. Means of notification

[0502] The generated work schedule is sent from the server to the user's device (such as a smartphone or tablet) and notified in real time.

[0503] 6. Feedback channels

[0504] Users provide feedback on the proposed work schedule, which is sent from the device to the server and reflected in schedule revisions.

[0505] 7. Final confirmation method

[0506] The server receives user feedback and determines the final work schedule, and then allocates related tasks based on this schedule.

[0507] Specific examples

[0508] For example, if Worker A says "I'm tired today," and the emotion engine determines from the voice and facial recognition data that the emotion is "I'm stressed," the system will process as follows:

[0509] 1. Information gathering

[0510] The server retrieves the user's past activity history and preference data, and retrieves weather information from the weather API.

[0511] 2. Emotion recognition

[0512] The emotion engine recognizes emotions such as "tired and stressed" from the user's voice and facial expression data.

[0513] 3. Initial schedule generation

[0514] The server generates a work schedule that suggests simple work tasks (e.g., quality checks) and short breaks based on the user's condition.

[0515] 4. Create a detailed schedule

[0516] The server creates a detailed schedule including suggested tasks and break times and sends it to the device, which then notifies the user and displays the schedule on the screen.

[0517] 5. User Feedback

[0518] The user provides feedback on the proposed schedule, requesting changes to some tasks.

[0519] 6. Final schedule and task allocation

[0520] The server reflects the user's feedback, determines the final schedule, and then assigns related tasks based on the determined schedule.

[0521] Prompt Sentence Examples

[0522] Prompt for the generative AI model:

[0523] The system analyzes the facial image data and voice data of workers to recognize their emotional state and assign them the next work task. For example, if a worker is recognized as "tired," it will schedule them for light work or a break.

[0524] In this way, the emotion engine can create a flexible work schedule that takes into account the emotional state of workers, and optimally allocate tasks. This system can simultaneously improve worker safety and efficiency.

[0525] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0526] Step 1:

[0527] The server obtains user (worker) information. As input, it receives the user ID and authentication information and extracts data from the user database, such as past work history, preferences, and feedback. It processes the data by filtering and integrating the necessary data. The output is the user's work history and preference data.

[0528] Step 2:

[0529] The server retrieves weather information. As input, a weather API request is sent, and the retrieved weather data is returned to the server. The data is processed by analyzing the current and future weather data and extracting the necessary parts. The output is real-time weather information.

[0530] Step 3:

[0531] The server recognizes the user's emotional state. The user's voice data and facial image data are used as input. An emotion engine is used to analyze tone and speed from the voice data and facial expressions from the facial image data. This determines the user's emotional state. The output is the user's current emotional state.

[0532] Step 4:

[0533] The server generates the work schedule. User preferences, weather information, and emotional information are used as input. This data is integrated and an AI model is used to calculate the optimal work schedule. Specifically, each data point is evaluated to select the most efficient and suitable task for the user. The output is the generated work schedule.

[0534] Step 5:

[0535] The server notifies the user of the generated work schedule. Work schedule data is given as input and sent to the terminal. The data is then converted into a notification format and sent to the user's smartphone or tablet. The output is a schedule notification on the user's terminal.

[0536] Step 6:

[0537] The user provides feedback on the work schedule. The input is the proposed schedule and the user's feedback. The terminal sends the user's opinions and change requests to the server. The data is processed by organizing and analyzing the feedback content. The output is user feedback data.

[0538] Step 7:

[0539] The server modifies the work schedule based on user feedback. The feedback data is used as input. The AI ​​model is then used again to update the schedule to reflect the feedback. The data is then processed to regenerate the schedule. The output is the modified work schedule.

[0540] Step 8:

[0541] The server finalizes the revised work schedule and allocates the associated tasks. The revised schedule data is used as input. The final schedule is finalized and each task is allocated to the appropriate worker. Data processing involves confirming and finalizing the task allocation. The output is an execution list of the allocated tasks.

[0542] 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.

[0543] 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.

[0544] 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.

[0545] [Second embodiment]

[0546] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0547] 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.

[0548] 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).

[0549] 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.

[0550] 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.

[0551] 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).

[0552] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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."

[0558] This invention is a system that saves users the trouble of making travel plans and quickly provides optimal travel plans. The system of the present invention operates by combining multiple means and generates travel plans based on data such as user information, weather information, and databases of tourist spots and restaurants.

[0559] This system is configured as follows:

[0560] 1. Collection of User Information

[0561] server

[0562] When a user logs in to the system, the server automatically retrieves the user's past travel history and preference data from the database, such as tourist spots the user has visited in the past, food preferences, and travel budget.

[0563] The server uses a specific API (e.g., an application or wearable device that manages health data) to obtain the user's current mood and physical condition.

[0564] 2. Integration of user information and weather information

[0565] server

[0566] The server uses a weather API to retrieve current and near-future weather information, including temperature, precipitation, wind speed, etc.

[0567] The server compares the acquired user information with weather information and selects a travel destination that suits the user's preferences and physical condition.

[0568] 3. Generate the initial plan

[0569] server

[0570] The server searches a tourist spot database and a restaurant database to select the tourist spot and restaurant that best suit the user's preferences and weather conditions.

[0571] The server calculates an efficient route based on the selected tourist spots and restaurants.

[0572] 4. Creating and notifying detailed plans

[0573] server

[0574] Based on the initial plan, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[0575] The generated schedule is sent to the user's device.

[0576] Terminal

[0577] The terminal notifies the user of the detailed schedule sent from the server and displays it on the screen.

[0578] User

[0579] Users can review the proposed itinerary and make any necessary modifications, for example, adding or removing specific tourist attractions.

[0580] 5. Finalize the plan and make a reservation

[0581] server

[0582] The server creates a final itinerary based on the modifications made by the user.

[0583] Based on the final plan created, accommodation reservations, transportation arrangements, and ticket purchases for sightseeing spots are automatically made. For example, hotel reservation APIs and plane ticket reservation APIs are used to quickly make the necessary reservations.

[0584] Specific examples

[0585] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[0586] 1. Information gathering

[0587] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0588] Get weather information from the weather API and check that the weather is good for the day.

[0589] 2. Initial plan generation

[0590] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0591] 3. Creating a detailed plan

[0592] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0593] The terminal notifies the user of the schedule and displays it on the screen.

[0594] 4. User Feedback

[0595] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0596] 5. Final planning and booking

[0597] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[0598] In this way, users can eliminate the need for tedious planning and quickly obtain optimal travel plans. This system allows users to enjoy their trips with ease and improves their satisfaction.

[0599] The processing flow will be explained below.

[0600] Step 1:

[0601] A user logs in to the system.

[0602] Step 2:

[0603] The server retrieves the user's past travel history and preference data from a database.

[0604] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[0605] Step 3:

[0606] The server sends a request to the weather API to obtain current and near-future weather information.

[0607] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[0608] Step 4:

[0609] The server obtains the user's current mood and physical condition from various sensors and input forms.

[0610] How it works: Collects health data from smartphone APIs and medical interview data from users.

[0611] Step 5:

[0612] The server integrates the user information and weather information and searches a database of tourist attractions and restaurants.

[0613] How it works: It runs a search query against each database based on the user's preferences and weather conditions to generate a list of candidates.

[0614] Step 6:

[0615] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[0616] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[0617] Step 7:

[0618] The server generates the initial itinerary and creates a detailed schedule.

[0619] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[0620] Step 8:

[0621] The server sends the generated schedule to the user's terminal.

[0622] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[0623] Step 9:

[0624] The terminal notifies the user of the detailed schedule received from the server.

[0625] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[0626] Step 10:

[0627] The user reviews the proposed itinerary and makes any necessary modifications.

[0628] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[0629] Step 11:

[0630] The server receives the user's modification requests and creates the final itinerary.

[0631] How it works: The algorithm re-optimizes the plan based on user feedback.

[0632] Step 12:

[0633] The server automatically makes related reservations based on the finalized plan.

[0634] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[0635] In this way, it is possible to provide the user with an optimal travel plan that meets their needs.

[0636] Example 1

[0637] 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."

[0638] Conventional travel planning systems require users to individually search for travel plans and manually plan them, which is time-consuming and laborious. It is also difficult to provide optimal travel plans that take into account weather and the user's health condition. It is also difficult to immediately reflect user feedback and revise travel plans in real time. To solve these issues, there is a need for a fast and flexible travel plan generation and booking automation system that takes into account user preferences, health condition, and weather information.

[0639] 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.

[0640] In this invention, the server includes means for acquiring user information, means for acquiring health status data, means for acquiring weather information, means for generating a travel plan based on the user's preferences, health status, and weather information, means for notifying the user of the generated travel plan, means for modifying the travel plan based on the user's feedback, and means for finalizing the modified travel plan and making related reservations. This allows users to quickly obtain an optimal travel plan based on their health status and weather conditions, eliminating the need for individual searches and manual planning. Furthermore, real-time plan modifications based on user feedback improve travel satisfaction.

[0641] "User information" is a general term for data such as a user's past travel history, preferences, budget, etc.

[0642] "Health data" refers to information about a user's current physical condition or mood, obtained from wearable devices or health management applications.

[0643] "Weather information" refers to data about current and near-future weather conditions obtained through weather APIs, including temperature, precipitation, wind speed, etc.

[0644] A "travel plan" is a detailed schedule that includes planned visits to tourist attractions and restaurants, generated based on the user's preferences, health status, and weather information.

[0645] "Device" is a general term for electronic devices used by users, including smartphones and tablets.

[0646] "Feedback" refers to any corrections or additional instructions given by the user to the proposed travel plan, which are sent to the server via the terminal.

[0647] "Reservation" refers to procedures such as purchasing accommodation, transportation, and tickets to tourist attractions based on a confirmed travel plan.

[0648] "Database" refers to an information accumulation system that stores user information, tourist destination data, restaurant data, etc., and can be searched and retrieved as needed.

[0649] An "API" is an interface that allows different software applications to communicate with each other, and is used to obtain weather information, health status data, etc.

[0650] "Route" refers to a calculated route for efficiently visiting tourist attractions and restaurants, and is used to optimize the user's travel.

[0651] A "schedule" is a plan detailing the order of visits, means of transportation, and duration of stay at each location.

[0652] This invention is a system for efficiently planning travel plans for users, in which the server, terminal, and user each play specific roles. Specifically, the system uses user information, health status data, and weather information to generate travel plans tailored to the user's needs and even automatically makes the necessary reservations.

[0653] Hardware and software used

[0654] server:

[0655] The server uses a database management system (DBMS) to manage user information, tourist destination data, and restaurant data.

[0656] Use APIs to retrieve external weather and health data, for example, use the OpenWeatherMap API to retrieve weather information and health data from the Google Fit API or other health management applications.

[0657] It uses generative AI models to generate optimal travel plans based on user preferences and current conditions.

[0658] Device:

[0659] The user's mobile device, such as a smartphone or tablet, is used. These devices receive the information sent from the server and notify and display it to the user.

[0660] user:

[0661] Users log in to the system and provide information about their preferences and physical condition, and feedback is also sent to the server via their device.

[0662] Data processing and calculation

[0663] server

[0664] The server automatically retrieves past travel history and preference data from the database when a user logs in, for example using SQL queries to find the required data.

[0665] The server utilizes specific APIs to collect data about the user's current mood and physical condition. Data obtained from the health status API includes, for example, sleep duration and activity level.

[0666] The server retrieves weather information through a weather API, including current and near-future weather, temperature, precipitation, and wind speed.

[0667] The server comprehensively analyzes the acquired data and generates a travel plan that best suits the user's preferences and health status. This analysis and plan generation is performed using a generative AI model.

[0668] After generating the plan, the server sends a detailed schedule to the user's smartphone or tablet.

[0669] The server receives feedback from the user, adjusts the final plan, and automatically makes all necessary reservations, for example using accommodation booking APIs and transportation booking APIs.

[0670] Terminal

[0671] The device notifies the user of the travel plan received from the server and displays it on the screen, allowing the user to review the proposed plan and enter any changes or additions.

[0672] Users can send feedback to the server via their devices, including changes to selected tourist spots and restaurants, or changes to the order of visits.

[0673] Specific examples

[0674] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[0675] 1. Information gathering

[0676] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0677] Get weather information from the weather API and check that the weather is good for the day.

[0678] 2. Initial plan generation

[0679] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0680] 3. Creating a detailed plan

[0681] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0682] The terminal notifies the user of the schedule and displays it on the screen.

[0683] 4. User Feedback

[0684] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0685] 5. Final planning and booking

[0686] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[0687] In this way, users are freed from the tedious task of planning trips and can quickly obtain the best travel plans, thereby enriching users' travel experience and increasing their satisfaction.

[0688] Prompt Sentence Examples

[0689] "Today I want to enjoy nature."

[0690] "Looking for tourist spots that can be enjoyed even in the rain"

[0691] "I want you to plan a gourmet tour."

[0692] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0693] Step 1: User login and information gathering

[0694] server

[0695] When a user logs into the system, the server authenticates the entered username and password and starts a session.

[0696] Input: Username, Password

[0697] Data processing: Performs the authentication process and generates session information if successful.

[0698] Output: Session information, user ID

[0699] server

[0700] The server retrieves the user's past travel history and preferences from a database using SQL queries to find the required data based on the user ID.

[0701] Input: User ID

[0702] Data processing: Search and extract data on past travel history and preferences.

[0703] Output: Travel history data, preference data

[0704] server

[0705] The server uses the health management API to obtain the user's current health status data, for example, to collect activity data and physical condition data for a specific date.

[0706] Input: Health management API token, user ID

[0707] Data processing: Send a request to the health management API and analyze the response data.

[0708] Output: Health status data

[0709] Step 2: Get weather information

[0710] server

[0711] The server uses the weather API to obtain current and near-future weather information (e.g., temperature, precipitation, wind speed, etc.).

[0712] Input: Location, Weather API token

[0713] Data processing: Send a request to the weather API and analyze the response data.

[0714] Output: Weather information data

[0715] Step 3: Generate an initial plan

[0716] server

[0717] The server refers to the tourist destination database and restaurant database to select the tourist destination and restaurant that best suits the user's preferences, health condition, and weather conditions, thereby providing the user with the best options for their current situation.

[0718] Input: Travel history data, preference data, health data, weather information data

[0719] Data processing: Use generative AI models to perform integrated analysis of user information and external data.

[0720] Output: Initial plan data

[0721] server

[0722] The server calculates an efficient route based on the selected tourist spots and restaurants, using Google Maps API and other tools to calculate the optimal travel route.

[0723] Input: Initial plan data, location data

[0724] Data processing: Calculate the optimal route using Google Maps API.

[0725] Output: Route information data

[0726] Step 4: Create and communicate a detailed plan

[0727] server

[0728] Based on the initial plan and route information, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[0729] Input: Initial plan data, route information data

[0730] Data processing: Apply a schedule generation algorithm to create a detailed schedule.

[0731] Output: Detailed schedule data

[0732] server

[0733] The server transmits the generated detailed schedule to the user's terminal.

[0734] Input: Detailed schedule data, user terminal information

[0735] Data processing: Convert detailed schedule data into a format suitable for the device.

[0736] Output: Schedule notification data

[0737] Terminal

[0738] The terminal receives the detailed schedule sent from the server, notifies the user, and displays it on the screen.

[0739] Input: Schedule notification data

[0740] Data processing: Converting schedule notification data into a format for display in the user interface.

[0741] Output: Screen display data

[0742] Step 5: Incorporating user feedback

[0743] user

[0744] Users can review the proposed itinerary and make any necessary modifications, including adding or removing attractions or restaurants, or changing the order in which they are visited.

[0745] Input: Proposed itinerary

[0746] Data processing: Accepts user corrections as input.

[0747] Output: Corrective feedback data

[0748] server

[0749] The server receives feedback from the user and creates the final itinerary, which includes recalculation to reflect the user's changes.

[0750] Input: Corrective feedback data, initial plan data

[0751] Data processing: Recalculate the plan based on the modifications and generate the final plan.

[0752] Output: Final plan data

[0753] Step 6: Finalize your plan and book

[0754] server

[0755] Based on the final plan, the server automatically reserves accommodation, secures transportation, purchases tickets to tourist attractions, etc. This is done using a reservation API.

[0756] Input: Final plan data, Reservation API token

[0757] Data processing: Send a request to the booking API to retrieve booking information.

[0758] Output: Confirmed reservation data

[0759] server

[0760] The server sends the confirmed reservation details to the user's terminal and notifies them for confirmation.

[0761] Input: Reservation confirmation data, user terminal information

[0762] Data processing: Converts reservation confirmation data into a format suitable for the device.

[0763] Output: Booking notification data

[0764] Terminal

[0765] The terminal receives the reservation details sent from the server, notifies the user, and displays them on the screen.

[0766] Input: Booking notification data

[0767] Data processing: Converting booking notification data into a format for display in the user interface.

[0768] Output: Screen display data

[0769] (Application example 1)

[0770] 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."

[0771] Conventional food delivery services require users to search and select menus themselves, making it difficult to provide appropriate suggestions based on their physical condition or weather conditions. This makes it difficult for some users to choose meals that take their physical condition and weather into consideration, which can lead to lower satisfaction. Furthermore, if an appropriate dish is not selected, there is a risk of harming their health. Furthermore, personalized suggestions are lacking because the service does not fully utilize users' preferences and past ordering history.

[0772] 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.

[0773] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for generating a food delivery plan based on the user's preferences and weather information, means for notifying the user of the generated food delivery plan, means for modifying the food delivery plan based on the user's feedback, and means for finalizing the modified food delivery plan and placing an associated order. This makes it possible to suggest optimal dishes based on the user's individual preferences, physical condition, and weather conditions, and to automatically confirm the order.

[0774] "Means for obtaining user information" refers to means for collecting a user's past order history, preference data, health status, etc.

[0775] "Means for obtaining weather information" refers to means for obtaining current and near-future weather information such as temperature, precipitation, and wind speed.

[0776] The "means for generating a food delivery plan" is a means for selecting dishes that suit the user's preferences and physical condition based on user information and weather information.

[0777] The "means for notifying the user of the food delivery plan" is a means for sending the generated food delivery plan to the user's terminal and notifying the user.

[0778] The "means for modifying the food delivery plan based on user feedback" refers to a means for modifying the selected food delivery plan based on feedback information from users.

[0779] "Means for finalizing the food delivery plan and placing the related orders" means the means for finalizing the optimal food order based on the revised food delivery plan and placing the order with the restaurant.

[0780] "Means for searching menu information of affiliated restaurants and delivery services" refers to means for searching a database for menu information of affiliated restaurants and delivery services.

[0781] "Means for selecting dishes that best suit the user's preferences and weather conditions" refers to means for selecting the most suitable dishes based on user information and weather information.

[0782] "A means for suggesting the optimal delivery method from the user's current location to the restaurant" is a means for suggesting the optimal delivery method based on the user's current location and the restaurant's location information.

[0783] The present invention is a system that collects user information, weather information, and restaurant menu information, and provides an optimal food delivery plan based on the user's preferences and physical condition. Specific examples are presented below to explain the detailed configuration and operation of the present invention.

[0784] 1. Collection of User Information

[0785] When a user logs in to the system, the server automatically retrieves the user's past order history and preference data from the database. Specifically, it collects data on the user's favorite dishes, favorite restaurants, past order history, and health status. It also retrieves the user's current physical condition data from healthcare applications and wearable devices. This provides the basic data needed to generate a personalized food delivery plan.

[0786] 2. Obtaining weather information

[0787] The server uses a weather API to obtain current and near-future weather information, including temperature, precipitation, wind speed, etc. For example, the server uses the Weather API to obtain real-time weather information for the user's location.

[0788] 3. Generate a food delivery plan

[0789] The server integrates user information and weather information to suggest the best dishes to suit the user's preferences and physical condition. It searches menu information from affiliated restaurants and delivery services to select dishes that meet the user's requirements. Since it also takes weather conditions into account, it can, for example, suggest cold dishes on hot days and hot dishes on cold days.

[0790] 4. Plan Notification and Feedback

[0791] The generated food delivery plan is sent from the server to the user's device and notified. The user can then review the proposed plan via their smartphone or smart glasses. If the user provides feedback, the server will modify the plan based on that feedback and finalize the plan. For example, modifications can be made to accommodate the user's requests, such as allergies to certain ingredients or requests for other dishes.

[0792] 5. Order confirmation and execution

[0793] The server automatically places an order with partner restaurants based on the finalized food delivery plan, allowing users to enjoy the best food without any hassle. Order information is sent via the restaurant or delivery service's API.

[0794] Hardware and software used

[0795] The hardware used includes a server, smartphone, and smart glasses, while the software uses Weather API, restaurant APIs, and a user information management system to obtain data via APIs.

[0796] Examples of specific examples and prompts

[0797] For example, if a user types, "It's hot today, I want to eat something light," the server will suggest cold Chinese noodles based on the weather information indicating the high temperature and the user's request.

[0798] Example prompt sentence:

[0799] "It's hot today, I want to eat something refreshing."

[0800] By entering this prompt, the system will suggest the most suitable dish and automatically confirm the order.

[0801] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0802] Step 1:

[0803] When a user logs in to the system, the server obtains user information, including the user's past order history, preference data, and health status data. The input is the user's login information, and the output is the user's detailed information. Specifically, based on the user ID, the server collects past order history, preference food, and health status data from the database. This data is used in the next step.

[0804] Step 2:

[0805] The server uses a weather API to obtain weather information for the user's location. The input is the user's location information, and the output is current and near-future weather data. Specifically, the server calls the Weather API to obtain information such as temperature, precipitation, and wind speed. This data is then used to generate the plan.

[0806] Step 3:

[0807] The server integrates user information and weather information to generate a food delivery plan based on the user's preferences, physical condition, and weather conditions. The input is the user information and weather information obtained in the previous step, and the output is a list of suggested dishes. Specifically, it searches a database of affiliated restaurants and selects the dish that best suits the user's requirements. For example, it suggests cold dishes on hot days and hot dishes on cold days.

[0808] Step 4:

[0809] The server sends the generated food delivery plan to the user's device and notifies them. The input is the generated list of dishes, and the output is a notification displayed on the user's device. Specifically, a notification is sent to the user's smartphone or smart glasses, displaying detailed information about the proposed dishes.

[0810] Step 5:

[0811] The user submits feedback on the proposed food delivery plan. The input is the user's feedback information, and the output is the requested corrections. Specifically, the user enters information about allergies to specific ingredients and other desired dishes on the app and sends it to the server.

[0812] Step 6:

[0813] The server modifies the food delivery plan based on the user's feedback. The input is the user's feedback information, and the output is the final modified plan. Specifically, it searches the database again and reselects dishes that match the user's preferences.

[0814] Step 7:

[0815] The server places an order with the partner restaurant based on the finalized food delivery plan. The input is the finalized dish information, and the output is a notification of order confirmation to the restaurant. Specifically, the server calls the restaurant's API to automatically send the order information and receive confirmation.

[0816] Step 8:

[0817] The restaurant prepares the food based on the received order and delivers it to the user through a delivery service. The input is the order information from the server, and the output is a notification that the food has been delivered. Specifically, after cooking is complete, the food is handed over to a delivery person who then delivers it to the user.

[0818] 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.

[0819] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[0820] System configuration

[0821] The system consists of the following main components:

[0822] 1. How we collect user information

[0823] 2. How to obtain weather information

[0824] 3. Emotion Engine

[0825] 4. Travel plan generation method

[0826] 5. Means of notification

[0827] 6. Feedback channels

[0828] 7. Final confirmation method

[0829] 8. Reservation Methods

[0830] 9. How to select tourist spots and restaurants

[0831] 10. Means of transportation suggestion

[0832] Obtaining user information and weather information

[0833] server

[0834] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[0835] The server obtains current and future weather information in real time via a weather API.

[0836] Emotion recognition by emotion engine

[0837] server

[0838] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[0839] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[0840] Travel plan generation and notification

[0841] server

[0842] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[0843] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[0844] The generated travel plan is sent to the user's device.

[0845] Terminal

[0846] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[0847] User feedback and plan revisions

[0848] User

[0849] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[0850] server

[0851] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[0852] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[0853] Specific examples

[0854] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[0855] 1. Information gathering

[0856] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0857] Get weather information from the weather API and check that the weather is good for the day.

[0858] 2. Emotion recognition

[0859] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[0860] 3. Initial plan generation

[0861] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0862] 4. Creating a detailed plan

[0863] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0864] The terminal notifies the user of the schedule and displays it on the screen.

[0865] 5. User Feedback

[0866] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0867] 6. Final planning and booking

[0868] The server incorporates user feedback and creates the final plan.

[0869] The server automatically issues park admission tickets and reserves cafe seats.

[0870] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] A user logs in to the system.

[0874] Step 2:

[0875] The server retrieves the user's past travel history and preference data from a database.

[0876] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[0877] Step 3:

[0878] The server sends a request to the weather API to obtain current and near-future weather information.

[0879] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[0880] Step 4:

[0881] The server uses an emotion engine to analyze voice input and facial recognition data to recognize the user's emotions.

[0882] How it works: Audio and video data captured through a microphone and camera is sent to the emotion engine, where it performs text analysis, audio analysis, image analysis, etc.

[0883] Example: When a user says, "I'm a little tired, but I want to go somewhere," the emotion engine analyzes the voice data and recognizes it as, "I'm tired, but I'm looking for a new experience."

[0884] Step 5:

[0885] The server integrates the above acquired data (user information, weather information, emotion data) and selects appropriate candidates from a tourist destination database and a restaurant database.

[0886] How it works: Extracts and filters a list of tourist attractions and restaurants from a database that match the user's preferences and current sentiment.

[0887] Step 6:

[0888] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[0889] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[0890] Step 7:

[0891] The server generates the initial itinerary and creates a detailed schedule.

[0892] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[0893] Example: Create a schedule that involves visiting a nature park in the morning and relaxing at a cafe in the afternoon.

[0894] Step 8:

[0895] The server sends the generated schedule to the user's terminal.

[0896] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[0897] Step 9:

[0898] The terminal notifies the user of the detailed schedule received from the server.

[0899] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[0900] Step 10:

[0901] The user reviews the proposed itinerary and makes any necessary modifications.

[0902] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[0903] Example: When a user says, "I want to add another tourist spot after the cafe," that information is sent to the server.

[0904] Step 11:

[0905] The server receives the user's modification requests and creates the final itinerary.

[0906] How it works: The algorithm re-applies the plan and optimizes it based on the corrections received from the user.

[0907] Step 12:

[0908] The server automatically makes related reservations based on the finalized plan.

[0909] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[0910] Example: Buying tickets online to selected tourist attractions and confirming cafe reservations.

[0911] In this way, an optimal travel plan that takes the user's emotions into account can be automatically generated and flexibly revised based on feedback.

[0912] Example 2

[0913] 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."

[0914] Conventional travel planning systems have difficulty generating plans that take into account the user's emotions and moods. Furthermore, the travel plans proposed to users are not always appropriate for the user's mood or real-time weather information, resulting in a decrease in user satisfaction. Therefore, there is a need for a system that can automatically generate more personalized travel plans based on the user's emotions and weather information, as well as flexible feedback and revisions based on those plans.

[0915] 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.

[0916] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for recognizing and analyzing user emotion data, means for generating a travel plan based on the user's preferences, weather information, and emotion data, means for notifying the user of the generated travel plan, means for modifying the travel plan based on user feedback, and means for finalizing the modified travel plan and making related reservations. This enables the generation of an optimal travel plan that takes into account the user's emotions, preferences, and real-time weather information, and the flexible modification of the plan based on user feedback.

[0917] "User Information" means data including a user's past travel history, preferences, budget, etc.

[0918] "Weather Information" means data about current and future weather conditions obtained through the Weather API.

[0919] "Emotional Data" refers to information about a user's emotional state based on tone, speed, facial expression, etc., obtained from their voice and facial expressions.

[0920] A "travel plan" is a plan that includes the selection of tourist spots and restaurants, as well as route planning, and is generated based on the user's emotions, preferences, and weather information.

[0921] "Feedback" refers to opinions and requests received by users when they input corrections or requests regarding the proposed travel plan.

[0922] "Notification" refers to the process of sending the travel plan generated by the server to the user's terminal and informing the user.

[0923] "Reservation" is the process of securing necessary accommodation, transportation, tickets to tourist attractions, etc. based on the final travel plan generated.

[0924] "Tourist destinations" refer to places and facilities that users would like to visit while traveling.

[0925] "Food and Beverage" refers to the restaurants and cafes that you choose to eat at during your trip.

[0926] "Transportation" refers to suggestions for transportation and routes that users can use to travel from their current location to their destination.

[0927] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[0928] System configuration

[0929] The system consists of the following main components:

[0930] 1. How we collect user information

[0931] 2. How to obtain weather information

[0932] 3. Emotion Engine

[0933] 4. Travel plan generation method

[0934] 5. Means of notification

[0935] 6. Feedback channels

[0936] 7. Final confirmation method

[0937] 8. Reservation Methods

[0938] 9. How to select tourist spots and restaurants

[0939] 10. Means of transportation suggestion

[0940] Obtaining user information and weather information

[0941] server

[0942] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[0943] The server obtains current and future weather information in real time via a weather API.

[0944] Emotion recognition by emotion engine

[0945] server

[0946] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[0947] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[0948] Travel plan generation and notification

[0949] server

[0950] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[0951] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[0952] The generated travel plan is sent to the user's device.

[0953] Terminal

[0954] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[0955] User feedback and plan revisions

[0956] User

[0957] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[0958] server

[0959] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[0960] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[0961] Specific examples

[0962] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[0963] 1. Information gathering

[0964] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[0965] Get weather information from the weather API and check that the weather is good for the day.

[0966] 2. Emotion recognition

[0967] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[0968] 3. Initial plan generation

[0969] The server suggests nearby nature parks and selects highly rated cafes in the area.

[0970] 4. Creating a detailed plan

[0971] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[0972] The terminal notifies the user of the schedule and displays it on the screen.

[0973] 5. User Feedback

[0974] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[0975] 6. Final planning and booking

[0976] The server incorporates user feedback and creates the final plan.

[0977] The server automatically issues park admission tickets and reserves cafe seats.

[0978] Example prompt: "I want to go somewhere for a change today. I'm tired, but I want to find a new place."

[0979] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[0980] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0981] Step 1: Get user information

[0982] When a user logs in to the system, the server reads the user's past travel history and preference data from the database. Specifically, it executes an SQL query such as SELECT FROM user_preferences WHERE user_id = :user_id;. The input data includes the user's ID, and the output is information about the user's past travel history and preferences. This obtains the user's individual information and serves as the basis for generating a customized travel plan.

[0983] Step 2: Get weather information

[0984] The server uses a weather API (for example, a general weather API service) to obtain current and future weather information. Specifically, it sends an API request such as curl -X GET "http: / / api.openweathermap.org / data / 2.5 / weather?q=City&appid=YOUR_API_KEY". This input data includes geographic location data, and the output is weather information for that location. This allows it to generate travel plans that take current and forecast weather into account.

[0985] Step 3: Emotion Recognition

[0986] The server uses an emotion engine to analyze the emotional data entered by the user through voice input or facial recognition. Emotions are recognized based on tone and speed in the voice data, and facial expressions in the facial recognition data. Specifically, the server sends audio and images as a POST request to an emotion engine API (such as a general emotion analysis API). This input data includes audio and image data, and the user's emotional state is obtained as output. This makes it possible to propose travel plans that take into account the user's current emotions.

[0987] Step 4: Generate your travel plan

[0988] The server generates a travel plan by integrating the user's preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it selects tourist spots where they can enjoy nature. Specifically, to extract travel destinations based on preferences, weather, and emotional information, it executes an SQL query such as SELECT FROM locations WHERE category = 'nature' AND suitability_score > 7;. The input data includes the user's emotional state and weather information, and the output is a list of candidate tourist spots and restaurants.

[0989] Step 5: Plan Notification

[0990] The server sends the generated itinerary to the user's device. Specifically, it sends the itinerary data via an HTTP request. The input includes the information about the generated itinerary, and the output is the data received by the user's device. The device receives the itinerary sent from the server and notifies the user using push notifications or in-app notifications.

[0991] Step 6: Gather user feedback

[0992] The user reviews the proposed travel plan and makes any necessary modifications. Specifically, the user enters and submits the modified data on the device. The device then sends a POST request using JSON-formatted data to send the user's feedback to the server. The input data includes the user's modification request, and the feedback data is sent to the server as output.

[0993] Step 7: Generate the final plan

[0994] The server generates a final itinerary based on the user's feedback. Specifically, it generates a new itinerary that reflects the user's modifications and queries the database again to update the optimal route and tourist destination information. The input data includes the user's feedback, and the revised itinerary is obtained as the output.

[0995] Step 8: Making a reservation

[0996] The server automatically makes the necessary reservations based on the final travel plan. Specifically, it uses a reservation API (for example, a general reservation service API) to reserve accommodations, tickets to tourist attractions, and restaurants. The input data includes details of the final travel plan, and the output is reservation confirmation data.

[0997] (Application example 2)

[0998] 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."

[0999] Conventional factory work schedule management is based primarily on work procedures and the efficiency of each process, but it is difficult to consider individual worker conditions such as the emotional state and fatigue level of workers. This has led to problems such as reduced production efficiency, increased work errors, and concerns about worker safety and health. The present invention aims to solve these problems by recognizing workers' emotional states in real time and managing work schedules flexibly based on this information.

[1000] The specific processing by the specific 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 acquiring user (worker) information, means for acquiring weather information, means for recognizing the emotional state of the user (worker), means for generating a work schedule based on the user's (worker's) preferences, weather information, and emotional information, means for notifying the user (worker) of the generated work schedule, means for modifying the work schedule based on user (worker) feedback, and means for finalizing the modified work schedule and allocating related tasks. This enables the generation of flexible and efficient work schedules that take into account the emotional state of workers.

[1001] "Means for obtaining user information" refers to the function by which the system collects personal information about users (workers), past work history, preferred tasks, etc.

[1002] "Means for obtaining weather information" refers to the function by which the system obtains data on weather and climate from external information services and reflects this in work schedules.

[1003] "Means for recognizing the user's emotional state" refers to the system's ability to detect the emotions and psychological state of workers in real time and analyze this as data.

[1004] The "means for generating a work schedule" is a function that automatically creates an optimal work schedule based on the user's preferences, weather information, and emotional information.

[1005] The "means for notifying the user of the generated work schedule" is a function that notifies the created work schedule to the worker in real time and provides the information.

[1006] "Means for modifying work schedules based on user feedback" is a function that receives the opinions and requests of workers and flexibly modifies the work schedule accordingly.

[1007] The "means for finalizing the revised work schedule and allocating related tasks" is a function for appropriately allocating various related work tasks based on the finalized work schedule.

[1008] "Means for selecting the optimal task according to the conditions of the work site and equipment and calculating the efficient work route" is a function that selects the optimal work task and calculates the efficient work sequence, taking into account the conditions of the work site and the operating status of the machines.

[1009] "A means for proposing the optimal means of transportation from the worker's current location to the target work location" is a function that suggests the optimal route and means of transportation from the worker's current location to the designated work location.

[1010] This system is a factory robot management system that optimizes work schedules based on the emotional state of the user (worker). The system consists of the following main components:

[1011] System configuration

[1012] 1. How we collect user information

[1013] The server retrieves the user's activity history, preferences, and past feedback from a database, including the tasks they have performed in the past, their preferred tasks, and their work pace.

[1014] 2. How to obtain weather information

[1015] The server uses external weather APIs to obtain real-time current and future weather information, which helps to adjust the environment within the factory and maximize work efficiency.

[1016] 3. Emotional state recognition method

[1017] The server uses an emotion engine to analyze the user's voice input, facial recognition, and vital sign data. The emotion engine determines the user's emotional state by analyzing tone and speed from the voice data and facial expressions from the facial data. This emotion engine uses voice recognition software and facial recognition libraries (e.g., OpenCV, Dlib).

[1018] 4. Work Schedule Generation Method

[1019] The server generates a work schedule by integrating user preferences, weather information, and emotional information, assigning lighter tasks when the user is tired and more complex tasks when the user is less stressed.

[1020] 5. Means of notification

[1021] The generated work schedule is sent from the server to the user's device (such as a smartphone or tablet) and notified in real time.

[1022] 6. Feedback channels

[1023] Users provide feedback on the proposed work schedule, which is sent from the device to the server and reflected in schedule revisions.

[1024] 7. Final confirmation method

[1025] The server receives user feedback and determines the final work schedule, and then allocates related tasks based on this schedule.

[1026] Specific examples

[1027] For example, if Worker A says "I'm tired today," and the emotion engine determines from the voice and facial recognition data that the emotion is "I'm stressed," the system will process as follows:

[1028] 1. Information gathering

[1029] The server retrieves the user's past activity history and preference data, and retrieves weather information from the weather API.

[1030] 2. Emotion recognition

[1031] The emotion engine recognizes emotions such as "tired and stressed" from the user's voice and facial expression data.

[1032] 3. Initial schedule generation

[1033] The server generates a work schedule that suggests simple work tasks (e.g., quality checks) and short breaks based on the user's condition.

[1034] 4. Create a detailed schedule

[1035] The server creates a detailed schedule including suggested tasks and break times and sends it to the device, which then notifies the user and displays the schedule on the screen.

[1036] 5. User Feedback

[1037] The user provides feedback on the proposed schedule, requesting changes to some tasks.

[1038] 6. Final schedule and task allocation

[1039] The server reflects the user's feedback, determines the final schedule, and then assigns related tasks based on the determined schedule.

[1040] Prompt Sentence Examples

[1041] Prompt for the generative AI model:

[1042] The system analyzes the facial image data and voice data of workers to recognize their emotional state and assign them the next work task. For example, if a worker is recognized as "tired," it will schedule them for light work or a break.

[1043] In this way, the emotion engine can create a flexible work schedule that takes into account the emotional state of workers, and optimally allocate tasks. This system can simultaneously improve worker safety and efficiency.

[1044] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1045] Step 1:

[1046] The server obtains user (worker) information. As input, it receives the user ID and authentication information and extracts data from the user database, such as past work history, preferences, and feedback. It processes the data by filtering and integrating the necessary data. The output is the user's work history and preference data.

[1047] Step 2:

[1048] The server retrieves weather information. As input, a weather API request is sent, and the retrieved weather data is returned to the server. The data is processed by analyzing the current and future weather data and extracting the necessary parts. The output is real-time weather information.

[1049] Step 3:

[1050] The server recognizes the user's emotional state. The user's voice data and facial image data are used as input. An emotion engine is used to analyze tone and speed from the voice data and facial expressions from the facial image data. This determines the user's emotional state. The output is the user's current emotional state.

[1051] Step 4:

[1052] The server generates the work schedule. User preferences, weather information, and emotional information are used as input. This data is integrated and an AI model is used to calculate the optimal work schedule. Specifically, each data point is evaluated to select the most efficient and suitable task for the user. The output is the generated work schedule.

[1053] Step 5:

[1054] The server notifies the user of the generated work schedule. Work schedule data is given as input and sent to the terminal. The data is then converted into a notification format and sent to the user's smartphone or tablet. The output is a schedule notification on the user's terminal.

[1055] Step 6:

[1056] The user provides feedback on the work schedule. The input is the proposed schedule and the user's feedback. The terminal sends the user's opinions and change requests to the server. The data is processed by organizing and analyzing the feedback content. The output is user feedback data.

[1057] Step 7:

[1058] The server modifies the work schedule based on user feedback. The feedback data is used as input. The AI ​​model is then used again to update the schedule to reflect the feedback. The data is then processed to regenerate the schedule. The output is the modified work schedule.

[1059] Step 8:

[1060] The server finalizes the revised work schedule and allocates the associated tasks. The revised schedule data is used as input. The final schedule is finalized and each task is allocated to the appropriate worker. Data processing involves confirming and finalizing the task allocation. The output is an execution list of the allocated tasks.

[1061] 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.

[1062] 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.

[1063] 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.

[1064] [Third embodiment]

[1065] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1066] 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.

[1067] 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).

[1068] 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.

[1069] 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.

[1070] 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).

[1071] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] 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.

[1076] 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."

[1077] This invention is a system that saves users the trouble of making travel plans and quickly provides optimal travel plans. The system of the present invention operates by combining multiple means and generates travel plans based on data such as user information, weather information, and databases of tourist spots and restaurants.

[1078] This system is configured as follows:

[1079] 1. Collection of User Information

[1080] server

[1081] When a user logs in to the system, the server automatically retrieves the user's past travel history and preference data from the database, such as tourist spots the user has visited in the past, food preferences, and travel budget.

[1082] The server uses a specific API (e.g., an application or wearable device that manages health data) to obtain the user's current mood and physical condition.

[1083] 2. Integration of user information and weather information

[1084] server

[1085] The server uses a weather API to retrieve current and near-future weather information, including temperature, precipitation, wind speed, etc.

[1086] The server compares the acquired user information with weather information and selects a travel destination that suits the user's preferences and physical condition.

[1087] 3. Generate the initial plan

[1088] server

[1089] The server searches a tourist spot database and a restaurant database to select the tourist spot and restaurant that best suit the user's preferences and weather conditions.

[1090] The server calculates an efficient route based on the selected tourist spots and restaurants.

[1091] 4. Creating and notifying detailed plans

[1092] server

[1093] Based on the initial plan, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[1094] The generated schedule is sent to the user's device.

[1095] Terminal

[1096] The terminal notifies the user of the detailed schedule sent from the server and displays it on the screen.

[1097] User

[1098] Users can review the proposed itinerary and make any necessary modifications, for example, adding or removing specific tourist attractions.

[1099] 5. Finalize the plan and make a reservation

[1100] server

[1101] The server creates a final itinerary based on the modifications made by the user.

[1102] Based on the final plan created, accommodation reservations, transportation arrangements, and ticket purchases for sightseeing spots are automatically made. For example, hotel reservation APIs and plane ticket reservation APIs are used to quickly make the necessary reservations.

[1103] Specific examples

[1104] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[1105] 1. Information gathering

[1106] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1107] Get weather information from the weather API and check that the weather is good for the day.

[1108] 2. Initial plan generation

[1109] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1110] 3. Creating a detailed plan

[1111] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1112] The terminal notifies the user of the schedule and displays it on the screen.

[1113] 4. User Feedback

[1114] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1115] 5. Final planning and booking

[1116] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[1117] In this way, users can eliminate the need for tedious planning and quickly obtain optimal travel plans. This system allows users to enjoy their trips with ease and improves their satisfaction.

[1118] The processing flow will be explained below.

[1119] Step 1:

[1120] A user logs in to the system.

[1121] Step 2:

[1122] The server retrieves the user's past travel history and preference data from a database.

[1123] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[1124] Step 3:

[1125] The server sends a request to the weather API to obtain current and near-future weather information.

[1126] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[1127] Step 4:

[1128] The server obtains the user's current mood and physical condition from various sensors and input forms.

[1129] How it works: Collects health data from smartphone APIs and medical interview data from users.

[1130] Step 5:

[1131] The server integrates the user information and weather information and searches a database of tourist attractions and restaurants.

[1132] How it works: It runs a search query against each database based on the user's preferences and weather conditions to generate a list of candidates.

[1133] Step 6:

[1134] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[1135] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[1136] Step 7:

[1137] The server generates the initial itinerary and creates a detailed schedule.

[1138] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[1139] Step 8:

[1140] The server sends the generated schedule to the user's terminal.

[1141] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[1142] Step 9:

[1143] The terminal notifies the user of the detailed schedule received from the server.

[1144] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[1145] Step 10:

[1146] The user reviews the proposed itinerary and makes any necessary modifications.

[1147] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[1148] Step 11:

[1149] The server receives the user's modification requests and creates the final itinerary.

[1150] How it works: The algorithm re-optimizes the plan based on user feedback.

[1151] Step 12:

[1152] The server automatically makes related reservations based on the finalized plan.

[1153] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[1154] In this way, it is possible to provide the user with an optimal travel plan that meets their needs.

[1155] Example 1

[1156] 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."

[1157] Conventional travel planning systems require users to individually search for travel plans and manually plan them, which is time-consuming and laborious. It is also difficult to provide optimal travel plans that take into account weather and the user's health condition. It is also difficult to immediately reflect user feedback and revise travel plans in real time. To solve these issues, there is a need for a fast and flexible travel plan generation and booking automation system that takes into account user preferences, health condition, and weather information.

[1158] 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.

[1159] In this invention, the server includes means for acquiring user information, means for acquiring health status data, means for acquiring weather information, means for generating a travel plan based on the user's preferences, health status, and weather information, means for notifying the user of the generated travel plan, means for modifying the travel plan based on the user's feedback, and means for finalizing the modified travel plan and making related reservations. This allows users to quickly obtain an optimal travel plan based on their health status and weather conditions, eliminating the need for individual searches and manual planning. Furthermore, real-time plan modifications based on user feedback improve travel satisfaction.

[1160] "User information" is a general term for data such as a user's past travel history, preferences, budget, etc.

[1161] "Health data" refers to information about a user's current physical condition or mood, obtained from wearable devices or health management applications.

[1162] "Weather information" refers to data about current and near-future weather conditions obtained through weather APIs, including temperature, precipitation, wind speed, etc.

[1163] A "travel plan" is a detailed schedule that includes planned visits to tourist attractions and restaurants, generated based on the user's preferences, health status, and weather information.

[1164] "Device" is a general term for electronic devices used by users, including smartphones and tablets.

[1165] "Feedback" refers to any corrections or additional instructions given by the user to the proposed travel plan, which are sent to the server via the terminal.

[1166] "Reservation" refers to procedures such as purchasing accommodation, transportation, and tickets to tourist attractions based on a confirmed travel plan.

[1167] "Database" refers to an information accumulation system that stores user information, tourist destination data, restaurant data, etc., and can be searched and retrieved as needed.

[1168] An "API" is an interface that allows different software applications to communicate with each other, and is used to obtain weather information, health status data, etc.

[1169] "Route" refers to a calculated route for efficiently visiting tourist attractions and restaurants, and is used to optimize the user's travel.

[1170] A "schedule" is a plan detailing the order of visits, means of transportation, and duration of stay at each location.

[1171] This invention is a system for efficiently planning travel plans for users, in which the server, terminal, and user each play specific roles. Specifically, the system uses user information, health status data, and weather information to generate travel plans tailored to the user's needs and even automatically makes the necessary reservations.

[1172] Hardware and software used

[1173] server:

[1174] The server uses a database management system (DBMS) to manage user information, tourist destination data, and restaurant data.

[1175] Use APIs to retrieve external weather and health data, for example, use the OpenWeatherMap API to retrieve weather information and health data from the Google Fit API or other health management applications.

[1176] It uses generative AI models to generate optimal travel plans based on user preferences and current conditions.

[1177] Device:

[1178] The user's mobile device, such as a smartphone or tablet, is used. These devices receive the information sent from the server and notify and display it to the user.

[1179] user:

[1180] Users log in to the system and provide information about their preferences and physical condition, and feedback is also sent to the server via their device.

[1181] Data processing and calculation

[1182] server

[1183] The server automatically retrieves past travel history and preference data from the database when a user logs in, for example using SQL queries to find the required data.

[1184] The server utilizes specific APIs to collect data about the user's current mood and physical condition. Data obtained from the health status API includes, for example, sleep duration and activity level.

[1185] The server retrieves weather information through a weather API, including current and near-future weather, temperature, precipitation, and wind speed.

[1186] The server comprehensively analyzes the acquired data and generates a travel plan that best suits the user's preferences and health status. This analysis and plan generation is performed using a generative AI model.

[1187] After generating the plan, the server sends a detailed schedule to the user's smartphone or tablet.

[1188] The server receives feedback from the user, adjusts the final plan, and automatically makes all necessary reservations, for example using accommodation booking APIs and transportation booking APIs.

[1189] Terminal

[1190] The device notifies the user of the travel plan received from the server and displays it on the screen, allowing the user to review the proposed plan and enter any changes or additions.

[1191] Users can send feedback to the server via their devices, including changes to selected tourist spots and restaurants, or changes to the order of visits.

[1192] Specific examples

[1193] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[1194] 1. Information gathering

[1195] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1196] Get weather information from the weather API and check that the weather is good for the day.

[1197] 2. Initial plan generation

[1198] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1199] 3. Creating a detailed plan

[1200] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1201] The terminal notifies the user of the schedule and displays it on the screen.

[1202] 4. User Feedback

[1203] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1204] 5. Final planning and booking

[1205] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[1206] In this way, users are freed from the tedious task of planning trips and can quickly obtain the best travel plans, thereby enriching users' travel experience and increasing their satisfaction.

[1207] Prompt Sentence Examples

[1208] "Today I want to enjoy nature."

[1209] "Looking for tourist spots that can be enjoyed even in the rain"

[1210] "I want you to plan a gourmet tour."

[1211] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1212] Step 1: User login and information gathering

[1213] server

[1214] When a user logs into the system, the server authenticates the entered username and password and starts a session.

[1215] Input: Username, Password

[1216] Data processing: Performs the authentication process and generates session information if successful.

[1217] Output: Session information, user ID

[1218] server

[1219] The server retrieves the user's past travel history and preferences from a database using SQL queries to find the required data based on the user ID.

[1220] Input: User ID

[1221] Data processing: Search and extract data on past travel history and preferences.

[1222] Output: Travel history data, preference data

[1223] server

[1224] The server uses the health management API to obtain the user's current health status data, for example, to collect activity data and physical condition data for a specific date.

[1225] Input: Health management API token, user ID

[1226] Data processing: Send a request to the health management API and analyze the response data.

[1227] Output: Health status data

[1228] Step 2: Get weather information

[1229] server

[1230] The server uses the weather API to obtain current and near-future weather information (e.g., temperature, precipitation, wind speed, etc.).

[1231] Input: Location, Weather API token

[1232] Data processing: Send a request to the weather API and analyze the response data.

[1233] Output: Weather information data

[1234] Step 3: Generate an initial plan

[1235] server

[1236] The server refers to the tourist destination database and restaurant database to select the tourist destination and restaurant that best suits the user's preferences, health condition, and weather conditions, thereby providing the user with the best options for their current situation.

[1237] Input: Travel history data, preference data, health data, weather information data

[1238] Data processing: Use generative AI models to perform integrated analysis of user information and external data.

[1239] Output: Initial plan data

[1240] server

[1241] The server calculates an efficient route based on the selected tourist spots and restaurants, using Google Maps API and other tools to calculate the optimal travel route.

[1242] Input: Initial plan data, location data

[1243] Data processing: Calculate the optimal route using Google Maps API.

[1244] Output: Route information data

[1245] Step 4: Create and communicate a detailed plan

[1246] server

[1247] Based on the initial plan and route information, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[1248] Input: Initial plan data, route information data

[1249] Data processing: Apply a schedule generation algorithm to create a detailed schedule.

[1250] Output: Detailed schedule data

[1251] server

[1252] The server transmits the generated detailed schedule to the user's terminal.

[1253] Input: Detailed schedule data, user terminal information

[1254] Data processing: Convert detailed schedule data into a format suitable for the device.

[1255] Output: Schedule notification data

[1256] Terminal

[1257] The terminal receives the detailed schedule sent from the server, notifies the user, and displays it on the screen.

[1258] Input: Schedule notification data

[1259] Data processing: Converting schedule notification data into a format for display in the user interface.

[1260] Output: Screen display data

[1261] Step 5: Incorporating user feedback

[1262] user

[1263] Users can review the proposed itinerary and make any necessary modifications, including adding or removing attractions or restaurants, or changing the order in which they are visited.

[1264] Input: Proposed itinerary

[1265] Data processing: Accepts user corrections as input.

[1266] Output: Corrective feedback data

[1267] server

[1268] The server receives feedback from the user and creates the final itinerary, which includes recalculation to reflect the user's changes.

[1269] Input: Corrective feedback data, initial plan data

[1270] Data processing: Recalculate the plan based on the modifications and generate the final plan.

[1271] Output: Final plan data

[1272] Step 6: Finalize your plan and book

[1273] server

[1274] Based on the final plan, the server automatically reserves accommodation, secures transportation, purchases tickets to tourist attractions, etc. This is done using a reservation API.

[1275] Input: Final plan data, Reservation API token

[1276] Data processing: Send a request to the booking API to retrieve booking information.

[1277] Output: Confirmed reservation data

[1278] server

[1279] The server sends the confirmed reservation details to the user's terminal and notifies them for confirmation.

[1280] Input: Reservation confirmation data, user terminal information

[1281] Data processing: Converts reservation confirmation data into a format suitable for the device.

[1282] Output: Booking notification data

[1283] Terminal

[1284] The terminal receives the reservation details sent from the server, notifies the user, and displays them on the screen.

[1285] Input: Booking notification data

[1286] Data processing: Converting booking notification data into a format for display in the user interface.

[1287] Output: Screen display data

[1288] (Application example 1)

[1289] 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."

[1290] Conventional food delivery services require users to search and select menus themselves, making it difficult to provide appropriate suggestions based on their physical condition or weather conditions. This makes it difficult for some users to choose meals that take their physical condition and weather into consideration, which can lead to lower satisfaction. Furthermore, if an appropriate dish is not selected, there is a risk of harming their health. Furthermore, personalized suggestions are lacking because the service does not fully utilize users' preferences and past ordering history.

[1291] 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.

[1292] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for generating a food delivery plan based on the user's preferences and weather information, means for notifying the user of the generated food delivery plan, means for modifying the food delivery plan based on the user's feedback, and means for finalizing the modified food delivery plan and placing an associated order. This makes it possible to suggest optimal dishes based on the user's individual preferences, physical condition, and weather conditions, and to automatically confirm the order.

[1293] "Means for obtaining user information" refers to means for collecting a user's past order history, preference data, health status, etc.

[1294] "Means for obtaining weather information" refers to means for obtaining current and near-future weather information such as temperature, precipitation, and wind speed.

[1295] The "means for generating a food delivery plan" is a means for selecting dishes that suit the user's preferences and physical condition based on user information and weather information.

[1296] The "means for notifying the user of the food delivery plan" is a means for sending the generated food delivery plan to the user's terminal and notifying the user.

[1297] The "means for modifying the food delivery plan based on user feedback" refers to a means for modifying the selected food delivery plan based on feedback information from users.

[1298] "Means for finalizing the food delivery plan and placing the related orders" means the means for finalizing the optimal food order based on the revised food delivery plan and placing the order with the restaurant.

[1299] "Means for searching menu information of affiliated restaurants and delivery services" refers to means for searching a database for menu information of affiliated restaurants and delivery services.

[1300] "Means for selecting dishes that best suit the user's preferences and weather conditions" refers to means for selecting the most suitable dishes based on user information and weather information.

[1301] "A means for suggesting the optimal delivery method from the user's current location to the restaurant" is a means for suggesting the optimal delivery method based on the user's current location and the restaurant's location information.

[1302] The present invention is a system that collects user information, weather information, and restaurant menu information, and provides an optimal food delivery plan based on the user's preferences and physical condition. Specific examples are presented below to explain the detailed configuration and operation of the present invention.

[1303] 1. Collection of User Information

[1304] When a user logs in to the system, the server automatically retrieves the user's past order history and preference data from the database. Specifically, it collects data on the user's favorite dishes, favorite restaurants, past order history, and health status. It also retrieves the user's current physical condition data from healthcare applications and wearable devices. This provides the basic data needed to generate a personalized food delivery plan.

[1305] 2. Obtaining weather information

[1306] The server uses a weather API to obtain current and near-future weather information, including temperature, precipitation, wind speed, etc. For example, the server uses the Weather API to obtain real-time weather information for the user's location.

[1307] 3. Generate a food delivery plan

[1308] The server integrates user information and weather information to suggest the best dishes to suit the user's preferences and physical condition. It searches menu information from affiliated restaurants and delivery services to select dishes that meet the user's requirements. Since it also takes weather conditions into account, it can, for example, suggest cold dishes on hot days and hot dishes on cold days.

[1309] 4. Plan Notification and Feedback

[1310] The generated food delivery plan is sent from the server to the user's device and notified. The user can then review the proposed plan via their smartphone or smart glasses. If the user provides feedback, the server will modify the plan based on that feedback and finalize the plan. For example, modifications can be made to accommodate the user's requests, such as allergies to certain ingredients or requests for other dishes.

[1311] 5. Order confirmation and execution

[1312] The server automatically places an order with partner restaurants based on the finalized food delivery plan, allowing users to enjoy the best food without any hassle. Order information is sent via the restaurant or delivery service's API.

[1313] Hardware and software used

[1314] The hardware used includes a server, smartphone, and smart glasses, while the software uses Weather API, restaurant APIs, and a user information management system to obtain data via APIs.

[1315] Examples of specific examples and prompts

[1316] For example, if a user types, "It's hot today, I want to eat something light," the server will suggest cold Chinese noodles based on the weather information indicating the high temperature and the user's request.

[1317] Example prompt sentence:

[1318] "It's hot today, I want to eat something refreshing."

[1319] By entering this prompt, the system will suggest the most suitable dish and automatically confirm the order.

[1320] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1321] Step 1:

[1322] When a user logs in to the system, the server obtains user information, including the user's past order history, preference data, and health status data. The input is the user's login information, and the output is the user's detailed information. Specifically, based on the user ID, the server collects past order history, preference food, and health status data from the database. This data is used in the next step.

[1323] Step 2:

[1324] The server uses a weather API to obtain weather information for the user's location. The input is the user's location information, and the output is current and near-future weather data. Specifically, the server calls the Weather API to obtain information such as temperature, precipitation, and wind speed. This data is then used to generate the plan.

[1325] Step 3:

[1326] The server integrates user information and weather information to generate a food delivery plan based on the user's preferences, physical condition, and weather conditions. The input is the user information and weather information obtained in the previous step, and the output is a list of suggested dishes. Specifically, it searches a database of affiliated restaurants and selects the dish that best suits the user's requirements. For example, it suggests cold dishes on hot days and hot dishes on cold days.

[1327] Step 4:

[1328] The server sends the generated food delivery plan to the user's device and notifies them. The input is the generated list of dishes, and the output is a notification displayed on the user's device. Specifically, a notification is sent to the user's smartphone or smart glasses, displaying detailed information about the proposed dishes.

[1329] Step 5:

[1330] The user submits feedback on the proposed food delivery plan. The input is the user's feedback information, and the output is the requested corrections. Specifically, the user enters information about allergies to specific ingredients and other desired dishes on the app and sends it to the server.

[1331] Step 6:

[1332] The server modifies the food delivery plan based on the user's feedback. The input is the user's feedback information, and the output is the final modified plan. Specifically, it searches the database again and reselects dishes that match the user's preferences.

[1333] Step 7:

[1334] The server places an order with the partner restaurant based on the finalized food delivery plan. The input is the finalized dish information, and the output is a notification of order confirmation to the restaurant. Specifically, the server calls the restaurant's API to automatically send the order information and receive confirmation.

[1335] Step 8:

[1336] The restaurant prepares the food based on the received order and delivers it to the user through a delivery service. The input is the order information from the server, and the output is a notification that the food has been delivered. Specifically, after cooking is complete, the food is handed over to a delivery person who then delivers it to the user.

[1337] 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.

[1338] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[1339] System configuration

[1340] The system consists of the following main components:

[1341] 1. How we collect user information

[1342] 2. How to obtain weather information

[1343] 3. Emotion Engine

[1344] 4. Travel plan generation method

[1345] 5. Means of notification

[1346] 6. Feedback channels

[1347] 7. Final confirmation method

[1348] 8. Reservation Methods

[1349] 9. How to select tourist spots and restaurants

[1350] 10. Means of transportation suggestion

[1351] Obtaining user information and weather information

[1352] server

[1353] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[1354] The server obtains current and future weather information in real time via a weather API.

[1355] Emotion recognition by emotion engine

[1356] server

[1357] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[1358] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[1359] Travel plan generation and notification

[1360] server

[1361] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[1362] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[1363] The generated travel plan is sent to the user's device.

[1364] Terminal

[1365] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[1366] User feedback and plan revisions

[1367] User

[1368] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[1369] server

[1370] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[1371] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[1372] Specific examples

[1373] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[1374] 1. Information gathering

[1375] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1376] Get weather information from the weather API and check that the weather is good for the day.

[1377] 2. Emotion recognition

[1378] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[1379] 3. Initial plan generation

[1380] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1381] 4. Creating a detailed plan

[1382] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1383] The terminal notifies the user of the schedule and displays it on the screen.

[1384] 5. User Feedback

[1385] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1386] 6. Final planning and booking

[1387] The server incorporates user feedback and creates the final plan.

[1388] The server automatically issues park admission tickets and reserves cafe seats.

[1389] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[1390] The processing flow will be explained below.

[1391] Step 1:

[1392] A user logs in to the system.

[1393] Step 2:

[1394] The server retrieves the user's past travel history and preference data from a database.

[1395] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[1396] Step 3:

[1397] The server sends a request to the weather API to obtain current and near-future weather information.

[1398] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[1399] Step 4:

[1400] The server uses an emotion engine to analyze voice input and facial recognition data to recognize the user's emotions.

[1401] How it works: Audio and video data captured through a microphone and camera is sent to the emotion engine, where it performs text analysis, audio analysis, image analysis, etc.

[1402] Example: When a user says, "I'm a little tired, but I want to go somewhere," the emotion engine analyzes the voice data and recognizes it as, "I'm tired, but I'm looking for a new experience."

[1403] Step 5:

[1404] The server integrates the above acquired data (user information, weather information, emotion data) and selects appropriate candidates from a tourist destination database and a restaurant database.

[1405] How it works: Extracts and filters a list of tourist attractions and restaurants from a database that match the user's preferences and current sentiment.

[1406] Step 6:

[1407] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[1408] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[1409] Step 7:

[1410] The server generates the initial itinerary and creates a detailed schedule.

[1411] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[1412] Example: Create a schedule that involves visiting a nature park in the morning and relaxing at a cafe in the afternoon.

[1413] Step 8:

[1414] The server sends the generated schedule to the user's terminal.

[1415] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[1416] Step 9:

[1417] The terminal notifies the user of the detailed schedule received from the server.

[1418] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[1419] Step 10:

[1420] The user reviews the proposed itinerary and makes any necessary modifications.

[1421] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[1422] Example: When a user says, "I want to add another tourist spot after the cafe," that information is sent to the server.

[1423] Step 11:

[1424] The server receives the user's modification requests and creates the final itinerary.

[1425] How it works: The algorithm re-applies the plan and optimizes it based on the corrections received from the user.

[1426] Step 12:

[1427] The server automatically makes related reservations based on the finalized plan.

[1428] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[1429] Example: Buying tickets online to selected tourist attractions and confirming cafe reservations.

[1430] In this way, an optimal travel plan that takes the user's emotions into account can be automatically generated and flexibly revised based on feedback.

[1431] Example 2

[1432] 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."

[1433] Conventional travel planning systems have difficulty generating plans that take into account the user's emotions and moods. Furthermore, the travel plans proposed to users are not always appropriate for the user's mood or real-time weather information, resulting in a decrease in user satisfaction. Therefore, there is a need for a system that can automatically generate more personalized travel plans based on the user's emotions and weather information, as well as flexible feedback and revisions based on those plans.

[1434] 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.

[1435] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for recognizing and analyzing user emotion data, means for generating a travel plan based on the user's preferences, weather information, and emotion data, means for notifying the user of the generated travel plan, means for modifying the travel plan based on user feedback, and means for finalizing the modified travel plan and making related reservations. This enables the generation of an optimal travel plan that takes into account the user's emotions, preferences, and real-time weather information, and the flexible modification of the plan based on user feedback.

[1436] "User Information" means data including a user's past travel history, preferences, budget, etc.

[1437] "Weather Information" means data about current and future weather conditions obtained through the Weather API.

[1438] "Emotional Data" refers to information about a user's emotional state based on tone, speed, facial expression, etc., obtained from their voice and facial expressions.

[1439] A "travel plan" is a plan that includes the selection of tourist spots and restaurants, as well as route planning, and is generated based on the user's emotions, preferences, and weather information.

[1440] "Feedback" refers to opinions and requests received by users when they input corrections or requests regarding the proposed travel plan.

[1441] "Notification" refers to the process of sending the travel plan generated by the server to the user's terminal and informing the user.

[1442] "Reservation" is the process of securing necessary accommodation, transportation, tickets to tourist attractions, etc. based on the final travel plan generated.

[1443] "Tourist destinations" refer to places and facilities that users would like to visit while traveling.

[1444] "Food and Beverage" refers to the restaurants and cafes that you choose to eat at during your trip.

[1445] "Transportation" refers to suggestions for transportation and routes that users can use to travel from their current location to their destination.

[1446] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[1447] System configuration

[1448] The system consists of the following main components:

[1449] 1. How we collect user information

[1450] 2. How to obtain weather information

[1451] 3. Emotion Engine

[1452] 4. Travel plan generation method

[1453] 5. Means of notification

[1454] 6. Feedback channels

[1455] 7. Final confirmation method

[1456] 8. Reservation Methods

[1457] 9. How to select tourist spots and restaurants

[1458] 10. Means of transportation suggestion

[1459] Obtaining user information and weather information

[1460] server

[1461] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[1462] The server obtains current and future weather information in real time via a weather API.

[1463] Emotion recognition by emotion engine

[1464] server

[1465] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[1466] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[1467] Travel plan generation and notification

[1468] server

[1469] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[1470] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[1471] The generated travel plan is sent to the user's device.

[1472] Terminal

[1473] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[1474] User feedback and plan revisions

[1475] User

[1476] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[1477] server

[1478] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[1479] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[1480] Specific examples

[1481] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[1482] 1. Information gathering

[1483] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1484] Get weather information from the weather API and check that the weather is good for the day.

[1485] 2. Emotion recognition

[1486] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[1487] 3. Initial plan generation

[1488] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1489] 4. Creating a detailed plan

[1490] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1491] The terminal notifies the user of the schedule and displays it on the screen.

[1492] 5. User Feedback

[1493] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1494] 6. Final planning and booking

[1495] The server incorporates user feedback and creates the final plan.

[1496] The server automatically issues park admission tickets and reserves cafe seats.

[1497] Example prompt: "I want to go somewhere for a change today. I'm tired, but I want to find a new place."

[1498] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[1499] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1500] Step 1: Get user information

[1501] When a user logs in to the system, the server reads the user's past travel history and preference data from the database. Specifically, it executes an SQL query such as SELECT FROM user_preferences WHERE user_id = :user_id;. The input data includes the user's ID, and the output is information about the user's past travel history and preferences. This obtains the user's individual information and serves as the basis for generating a customized travel plan.

[1502] Step 2: Get weather information

[1503] The server uses a weather API (for example, a general weather API service) to obtain current and future weather information. Specifically, it sends an API request such as curl -X GET "http: / / api.openweathermap.org / data / 2.5 / weather?q=City&appid=YOUR_API_KEY". This input data includes geographic location data, and the output is weather information for that location. This allows it to generate travel plans that take current and forecast weather into account.

[1504] Step 3: Emotion Recognition

[1505] The server uses an emotion engine to analyze the emotional data entered by the user through voice input or facial recognition. Emotions are recognized based on tone and speed in the voice data, and facial expressions in the facial recognition data. Specifically, the server sends audio and images as a POST request to an emotion engine API (such as a general emotion analysis API). This input data includes audio and image data, and the user's emotional state is obtained as output. This makes it possible to propose travel plans that take into account the user's current emotions.

[1506] Step 4: Generate your travel plan

[1507] The server generates a travel plan by integrating the user's preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it selects tourist spots where they can enjoy nature. Specifically, to extract travel destinations based on preferences, weather, and emotional information, it executes an SQL query such as SELECT FROM locations WHERE category = 'nature' AND suitability_score > 7;. The input data includes the user's emotional state and weather information, and the output is a list of candidate tourist spots and restaurants.

[1508] Step 5: Plan Notification

[1509] The server sends the generated itinerary to the user's device. Specifically, it sends the itinerary data via an HTTP request. The input includes the information about the generated itinerary, and the output is the data received by the user's device. The device receives the itinerary sent from the server and notifies the user using push notifications or in-app notifications.

[1510] Step 6: Gather user feedback

[1511] The user reviews the proposed travel plan and makes any necessary modifications. Specifically, the user enters and submits the modified data on the device. The device then sends a POST request using JSON-formatted data to send the user's feedback to the server. The input data includes the user's modification request, and the feedback data is sent to the server as output.

[1512] Step 7: Generate the final plan

[1513] The server generates a final itinerary based on the user's feedback. Specifically, it generates a new itinerary that reflects the user's modifications and queries the database again to update the optimal route and tourist destination information. The input data includes the user's feedback, and the revised itinerary is obtained as the output.

[1514] Step 8: Making a reservation

[1515] The server automatically makes the necessary reservations based on the final travel plan. Specifically, it uses a reservation API (for example, a general reservation service API) to reserve accommodations, tickets to tourist attractions, and restaurants. The input data includes details of the final travel plan, and the output is reservation confirmation data.

[1516] (Application example 2)

[1517] 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."

[1518] Conventional factory work schedule management is based primarily on work procedures and the efficiency of each process, but it is difficult to consider individual worker conditions such as the emotional state and fatigue level of workers. This has led to problems such as reduced production efficiency, increased work errors, and concerns about worker safety and health. The present invention aims to solve these problems by recognizing workers' emotional states in real time and managing work schedules flexibly based on this information.

[1519] The specific processing by the specific 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 acquiring user (worker) information, means for acquiring weather information, means for recognizing the emotional state of the user (worker), means for generating a work schedule based on the user's (worker's) preferences, weather information, and emotional information, means for notifying the user (worker) of the generated work schedule, means for modifying the work schedule based on user (worker) feedback, and means for finalizing the modified work schedule and allocating related tasks. This enables the generation of flexible and efficient work schedules that take into account the emotional state of workers.

[1520] "Means for obtaining user information" refers to the function by which the system collects personal information about users (workers), past work history, preferred tasks, etc.

[1521] "Means for obtaining weather information" refers to the function by which the system obtains data on weather and climate from external information services and reflects this in work schedules.

[1522] "Means for recognizing the user's emotional state" refers to the system's ability to detect the emotions and psychological state of workers in real time and analyze this as data.

[1523] The "means for generating a work schedule" is a function that automatically creates an optimal work schedule based on the user's preferences, weather information, and emotional information.

[1524] The "means for notifying the user of the generated work schedule" is a function that notifies the created work schedule to the worker in real time and provides the information.

[1525] "Means for modifying work schedules based on user feedback" is a function that receives the opinions and requests of workers and flexibly modifies the work schedule accordingly.

[1526] The "means for finalizing the revised work schedule and allocating related tasks" is a function for appropriately allocating various related work tasks based on the finalized work schedule.

[1527] "Means for selecting the optimal task according to the conditions of the work site and equipment and calculating the efficient work route" is a function that selects the optimal work task and calculates the efficient work sequence, taking into account the conditions of the work site and the operating status of the machines.

[1528] "A means for proposing the optimal means of transportation from the worker's current location to the target work location" is a function that suggests the optimal route and means of transportation from the worker's current location to the designated work location.

[1529] This system is a factory robot management system that optimizes work schedules based on the emotional state of the user (worker). The system consists of the following main components:

[1530] System configuration

[1531] 1. How we collect user information

[1532] The server retrieves the user's activity history, preferences, and past feedback from a database, including the tasks they have performed in the past, their preferred tasks, and their work pace.

[1533] 2. How to obtain weather information

[1534] The server uses external weather APIs to obtain real-time current and future weather information, which helps to adjust the environment within the factory and maximize work efficiency.

[1535] 3. Emotional state recognition method

[1536] The server uses an emotion engine to analyze the user's voice input, facial recognition, and vital sign data. The emotion engine determines the user's emotional state by analyzing tone and speed from the voice data and facial expressions from the facial data. This emotion engine uses voice recognition software and facial recognition libraries (e.g., OpenCV, Dlib).

[1537] 4. Work Schedule Generation Method

[1538] The server generates a work schedule by integrating user preferences, weather information, and emotional information, assigning lighter tasks when the user is tired and more complex tasks when the user is less stressed.

[1539] 5. Means of notification

[1540] The generated work schedule is sent from the server to the user's device (such as a smartphone or tablet) and notified in real time.

[1541] 6. Feedback channels

[1542] Users provide feedback on the proposed work schedule, which is sent from the device to the server and reflected in schedule revisions.

[1543] 7. Final confirmation method

[1544] The server receives user feedback and determines the final work schedule, and then allocates related tasks based on this schedule.

[1545] Specific examples

[1546] For example, if Worker A says "I'm tired today," and the emotion engine determines from the voice and facial recognition data that the emotion is "I'm stressed," the system will process as follows:

[1547] 1. Information gathering

[1548] The server retrieves the user's past activity history and preference data, and retrieves weather information from the weather API.

[1549] 2. Emotion recognition

[1550] The emotion engine recognizes emotions such as "tired and stressed" from the user's voice and facial expression data.

[1551] 3. Initial schedule generation

[1552] The server generates a work schedule that suggests simple work tasks (e.g., quality checks) and short breaks based on the user's condition.

[1553] 4. Create a detailed schedule

[1554] The server creates a detailed schedule including suggested tasks and break times and sends it to the device, which then notifies the user and displays the schedule on the screen.

[1555] 5. User Feedback

[1556] The user provides feedback on the proposed schedule, requesting changes to some tasks.

[1557] 6. Final schedule and task allocation

[1558] The server reflects the user's feedback, determines the final schedule, and then assigns related tasks based on the determined schedule.

[1559] Prompt Sentence Examples

[1560] Prompt for the generative AI model:

[1561] The system analyzes the facial image data and voice data of workers to recognize their emotional state and assign them the next work task. For example, if a worker is recognized as "tired," it will schedule them for light work or a break.

[1562] In this way, the emotion engine can create a flexible work schedule that takes into account the emotional state of workers, and optimally allocate tasks. This system can simultaneously improve worker safety and efficiency.

[1563] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1564] Step 1:

[1565] The server obtains user (worker) information. As input, it receives the user ID and authentication information and extracts data from the user database, such as past work history, preferences, and feedback. It processes the data by filtering and integrating the necessary data. The output is the user's work history and preference data.

[1566] Step 2:

[1567] The server retrieves weather information. As input, a weather API request is sent, and the retrieved weather data is returned to the server. The data is processed by analyzing the current and future weather data and extracting the necessary parts. The output is real-time weather information.

[1568] Step 3:

[1569] The server recognizes the user's emotional state. The user's voice data and facial image data are used as input. An emotion engine is used to analyze tone and speed from the voice data and facial expressions from the facial image data. This determines the user's emotional state. The output is the user's current emotional state.

[1570] Step 4:

[1571] The server generates the work schedule. User preferences, weather information, and emotional information are used as input. This data is integrated and an AI model is used to calculate the optimal work schedule. Specifically, each data point is evaluated to select the most efficient and suitable task for the user. The output is the generated work schedule.

[1572] Step 5:

[1573] The server notifies the user of the generated work schedule. Work schedule data is given as input and sent to the terminal. The data is then converted into a notification format and sent to the user's smartphone or tablet. The output is a schedule notification on the user's terminal.

[1574] Step 6:

[1575] The user provides feedback on the work schedule. The input is the proposed schedule and the user's feedback. The terminal sends the user's opinions and change requests to the server. The data is processed by organizing and analyzing the feedback content. The output is user feedback data.

[1576] Step 7:

[1577] The server modifies the work schedule based on user feedback. The feedback data is used as input. The AI ​​model is then used again to update the schedule to reflect the feedback. The data is then processed to regenerate the schedule. The output is the modified work schedule.

[1578] Step 8:

[1579] The server finalizes the revised work schedule and allocates the associated tasks. The revised schedule data is used as input. The final schedule is finalized and each task is allocated to the appropriate worker. Data processing involves confirming and finalizing the task allocation. The output is an execution list of the allocated tasks.

[1580] 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.

[1581] 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.

[1582] 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.

[1583] [Fourth embodiment]

[1584] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1585] 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.

[1586] 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).

[1587] 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.

[1588] 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.

[1589] 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).

[1590] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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.

[1596] 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."

[1597] This invention is a system that saves users the trouble of making travel plans and quickly provides optimal travel plans. The system of the present invention operates by combining multiple means and generates travel plans based on data such as user information, weather information, and databases of tourist spots and restaurants.

[1598] This system is configured as follows:

[1599] 1. Collection of User Information

[1600] server

[1601] When a user logs in to the system, the server automatically retrieves the user's past travel history and preference data from the database, such as tourist spots the user has visited in the past, food preferences, and travel budget.

[1602] The server uses a specific API (e.g., an application or wearable device that manages health data) to obtain the user's current mood and physical condition.

[1603] 2. Integration of user information and weather information

[1604] server

[1605] The server uses a weather API to retrieve current and near-future weather information, including temperature, precipitation, wind speed, etc.

[1606] The server compares the acquired user information with weather information and selects a travel destination that suits the user's preferences and physical condition.

[1607] 3. Generate the initial plan

[1608] server

[1609] The server searches a tourist spot database and a restaurant database to select the tourist spot and restaurant that best suit the user's preferences and weather conditions.

[1610] The server calculates an efficient route based on the selected tourist spots and restaurants.

[1611] 4. Creating and notifying detailed plans

[1612] server

[1613] Based on the initial plan, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[1614] The generated schedule is sent to the user's device.

[1615] Terminal

[1616] The terminal notifies the user of the detailed schedule sent from the server and displays it on the screen.

[1617] User

[1618] Users can review the proposed itinerary and make any necessary modifications, for example, adding or removing specific tourist attractions.

[1619] 5. Finalize the plan and make a reservation

[1620] server

[1621] The server creates a final itinerary based on the modifications made by the user.

[1622] Based on the final plan created, accommodation reservations, transportation arrangements, and ticket purchases for sightseeing spots are automatically made. For example, hotel reservation APIs and plane ticket reservation APIs are used to quickly make the necessary reservations.

[1623] Specific examples

[1624] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[1625] 1. Information gathering

[1626] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1627] Get weather information from the weather API and check that the weather is good for the day.

[1628] 2. Initial plan generation

[1629] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1630] 3. Creating a detailed plan

[1631] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1632] The terminal notifies the user of the schedule and displays it on the screen.

[1633] 4. User Feedback

[1634] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1635] 5. Final planning and booking

[1636] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[1637] In this way, users can eliminate the need for tedious planning and quickly obtain optimal travel plans. This system allows users to enjoy their trips with ease and improves their satisfaction.

[1638] The processing flow will be explained below.

[1639] Step 1:

[1640] A user logs in to the system.

[1641] Step 2:

[1642] The server retrieves the user's past travel history and preference data from a database.

[1643] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[1644] Step 3:

[1645] The server sends a request to the weather API to obtain current and near-future weather information.

[1646] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[1647] Step 4:

[1648] The server obtains the user's current mood and physical condition from various sensors and input forms.

[1649] How it works: Collects health data from smartphone APIs and medical interview data from users.

[1650] Step 5:

[1651] The server integrates the user information and weather information and searches a database of tourist attractions and restaurants.

[1652] How it works: It runs a search query against each database based on the user's preferences and weather conditions to generate a list of candidates.

[1653] Step 6:

[1654] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[1655] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[1656] Step 7:

[1657] The server generates the initial itinerary and creates a detailed schedule.

[1658] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[1659] Step 8:

[1660] The server sends the generated schedule to the user's terminal.

[1661] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[1662] Step 9:

[1663] The terminal notifies the user of the detailed schedule received from the server.

[1664] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[1665] Step 10:

[1666] The user reviews the proposed itinerary and makes any necessary modifications.

[1667] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[1668] Step 11:

[1669] The server receives the user's modification requests and creates the final itinerary.

[1670] How it works: The algorithm re-optimizes the plan based on user feedback.

[1671] Step 12:

[1672] The server automatically makes related reservations based on the finalized plan.

[1673] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[1674] In this way, it is possible to provide the user with an optimal travel plan that meets their needs.

[1675] Example 1

[1676] 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."

[1677] Conventional travel planning systems require users to individually search for travel plans and manually plan them, which is time-consuming and laborious. It is also difficult to provide optimal travel plans that take into account weather and the user's health condition. It is also difficult to immediately reflect user feedback and revise travel plans in real time. To solve these issues, there is a need for a fast and flexible travel plan generation and booking automation system that takes into account user preferences, health condition, and weather information.

[1678] 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.

[1679] In this invention, the server includes means for acquiring user information, means for acquiring health status data, means for acquiring weather information, means for generating a travel plan based on the user's preferences, health status, and weather information, means for notifying the user of the generated travel plan, means for modifying the travel plan based on the user's feedback, and means for finalizing the modified travel plan and making related reservations. This allows users to quickly obtain an optimal travel plan based on their health status and weather conditions, eliminating the need for individual searches and manual planning. Furthermore, real-time plan modifications based on user feedback improve travel satisfaction.

[1680] "User information" is a general term for data such as a user's past travel history, preferences, budget, etc.

[1681] "Health data" refers to information about a user's current physical condition or mood, obtained from wearable devices or health management applications.

[1682] "Weather information" refers to data about current and near-future weather conditions obtained through weather APIs, including temperature, precipitation, wind speed, etc.

[1683] A "travel plan" is a detailed schedule that includes planned visits to tourist attractions and restaurants, generated based on the user's preferences, health status, and weather information.

[1684] "Device" is a general term for electronic devices used by users, including smartphones and tablets.

[1685] "Feedback" refers to any corrections or additional instructions given by the user to the proposed travel plan, which are sent to the server via the terminal.

[1686] "Reservation" refers to procedures such as purchasing accommodation, transportation, and tickets to tourist attractions based on a confirmed travel plan.

[1687] "Database" refers to an information accumulation system that stores user information, tourist destination data, restaurant data, etc., and can be searched and retrieved as needed.

[1688] An "API" is an interface that allows different software applications to communicate with each other, and is used to obtain weather information, health status data, etc.

[1689] "Route" refers to a calculated route for efficiently visiting tourist attractions and restaurants, and is used to optimize the user's travel.

[1690] A "schedule" is a plan detailing the order of visits, means of transportation, and duration of stay at each location.

[1691] This invention is a system for efficiently planning travel plans for users, in which the server, terminal, and user each play specific roles. Specifically, the system uses user information, health status data, and weather information to generate travel plans tailored to the user's needs and even automatically makes the necessary reservations.

[1692] Hardware and software used

[1693] server:

[1694] The server uses a database management system (DBMS) to manage user information, tourist destination data, and restaurant data.

[1695] Use APIs to retrieve external weather and health data, for example, use the OpenWeatherMap API to retrieve weather information and health data from the Google Fit API or other health management applications.

[1696] It uses generative AI models to generate optimal travel plans based on user preferences and current conditions.

[1697] Device:

[1698] The user's mobile device, such as a smartphone or tablet, is used. These devices receive the information sent from the server and notify and display it to the user.

[1699] user:

[1700] Users log in to the system and provide information about their preferences and physical condition, and feedback is also sent to the server via their device.

[1701] Data processing and calculation

[1702] server

[1703] The server automatically retrieves past travel history and preference data from the database when a user logs in, for example using SQL queries to find the required data.

[1704] The server utilizes specific APIs to collect data about the user's current mood and physical condition. Data obtained from the health status API includes, for example, sleep duration and activity level.

[1705] The server retrieves weather information through a weather API, including current and near-future weather, temperature, precipitation, and wind speed.

[1706] The server comprehensively analyzes the acquired data and generates a travel plan that best suits the user's preferences and health status. This analysis and plan generation is performed using a generative AI model.

[1707] After generating the plan, the server sends a detailed schedule to the user's smartphone or tablet.

[1708] The server receives feedback from the user, adjusts the final plan, and automatically makes all necessary reservations, for example using accommodation booking APIs and transportation booking APIs.

[1709] Terminal

[1710] The device notifies the user of the travel plan received from the server and displays it on the screen, allowing the user to review the proposed plan and enter any changes or additions.

[1711] Users can send feedback to the server via their devices, including changes to selected tourist spots and restaurants, or changes to the order of visits.

[1712] Specific examples

[1713] For example, if a user inputs "I want to enjoy nature today," the following processing occurs:

[1714] 1. Information gathering

[1715] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1716] Get weather information from the weather API and check that the weather is good for the day.

[1717] 2. Initial plan generation

[1718] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1719] 3. Creating a detailed plan

[1720] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1721] The terminal notifies the user of the schedule and displays it on the screen.

[1722] 4. User Feedback

[1723] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1724] 5. Final planning and booking

[1725] The server creates a final plan that incorporates user feedback and automatically reserves park admission tickets and cafe seats.

[1726] In this way, users are freed from the tedious task of planning trips and can quickly obtain the best travel plans, thereby enriching users' travel experience and increasing their satisfaction.

[1727] Prompt Sentence Examples

[1728] "Today I want to enjoy nature."

[1729] "Looking for tourist spots that can be enjoyed even in the rain"

[1730] "I want you to plan a gourmet tour."

[1731] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1732] Step 1: User login and information gathering

[1733] server

[1734] When a user logs into the system, the server authenticates the entered username and password and starts a session.

[1735] Input: Username, Password

[1736] Data processing: Performs the authentication process and generates session information if successful.

[1737] Output: Session information, user ID

[1738] server

[1739] The server retrieves the user's past travel history and preferences from a database using SQL queries to find the required data based on the user ID.

[1740] Input: User ID

[1741] Data processing: Search and extract data on past travel history and preferences.

[1742] Output: Travel history data, preference data

[1743] server

[1744] The server uses the health management API to obtain the user's current health status data, for example, to collect activity data and physical condition data for a specific date.

[1745] Input: Health management API token, user ID

[1746] Data processing: Send a request to the health management API and analyze the response data.

[1747] Output: Health status data

[1748] Step 2: Get weather information

[1749] server

[1750] The server uses the weather API to obtain current and near-future weather information (e.g., temperature, precipitation, wind speed, etc.).

[1751] Input: Location, Weather API token

[1752] Data processing: Send a request to the weather API and analyze the response data.

[1753] Output: Weather information data

[1754] Step 3: Generate an initial plan

[1755] server

[1756] The server refers to the tourist destination database and restaurant database to select the tourist destination and restaurant that best suits the user's preferences, health condition, and weather conditions, thereby providing the user with the best options for their current situation.

[1757] Input: Travel history data, preference data, health data, weather information data

[1758] Data processing: Use generative AI models to perform integrated analysis of user information and external data.

[1759] Output: Initial plan data

[1760] server

[1761] The server calculates an efficient route based on the selected tourist spots and restaurants, using Google Maps API and other tools to calculate the optimal travel route.

[1762] Input: Initial plan data, location data

[1763] Data processing: Calculate the optimal route using Google Maps API.

[1764] Output: Route information data

[1765] Step 4: Create and communicate a detailed plan

[1766] server

[1767] Based on the initial plan and route information, the server generates a daily schedule detailing the order of visits, means of transportation, and duration of stay at each location.

[1768] Input: Initial plan data, route information data

[1769] Data processing: Apply a schedule generation algorithm to create a detailed schedule.

[1770] Output: Detailed schedule data

[1771] server

[1772] The server transmits the generated detailed schedule to the user's terminal.

[1773] Input: Detailed schedule data, user terminal information

[1774] Data processing: Convert detailed schedule data into a format suitable for the device.

[1775] Output: Schedule notification data

[1776] Terminal

[1777] The terminal receives the detailed schedule sent from the server, notifies the user, and displays it on the screen.

[1778] Input: Schedule notification data

[1779] Data processing: Converting schedule notification data into a format for display in the user interface.

[1780] Output: Screen display data

[1781] Step 5: Incorporating user feedback

[1782] user

[1783] Users can review the proposed itinerary and make any necessary modifications, including adding or removing attractions or restaurants, or changing the order in which they are visited.

[1784] Input: Proposed itinerary

[1785] Data processing: Accepts user corrections as input.

[1786] Output: Corrective feedback data

[1787] server

[1788] The server receives feedback from the user and creates the final itinerary, which includes recalculation to reflect the user's changes.

[1789] Input: Corrective feedback data, initial plan data

[1790] Data processing: Recalculate the plan based on the modifications and generate the final plan.

[1791] Output: Final plan data

[1792] Step 6: Finalize your plan and book

[1793] server

[1794] Based on the final plan, the server automatically reserves accommodation, secures transportation, purchases tickets to tourist attractions, etc. This is done using a reservation API.

[1795] Input: Final plan data, Reservation API token

[1796] Data processing: Send a request to the booking API to retrieve booking information.

[1797] Output: Confirmed reservation data

[1798] server

[1799] The server sends the confirmed reservation details to the user's terminal and notifies them for confirmation.

[1800] Input: Reservation confirmation data, user terminal information

[1801] Data processing: Converts reservation confirmation data into a format suitable for the device.

[1802] Output: Booking notification data

[1803] Terminal

[1804] The terminal receives the reservation details sent from the server, notifies the user, and displays them on the screen.

[1805] Input: Booking notification data

[1806] Data processing: Converting booking notification data into a format for display in the user interface.

[1807] Output: Screen display data

[1808] (Application example 1)

[1809] 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."

[1810] Conventional food delivery services require users to search and select menus themselves, making it difficult to provide appropriate suggestions based on their physical condition or weather conditions. This makes it difficult for some users to choose meals that take their physical condition and weather into consideration, which can lead to lower satisfaction. Furthermore, if an appropriate dish is not selected, there is a risk of harming their health. Furthermore, personalized suggestions are lacking because the service does not fully utilize users' preferences and past ordering history.

[1811] 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.

[1812] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for generating a food delivery plan based on the user's preferences and weather information, means for notifying the user of the generated food delivery plan, means for modifying the food delivery plan based on the user's feedback, and means for finalizing the modified food delivery plan and placing an associated order. This makes it possible to suggest optimal dishes based on the user's individual preferences, physical condition, and weather conditions, and to automatically confirm the order.

[1813] "Means for obtaining user information" refers to means for collecting a user's past order history, preference data, health status, etc.

[1814] "Means for obtaining weather information" refers to means for obtaining current and near-future weather information such as temperature, precipitation, and wind speed.

[1815] The "means for generating a food delivery plan" is a means for selecting dishes that suit the user's preferences and physical condition based on user information and weather information.

[1816] The "means for notifying the user of the food delivery plan" is a means for sending the generated food delivery plan to the user's terminal and notifying the user.

[1817] The "means for modifying the food delivery plan based on user feedback" refers to a means for modifying the selected food delivery plan based on feedback information from users.

[1818] "Means for finalizing the food delivery plan and placing the related orders" means the means for finalizing the optimal food order based on the revised food delivery plan and placing the order with the restaurant.

[1819] "Means for searching menu information of affiliated restaurants and delivery services" refers to means for searching a database for menu information of affiliated restaurants and delivery services.

[1820] "Means for selecting dishes that best suit the user's preferences and weather conditions" refers to means for selecting the most suitable dishes based on user information and weather information.

[1821] "A means for suggesting the optimal delivery method from the user's current location to the restaurant" is a means for suggesting the optimal delivery method based on the user's current location and the restaurant's location information.

[1822] The present invention is a system that collects user information, weather information, and restaurant menu information, and provides an optimal food delivery plan based on the user's preferences and physical condition. Specific examples are presented below to explain the detailed configuration and operation of the present invention.

[1823] 1. Collection of User Information

[1824] When a user logs in to the system, the server automatically retrieves the user's past order history and preference data from the database. Specifically, it collects data on the user's favorite dishes, favorite restaurants, past order history, and health status. It also retrieves the user's current physical condition data from healthcare applications and wearable devices. This provides the basic data needed to generate a personalized food delivery plan.

[1825] 2. Obtaining weather information

[1826] The server uses a weather API to obtain current and near-future weather information, including temperature, precipitation, wind speed, etc. For example, the server uses the Weather API to obtain real-time weather information for the user's location.

[1827] 3. Generate a food delivery plan

[1828] The server integrates user information and weather information to suggest the best dishes to suit the user's preferences and physical condition. It searches menu information from affiliated restaurants and delivery services to select dishes that meet the user's requirements. Since it also takes weather conditions into account, it can, for example, suggest cold dishes on hot days and hot dishes on cold days.

[1829] 4. Plan Notification and Feedback

[1830] The generated food delivery plan is sent from the server to the user's device and notified. The user can then review the proposed plan via their smartphone or smart glasses. If the user provides feedback, the server will modify the plan based on that feedback and finalize the plan. For example, modifications can be made to accommodate the user's requests, such as allergies to certain ingredients or requests for other dishes.

[1831] 5. Order confirmation and execution

[1832] The server automatically places an order with partner restaurants based on the finalized food delivery plan, allowing users to enjoy the best food without any hassle. Order information is sent via the restaurant or delivery service's API.

[1833] Hardware and software used

[1834] The hardware used includes a server, smartphone, and smart glasses, while the software uses Weather API, restaurant APIs, and a user information management system to obtain data via APIs.

[1835] Examples of specific examples and prompts

[1836] For example, if a user types, "It's hot today, I want to eat something light," the server will suggest cold Chinese noodles based on the weather information indicating the high temperature and the user's request.

[1837] Example prompt sentence:

[1838] "It's hot today, I want to eat something refreshing."

[1839] By entering this prompt, the system will suggest the most suitable dish and automatically confirm the order.

[1840] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1841] Step 1:

[1842] When a user logs in to the system, the server obtains user information, including the user's past order history, preference data, and health status data. The input is the user's login information, and the output is the user's detailed information. Specifically, based on the user ID, the server collects past order history, preference food, and health status data from the database. This data is used in the next step.

[1843] Step 2:

[1844] The server uses a weather API to obtain weather information for the user's location. The input is the user's location information, and the output is current and near-future weather data. Specifically, the server calls the Weather API to obtain information such as temperature, precipitation, and wind speed. This data is then used to generate the plan.

[1845] Step 3:

[1846] The server integrates user information and weather information to generate a food delivery plan based on the user's preferences, physical condition, and weather conditions. The input is the user information and weather information obtained in the previous step, and the output is a list of suggested dishes. Specifically, it searches a database of affiliated restaurants and selects the dish that best suits the user's requirements. For example, it suggests cold dishes on hot days and hot dishes on cold days.

[1847] Step 4:

[1848] The server sends the generated food delivery plan to the user's device and notifies them. The input is the generated list of dishes, and the output is a notification displayed on the user's device. Specifically, a notification is sent to the user's smartphone or smart glasses, displaying detailed information about the proposed dishes.

[1849] Step 5:

[1850] The user submits feedback on the proposed food delivery plan. The input is the user's feedback information, and the output is the requested corrections. Specifically, the user enters information about allergies to specific ingredients and other desired dishes on the app and sends it to the server.

[1851] Step 6:

[1852] The server modifies the food delivery plan based on the user's feedback. The input is the user's feedback information, and the output is the final modified plan. Specifically, it searches the database again and reselects dishes that match the user's preferences.

[1853] Step 7:

[1854] The server places an order with the partner restaurant based on the finalized food delivery plan. The input is the finalized dish information, and the output is a notification of order confirmation to the restaurant. Specifically, the server calls the restaurant's API to automatically send the order information and receive confirmation.

[1855] Step 8:

[1856] The restaurant prepares the food based on the received order and delivers it to the user through a delivery service. The input is the order information from the server, and the output is a notification that the food has been delivered. Specifically, after cooking is complete, the food is handed over to a delivery person who then delivers it to the user.

[1857] 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.

[1858] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[1859] System configuration

[1860] The system consists of the following main components:

[1861] 1. How we collect user information

[1862] 2. How to obtain weather information

[1863] 3. Emotion Engine

[1864] 4. Travel plan generation method

[1865] 5. Means of notification

[1866] 6. Feedback channels

[1867] 7. Final confirmation method

[1868] 8. Reservation Methods

[1869] 9. How to select tourist spots and restaurants

[1870] 10. Means of transportation suggestion

[1871] Obtaining user information and weather information

[1872] server

[1873] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[1874] The server obtains current and future weather information in real time via a weather API.

[1875] Emotion recognition by emotion engine

[1876] server

[1877] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[1878] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[1879] Travel plan generation and notification

[1880] server

[1881] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[1882] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[1883] The generated travel plan is sent to the user's device.

[1884] Terminal

[1885] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[1886] User feedback and plan revisions

[1887] User

[1888] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[1889] server

[1890] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[1891] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[1892] Specific examples

[1893] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[1894] 1. Information gathering

[1895] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[1896] Get weather information from the weather API and check that the weather is good for the day.

[1897] 2. Emotion recognition

[1898] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[1899] 3. Initial plan generation

[1900] The server suggests nearby nature parks and selects highly rated cafes in the area.

[1901] 4. Creating a detailed plan

[1902] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[1903] The terminal notifies the user of the schedule and displays it on the screen.

[1904] 5. User Feedback

[1905] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[1906] 6. Final planning and booking

[1907] The server incorporates user feedback and creates the final plan.

[1908] The server automatically issues park admission tickets and reserves cafe seats.

[1909] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[1910] The processing flow will be explained below.

[1911] Step 1:

[1912] A user logs in to the system.

[1913] Step 2:

[1914] The server retrieves the user's past travel history and preference data from a database.

[1915] What it does: It uses an SQL query to extract data from a past trip history table using the user ID as the key.

[1916] Step 3:

[1917] The server sends a request to the weather API to obtain current and near-future weather information.

[1918] How it works: Sends an HTTP request to a weather API and receives weather data in JSON format in response.

[1919] Step 4:

[1920] The server uses an emotion engine to analyze voice input and facial recognition data to recognize the user's emotions.

[1921] How it works: Audio and video data captured through a microphone and camera is sent to the emotion engine, where it performs text analysis, audio analysis, image analysis, etc.

[1922] Example: When a user says, "I'm a little tired, but I want to go somewhere," the emotion engine analyzes the voice data and recognizes it as, "I'm tired, but I'm looking for a new experience."

[1923] Step 5:

[1924] The server integrates the above acquired data (user information, weather information, emotion data) and selects appropriate candidates from a tourist destination database and a restaurant database.

[1925] How it works: Extracts and filters a list of tourist attractions and restaurants from a database that match the user's preferences and current sentiment.

[1926] Step 6:

[1927] The server makes the optimal selection from a list of tourist attractions and restaurants and calculates an efficient route.

[1928] How it works: It uses GIS (geographic information systems) to analyze the locations of tourist attractions and restaurants, and applies algorithms to optimize the order of visits and transportation methods.

[1929] Step 7:

[1930] The server generates the initial itinerary and creates a detailed schedule.

[1931] How it works: Create a chronological schedule for the day, taking into account the time spent at tourist spots and restaurants, and travel time.

[1932] Example: Create a schedule that involves visiting a nature park in the morning and relaxing at a cafe in the afternoon.

[1933] Step 8:

[1934] The server sends the generated schedule to the user's terminal.

[1935] Operation: The created schedule is encoded in JSON format and sent to the device via API.

[1936] Step 9:

[1937] The terminal notifies the user of the detailed schedule received from the server.

[1938] How it works: Uses the notification system to notify you via a popup or push notification, and displays details in the GUI.

[1939] Step 10:

[1940] The user reviews the proposed itinerary and makes any necessary modifications.

[1941] Operation: Enter modification requests such as adding or deleting destinations or changing time through the terminal interface.

[1942] Example: When a user says, "I want to add another tourist spot after the cafe," that information is sent to the server.

[1943] Step 11:

[1944] The server receives the user's modification requests and creates the final itinerary.

[1945] How it works: The algorithm re-applies the plan and optimizes it based on the corrections received from the user.

[1946] Step 12:

[1947] The server automatically makes related reservations based on the finalized plan.

[1948] How it works: Reservations are made using ticket purchasing APIs for accommodation, transportation, and tourist attractions.

[1949] Example: Buying tickets online to selected tourist attractions and confirming cafe reservations.

[1950] In this way, an optimal travel plan that takes the user's emotions into account can be automatically generated and flexibly revised based on feedback.

[1951] Example 2

[1952] 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."

[1953] Conventional travel planning systems have difficulty generating plans that take into account the user's emotions and moods. Furthermore, the travel plans proposed to users are not always appropriate for the user's mood or real-time weather information, resulting in a decrease in user satisfaction. Therefore, there is a need for a system that can automatically generate more personalized travel plans based on the user's emotions and weather information, as well as flexible feedback and revisions based on those plans.

[1954] 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.

[1955] In this invention, the server includes means for acquiring user information, means for acquiring weather information, means for recognizing and analyzing user emotion data, means for generating a travel plan based on the user's preferences, weather information, and emotion data, means for notifying the user of the generated travel plan, means for modifying the travel plan based on user feedback, and means for finalizing the modified travel plan and making related reservations. This enables the generation of an optimal travel plan that takes into account the user's emotions, preferences, and real-time weather information, and the flexible modification of the plan based on user feedback.

[1956] "User Information" means data including a user's past travel history, preferences, budget, etc.

[1957] "Weather Information" means data about current and future weather conditions obtained through the Weather API.

[1958] "Emotional Data" refers to information about a user's emotional state based on tone, speed, facial expression, etc., obtained from their voice and facial expressions.

[1959] A "travel plan" is a plan that includes the selection of tourist spots and restaurants, as well as route planning, and is generated based on the user's emotions, preferences, and weather information.

[1960] "Feedback" refers to opinions and requests received by users when they input corrections or requests regarding the proposed travel plan.

[1961] "Notification" refers to the process of sending the travel plan generated by the server to the user's terminal and informing the user.

[1962] "Reservation" is the process of securing necessary accommodation, transportation, tickets to tourist attractions, etc. based on the final travel plan generated.

[1963] "Tourist destinations" refer to places and facilities that users would like to visit while traveling.

[1964] "Food and Beverage" refers to the restaurants and cafes that you choose to eat at during your trip.

[1965] "Transportation" refers to suggestions for transportation and routes that users can use to travel from their current location to their destination.

[1966] This invention combines a system that automatically creates travel plans for users with an emotion engine that recognizes the user's emotions. The purpose of this system is to generate optimal travel plans based on user information, weather information, and emotion information, and provide them to the user.

[1967] System configuration

[1968] The system consists of the following main components:

[1969] 1. How we collect user information

[1970] 2. How to obtain weather information

[1971] 3. Emotion Engine

[1972] 4. Travel plan generation method

[1973] 5. Means of notification

[1974] 6. Feedback channels

[1975] 7. Final confirmation method

[1976] 8. Reservation Methods

[1977] 9. How to select tourist spots and restaurants

[1978] 10. Means of transportation suggestion

[1979] Obtaining user information and weather information

[1980] server

[1981] When a user logs into the system, the server retrieves the user's past travel history and preferences from a database, including tourist spots visited, favorite dishes, and travel budget.

[1982] The server obtains current and future weather information in real time via a weather API.

[1983] Emotion recognition by emotion engine

[1984] server

[1985] The server uses an emotion engine to analyze emotion data entered by the user through voice input or facial recognition, recognizing emotions based on tone and speed from the voice data and facial expressions from the facial data.

[1986] The emotion engine also takes into account the user's past emotional history to determine changes in their emotions and their mood for the day.

[1987] Travel plan generation and notification

[1988] server

[1989] The server generates a travel plan by integrating user preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it will choose tourist spots that allow them to enjoy nature.

[1990] The server selects the best tourist spots and restaurants and calculates the most efficient route.

[1991] The generated travel plan is sent to the user's device.

[1992] Terminal

[1993] The terminal notifies the user of the travel plan sent from the server and displays it on the screen.

[1994] User feedback and plan revisions

[1995] User

[1996] Users can review the proposed itinerary and make any necessary modifications, such as deleting tourist spots they don't want to visit or adding locations they want to add.

[1997] server

[1998] The server receives feedback from the user and creates a final itinerary that reflects that feedback.

[1999] Based on the finalized plan, necessary reservations (accommodation, transportation, tickets to tourist attractions, etc.) will be made automatically.

[2000] Specific examples

[2001] For example, if a user inputs "I want to go somewhere today to change my mood," and then voice input and facial recognition recognize the emotion "I'm tired, but I want to find a new place," the system processes as follows:

[2002] 1. Information gathering

[2003] The server acquires data on the user's past travel history and preferences, such as a love of nature, as well as current physical condition data.

[2004] Get weather information from the weather API and check that the weather is good for the day.

[2005] 2. Emotion recognition

[2006] The emotion engine recognizes the emotion "I want to enjoy something new even though I'm tired" from the user's voice and facial expressions.

[2007] 3. Initial plan generation

[2008] The server suggests nearby nature parks and selects highly rated cafes in the area.

[2009] 4. Creating a detailed plan

[2010] The server creates a detailed schedule including the time spent walking in the nature park and the time spent taking a break at a cafe afterwards, and sends it to the terminal.

[2011] The terminal notifies the user of the schedule and displays it on the screen.

[2012] 5. User Feedback

[2013] The user can send feedback from the terminal to change the order of visits based on the proposed schedule.

[2014] 6. Final planning and booking

[2015] The server incorporates user feedback and creates the final plan.

[2016] The server automatically issues park admission tickets and reserves cafe seats.

[2017] Example prompt: "I want to go somewhere for a change today. I'm tired, but I want to find a new place."

[2018] In this way, the emotion engine can easily create travel plans that take the user's moods and emotions into account, and can flexibly modify them based on feedback. This system allows users to easily create appropriate travel plans.

[2019] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2020] Step 1: Get user information

[2021] When a user logs in to the system, the server reads the user's past travel history and preference data from the database. Specifically, it executes an SQL query such as SELECT FROM user_preferences WHERE user_id = :user_id;. The input data includes the user's ID, and the output is information about the user's past travel history and preferences. This obtains the user's individual information and serves as the basis for generating a customized travel plan.

[2022] Step 2: Get weather information

[2023] The server uses a weather API (for example, a general weather API service) to obtain current and future weather information. Specifically, it sends an API request such as curl -X GET "http: / / api.openweathermap.org / data / 2.5 / weather?q=City&appid=YOUR_API_KEY". This input data includes geographic location data, and the output is weather information for that location. This allows it to generate travel plans that take current and forecast weather into account.

[2024] Step 3: Emotion Recognition

[2025] The server uses an emotion engine to analyze the emotional data entered by the user through voice input or facial recognition. Emotions are recognized based on tone and speed in the voice data, and facial expressions in the facial recognition data. Specifically, the server sends audio and images as a POST request to an emotion engine API (such as a general emotion analysis API). This input data includes audio and image data, and the user's emotional state is obtained as output. This makes it possible to propose travel plans that take into account the user's current emotions.

[2026] Step 4: Generate your travel plan

[2027] The server generates a travel plan by integrating the user's preferences, weather information, and emotional data. For example, if the user is in the mood to relax, it selects tourist spots where they can enjoy nature. Specifically, to extract travel destinations based on preferences, weather, and emotional information, it executes an SQL query such as SELECT FROM locations WHERE category = 'nature' AND suitability_score > 7;. The input data includes the user's emotional state and weather information, and the output is a list of candidate tourist spots and restaurants.

[2028] Step 5: Plan Notification

[2029] The server sends the generated itinerary to the user's device. Specifically, it sends the itinerary data via an HTTP request. The input includes the information about the generated itinerary, and the output is the data received by the user's device. The device receives the itinerary sent from the server and notifies the user using push notifications or in-app notifications.

[2030] Step 6: Gather user feedback

[2031] The user reviews the proposed travel plan and makes any necessary modifications. Specifically, the user enters and submits the modified data on the device. The device then sends a POST request using JSON-formatted data to send the user's feedback to the server. The input data includes the user's modification request, and the feedback data is sent to the server as output.

[2032] Step 7: Generate the final plan

[2033] The server generates a final itinerary based on the user's feedback. Specifically, it generates a new itinerary that reflects the user's modifications and queries the database again to update the optimal route and tourist destination information. The input data includes the user's feedback, and the revised itinerary is obtained as the output.

[2034] Step 8: Making a reservation

[2035] The server automatically makes the necessary reservations based on the final travel plan. Specifically, it uses a reservation API (for example, a general reservation service API) to reserve accommodations, tickets to tourist attractions, and restaurants. The input data includes details of the final travel plan, and the output is reservation confirmation data.

[2036] (Application example 2)

[2037] 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."

[2038] Conventional factory work schedule management is based primarily on work procedures and the efficiency of each process, but it is difficult to consider individual worker conditions such as the emotional state and fatigue level of workers. This has led to problems such as reduced production efficiency, increased work errors, and concerns about worker safety and health. The present invention aims to solve these problems by recognizing workers' emotional states in real time and managing work schedules flexibly based on this information.

[2039] The specific processing by the specific 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 acquiring user (worker) information, means for acquiring weather information, means for recognizing the emotional state of the user (worker), means for generating a work schedule based on the user's (worker's) preferences, weather information, and emotional information, means for notifying the user (worker) of the generated work schedule, means for modifying the work schedule based on user (worker) feedback, and means for finalizing the modified work schedule and allocating related tasks. This enables the generation of flexible and efficient work schedules that take into account the emotional state of workers.

[2040] "Means for obtaining user information" refers to the function by which the system collects personal information about users (workers), past work history, preferred tasks, etc.

[2041] "Means for obtaining weather information" refers to the function by which the system obtains data on weather and climate from external information services and reflects this in work schedules.

[2042] "Means for recognizing the user's emotional state" refers to the system's ability to detect the emotions and psychological state of workers in real time and analyze this as data.

[2043] The "means for generating a work schedule" is a function that automatically creates an optimal work schedule based on the user's preferences, weather information, and emotional information.

[2044] The "means for notifying the user of the generated work schedule" is a function that notifies the created work schedule to the worker in real time and provides the information.

[2045] "Means for modifying work schedules based on user feedback" is a function that receives the opinions and requests of workers and flexibly modifies the work schedule accordingly.

[2046] The "means for finalizing the revised work schedule and allocating related tasks" is a function for appropriately allocating various related work tasks based on the finalized work schedule.

[2047] "Means for selecting the optimal task according to the conditions of the work site and equipment and calculating the efficient work route" is a function that selects the optimal work task and calculates the efficient work sequence, taking into account the conditions of the work site and the operating status of the machines.

[2048] "A means for proposing the optimal means of transportation from the worker's current location to the target work location" is a function that suggests the optimal route and means of transportation from the worker's current location to the designated work location.

[2049] This system is a factory robot management system that optimizes work schedules based on the emotional state of the user (worker). The system consists of the following main components:

[2050] System configuration

[2051] 1. How we collect user information

[2052] The server retrieves the user's activity history, preferences, and past feedback from a database, including the tasks they have performed in the past, their preferred tasks, and their work pace.

[2053] 2. How to obtain weather information

[2054] The server uses external weather APIs to obtain real-time current and future weather information, which helps to adjust the environment within the factory and maximize work efficiency.

[2055] 3. Emotional state recognition method

[2056] The server uses an emotion engine to analyze the user's voice input, facial recognition, and vital sign data. The emotion engine determines the user's emotional state by analyzing tone and speed from the voice data and facial expressions from the facial data. This emotion engine uses voice recognition software and facial recognition libraries (e.g., OpenCV, Dlib).

[2057] 4. Work Schedule Generation Method

[2058] The server generates a work schedule by integrating user preferences, weather information, and emotional information, assigning lighter tasks when the user is tired and more complex tasks when the user is less stressed.

[2059] 5. Means of notification

[2060] The generated work schedule is sent from the server to the user's device (such as a smartphone or tablet) and notified in real time.

[2061] 6. Feedback channels

[2062] Users provide feedback on the proposed work schedule, which is sent from the device to the server and reflected in schedule revisions.

[2063] 7. Final confirmation method

[2064] The server receives user feedback and determines the final work schedule, and then allocates related tasks based on this schedule.

[2065] Specific examples

[2066] For example, if Worker A says "I'm tired today," and the emotion engine determines from the voice and facial recognition data that the emotion is "I'm stressed," the system will process as follows:

[2067] 1. Information gathering

[2068] The server retrieves the user's past activity history and preference data, and retrieves weather information from the weather API.

[2069] 2. Emotion recognition

[2070] The emotion engine recognizes emotions such as "tired and stressed" from the user's voice and facial expression data.

[2071] 3. Initial schedule generation

[2072] The server generates a work schedule that suggests simple work tasks (e.g., quality checks) and short breaks based on the user's condition.

[2073] 4. Create a detailed schedule

[2074] The server creates a detailed schedule including suggested tasks and break times and sends it to the device, which then notifies the user and displays the schedule on the screen.

[2075] 5. User Feedback

[2076] The user provides feedback on the proposed schedule, requesting changes to some tasks.

[2077] 6. Final schedule and task allocation

[2078] The server reflects the user's feedback, determines the final schedule, and then assigns related tasks based on the determined schedule.

[2079] Prompt Sentence Examples

[2080] Prompt for the generative AI model:

[2081] The system analyzes the facial image data and voice data of workers to recognize their emotional state and assign them the next work task. For example, if a worker is recognized as "tired," it will schedule them for light work or a break.

[2082] In this way, the emotion engine can create a flexible work schedule that takes into account the emotional state of workers, and optimally allocate tasks. This system can simultaneously improve worker safety and efficiency.

[2083] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2084] Step 1:

[2085] The server obtains user (worker) information. As input, it receives the user ID and authentication information and extracts data from the user database, such as past work history, preferences, and feedback. It processes the data by filtering and integrating the necessary data. The output is the user's work history and preference data.

[2086] Step 2:

[2087] The server retrieves weather information. As input, a weather API request is sent, and the retrieved weather data is returned to the server. The data is processed by analyzing the current and future weather data and extracting the necessary parts. The output is real-time weather information.

[2088] Step 3:

[2089] The server recognizes the user's emotional state. The user's voice data and facial image data are used as input. An emotion engine is used to analyze tone and speed from the voice data and facial expressions from the facial image data. This determines the user's emotional state. The output is the user's current emotional state.

[2090] Step 4:

[2091] The server generates the work schedule. User preferences, weather information, and emotional information are used as input. This data is integrated and an AI model is used to calculate the optimal work schedule. Specifically, each data point is evaluated to select the most efficient and suitable task for the user. The output is the generated work schedule.

[2092] Step 5:

[2093] The server notifies the user of the generated work schedule. Work schedule data is given as input and sent to the terminal. The data is then converted into a notification format and sent to the user's smartphone or tablet. The output is a schedule notification on the user's terminal.

[2094] Step 6:

[2095] The user provides feedback on the work schedule. The input is the proposed schedule and the user's feedback. The terminal sends the user's opinions and change requests to the server. The data is processed by organizing and analyzing the feedback content. The output is user feedback data.

[2096] Step 7:

[2097] The server modifies the work schedule based on user feedback. The feedback data is used as input. The AI ​​model is then used again to update the schedule to reflect the feedback. The data is then processed to regenerate the schedule. The output is the modified work schedule.

[2098] Step 8:

[2099] The server finalizes the revised work schedule and allocates the associated tasks. The revised schedule data is used as input. The final schedule is finalized and each task is allocated to the appropriate worker. Data processing involves confirming and finalizing the task allocation. The output is an execution list of the allocated tasks.

[2100] 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.

[2101] 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.

[2102] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2103] 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.

[2104] 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.

[2105] 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.

[2106] 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).

[2107] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2108] 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."

[2109] 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.

[2110] 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).

[2111] 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.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] 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.

[2117] 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.

[2118] 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.

[2119] 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.

[2120] 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.

[2121] The following is further disclosed regarding the above embodiment.

[2122] (Claim 1)

[2123] A means for obtaining user information;

[2124] a means for obtaining weather information;

[2125] means for generating a travel plan based on user preferences and weather information;

[2126] means for notifying the user of the generated travel plan;

[2127] a means of modifying the travel plan based on user feedback;

[2128] a means to finalize revised travel plans and make related reservations;

[2129] A system including:

[2130] (Claim 2)

[2131] 10. The system according to claim 1, further comprising means for selecting tourist spots and restaurants and calculating an efficient route.

[2132] (Claim 3)

[2133] 10. The system of claim 1, further comprising means for suggesting an optimal means of transportation from the user's current location to the destination.

[2134] "Example 1"

[2135] (Claim 1)

[2136] A means for obtaining user information;

[2137] a means for acquiring health status data;

[2138] a means for obtaining weather information;

[2139] means for generating a travel plan based on the user's preferences, health status, and weather information;

[2140] means for notifying a user device of the generated travel plan;

[2141] a means of modifying the travel plan based on user feedback;

[2142] a means to finalize revised travel plans and make related reservations;

[2143] A system including:

[2144] (Claim 2)

[2145] A way to select tourist spots and restaurants and calculate efficient routes,

[2146] A means of generating a schedule detailing the order of visits, means of transportation, and duration of stay at each location;

[2147] A way to incorporate user feedback into the final itinerary;

[2148] 10. The system of claim 1, further comprising means for expediting reservations.

[2149] (Claim 3)

[2150] A means of suggesting the best means of transportation from the user's current location to their destination,

[2151] 2. The system according to claim 1, further comprising means for automatically reserving tickets to tourist attractions and accommodations.

[2152] "Application Example 1"

[2153] (Claim 1)

[2154] A means for obtaining user information;

[2155] a means for obtaining weather information;

[2156] means for generating a food delivery plan based on user preferences and weather information;

[2157] a means for notifying the user of the generated food delivery plan;

[2158] A means to modify food delivery plans based on user feedback; and

[2159] the means to finalize the revised food delivery plan and place related orders;

[2160] A system including:

[2161] (Claim 2)

[2162] The system of claim 1, further comprising means for searching menu information of affiliated restaurants and delivery services and selecting a dish that best suits the user's preferences and weather conditions.

[2163] ...

Claims

1. A means for obtaining user information; a means for obtaining weather information; means for generating a travel plan based on user preferences and weather information; means for notifying the user of the generated travel plan; a means of modifying the travel plan based on user feedback; a means to finalize revised travel plans and make related reservations; A system including:

2. The system according to claim 1 , further comprising means for selecting tourist spots and restaurants and calculating an efficient route.

3. The system of claim 1 further comprising means for suggesting an optimal means of transportation from the user's current location to the destination.

Images