System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving task information of a remote operation input by a user; means for tokenizing the received task information and storing the tokenized task information in a database; means for managing a task progress status based on the stored task information; means for receiving travel plan condition information from the user; means for generating a travel plan via an external generative AI model based on the received travel condition information; and means for presenting the generated travel plan to the user.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] With the advancement of modern work style reforms, flexible working styles such as remote work and digital nomadism are becoming more common. However, remote work presents challenges such as difficulty in task management and scheduling, increased stress, and the complexity of simultaneously planning travel. To address these challenges, there is a growing need for a system that can centrally manage efficient task management and travel planning. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving remote work task information entered by a user, a means for tokenizing the received task information and saving it in a database, a means for managing task progress based on the saved task information, a means for receiving travel plan condition information from a user, a means for generating a travel plan via an external generative AI model based on the received travel condition information, and a means for presenting the generated travel plan to the user. This system allows users to efficiently manage remote work and plan travel plans in a unified manner, providing a mechanism for improving work-life balance.

[0006] "User" refers to an individual or corporation that uses the system to manage remote work tasks or plan trips.

[0007] "Input remote work task information" refers to information such as the content, priority, and deadline of tasks related to remote work that the user provides to the system.

[0008] The "means for receiving task information" refers to a function or device for receiving task information input by a user within the system.

[0009] "Tokenization" refers to a technical method of converting data from one format to another for secure storage and management.

[0010] "Database" refers to a system or software that stores information in an organized manner and allows it to be accessed, managed, and updated as needed.

[0011] "Means for managing task progress" refers to a function or device that tracks the status of a task based on stored task information and manages the status, including whether it is complete or incomplete.

[0012] "Travel planning condition information" refers to condition information that a user provides to the system when planning a trip, such as travel destination, budget, period, and purpose.

[0013] "Generative AI model" refers to an artificial intelligence model that automatically generates travel plans based on information provided by the user.

[0014] "Means for generating travel plans" refers to functions and devices for creating travel plans using a generative AI model based on the user's travel condition information.

[0015] The "presentation means" refers to a function or device for visually displaying the generated travel plan to the user.

[0016] "Centralized management" refers to efficiently managing multiple tasks and plans on a single platform.

[0017] "Work-life balance" refers to a state in which one's work and personal life are balanced and one is able to enrich both. [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] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[0040] Components:

[0041] 1. A means of receiving task information for a user's remote work

[0042] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[0043] Server: Receives task information sent from the device.

[0044] 2. A way to tokenize task information and store it in a database

[0045] Server: Tokenizes received task information and stores it securely in a database.

[0046] 3. A way to manage task progress based on saved task information

[0047] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[0048] Terminal: Provides the user with a visual indication of task progress.

[0049] 4. Means for receiving travel planning condition information from a user

[0050] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[0051] Server: Receives travel condition information sent from the terminal.

[0052] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0053] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0054] 6. Means of presenting the generated travel plan to the user

[0055] Server: Retrieves the generated travel plan and sends it to the device.

[0056] Terminal: Visually displays the generated itinerary to the user.

[0057] Specific operation explanation:

[0058] User task management

[0059] 1. User enters a task:

[0060] The user accesses the task management interface, enters detailed information about the task, and submits it.

[0061] 2. The device sends task information to the server:

[0062] The terminal transmits the input task information to the server.

[0063] 3. The server receives the task information and tokenizes it:

[0064] The server tokenizes the received task information and stores it securely in a database.

[0065] 4. The server manages the task progress:

[0066] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[0067] 5. The device will display the task progress:

[0068] Users can visually check task progress on a dashboard.

[0069] User travel planning

[0070] 1. User enters travel requirements:

[0071] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[0072] 2. The device sends travel condition information to the server:

[0073] The terminal transmits the input travel condition information to the server.

[0074] 3. The server receives the travel condition information and provides it to the AI ​​model:

[0075] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[0076] 4. The server retrieves the generated itinerary:

[0077] The server retrieves the travel plan generated from the AI ​​model and sends it to the device.

[0078] 5. The device displays your travel plan:

[0079] Users can visually check the generated travel plan on a dashboard.

[0080] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[0081] The processing flow will be explained below.

[0082] Task management process flow

[0083] User task management

[0084] Step 1:

[0085] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[0086] Step 2:

[0087] The terminal sends the entered task information to the server as an AJAX request.

[0088] Step 3:

[0089] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[0090] Step 4:

[0091] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[0092] Step 5:

[0093] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[0094] Step 6:

[0095] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[0096] Step 7:

[0097] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[0098] Step 8:

[0099] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[0100] Travel planning process flow

[0101] User travel planning

[0102] Step 1:

[0103] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[0104] Step 2:

[0105] The terminal sends the entered travel condition information to the server as an AJAX request.

[0106] Step 3:

[0107] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[0108] Step 4:

[0109] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[0110] Step 5:

[0111] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[0112] Step 6:

[0113] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0114] Step 7:

[0115] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[0116] Step 8:

[0117] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[0118] In this way, the roles of the user, terminal, and server work together to manage tasks and plan trips, thereby improving the user's work-life balance.

[0119] Example 1

[0120] 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."

[0121] In today's remote work environment, effective task management and trip planning are essential to maximize work efficiency. However, there are few platforms that centrally manage these functions, forcing users to use multiple tools. As a result, it is difficult to integrate task management and trip planning, making it difficult to achieve work-life balance.

[0122] 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.

[0123] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, and means for integrating and displaying the task progress and travel plan in real time on a user dashboard. This allows users to centrally manage remote work tasks and travel planning, enabling an efficient work-life balance.

[0124] "Remote work task information" is information about the specific work that a user needs to accomplish when working remotely and the progress of that work.

[0125] "Tokenization" is the process of breaking down input information into smaller units and converting each unit into a separately identifiable form.

[0126] A "database" is a system for safely and efficiently storing information so that it can be searched and retrieved later.

[0127] "Task progress status" is information indicating the progress and completion status of tasks that a user performs while working remotely.

[0128] "Planning condition information" is information relating to conditions such as travel destination, budget, number of days, etc. that a user specifies when planning a trip.

[0129] A "generative AI model" is an artificial intelligence model that has the ability to generate new information or plans based on given input.

[0130] A "travel plan" is a plan that includes details of a trip, such as a specific schedule, places to visit, and accommodation.

[0131] A "dashboard" is an interface that displays information in a format that allows users to easily view it visually.

[0132] "Real-time" means that information is reflected immediately and there is almost no time delay in updating.

[0133] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[0134] Components:

[0135] 1. A means for receiving task information for a user's remote work:

[0136] Terminal: The user accesses the task management interface and enters the task title, description, priority, deadline, etc. For example, the user enters information such as "Create presentation materials," "Complete by the deadline," "High," and "2023-04-30."

[0137] 2. How to tokenize task information and store it in the database:

[0138] Server: Receives task information sent from the device, tokenizes it, and stores it in a database such as MongoDB.

[0139] 3. How to manage task progress based on saved task information:

[0140] Server: Tracks and manages the progress status (not started, in progress, completed, etc.) based on task information, and monitors the user's progress.

[0141] 4. How to display task progress based on saved task information:

[0142] On the device: Users can visually check task progress on a dashboard, which is visualized in graphs and lists.

[0143] 5. Means for receiving travel planning requirements information from a user:

[0144] User: Accesses a trip planning interface and enters travel destination, budget, number of days, etc. For example, the user enters "Tokyo as destination," "100,000 yen as budget," and "3 days as number of days."

[0145] 6. A means for generating a travel plan via an external generative AI model based on the received travel condition information:

[0146] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan. The generative AI model used is OpenAI's GPT-3. An example of a prompt is "Please create a three-day travel plan to Tokyo. The budget is 100,000 yen."

[0147] 7. Means for presenting the generated travel plan to the user:

[0148] Server: Takes the generated itinerary, formats it appropriately, and sends it to the device.

[0149] Terminal: The user visually checks the generated itinerary on a dashboard.

[0150] 8. Integrated display of task progress and travel plans:

[0151] Terminal: Task progress and travel plans retrieved from the server are displayed in a unified manner, allowing users to manage their remote work progress and travel plans simultaneously.

[0152] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[0153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0154] System program processing flow

[0155] Step 1:

[0156] User enters task

[0157] User: Accesses the task management interface and enters the task title, description, priority, due date, etc.

[0158] Input: "Create presentation materials" "Complete by deadline" "Expensive" "2023-04-30"

[0159] What happens: A user fills out a form and clicks the "Submit" button. The data is converted from the form into JSON format data.

[0160] Step 2:

[0161] The device sends task information to the server

[0162] Terminal: Sends the entered task information to the server.

[0163] Input: Task information entered by the user (JSON format)

[0164] Output: HTTP POST request to the server

[0165] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[0166] Step 3:

[0167] The server receives and tokenizes the task information.

[0168] Server: Tokenizes the received task information and stores it in the database.

[0169] Input: Task information sent from the device (JSON format)

[0170] Output: Tokenized task information (database format)

[0171] Specific operation: Parse the JSON data, tokenize each element of the task (break it down into keywords and tags), and store it in a database such as MongoDB.

[0172] Step 4:

[0173] The server manages the task progress

[0174] Server: Manages the progress status of tasks (not started, in progress, completed, etc.) based on the saved task information.

[0175] Input: Tokenized task information stored in a database

[0176] Output: Updated task progress status

[0177] Specific behavior: Periodically check the status of each task and update the status according to user actions.

[0178] Step 5:

[0179] The device displays task progress

[0180] Terminal: Visually display task progress retrieved from the server on a dashboard.

[0181] Input: Task progress status obtained from the server

[0182] Output: Visual display of task progress

[0183] What it does: View task progress on a dashboard in graph, list, or calendar format.

[0184] Step 6:

[0185] User enters travel conditions

[0186] User: Accesses a trip planning interface and enters travel destination, budget, number of days, and other travel criteria.

[0187] Input: "Destination: Tokyo" "Budget: 100,000 yen" "Number of days: 3 days"

[0188] Specific Actions: The user fills out the form with the necessary travel requirements and clicks the "Submit" button again.

[0189] Step 7:

[0190] The device sends travel condition information to the server

[0191] Terminal: Sends the entered travel conditions information to the server.

[0192] Input: Travel conditions information entered by the user (JSON format)

[0193] Output: HTTP POST request to the server

[0194] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[0195] Step 8:

[0196] The server receives travel condition information and provides it to the AI ​​model

[0197] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0198] Input: Travel conditions information sent from the device (JSON format)

[0199] Output: A trip plan from the generative AI model

[0200] Specific behavior: Generate prompts for the AI ​​model and receive travel plans via API. Example: "Please create a three-day travel plan for Tokyo with a budget of 100,000 yen."

[0201] Step 9:

[0202] The server retrieves the generated itinerary

[0203] Server: Retrieves the itinerary generated by the AI ​​model, formats it appropriately, and sends it to the device.

[0204] Input: Travel itinerary from a generative AI model

[0205] Output: A formatted itinerary

[0206] Specific operation: Organize the obtained travel plans into a format that is easy for the user to understand.

[0207] Step 10:

[0208] The device displays the travel plan

[0209] Terminal: Visually displays the generated travel plan received from the server to the user.

[0210] Input: Formatted itinerary

[0211] Output: A visual representation of the itinerary

[0212] Specific operation: Display travel schedule, destination details, budget allocation, etc. on a dashboard.

[0213] integrated management

[0214] By following these steps, users can manage remote work tasks and travel planning in a unified manner, enabling them to efficiently achieve a work-life balance.

[0215] (Application example 1)

[0216] 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."

[0217] With the spread of remote work, there is a demand for tools to improve remote work efficiency, but conventional travel planning tools have difficulty providing plans that are linked to remote work schedules. For this reason, there is a need for a system that provides information on cafes and coworking spaces that users can use while working remotely, and can also centrally manage on-site remote work and travel planning.

[0218] 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.

[0219] In this invention, the server includes means for receiving remote work task information entered by a user via a task management interface, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel planning condition information from the user via a travel planning interface, means for generating a travel plan via a generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for providing store information available during remote work, and means for obtaining store reservations and usage status using an external service based on the user's current location information. This allows users to centrally manage their remote work and travel plans, further improving the efficiency of remote work.

[0220] The "task management interface" is a user interface that allows a user to input and send task information for remote work.

[0221] "Task information" is data about remote work, including detailed information such as the task title, description, priority, and deadline.

[0222] "Tokenization" is the process of converting received information into a format that can be securely processed and stored, for example by encrypting or encoding it.

[0223] A "database" is a digital warehouse for safely storing and managing users' task information, progress, and so on.

[0224] "Task progress" is status data that tracks and manages the status of a task, such as not started, in progress, or completed, based on saved task information.

[0225] The "interface for travel planning" is a user interface that allows a user to input and transmit travel planning condition information.

[0226] "Travel planning condition information" is condition data necessary when planning a trip, such as the travel destination, budget, number of days, etc.

[0227] A "generative AI model" is an artificial intelligence model that generates optimal travel plans based on travel planning condition information received from the user.

[0228] A "travel plan" is a specific plan that includes the travel destination, itinerary, places to visit, accommodation, etc.

[0229] "Store information available for use while working remotely" refers to information about facilities that can be used while working remotely, such as cafes and coworking spaces.

[0230] "User's current location information" means current geographic location data obtained from a user's smartphone or other device.

[0231] "External Services" are external software services, such as APIs and databases provided by third parties, that are used to extend the functionality of an application.

[0232] "Obtaining store reservations and usage status" refers to the process of using the provided API or database to obtain information such as the reservation status and current congestion level of a specific cafe or coworking space.

[0233] The system "Remote Cafe & Trip" of the present invention provides functions for improving the efficiency of users' remote work and centrally managing travel planning. Each component of the system and its specific operation are described below.

[0234] Components:

[0235] Task management interface

[0236] The user inputs remote task information through a task management interface. The device then sends the received task information to the server. The task information entered by the user includes details such as the task title, description, priority, and deadline.

[0237] Tokenized data storage

[0238] The server tokenizes the received task information and stores it securely in a database. The tokenization process ensures data security.

[0239] Task progress management

[0240] The server manages the progress of tasks based on the saved task information. It tracks the progress status (not started, in progress, completed, etc.) and displays it on the user's device. The user can visually check the progress of the task.

[0241] Trip planning interface

[0242] The user uses a trip planning interface to input conditions such as the travel destination, budget, and number of days, and sends the input to the server.

[0243] Travel plan generation using generative AI models

[0244] The server sends prompts to the generative AI model based on the received travel condition information to generate a travel plan. This generative AI model uses OpenAI's API.

[0245] Presenting your travel plan

[0246] The server acquires the generated itinerary and sends it to the user's terminal, where the user can visually display the generated itinerary.

[0247] Providing store information that can be used while working remotely

[0248] The server uses external services (such as Google Maps API) based on the user's current location information to obtain information about nearby cafes and coworking spaces, allowing users to easily find stores they can use while working remotely.

[0249] Obtaining store reservations and usage status

[0250] The server uses external services to obtain reservation and usage status for specific cafes and coworking spaces and provides this information to users.

[0251] Examples:

[0252] Task Management

[0253] For example, when a user enters a task to create a monthly report, they enter the following information into the interface: "Create monthly report," "Create monthly sales performance report," "High," "2023-10-31." The device sends this to the server, where it is tokenized and stored in the database. The task progress is then displayed on the dashboard.

[0254] Travel plan generation

[0255] If a user inputs travel criteria such as "Kyoto," "budget of 100,000 yen," and "3 days," the server sends the following prompt to the generative AI model:

[0256] "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[0257] The answer from the AI ​​model is

[0258] Day 1: After arriving at Kyoto Station, visit Kiyomizu-dera Temple and Gion. Visit Fushimi Inari Taisha Shrine, and have dinner around Kyoto Station in the evening.

[0259] Day 2: Visit Kinkakuji Temple and Ryoanji Temple. Visit Arashiyama in the evening and stroll through the bamboo forest. Dinner in Arashiyama.

[0260] Day 3: Visit the Kyoto National Museum. In the afternoon, stroll through Kyoto Gyoen National Garden and have lunch along the Kamo River. In the evening, return to Kyoto Station for the return journey.

[0261] The plan is generated and presented to the user.

[0262] This system allows users to centrally manage their remote work and travel plans, improving the efficiency of remote work.

[0263] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0264] Step 1:

[0265] The user enters remote work task information through a task management interface. The task information entered by the user includes the task title, description, priority, and deadline. For example, input data such as "Create monthly report," "Create monthly sales performance report," "High," and "2023-10-31" is sent.

[0266] Step 2:

[0267] The device sends the task information entered by the user to the server. At this time, the entered task information is configured as a data packet and passed to the server via the network. The input data is JSON format data of the task information.

[0268] Step 3:

[0269] The server tokenizes the received task information. Tokenization is the process of encrypting or encoding input data to make it safe. For example, the input data "Create monthly report" is converted to "token1234."

[0270] Step 4:

[0271] The server saves the tokenized task information to the database. At this time, the tokenized information is inserted into the appropriate field in the database and the index information is updated. For example, "token1234" is saved in the task information table in the database.

[0272] Step 5:

[0273] The server manages the progress of tasks based on the stored task information and tracks their progress status. The server uses an algorithm to manage the task state (not started, in progress, completed) and updates the progress in conjunction with the database. For example, "in progress" may be updated to "completed."

[0274] Step 6:

[0275] The user accesses the trip planning interface, inputs travel information (destination, budget, number of days), and sends it to the server via the terminal. The input data sent is "Kyoto," "budget of 100,000 yen," and "3 days."

[0276] Step 7:

[0277] The server sends a prompt to the generative AI model based on the received travel condition information. This prompt is composed of a natural language sentence that includes the travel condition information. An example of a prompt sentence is, "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[0278] Step 8:

[0279] The generative AI model takes a prompt as input and generates a travel plan using natural language processing and machine learning algorithms. Based on the input, the AI ​​model suggests suitable travel destinations, sightseeing spots, and itineraries.

[0280] Step 9:

[0281] The server retrieves the generated travel plan and sends it to the terminal to present to the user. The generated travel plan is configured as data and transferred to the terminal via the network. The output data may be in the form of, for example, "Day 1: Kiyomizu-dera Temple, Day 2: Kinkaku-ji Temple."

[0282] Step 10:

[0283] Users can request information about available stores through their devices while working remotely. The user's current location information is acquired and sent to the server.

[0284] Step 11:

[0285] The server uses an external service (e.g., Google Maps API) to obtain information about nearby cafes and coworking spaces based on the user's current location. The server sends an API request and stores the store information obtained from the external service in a database.

[0286] Step 12:

[0287] The server presents store information to the user's device based on the acquired store information. By also displaying the store's reservation status and usage status, the user can select an appropriate store while working remotely. The output data will be information such as "Nearby Cafe A, reservation status is available."

[0288] 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.

[0289] The system of the present invention centrally manages the efficiency of users' remote work and travel planning, and also provides the function of recognizing and dynamically responding to users' emotions. Each component of the system and its specific operation are described below.

[0290] Components:

[0291] 1. A means of receiving task information for a user's remote work

[0292] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[0293] Server: Receives task information sent from the device.

[0294] 2. A way to tokenize task information and store it in a database

[0295] Server: Tokenizes received task information and stores it securely in a database.

[0296] 3. A way to manage task progress based on saved task information

[0297] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[0298] Terminal: Provides the user with a visual indication of task progress.

[0299] 4. Means for receiving travel planning condition information from a user

[0300] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[0301] Server: Receives travel condition information sent from the terminal.

[0302] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0303] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0304] 6. Means of presenting the generated travel plan to the user

[0305] Server: Retrieves the generated travel plan and sends it to the device.

[0306] Terminal: Visually displays the generated itinerary to the user.

[0307] 7. Emotion engine that recognizes user emotions

[0308] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine.

[0309] Server: Receives and manages emotion data recognized by the emotion engine.

[0310] 8. A method for automatically adjusting task and travel plan content based on recognized emotional information

[0311] Server: Dynamically adjusts task priorities and travel plan suggestions based on recognized emotion data.

[0312] 9. A means of analyzing emotional information and providing advice

[0313] Server: Analyzes emotional data and generates advice aimed at reducing stress and improving motivation.

[0314] Terminal: Notifies the user of advice from the server.

[0315] Specific operation explanation:

[0316] User task management

[0317] 1. User enters a task:

[0318] The user accesses the task management interface, enters detailed information about the task, and submits it.

[0319] 2. The device sends task information to the server:

[0320] The terminal transmits the input task information to the server.

[0321] 3. The server receives the task information and tokenizes it:

[0322] The server tokenizes the received task information and stores it securely in a database.

[0323] 4. The server manages the task progress:

[0324] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[0325] 5. The device will display the task progress:

[0326] Users can visually check task progress on a dashboard.

[0327] User travel planning

[0328] 1. User enters travel requirements:

[0329] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[0330] 2. The device sends travel condition information to the server:

[0331] The terminal transmits the input travel condition information to the server.

[0332] 3. The server receives the travel condition information and provides it to the AI ​​model:

[0333] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[0334] 4. The server retrieves the generated itinerary:

[0335] The server retrieves the itinerary generated by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0336] 5. The device displays your travel plan:

[0337] Users can visually check the generated travel plan on a dashboard.

[0338] User Emotion Recognition and Dynamic Adjustment

[0339] 1. Recognize user emotions:

[0340] The emotion engine analyzes the user's facial expressions and voice in real time to identify the user's current emotion (e.g., stress, happiness, anxiety, etc.).

[0341] 2. The device sends emotional information to the server:

[0342] The device transmits the recognized emotion data to the server.

[0343] 3. The server manages emotional information and adjusts tasks and travel plans:

[0344] The server dynamically adjusts task priorities and travel plan suggestions based on emotion data. For example, if a user is feeling stressed, it may lower task priorities or suggest additional breaks to reduce task load.

[0345] 4. Analyze sentiment information and generate advice:

[0346] The server analyzes the emotional data and generates advice aimed at reducing the user's stress and increasing their motivation.

[0347] 5. The device notifies the user of the advice:

[0348] The device notifies the user of the generated advice, such as "Take a break" or "Take a deep breath and relax."

[0349] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0350] The processing flow will be explained below.

[0351] Task management process flow

[0352] User task management

[0353] Step 1:

[0354] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[0355] Step 2:

[0356] The terminal sends the entered task information to the server as an AJAX request.

[0357] Step 3:

[0358] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[0359] Step 4:

[0360] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[0361] Step 5:

[0362] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[0363] Step 6:

[0364] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[0365] Step 7:

[0366] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[0367] Step 8:

[0368] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[0369] Travel planning process flow

[0370] User travel planning

[0371] Step 1:

[0372] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[0373] Step 2:

[0374] The terminal sends the entered travel condition information to the server as an AJAX request.

[0375] Step 3:

[0376] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[0377] Step 4:

[0378] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[0379] Step 5:

[0380] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[0381] Step 6:

[0382] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0383] Step 7:

[0384] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[0385] Step 8:

[0386] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[0387] Emotion recognition and dynamic adjustment processing flow

[0388] User Emotion Recognition and Dynamic Adjustment

[0389] Step 1:

[0390] While the user is using the system, the emotion engine analyzes the user's facial expressions and voice in real time to identify their current emotion (e.g., stress, happiness, anxiety, etc.).

[0391] Step 2:

[0392] The terminal transmits the emotion information recognized by the emotion engine to the server.

[0393] Step 3:

[0394] The server manages the received emotion information.

[0395] Step 4:

[0396] The server dynamically adjusts remote work task priorities and travel plan suggestions based on the recognized emotional information. For example, if the user is feeling stressed, it may lower the priority of a task to reduce the burden or suggest additional breaks.

[0397] Step 5:

[0398] The server stores the adjusted task information and travel plans in a database.

[0399] Step 6:

[0400] The terminal retrieves the adjustment information from the server and visually displays it to the user.

[0401] Step 7:

[0402] The server analyzes the emotional information and generates advice aimed at reducing the user's stress and improving their motivation.

[0403] Step 8:

[0404] The device notifies the user of advice generated by the server, such as "Take a break" or "Take a deep breath and relax."

[0405] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0406] Example 2

[0407] 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."

[0408] Conventional remote work and travel planning management systems have difficulty providing distributed functions in an integrated manner. Furthermore, they lack the ability to recognize and dynamically respond to users' emotions in real time, which hinders the improvement of users' work-life balance. This leaves users without a means to efficiently manage tasks and create optimal travel plans.

[0409] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving remote work task information input by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for recognizing the user's emotions, and means for dynamically adjusting the content of the task or travel plan based on the recognized emotion information. This enables efficient, unified management of the user's remote work and travel planning, and also enables appropriate responses according to the user's emotions.

[0410] "Remote work" refers to work done over a communications network such as the internet.

[0411] "Task information" is detailed information about a task item that a user must perform, and includes a title, description, priority, deadline, and the like.

[0412] "Tokenization" refers to the process of analyzing information and breaking it down into smaller units (tokens) based on meaning and structure.

[0413] "Database" means an electronic system for efficiently and securely storing and managing digital data.

[0414] "Task progress management" refers to the process of monitoring and updating the progress of a task (not started, in progress, completed, etc.) based on stored task information.

[0415] "Travel planning" refers to creating a plan based on conditions such as the travel destination, budget, and number of days.

[0416] A "generative AI model" refers to a computer program that uses artificial intelligence technology to provide generated content or answers based on input conditions.

[0417] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state (e.g., stress, happiness, anxiety, etc.).

[0418] "Dynamic adjustment" refers to the process of changing content and settings in real time based on the situation.

[0419] A "dashboard" refers to an interface for visually and comprehensively displaying various information.

[0420] The system according to the present invention provides a unified management system for improving the efficiency of remote work and travel planning for users, and also provides a function for recognizing and dynamically responding to user emotions. The system of the present invention includes the following components.

[0421] 1. A means of receiving task information for a user's remote work

[0422] Terminal: The user accesses a task management interface and enters the task title, description, priority, due date, etc. For example, the user adds a task called "Write a progress report for Project X" and sets the priority to high and the due date to the end of this week.

[0423] Server: Receives task information sent from the device.

[0424] 2. A way to tokenize task information and store it in a database

[0425] Server: Tokenizes the received task information and stores it securely in a database. Specifically, the task information is split into tokens such as "Project X," "Progress Report," "Created," "High," and "This weekend," and stored in a DBMS (e.g., MySQL).

[0426] 3. A way to manage task progress based on saved task information

[0427] Server: Manages task information appropriately and tracks task progress status (not started, in progress, completed, etc.) When a user updates a task, the server updates the corresponding record in the database.

[0428] 4. How the device displays task progress

[0429] On the device: Users can visually see the progress of their tasks on a dashboard, with incomplete tasks displayed in red, in progress in yellow, and completed in green.

[0430] 5. Means for receiving travel planning condition information from a user

[0431] User: Accesses a travel planning interface and inputs travel destination, budget, number of days, etc. For example, a user might set the conditions as "Tokyo," "300,000 yen," and "5 days."

[0432] Server: Receives travel condition information sent from the terminal.

[0433] 6. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0434] Server: Provides the received travel condition information to an external generative AI model and generates a travel plan. Specifically, it sends the following prompt to the generative AI model:

[0435] "Please create a five-day travel plan for Tokyo with a budget of 300,000 yen."

[0436] 7. Means of presenting the generated travel plan to the user

[0437] Server: Retrieves the generated itinerary, formats it as needed, and sends it to the device.

[0438] Device: The user can visually check the generated travel plan on a dashboard, for example, displaying the itinerary and cost list.

[0439] 8. How to Recognize User Emotions

[0440] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine. For example, a facial expression recognition API can be used to determine "stress" or "happiness."

[0441] 9. A means of dynamically adjusting the content of a task or itinerary based on recognized emotional information

[0442] Server: Dynamically adjust task priorities and travel plan suggestions based on recognized emotion data. For example, if the user is feeling stressed, lower the priority or suggest additional breaks to reduce task load.

[0443] These components enable the system of the present invention to comprehensively support users in improving the efficiency of remote work and travel planning, and also to flexibly respond to users' emotions. Users can efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0444] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0445] Processing flow and specific operations

[0446] Task Management

[0447] Step 1:

[0448] The user accesses the task management interface and inputs the task title, description, priority, deadline, etc. The task information is sent to the server as input data. Specifically, the user inputs information such as "Create a progress report for Project X," "High," and "This weekend."

[0449] Step 2:

[0450] The device sends the entered task information to the server's API endpoint via an HTTP POST request. The input is the task information entered by the user, and the output is the status of successful submission to the server.

[0451] Step 3:

[0452] The server receives an HTTP request and tokenizes the task information. Specifically, it splits the task information into tokens such as "Project X," "Progress Report," "Create," "High," and "This Weekend." The input is the received task information, and the output is the tokenized task data.

[0453] Step 4:

[0454] The server stores the tokenized task data in a database (e.g., MySQL). The input is the tokenized task data, and the output is the task information stored in the database.

[0455] Step 5:

[0456] The server manages the task progress and tracks and updates the progress status (not started, in progress, completed, etc.). For example, when a user marks a task as progressed, the server updates the corresponding record in the database. The input is the current task information and the user's actions, and the output is the updated task progress status.

[0457] Step 6:

[0458] The terminal periodically retrieves task progress information from the server and displays it visually on a dashboard. Specifically, tasks that have not been started are displayed in red, tasks in progress in yellow, and completed tasks in green. The input is the progress data retrieved from the server, and the output is the visual display to the user.

[0459] Travel Planning

[0460] Step 1:

[0461] The user accesses the trip planning interface and inputs travel conditions such as destination, budget, and number of days. The travel condition information is sent as input data to the server. Specifically, the user enters the conditions "Tokyo," "300,000 yen," and "5 days."

[0462] Step 2:

[0463] The device sends the entered travel condition information to the server's API endpoint via an HTTP POST request. The input is the travel condition information entered by the user, and the output is the status of successful transmission to the server.

[0464] Step 3:

[0465] The server receives the HTTP request and provides the received travel condition information to an external generative AI model. Specifically, it sends the following prompt to the generative AI model: "Please create a 5-day travel plan for Tokyo. The budget is 300,000 yen." The input is the received travel condition information, and the output is the prompt sent to the generative AI model.

[0466] Step 4:

[0467] The server retrieves the itinerary from the generative AI model and formats it as needed. The input is the generated itinerary, and the output is the formatted itinerary data.

[0468] Step 5:

[0469] The server sends the travel plan data to the terminal. The input is the formatted travel plan data, and the output is the status of successful transmission to the terminal.

[0470] Step 6:

[0471] The terminal visually displays the travel plan on a dashboard, specifically showing the itinerary, cost list, etc. The input is the travel plan data sent from the server, and the output is the visual display to the user.

[0472] Emotion Recognition and Dynamic Regulation

[0473] Step 1:

[0474] The device uses an emotion engine to analyze the user's facial expressions and voice in real time and recognize their emotions. Specifically, it uses a facial expression recognition API to determine "stress" and "happiness." The input is the user's video and audio data, and the output is recognized emotional data.

[0475] Step 2:

[0476] The device sends the recognized emotion data to the server via an HTTP POST request. The input is the recognized emotion data, and the output is the status of successful transmission to the server.

[0477] Step 3:

[0478] The server receives emotional information and dynamically adjusts task priorities and travel plan suggestions based on that information. For example, if the user is feeling stressed, the server lowers task priorities to reduce the task load. The input is the received emotional information, and the output is the adjusted task or travel plan data.

[0479] Step 4:

[0480] The server sends the adjusted task or travel plan data to the terminal, where the input is the adjusted task or travel plan data and the output is a successful transmission status to the terminal.

[0481] Step 5:

[0482] The device generates advice based on the emotion data and notifies the user. For example, it displays advice such as "Take a deep breath" or "We recommend taking a short break." The input is the advice data sent from the server, and the output is a visual display to the user.

[0483] (Application example 2)

[0484] 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."

[0485] While modern factory robots efficiently perform a variety of tasks, their long working hours and complex operations have led to problems with declining operational efficiency and reliability. In particular, the lack of emotion-based maintenance or dynamic task adjustments increases the risk of unexpected malfunctions and operational shutdowns. Furthermore, the lack of a means to comprehensively manage robots' operational efficiency and maintenance plans in real time makes it difficult for managers to respond appropriately. Given these circumstances, there is a growing need for a system that improves the operational efficiency and reliability of factory robots.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0487] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from a user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for receiving robot emotion data using an emotion recognition engine, means for dynamically adjusting the robot's task priority based on the emotion data, and means for presenting the generated travel plan to the user. This enables centralized management of factory robot work efficiency and maintenance plans, and dynamic adjustment of tasks based on emotion data.

[0488] A "user" is an entity that uses this system to input task information and set travel conditions.

[0489] "Remote work task information" refers to detailed task information entered by a user to manage remote work, including the task title, description, priority, deadline, etc.

[0490] "Tokenization" is a method of securely storing received data in a database using methods such as encryption and hashing.

[0491] "Database" means a collection of data that securely stores tokenized task information and makes it accessible as needed.

[0492] "Task progress management" is the process of tracking and updating the progress status of a task based on stored task information.

[0493] "Travel planning condition information" is condition information such as the travel destination, budget, number of days, etc. that the user sets when planning a trip.

[0494] An "external generative AI model" is an artificial intelligence model that receives travel condition information set by the user and generates a travel plan based on that information.

[0495] A "travel plan" is a detailed travel schedule or itinerary created by a generative AI model based on travel planning condition information.

[0496] An "emotion recognition engine" is an engine that analyzes a robot's emotional data (such as vibrations and temperature) in real time and identifies its emotional state.

[0497] "Emotion data" is data that indicates the current emotional state of the robot, obtained by the emotion recognition engine.

[0498] "Dynamic adjustment of task priorities" is a process that automatically changes task priorities based on acquired emotional data to optimize the robot's workload.

[0499] A "maintenance plan" is a plan to create a maintenance schedule based on the robot's emotional data and maintain the robot's performance.

[0500] "Integrated display" means that users can see the progress of remote work tasks and the status of travel plans all in one dashboard.

[0501] This invention relates to a system that manages the work efficiency and maintenance plans of factory robots in an integrated manner and dynamically adjusts task priorities based on emotion data. The specific configuration and operation of the system are described below.

[0502] The system includes the following major hardware and software components:

[0503] Hardware

[0504] Factory robots: Robots equipped with emotion recognition sensors and controlled remotely.

[0505] Server: A central server that manages tasks, generates travel plans, and manages emotion data.

[0506] software

[0507] Task Management API: An API for receiving task information, tokenizing it, and storing it in a database.

[0508] Emotion recognition engine: An engine that analyzes the robot's emotional data (e.g., vibration and temperature) and identifies its emotional state.

[0509] Generative AI model: An AI model for generating optimal travel plans based on received travel condition information.

[0510] System Operation

[0511] 1. User task management

[0512] Users access the task management interface remotely and enter detailed task information (title, description, priority, deadline, etc.). The entered task information is sent to the server via the terminal. The server tokenizes the received task information, stores it in a database, and manages the task progress.

[0513] 2. Generate a travel plan

[0514] The user accesses a trip planning interface and inputs travel conditions (destination, budget, number of days, etc.). The input information is sent to the server via the device, and the server provides this information to an external generative AI model to generate a travel plan. The generated travel plan is then presented to the user via the server.

[0515] 3. Acquiring Emotional Data and Dynamic Task Adjustment

[0516] The robot's emotion recognition sensors monitor the robot's condition (e.g., vibration and temperature) in real time, and the emotion recognition engine analyzes this to generate emotion data. The generated emotion data is sent to the server, and task priorities are automatically adjusted. For example, if the robot is feeling "stressed," the task priority will be changed to "urgent" and a maintenance notification will be issued immediately.

[0517] Specific examples

[0518] For example, consider the case where a manager assigns a task called "Routine Maintenance" to a factory robot. This task information is sent to the server via an input terminal, tokenized, and stored in a database. Meanwhile, if the robot's emotion recognition sensor detects an emotional state of "stress," the server will use this emotional data to adjust the task priority to "urgent" and immediately send a maintenance notification to the manager.

[0519] Prompt Sentence Examples

[0520] An example of a prompt to be input to the generative AI model is as follows:

[0521] Robot ID: 1

[0522] Emotional state: Stress

[0523] Recommended action: Prompt maintenance

[0524] Task Priority: Urgent

[0525] This prompt is then fed into a generative AI model and used to generate an optimal plan of action or set of actions.

[0526] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0527] Step 1:

[0528] The user inputs task information for remote work. The terminal receives the input information such as the task title, description, priority, and deadline, and sends it to the server. Input: Task information (title, description, priority, deadline). Output: Task information sent to the server.

[0529] Step 2:

[0530] The server receives task information and tokenizes each task. The tokenized task information is saved in a database. Input: Task information received from the device. Output: Tokenized task information saved in a database.

[0531] Step 3:

[0532] The server manages task progress based on task information stored in the database. It tracks task progress status (e.g. not started, in progress, completed) and updates it as needed. Input: Task information stored in the database. Output: Updated task progress status.

[0533] Step 4:

[0534] The user inputs travel plan condition information. The terminal receives condition information such as travel destination, budget, number of days, etc. and sends it to the server. Input: Travel plan condition information (travel destination, budget, number of days). Output: Travel condition information sent to the server.

[0535] Step 5:

[0536] The server receives travel condition information and provides it to an external generative AI model to generate a travel plan. The generated travel plan is organized and saved in a database. Input: Travel condition information provided to the external generative AI model. Output: Generated travel plan.

[0537] Step 6:

[0538] The generated itinerary is sent from the server to the terminal and presented to the user. Input: Generated itinerary. Output: Itinerary visually displayed on the terminal.

[0539] Step 7:

[0540] The robot's emotion recognition sensor acquires the robot's emotion data in real time, and the emotion recognition engine analyzes this emotion data. Input: Emotion data acquired from the robot. Output: Analyzed emotional state.

[0541] Step 8:

[0542] The emotion recognition engine sends the analyzed emotion data to the server, which then dynamically adjusts task priorities based on the emotion data. Input: Analyzed emotion data. Output: Adjusted task priorities.

[0543] Step 9:

[0544] The server analyzes the emotion data and sends appropriate maintenance notifications to the user or administrator. For example, if the robot's emotional state is "stressed," it issues a notification such as "Perform prompt maintenance." Input: Analyzed emotion data. Output: Maintenance notification sent to the user or administrator.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] [Second embodiment]

[0549] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0550] 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.

[0551] 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).

[0552] 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.

[0553] 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.

[0554] 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).

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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."

[0561] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[0562] Components:

[0563] 1. A means of receiving task information for a user's remote work

[0564] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[0565] Server: Receives task information sent from the device.

[0566] 2. A way to tokenize task information and store it in a database

[0567] Server: Tokenizes received task information and stores it securely in a database.

[0568] 3. A way to manage task progress based on saved task information

[0569] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[0570] Terminal: Provides the user with a visual indication of task progress.

[0571] 4. Means for receiving travel planning condition information from a user

[0572] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[0573] Server: Receives travel condition information sent from the terminal.

[0574] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0575] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0576] 6. Means of presenting the generated travel plan to the user

[0577] Server: Retrieves the generated travel plan and sends it to the device.

[0578] Terminal: Visually displays the generated itinerary to the user.

[0579] Specific operation explanation:

[0580] User task management

[0581] 1. User enters a task:

[0582] The user accesses the task management interface, enters detailed information about the task, and submits it.

[0583] 2. The device sends task information to the server:

[0584] The terminal transmits the input task information to the server.

[0585] 3. The server receives the task information and tokenizes it:

[0586] The server tokenizes the received task information and stores it securely in a database.

[0587] 4. The server manages the task progress:

[0588] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[0589] 5. The device will display the task progress:

[0590] Users can visually check task progress on a dashboard.

[0591] User travel planning

[0592] 1. User enters travel requirements:

[0593] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[0594] 2. The device sends travel condition information to the server:

[0595] The terminal transmits the input travel condition information to the server.

[0596] 3. The server receives the travel condition information and provides it to the AI ​​model:

[0597] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[0598] 4. The server retrieves the generated itinerary:

[0599] The server retrieves the travel plan generated from the AI ​​model and sends it to the device.

[0600] 5. The device displays your travel plan:

[0601] Users can visually check the generated travel plan on a dashboard.

[0602] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[0603] The processing flow will be explained below.

[0604] Task management process flow

[0605] User task management

[0606] Step 1:

[0607] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[0608] Step 2:

[0609] The terminal sends the entered task information to the server as an AJAX request.

[0610] Step 3:

[0611] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[0612] Step 4:

[0613] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[0614] Step 5:

[0615] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[0616] Step 6:

[0617] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[0618] Step 7:

[0619] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[0620] Step 8:

[0621] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[0622] Trip planning process flow

[0623] User travel planning

[0624] Step 1:

[0625] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[0626] Step 2:

[0627] The terminal sends the entered travel condition information to the server as an AJAX request.

[0628] Step 3:

[0629] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[0630] Step 4:

[0631] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[0632] Step 5:

[0633] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[0634] Step 6:

[0635] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0636] Step 7:

[0637] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[0638] Step 8:

[0639] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[0640] In this way, the roles of the user, terminal, and server work together to manage tasks and plan trips, thereby improving the user's work-life balance.

[0641] Example 1

[0642] 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."

[0643] In today's remote work environment, effective task management and trip planning are essential to maximize work efficiency. However, there are few platforms that centrally manage these functions, forcing users to use multiple tools. As a result, it is difficult to integrate task management and trip planning, making it difficult to achieve work-life balance.

[0644] 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.

[0645] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, and means for integrating and displaying the task progress and travel plan in real time on a user dashboard. This allows users to centrally manage remote work tasks and travel planning, enabling an efficient work-life balance.

[0646] "Remote work task information" is information about the specific work that a user needs to accomplish when working remotely and the progress of that work.

[0647] "Tokenization" is the process of breaking down input information into smaller units and converting each unit into a separately identifiable form.

[0648] A "database" is a system for safely and efficiently storing information so that it can be searched and retrieved later.

[0649] "Task progress status" is information indicating the progress and completion status of tasks that a user performs while working remotely.

[0650] "Planning condition information" is information relating to conditions such as travel destination, budget, number of days, etc. that a user specifies when planning a trip.

[0651] A "generative AI model" is an artificial intelligence model that has the ability to generate new information or plans based on given input.

[0652] A "travel plan" is a plan that includes details of a trip, such as a specific schedule, places to visit, and accommodation.

[0653] A "dashboard" is an interface that displays information in a format that allows users to easily view it visually.

[0654] "Real-time" means that information is reflected immediately and there is almost no time delay in updating.

[0655] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[0656] Components:

[0657] 1. A means for receiving task information for a user's remote work:

[0658] Terminal: The user accesses the task management interface and enters the task title, description, priority, deadline, etc. For example, the user enters information such as "Create presentation materials," "Complete by the deadline," "High," and "2023-04-30."

[0659] 2. How to tokenize task information and store it in the database:

[0660] Server: Receives task information sent from the device, tokenizes it, and stores it in a database such as MongoDB.

[0661] 3. How to manage task progress based on saved task information:

[0662] Server: Tracks and manages the progress status (not started, in progress, completed, etc.) based on task information, and monitors the user's progress.

[0663] 4. How to display task progress based on saved task information:

[0664] On the device: Users can visually check task progress on a dashboard, which is visualized in graphs and lists.

[0665] 5. Means for receiving travel planning requirements information from a user:

[0666] User: Accesses a trip planning interface and enters travel destination, budget, number of days, etc. For example, the user enters "Tokyo as destination," "100,000 yen as budget," and "3 days as number of days."

[0667] 6. A means for generating a travel plan via an external generative AI model based on the received travel condition information:

[0668] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan. The generative AI model used is OpenAI's GPT-3. An example of a prompt is "Please create a three-day travel plan to Tokyo. The budget is 100,000 yen."

[0669] 7. Means for presenting the generated travel plan to the user:

[0670] Server: Takes the generated itinerary, formats it appropriately, and sends it to the device.

[0671] Terminal: The user visually checks the generated itinerary on a dashboard.

[0672] 8. Integrated display of task progress and travel plans:

[0673] Terminal: Task progress and travel plans retrieved from the server are displayed in a unified manner, allowing users to simultaneously manage their remote work progress and travel plans.

[0674] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[0675] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0676] System program processing flow

[0677] Step 1:

[0678] User enters task

[0679] User: Accesses the task management interface and enters the task title, description, priority, due date, etc.

[0680] Input: "Create presentation materials" "Complete by deadline" "Expensive" "2023-04-30"

[0681] What happens: A user fills out a form and clicks the "Submit" button. The data is converted from the form into JSON format data.

[0682] Step 2:

[0683] The device sends task information to the server

[0684] Terminal: Sends the entered task information to the server.

[0685] Input: Task information entered by the user (JSON format)

[0686] Output: HTTP POST request to the server

[0687] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[0688] Step 3:

[0689] The server receives and tokenizes the task information.

[0690] Server: Tokenizes the received task information and stores it in the database.

[0691] Input: Task information sent from the device (JSON format)

[0692] Output: Tokenized task information (database format)

[0693] Specific operation: Parse the JSON data, tokenize each element of the task (break it down into keywords and tags), and store it in a database such as MongoDB.

[0694] Step 4:

[0695] The server manages the task progress

[0696] Server: Manages the progress status of tasks (not started, in progress, completed, etc.) based on the saved task information.

[0697] Input: Tokenized task information stored in a database

[0698] Output: Updated task progress status

[0699] Specific behavior: Periodically check the status of each task and update the status according to user actions.

[0700] Step 5:

[0701] The device displays task progress

[0702] Terminal: Visually display task progress retrieved from the server on a dashboard.

[0703] Input: Task progress status obtained from the server

[0704] Output: Visual display of task progress

[0705] What it does: View task progress on a dashboard in graph, list, or calendar format.

[0706] Step 6:

[0707] User enters travel conditions

[0708] User: Accesses a trip planning interface and enters travel destination, budget, number of days, and other travel criteria.

[0709] Input: "Destination: Tokyo" "Budget: 100,000 yen" "Number of days: 3 days"

[0710] Specific Actions: The user fills out the form with the necessary travel requirements and clicks the "Submit" button again.

[0711] Step 7:

[0712] The device sends travel condition information to the server

[0713] Terminal: Sends the entered travel conditions information to the server.

[0714] Input: Travel conditions information entered by the user (JSON format)

[0715] Output: HTTP POST request to the server

[0716] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[0717] Step 8:

[0718] The server receives travel condition information and provides it to the AI ​​model

[0719] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0720] Input: Travel conditions information sent from the device (JSON format)

[0721] Output: A trip plan from the generative AI model

[0722] Specific behavior: Generate prompts for the AI ​​model and receive travel plans via API. Example: "Please create a three-day travel plan for Tokyo with a budget of 100,000 yen."

[0723] Step 9:

[0724] The server retrieves the generated itinerary

[0725] Server: Retrieves the itinerary generated by the AI ​​model, formats it appropriately, and sends it to the device.

[0726] Input: Travel itinerary from a generative AI model

[0727] Output: A formatted itinerary

[0728] Specific operation: Organize the obtained travel plans into a format that is easy for the user to understand.

[0729] Step 10:

[0730] The device displays the travel plan

[0731] Terminal: Visually displays the generated travel plan received from the server to the user.

[0732] Input: Formatted itinerary

[0733] Output: A visual representation of the itinerary

[0734] Specific operation: Display travel schedule, destination details, budget allocation, etc. on a dashboard.

[0735] integrated management

[0736] By following these steps, users can manage remote work tasks and travel planning in a unified manner, enabling them to efficiently achieve a work-life balance.

[0737] (Application example 1)

[0738] 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."

[0739] With the spread of remote work, there is a demand for tools to improve remote work efficiency, but conventional travel planning tools have difficulty providing plans that are linked to remote work schedules. For this reason, there is a need for a system that provides information on cafes and coworking spaces that users can use while working remotely, and can also centrally manage on-site remote work and travel planning.

[0740] 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.

[0741] In this invention, the server includes means for receiving remote work task information entered by a user via a task management interface, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel planning condition information from the user via a travel planning interface, means for generating a travel plan via a generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for providing store information available during remote work, and means for obtaining store reservations and usage status using an external service based on the user's current location information. This allows users to centrally manage their remote work and travel plans, further improving the efficiency of remote work.

[0742] The "task management interface" is a user interface that allows a user to input and send task information for remote work.

[0743] "Task information" is data about remote work, including detailed information such as the task title, description, priority, and deadline.

[0744] "Tokenization" is the process of converting received information into a format that can be securely processed and stored, for example by encrypting or encoding it.

[0745] A "database" is a digital warehouse for safely storing and managing users' task information, progress, and so on.

[0746] "Task progress" is status data that tracks and manages the status of a task, such as not started, in progress, or completed, based on saved task information.

[0747] The "interface for travel planning" is a user interface that allows a user to input and transmit travel planning condition information.

[0748] "Travel planning condition information" is condition data necessary when planning a trip, such as the travel destination, budget, number of days, etc.

[0749] A "generative AI model" is an artificial intelligence model that generates optimal travel plans based on travel planning condition information received from a user.

[0750] A "travel plan" is a specific plan that includes the travel destination, itinerary, places to visit, accommodation, etc.

[0751] "Store information available for use while working remotely" refers to information about facilities that can be used while working remotely, such as cafes and coworking spaces.

[0752] "User's current location information" means current geographic location data obtained from a user's smartphone or other device.

[0753] "External Services" are external software services, such as APIs and databases provided by third parties, that are used to extend the functionality of an application.

[0754] "Obtaining store reservations and usage status" refers to the process of using the provided API or database to obtain information such as the reservation status and current congestion level of a specific cafe or coworking space.

[0755] The system "Remote Cafe & Trip" of the present invention provides functions for improving the efficiency of users' remote work and centrally managing travel planning. Each component of the system and its specific operation are described below.

[0756] Components:

[0757] Task management interface

[0758] The user inputs remote task information through a task management interface. The device then sends the received task information to the server. The task information entered by the user includes details such as the task title, description, priority, and deadline.

[0759] Tokenized data storage

[0760] The server tokenizes the received task information and stores it securely in a database. The tokenization process ensures data security.

[0761] Task progress management

[0762] The server manages the progress of tasks based on the saved task information. It tracks the progress status (not started, in progress, completed, etc.) and displays it on the user's device. The user can visually check the progress of the task.

[0763] Trip planning interface

[0764] The user uses a trip planning interface to input conditions such as the travel destination, budget, and number of days, and sends the input to the server.

[0765] Travel plan generation using generative AI models

[0766] The server sends prompts to the generative AI model based on the received travel condition information to generate a travel plan. This generative AI model uses OpenAI's API.

[0767] Presenting your travel plan

[0768] The server acquires the generated itinerary and sends it to the user's terminal, where the user can visually display the generated itinerary.

[0769] Providing store information that can be used while working remotely

[0770] The server uses external services (such as Google Maps API) based on the user's current location information to obtain information about nearby cafes and coworking spaces, allowing users to easily find stores they can use while working remotely.

[0771] Obtaining store reservations and usage status

[0772] The server uses external services to obtain reservation and usage status for specific cafes and coworking spaces and provides this information to users.

[0773] Examples:

[0774] Task Management

[0775] For example, when a user enters a task to create a monthly report, they enter the following information into the interface: "Create monthly report," "Create monthly sales performance report," "High," "2023-10-31." The device sends this to the server, where it is tokenized and stored in the database. The task progress is then displayed on the dashboard.

[0776] Travel plan generation

[0777] If a user inputs travel criteria such as "Kyoto," "budget of 100,000 yen," and "3 days," the server sends the following prompt to the generative AI model:

[0778] "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[0779] The answer from the AI ​​model is

[0780] Day 1: After arriving at Kyoto Station, visit Kiyomizu-dera Temple and Gion. Visit Fushimi Inari Taisha Shrine, and have dinner around Kyoto Station in the evening.

[0781] Day 2: Visit Kinkakuji Temple and Ryoanji Temple. Visit Arashiyama in the evening and stroll through the bamboo forest. Dinner in Arashiyama.

[0782] Day 3: Visit the Kyoto National Museum. In the afternoon, stroll through Kyoto Gyoen National Garden and have lunch along the Kamo River. In the evening, return to Kyoto Station for the return journey.

[0783] The plan is generated and presented to the user.

[0784] This system allows users to centrally manage their remote work and travel plans, improving the efficiency of remote work.

[0785] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0786] Step 1:

[0787] The user enters remote work task information through a task management interface. The task information entered by the user includes the task title, description, priority, and deadline. For example, input data such as "Create monthly report," "Create monthly sales performance report," "High," and "2023-10-31" is sent.

[0788] Step 2:

[0789] The device sends the task information entered by the user to the server. At this time, the entered task information is configured as a data packet and passed to the server via the network. The input data is JSON format data of the task information.

[0790] Step 3:

[0791] The server tokenizes the received task information. Tokenization is the process of encrypting or encoding input data to make it safe. For example, the input data "Create monthly report" is converted to "token1234."

[0792] Step 4:

[0793] The server saves the tokenized task information to the database. At this time, the tokenized information is inserted into the appropriate field in the database and the index information is updated. For example, "token1234" is saved in the task information table in the database.

[0794] Step 5:

[0795] The server manages the progress of tasks based on the stored task information and tracks their progress status. The server uses an algorithm to manage the task state (not started, in progress, completed) and updates the progress in conjunction with the database. For example, "in progress" may be updated to "completed."

[0796] Step 6:

[0797] The user accesses the trip planning interface, inputs travel information (destination, budget, number of days), and sends it to the server via the terminal. The input data sent is "Kyoto," "budget of 100,000 yen," and "3 days."

[0798] Step 7:

[0799] The server sends a prompt to the generative AI model based on the received travel condition information. This prompt is composed of a natural language sentence that includes the travel condition information. An example of a prompt sentence is, "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[0800] Step 8:

[0801] The generative AI model takes a prompt as input and generates a travel plan using natural language processing and machine learning algorithms. Based on the input, the AI ​​model suggests suitable travel destinations, sightseeing spots, and itineraries.

[0802] Step 9:

[0803] The server retrieves the generated travel plan and sends it to the terminal to present to the user. The generated travel plan is configured as data and transferred to the terminal via the network. The output data may be in the form of, for example, "Day 1: Kiyomizu-dera Temple, Day 2: Kinkaku-ji Temple."

[0804] Step 10:

[0805] Users can request information about available stores through their devices while working remotely. The user's current location information is acquired and sent to the server.

[0806] Step 11:

[0807] The server uses an external service (e.g., Google Maps API) to obtain information about nearby cafes and coworking spaces based on the user's current location. The server sends an API request and stores the store information obtained from the external service in a database.

[0808] Step 12:

[0809] The server presents store information to the user's device based on the acquired store information. By also displaying the store's reservation status and usage status, the user can select an appropriate store while working remotely. The output data will be information such as "Nearby Cafe A, reservation status is available."

[0810] 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.

[0811] The system of the present invention centrally manages the efficiency of users' remote work and travel planning, and also provides the function of recognizing and dynamically responding to users' emotions. Each component of the system and its specific operation are described below.

[0812] Components:

[0813] 1. A means of receiving task information for a user's remote work

[0814] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[0815] Server: Receives task information sent from the device.

[0816] 2. A way to tokenize task information and store it in a database

[0817] Server: Tokenizes received task information and stores it securely in a database.

[0818] 3. A way to manage task progress based on saved task information

[0819] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[0820] Terminal: Provides the user with a visual indication of task progress.

[0821] 4. Means for receiving travel planning condition information from a user

[0822] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[0823] Server: Receives travel condition information sent from the terminal.

[0824] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0825] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[0826] 6. Means of presenting the generated travel plan to the user

[0827] Server: Retrieves the generated travel plan and sends it to the device.

[0828] Terminal: Visually displays the generated itinerary to the user.

[0829] 7. Emotion engine that recognizes user emotions

[0830] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine.

[0831] Server: Receives and manages emotion data recognized by the emotion engine.

[0832] 8. A method for automatically adjusting task and travel plan content based on recognized emotional information

[0833] Server: Dynamically adjusts task priorities and travel plan suggestions based on recognized emotion data.

[0834] 9. A means of analyzing emotional information and providing advice

[0835] Server: Analyzes emotional data and generates advice aimed at reducing stress and improving motivation.

[0836] Terminal: Notifies the user of advice from the server.

[0837] Specific operation explanation:

[0838] User task management

[0839] 1. User enters a task:

[0840] The user accesses the task management interface, enters detailed information about the task, and submits it.

[0841] 2. The device sends task information to the server:

[0842] The terminal transmits the input task information to the server.

[0843] 3. The server receives the task information and tokenizes it:

[0844] The server tokenizes the received task information and stores it securely in a database.

[0845] 4. The server manages the task progress:

[0846] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[0847] 5. The device will display the task progress:

[0848] Users can visually check task progress on a dashboard.

[0849] User travel planning

[0850] 1. User enters travel requirements:

[0851] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[0852] 2. The device sends travel condition information to the server:

[0853] The terminal transmits the input travel condition information to the server.

[0854] 3. The server receives the travel condition information and provides it to the AI ​​model:

[0855] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[0856] 4. The server retrieves the generated itinerary:

[0857] The server retrieves the itinerary generated by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0858] 5. The device displays your travel plan:

[0859] Users can visually check the generated travel plan on a dashboard.

[0860] User Emotion Recognition and Dynamic Adjustment

[0861] 1. Recognize user emotions:

[0862] The emotion engine analyzes the user's facial expressions and voice in real time to identify the user's current emotion (e.g., stress, happiness, anxiety, etc.).

[0863] 2. The device sends emotional information to the server:

[0864] The device transmits the recognized emotion data to the server.

[0865] 3. The server manages emotional information and adjusts tasks and travel plans:

[0866] The server dynamically adjusts task priorities and travel plan suggestions based on emotion data. For example, if a user is feeling stressed, it may lower task priorities or suggest additional breaks to reduce task load.

[0867] 4. Analyze sentiment information and generate advice:

[0868] The server analyzes the emotional data and generates advice aimed at reducing the user's stress and increasing their motivation.

[0869] 5. The device notifies the user of the advice:

[0870] The device notifies the user of the generated advice, such as "Take a break" or "Take a deep breath and relax."

[0871] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0872] The processing flow will be explained below.

[0873] Task management process flow

[0874] User task management

[0875] Step 1:

[0876] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[0877] Step 2:

[0878] The terminal sends the entered task information to the server as an AJAX request.

[0879] Step 3:

[0880] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[0881] Step 4:

[0882] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[0883] Step 5:

[0884] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[0885] Step 6:

[0886] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[0887] Step 7:

[0888] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[0889] Step 8:

[0890] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[0891] Travel planning process flow

[0892] User travel planning

[0893] Step 1:

[0894] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[0895] Step 2:

[0896] The terminal sends the entered travel condition information to the server as an AJAX request.

[0897] Step 3:

[0898] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[0899] Step 4:

[0900] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[0901] Step 5:

[0902] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[0903] Step 6:

[0904] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[0905] Step 7:

[0906] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[0907] Step 8:

[0908] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[0909] Emotion recognition and dynamic adjustment processing flow

[0910] User Emotion Recognition and Dynamic Adjustment

[0911] Step 1:

[0912] While the user is using the system, the emotion engine analyzes the user's facial expressions and voice in real time to identify their current emotion (e.g., stress, happiness, anxiety, etc.).

[0913] Step 2:

[0914] The terminal transmits the emotion information recognized by the emotion engine to the server.

[0915] Step 3:

[0916] The server manages the received emotion information.

[0917] Step 4:

[0918] The server dynamically adjusts remote work task priorities and travel plan suggestions based on the recognized emotional information. For example, if the user is feeling stressed, it may lower the priority of a task to reduce the burden or suggest additional breaks.

[0919] Step 5:

[0920] The server stores the adjusted task information and travel plans in a database.

[0921] Step 6:

[0922] The terminal retrieves the adjustment information from the server and visually displays it to the user.

[0923] Step 7:

[0924] The server analyzes the emotional information and generates advice aimed at reducing the user's stress and improving their motivation.

[0925] Step 8:

[0926] The device notifies the user of advice generated by the server, such as "Take a break" or "Take a deep breath and relax."

[0927] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0928] Example 2

[0929] 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."

[0930] Conventional remote work and travel planning management systems have difficulty providing distributed functions in an integrated manner. Furthermore, they lack the ability to recognize and dynamically respond to users' emotions in real time, which hinders the improvement of users' work-life balance. This leaves users without a means to efficiently manage tasks and create optimal travel plans.

[0931] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving remote work task information input by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for recognizing the user's emotions, and means for dynamically adjusting the content of the task or travel plan based on the recognized emotion information. This enables efficient, unified management of the user's remote work and travel planning, and also enables appropriate responses according to the user's emotions.

[0932] "Remote work" refers to work done over a communications network such as the internet.

[0933] "Task information" is detailed information about a task item that a user must perform, and includes a title, description, priority, deadline, and the like.

[0934] "Tokenization" refers to the process of analyzing information and breaking it down into smaller units (tokens) based on meaning and structure.

[0935] "Database" means an electronic system for efficiently and securely storing and managing digital data.

[0936] "Task progress management" refers to the process of monitoring and updating the progress of a task (not started, in progress, completed, etc.) based on stored task information.

[0937] "Travel planning" refers to creating a plan based on conditions such as the travel destination, budget, and number of days.

[0938] A "generative AI model" refers to a computer program that uses artificial intelligence technology to provide generated content or answers based on input conditions.

[0939] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state (e.g., stress, happiness, anxiety, etc.).

[0940] "Dynamic adjustment" refers to the process of changing content and settings in real time based on the situation.

[0941] A "dashboard" refers to an interface for visually and comprehensively displaying various information.

[0942] The system according to the present invention provides a unified management system for improving the efficiency of remote work and travel planning for users, and also provides a function for recognizing and dynamically responding to user emotions. The system of the present invention includes the following components.

[0943] 1. A means of receiving task information for a user's remote work

[0944] Terminal: The user accesses a task management interface and enters the task title, description, priority, due date, etc. For example, the user adds a task called "Write a progress report for Project X" and sets the priority to high and the due date to the end of this week.

[0945] Server: Receives task information sent from the device.

[0946] 2. A way to tokenize task information and store it in a database

[0947] Server: Tokenizes the received task information and stores it securely in a database. Specifically, the task information is split into tokens such as "Project X," "Progress Report," "Created," "High," and "This weekend," and stored in a DBMS (e.g., MySQL).

[0948] 3. A way to manage task progress based on saved task information

[0949] Server: Manages task information appropriately and tracks task progress status (not started, in progress, completed, etc.) When a user updates a task, the server updates the corresponding record in the database.

[0950] 4. How the device displays task progress

[0951] On the device: Users can visually see the progress of their tasks on a dashboard, with incomplete tasks displayed in red, in progress in yellow, and completed in green.

[0952] 5. Means for receiving travel planning condition information from a user

[0953] User: Accesses a travel planning interface and inputs travel destination, budget, number of days, etc. For example, a user might set the conditions as "Tokyo," "300,000 yen," and "5 days."

[0954] Server: Receives travel condition information sent from the terminal.

[0955] 6. A means of generating a travel plan based on received travel condition information via an external generative AI model

[0956] Server: Provides the received travel condition information to an external generative AI model and generates a travel plan. Specifically, it sends the following prompt to the generative AI model:

[0957] "Please create a five-day travel plan for Tokyo with a budget of 300,000 yen."

[0958] 7. Means of presenting the generated travel plan to the user

[0959] Server: Retrieves the generated itinerary, formats it as needed, and sends it to the device.

[0960] Device: The user can visually check the generated travel plan on a dashboard, for example, displaying the itinerary and cost list.

[0961] 8. How to Recognize User Emotions

[0962] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine. For example, a facial expression recognition API can be used to determine "stress" or "happiness."

[0963] 9. A means of dynamically adjusting the content of a task or itinerary based on recognized emotional information

[0964] Server: Dynamically adjust task priorities and travel plan suggestions based on recognized emotion data. For example, if the user is feeling stressed, lower the priority or suggest additional breaks to reduce task load.

[0965] These components enable the system of the present invention to comprehensively support users in improving the efficiency of remote work and travel planning, and also to flexibly respond to users' emotions. Users can efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[0966] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0967] Processing flow and specific operations

[0968] Task Management

[0969] Step 1:

[0970] The user accesses the task management interface and inputs the task title, description, priority, deadline, etc. The task information is sent to the server as input data. Specifically, the user inputs information such as "Create a progress report for Project X," "High," and "This weekend."

[0971] Step 2:

[0972] The device sends the entered task information to the server's API endpoint via an HTTP POST request. The input is the task information entered by the user, and the output is the status of successful submission to the server.

[0973] Step 3:

[0974] The server receives an HTTP request and tokenizes the task information. Specifically, it splits the task information into tokens such as "Project X," "Progress Report," "Create," "High," and "This Weekend." The input is the received task information, and the output is the tokenized task data.

[0975] Step 4:

[0976] The server stores the tokenized task data in a database (e.g., MySQL). The input is the tokenized task data, and the output is the task information stored in the database.

[0977] Step 5:

[0978] The server manages the task progress and tracks and updates the progress status (not started, in progress, completed, etc.). For example, when a user marks a task as progressed, the server updates the corresponding record in the database. The input is the current task information and the user's actions, and the output is the updated task progress status.

[0979] Step 6:

[0980] The terminal periodically retrieves task progress information from the server and displays it visually on a dashboard. Specifically, tasks that have not been started are displayed in red, tasks in progress in yellow, and completed tasks in green. The input is the progress data retrieved from the server, and the output is the visual display to the user.

[0981] Travel Planning

[0982] Step 1:

[0983] The user accesses the trip planning interface and inputs travel conditions such as destination, budget, and number of days. The travel condition information is sent as input data to the server. Specifically, the user enters the conditions "Tokyo," "300,000 yen," and "5 days."

[0984] Step 2:

[0985] The device sends the entered travel condition information to the server's API endpoint via an HTTP POST request. The input is the travel condition information entered by the user, and the output is the status of successful transmission to the server.

[0986] Step 3:

[0987] The server receives the HTTP request and provides the received travel condition information to an external generative AI model. Specifically, it sends the following prompt to the generative AI model: "Please create a 5-day travel plan to Tokyo. The budget is 300,000 yen." The input is the received travel condition information, and the output is the prompt sent to the generative AI model.

[0988] Step 4:

[0989] The server retrieves the itinerary from the generative AI model and formats it as needed. The input is the generated itinerary, and the output is the formatted itinerary data.

[0990] Step 5:

[0991] The server sends the travel plan data to the terminal. The input is the formatted travel plan data, and the output is the status of successful transmission to the terminal.

[0992] Step 6:

[0993] The terminal visually displays the travel plan on a dashboard, specifically showing the itinerary, cost list, etc. The input is the travel plan data sent from the server, and the output is the visual display to the user.

[0994] Emotion Recognition and Dynamic Regulation

[0995] Step 1:

[0996] The device uses an emotion engine to analyze the user's facial expressions and voice in real time and recognize their emotions. Specifically, it uses a facial expression recognition API to determine "stress" and "happiness." The input is the user's video and audio data, and the output is recognized emotional data.

[0997] Step 2:

[0998] The device sends the recognized emotion data to the server via an HTTP POST request. The input is the recognized emotion data, and the output is the status of successful transmission to the server.

[0999] Step 3:

[1000] The server receives emotional information and dynamically adjusts task priorities and travel plan suggestions based on that information. For example, if the user is feeling stressed, the server lowers task priorities to reduce the task load. The input is the received emotional information, and the output is the adjusted task or travel plan data.

[1001] Step 4:

[1002] The server sends the adjusted task or travel plan data to the terminal, where the input is the adjusted task or travel plan data and the output is a transmission success status to the terminal.

[1003] Step 5:

[1004] The device generates advice based on the emotion data and notifies the user. For example, it displays advice such as "Take a deep breath" or "We recommend taking a short break." The input is the advice data sent from the server, and the output is a visual display to the user.

[1005] (Application example 2)

[1006] 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."

[1007] While modern factory robots efficiently perform a variety of tasks, their long working hours and complex operations have led to problems with declining operational efficiency and reliability. In particular, the lack of emotion-based maintenance or dynamic task adjustments increases the risk of unexpected malfunctions and operational shutdowns. Furthermore, the lack of a means to comprehensively manage robots' operational efficiency and maintenance plans in real time makes it difficult for managers to respond appropriately. Given these circumstances, there is a growing need for a system that improves the operational efficiency and reliability of factory robots.

[1008] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1009] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from a user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for receiving robot emotion data using an emotion recognition engine, means for dynamically adjusting the robot's task priority based on the emotion data, and means for presenting the generated travel plan to the user. This enables centralized management of factory robot work efficiency and maintenance plans, and dynamic adjustment of tasks based on emotion data.

[1010] A "user" is an entity that uses this system to input task information and set travel conditions.

[1011] "Remote work task information" refers to detailed task information entered by a user to manage remote work, including the task title, description, priority, deadline, etc.

[1012] "Tokenization" is a method of securely storing received data in a database using methods such as encryption and hashing.

[1013] "Database" means a collection of data that securely stores tokenized task information and makes it accessible as needed.

[1014] "Task progress management" is the process of tracking and updating the progress status of a task based on stored task information.

[1015] "Travel planning condition information" is condition information such as the travel destination, budget, number of days, etc. that the user sets when planning a trip.

[1016] An "external generative AI model" is an artificial intelligence model that receives travel condition information set by the user and generates a travel plan based on that information.

[1017] A "travel plan" is a detailed travel schedule or itinerary created by a generative AI model based on travel planning condition information.

[1018] An "emotion recognition engine" is an engine that analyzes a robot's emotional data (such as vibrations and temperature) in real time and identifies its emotional state.

[1019] "Emotion data" is data that indicates the current emotional state of the robot, obtained by the emotion recognition engine.

[1020] "Dynamic adjustment of task priorities" is a process that automatically changes task priorities based on acquired emotional data to optimize the robot's workload.

[1021] A "maintenance plan" is a plan to create a maintenance schedule based on the robot's emotional data and maintain the robot's performance.

[1022] "Integrated display" means that users can see the progress of remote work tasks and the status of travel plans all in one dashboard.

[1023] This invention relates to a system that manages the work efficiency and maintenance plans of factory robots in an integrated manner and dynamically adjusts task priorities based on emotion data. The specific configuration and operation of the system are described below.

[1024] The system includes the following major hardware and software components:

[1025] Hardware

[1026] Factory robots: Robots equipped with emotion recognition sensors and controlled remotely.

[1027] Server: A central server that manages tasks, generates travel plans, and manages emotion data.

[1028] software

[1029] Task Management API: An API for receiving task information, tokenizing it, and storing it in a database.

[1030] Emotion recognition engine: An engine that analyzes the robot's emotional data (e.g., vibration and temperature) and identifies its emotional state.

[1031] Generative AI model: An AI model for generating optimal travel plans based on received travel condition information.

[1032] System Operation

[1033] 1. User task management

[1034] Users access the task management interface remotely and enter detailed task information (title, description, priority, deadline, etc.). The entered task information is sent to the server via the terminal. The server tokenizes the received task information, stores it in a database, and manages the task progress.

[1035] 2. Generate a travel plan

[1036] The user accesses a trip planning interface and inputs travel conditions (destination, budget, number of days, etc.). The input information is sent to the server via the device, and the server provides this information to an external generative AI model to generate a travel plan. The generated travel plan is then presented to the user via the server.

[1037] 3. Acquiring Emotional Data and Dynamic Task Adjustment

[1038] The robot's emotion recognition sensors monitor the robot's condition (e.g., vibration and temperature) in real time, and the emotion recognition engine analyzes this to generate emotion data. The generated emotion data is sent to the server, and task priorities are automatically adjusted. For example, if the robot is feeling "stressed," the task priority will be changed to "urgent" and a maintenance notification will be issued immediately.

[1039] Specific examples

[1040] For example, consider the case where a manager assigns a task called "Routine Maintenance" to a factory robot. This task information is sent to the server via an input terminal, tokenized, and stored in a database. Meanwhile, if the robot's emotion recognition sensor detects an emotional state of "stress," the server will use this emotional data to adjust the task priority to "urgent" and immediately send a maintenance notification to the manager.

[1041] Prompt Sentence Examples

[1042] An example of a prompt to be input to the generative AI model is as follows:

[1043] Robot ID: 1

[1044] Emotional state: Stress

[1045] Recommended action: Prompt maintenance

[1046] Task Priority: Urgent

[1047] This prompt is then fed into a generative AI model and used to generate an optimal plan of action or set of actions.

[1048] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1049] Step 1:

[1050] The user inputs task information for remote work. The terminal receives the input information such as the task title, description, priority, and deadline, and sends it to the server. Input: Task information (title, description, priority, deadline). Output: Task information sent to the server.

[1051] Step 2:

[1052] The server receives task information and tokenizes each task. The tokenized task information is saved in a database. Input: Task information received from the device. Output: Tokenized task information saved in a database.

[1053] Step 3:

[1054] The server manages task progress based on task information stored in the database. It tracks task progress status (e.g. not started, in progress, completed) and updates it as needed. Input: Task information stored in the database. Output: Updated task progress status.

[1055] Step 4:

[1056] The user inputs travel plan condition information. The terminal receives condition information such as travel destination, budget, number of days, etc. and sends it to the server. Input: Travel plan condition information (travel destination, budget, number of days). Output: Travel condition information sent to the server.

[1057] Step 5:

[1058] The server receives travel condition information and provides it to an external generative AI model to generate a travel plan. The generated travel plan is organized and saved in a database. Input: Travel condition information provided to the external generative AI model. Output: Generated travel plan.

[1059] Step 6:

[1060] The generated itinerary is sent from the server to the terminal and presented to the user. Input: Generated itinerary. Output: Itinerary visually displayed on the terminal.

[1061] Step 7:

[1062] The robot's emotion recognition sensor acquires the robot's emotion data in real time, and the emotion recognition engine analyzes this emotion data. Input: Emotion data acquired from the robot. Output: Analyzed emotional state.

[1063] Step 8:

[1064] The emotion recognition engine sends the analyzed emotion data to the server, which then dynamically adjusts task priorities based on the emotion data. Input: Analyzed emotion data. Output: Adjusted task priorities.

[1065] Step 9:

[1066] The server analyzes the emotion data and sends appropriate maintenance notifications to the user or administrator. For example, if the robot's emotional state is "stressed," it issues a notification such as "Perform prompt maintenance." Input: Analyzed emotion data. Output: Maintenance notification sent to the user or administrator.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] [Third embodiment]

[1071] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1072] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1073] 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).

[1074] 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.

[1075] 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.

[1076] 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).

[1077] 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.

[1078] 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.

[1079] 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.

[1080] 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.

[1081] 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.

[1082] 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."

[1083] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[1084] Components:

[1085] 1. A means of receiving task information for a user's remote work

[1086] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[1087] Server: Receives task information sent from the device.

[1088] 2. A way to tokenize task information and store it in a database

[1089] Server: Tokenizes received task information and stores it securely in a database.

[1090] 3. A way to manage task progress based on saved task information

[1091] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[1092] Terminal: Provides the user with a visual indication of task progress.

[1093] 4. Means for receiving travel planning condition information from a user

[1094] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[1095] Server: Receives travel condition information sent from the terminal.

[1096] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[1097] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1098] 6. Means of presenting the generated travel plan to the user

[1099] Server: Retrieves the generated travel plan and sends it to the device.

[1100] Terminal: Visually displays the generated itinerary to the user.

[1101] Specific operation explanation:

[1102] User task management

[1103] 1. User enters a task:

[1104] The user accesses the task management interface, enters detailed information about the task, and submits it.

[1105] 2. The device sends task information to the server:

[1106] The terminal transmits the input task information to the server.

[1107] 3. The server receives the task information and tokenizes it:

[1108] The server tokenizes the received task information and stores it securely in a database.

[1109] 4. The server manages the task progress:

[1110] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[1111] 5. The device will display the task progress:

[1112] Users can visually check task progress on a dashboard.

[1113] User travel planning

[1114] 1. User enters travel requirements:

[1115] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[1116] 2. The device sends travel condition information to the server:

[1117] The terminal transmits the input travel condition information to the server.

[1118] 3. The server receives the travel condition information and provides it to the AI ​​model:

[1119] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[1120] 4. The server retrieves the generated itinerary:

[1121] The server retrieves the travel plan generated from the AI ​​model and sends it to the device.

[1122] 5. The device displays your travel plan:

[1123] Users can visually check the generated travel plan on a dashboard.

[1124] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[1125] The processing flow will be explained below.

[1126] Task management process flow

[1127] User task management

[1128] Step 1:

[1129] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[1130] Step 2:

[1131] The terminal sends the entered task information to the server as an AJAX request.

[1132] Step 3:

[1133] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[1134] Step 4:

[1135] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[1136] Step 5:

[1137] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[1138] Step 6:

[1139] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[1140] Step 7:

[1141] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[1142] Step 8:

[1143] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[1144] Trip planning process flow

[1145] User travel planning

[1146] Step 1:

[1147] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[1148] Step 2:

[1149] The terminal sends the entered travel condition information to the server as an AJAX request.

[1150] Step 3:

[1151] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[1152] Step 4:

[1153] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[1154] Step 5:

[1155] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[1156] Step 6:

[1157] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1158] Step 7:

[1159] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[1160] Step 8:

[1161] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[1162] In this way, the roles of the user, terminal, and server work together to manage tasks and plan trips, thereby improving the user's work-life balance.

[1163] Example 1

[1164] 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."

[1165] In today's remote work environment, effective task management and trip planning are essential to maximize work efficiency. However, there are few platforms that centrally manage these functions, forcing users to use multiple tools. As a result, it is difficult to integrate task management and trip planning, making it difficult to achieve work-life balance.

[1166] 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.

[1167] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, and means for integrating and displaying the task progress and travel plan in real time on a user dashboard. This allows users to centrally manage remote work tasks and travel planning, enabling an efficient work-life balance.

[1168] "Remote work task information" is information about the specific work that a user needs to accomplish when working remotely and the progress of that work.

[1169] "Tokenization" is the process of breaking down input information into smaller units and converting each unit into a separately identifiable form.

[1170] A "database" is a system for safely and efficiently storing information so that it can be searched and retrieved later.

[1171] "Task progress status" is information indicating the progress and completion status of tasks that a user performs while working remotely.

[1172] "Planning condition information" is information relating to conditions such as travel destination, budget, number of days, etc. that a user specifies when planning a trip.

[1173] A "generative AI model" is an artificial intelligence model that has the ability to generate new information or plans based on given input.

[1174] A "travel plan" is a plan that includes details of a trip, such as a specific schedule, places to visit, and accommodation.

[1175] A "dashboard" is an interface that displays information in a format that allows users to easily view it visually.

[1176] "Real-time" means that information is reflected immediately and there is almost no time delay in updating.

[1177] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[1178] Components:

[1179] 1. A means for receiving task information for a user's remote work:

[1180] Terminal: The user accesses the task management interface and enters the task title, description, priority, deadline, etc. For example, the user enters information such as "Create presentation materials," "Complete by the deadline," "High," and "2023-04-30."

[1181] 2. How to tokenize task information and store it in the database:

[1182] Server: Receives task information sent from the device, tokenizes it, and stores it in a database such as MongoDB.

[1183] 3. How to manage task progress based on saved task information:

[1184] Server: Tracks and manages the progress status (not started, in progress, completed, etc.) based on task information, and monitors the user's progress.

[1185] 4. How to display task progress based on saved task information:

[1186] On the device: Users can visually check task progress on a dashboard, which is visualized in graphs and lists.

[1187] 5. Means for receiving travel planning requirements information from a user:

[1188] User: Accesses a trip planning interface and enters travel destination, budget, number of days, etc. For example, the user enters "Tokyo as destination," "100,000 yen as budget," and "3 days as number of days."

[1189] 6. A means for generating a travel plan via an external generative AI model based on the received travel condition information:

[1190] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan. The generative AI model used is OpenAI's GPT-3. An example of a prompt is "Please create a three-day travel plan to Tokyo. The budget is 100,000 yen."

[1191] 7. Means for presenting the generated travel plan to the user:

[1192] Server: Takes the generated itinerary, formats it appropriately, and sends it to the device.

[1193] Terminal: The user visually checks the generated itinerary on a dashboard.

[1194] 8. Integrated display of task progress and travel plans:

[1195] Terminal: Task progress and travel plans retrieved from the server are displayed in a unified manner, allowing users to simultaneously manage their remote work progress and travel plans.

[1196] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[1197] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1198] System program processing flow

[1199] Step 1:

[1200] User enters task

[1201] User: Accesses the task management interface and enters the task title, description, priority, due date, etc.

[1202] Input: "Create presentation materials" "Complete by deadline" "Expensive" "2023-04-30"

[1203] What happens: A user fills out a form and clicks the "Submit" button. The data is converted from the form into JSON format data.

[1204] Step 2:

[1205] The device sends task information to the server

[1206] Terminal: Sends the entered task information to the server.

[1207] Input: Task information entered by the user (JSON format)

[1208] Output: HTTP POST request to the server

[1209] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[1210] Step 3:

[1211] The server receives and tokenizes the task information.

[1212] Server: Tokenizes the received task information and stores it in the database.

[1213] Input: Task information sent from the device (JSON format)

[1214] Output: Tokenized task information (database format)

[1215] Specific operation: Parse the JSON data, tokenize each element of the task (break it down into keywords and tags), and store it in a database such as MongoDB.

[1216] Step 4:

[1217] The server manages the task progress

[1218] Server: Manages the progress status of tasks (not started, in progress, completed, etc.) based on the saved task information.

[1219] Input: Tokenized task information stored in a database

[1220] Output: Updated task progress status

[1221] Specific behavior: Periodically check the status of each task and update the status according to user actions.

[1222] Step 5:

[1223] The device displays task progress

[1224] Terminal: Visually display task progress retrieved from the server on a dashboard.

[1225] Input: Task progress status obtained from the server

[1226] Output: Visual display of task progress

[1227] What it does: View task progress on a dashboard in graph, list, or calendar format.

[1228] Step 6:

[1229] User enters travel conditions

[1230] User: Accesses a trip planning interface and enters travel destination, budget, number of days, and other travel criteria.

[1231] Input: "Destination: Tokyo" "Budget: 100,000 yen" "Number of days: 3 days"

[1232] Specific Actions: The user fills out the form with the necessary travel requirements and clicks the "Submit" button again.

[1233] Step 7:

[1234] The device sends travel condition information to the server

[1235] Terminal: Sends the entered travel conditions information to the server.

[1236] Input: Travel conditions information entered by the user (JSON format)

[1237] Output: HTTP POST request to the server

[1238] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[1239] Step 8:

[1240] The server receives travel condition information and provides it to the AI ​​model

[1241] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1242] Input: Travel conditions information sent from the device (JSON format)

[1243] Output: A trip plan from the generative AI model

[1244] Specific behavior: Generate prompts for the AI ​​model and receive travel plans via API. Example: "Please create a three-day travel plan for Tokyo with a budget of 100,000 yen."

[1245] Step 9:

[1246] The server retrieves the generated itinerary

[1247] Server: Retrieves the itinerary generated by the AI ​​model, formats it appropriately, and sends it to the device.

[1248] Input: Travel itinerary from a generative AI model

[1249] Output: A formatted itinerary

[1250] Specific operation: Organize the obtained travel plans into a format that is easy for the user to understand.

[1251] Step 10:

[1252] The device displays the travel plan

[1253] Terminal: Visually displays the generated travel plan received from the server to the user.

[1254] Input: Formatted itinerary

[1255] Output: A visual representation of the itinerary

[1256] Specific operation: Display travel schedule, destination details, budget allocation, etc. on a dashboard.

[1257] integrated management

[1258] By following these steps, users can manage remote work tasks and travel planning in a unified manner, enabling them to efficiently achieve a work-life balance.

[1259] (Application example 1)

[1260] 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."

[1261] With the spread of remote work, there is a demand for tools to improve remote work efficiency, but conventional travel planning tools have difficulty providing plans that are linked to remote work schedules. For this reason, there is a need for a system that provides information on cafes and coworking spaces that users can use while working remotely, and can also centrally manage on-site remote work and travel planning.

[1262] 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.

[1263] In this invention, the server includes means for receiving remote work task information entered by a user via a task management interface, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel planning condition information from the user via a travel planning interface, means for generating a travel plan via a generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for providing store information available during remote work, and means for obtaining store reservations and usage status using an external service based on the user's current location information. This allows users to centrally manage their remote work and travel plans, further improving the efficiency of remote work.

[1264] The "task management interface" is a user interface that allows a user to input and send task information for remote work.

[1265] "Task information" is data about remote work, including detailed information such as the task title, description, priority, and deadline.

[1266] "Tokenization" is the process of converting received information into a format that can be securely processed and stored, for example by encrypting or encoding it.

[1267] A "database" is a digital warehouse for safely storing and managing users' task information, progress, and so on.

[1268] "Task progress" is status data that tracks and manages the status of a task, such as not started, in progress, or completed, based on saved task information.

[1269] The "interface for travel planning" is a user interface that allows a user to input and transmit travel planning condition information.

[1270] "Travel planning condition information" is condition data necessary when planning a trip, such as the travel destination, budget, number of days, etc.

[1271] A "generative AI model" is an artificial intelligence model that generates optimal travel plans based on travel planning condition information received from a user.

[1272] A "travel plan" is a specific plan that includes the travel destination, itinerary, places to visit, accommodation, etc.

[1273] "Store information available for use while working remotely" refers to information about facilities that can be used while working remotely, such as cafes and coworking spaces.

[1274] "User's current location information" means current geographic location data obtained from a user's smartphone or other device.

[1275] "External Services" are external software services, such as APIs and databases provided by third parties, that are used to extend the functionality of an application.

[1276] "Obtaining store reservations and usage status" refers to the process of using the provided API or database to obtain information such as the reservation status and current congestion level of a specific cafe or coworking space.

[1277] The system "Remote Cafe & Trip" of the present invention provides functions for improving the efficiency of users' remote work and centrally managing travel planning. Each component of the system and its specific operation are described below.

[1278] Components:

[1279] Task management interface

[1280] The user inputs remote task information through a task management interface. The device then sends the received task information to the server. The task information entered by the user includes details such as the task title, description, priority, and deadline.

[1281] Tokenized data storage

[1282] The server tokenizes the received task information and stores it securely in a database. The tokenization process ensures data security.

[1283] Task progress management

[1284] The server manages the progress of tasks based on the saved task information. It tracks the progress status (not started, in progress, completed, etc.) and displays it on the user's device. The user can visually check the progress of the task.

[1285] Trip planning interface

[1286] The user uses a trip planning interface to input conditions such as the travel destination, budget, and number of days, and sends the input to the server.

[1287] Travel plan generation using generative AI models

[1288] The server sends prompts to the generative AI model based on the received travel condition information to generate a travel plan. This generative AI model uses OpenAI's API.

[1289] Presenting your travel plan

[1290] The server acquires the generated itinerary and sends it to the user's terminal, where the user can visually display the generated itinerary.

[1291] Providing store information that can be used while working remotely

[1292] The server uses external services (such as Google Maps API) based on the user's current location information to obtain information about nearby cafes and coworking spaces, allowing users to easily find stores they can use while working remotely.

[1293] Obtaining store reservations and usage status

[1294] The server uses external services to obtain reservation and usage status for specific cafes and coworking spaces and provides this information to users.

[1295] Examples:

[1296] Task Management

[1297] For example, when a user enters a task to create a monthly report, they enter the following information into the interface: "Create monthly report," "Create monthly sales performance report," "High," "2023-10-31." The device sends this to the server, where it is tokenized and stored in the database. The task progress is then displayed on the dashboard.

[1298] Travel plan generation

[1299] If a user inputs travel criteria such as "Kyoto," "budget of 100,000 yen," and "3 days," the server sends the following prompt to the generative AI model:

[1300] "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[1301] The answer from the AI ​​model is

[1302] Day 1: After arriving at Kyoto Station, visit Kiyomizu-dera Temple and Gion. Visit Fushimi Inari Taisha Shrine, and have dinner around Kyoto Station in the evening.

[1303] Day 2: Visit Kinkakuji Temple and Ryoanji Temple. Visit Arashiyama in the evening and stroll through the bamboo forest. Dinner in Arashiyama.

[1304] Day 3: Visit the Kyoto National Museum. In the afternoon, stroll through Kyoto Gyoen National Garden and have lunch along the Kamo River. In the evening, return to Kyoto Station for the return journey.

[1305] The plan is generated and presented to the user.

[1306] This system allows users to centrally manage their remote work and travel plans, improving the efficiency of remote work.

[1307] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1308] Step 1:

[1309] The user enters remote work task information through a task management interface. The task information entered by the user includes the task title, description, priority, and deadline. For example, input data such as "Create monthly report," "Create monthly sales performance report," "High," and "2023-10-31" is sent.

[1310] Step 2:

[1311] The device sends the task information entered by the user to the server. At this time, the entered task information is configured as a data packet and passed to the server via the network. The input data is JSON format data of the task information.

[1312] Step 3:

[1313] The server tokenizes the received task information. Tokenization is the process of encrypting or encoding input data to make it safe to handle. For example, input data such as "Create monthly report" is converted to "token1234."

[1314] Step 4:

[1315] The server stores the tokenized task information in the database. At this time, the tokenized information is inserted into the appropriate field in the database and the index information is updated. For example, "token1234" is stored in the task information table in the database.

[1316] Step 5:

[1317] The server manages the progress of tasks based on the stored task information and tracks their progress status. The server uses an algorithm to manage the task state (not started, in progress, completed) and updates the progress in conjunction with the database. For example, "in progress" may be updated to "completed."

[1318] Step 6:

[1319] The user accesses the trip planning interface, inputs travel information (destination, budget, number of days), and sends it to the server via the terminal. The input data sent is "Kyoto," "budget of 100,000 yen," and "3 days."

[1320] Step 7:

[1321] The server sends a prompt to the generative AI model based on the received travel condition information. This prompt is composed of a natural language sentence that includes the travel condition information. An example of a prompt sentence is, "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[1322] Step 8:

[1323] The generative AI model takes a prompt as input and generates a travel plan using natural language processing and machine learning algorithms. Based on the input, the AI ​​model suggests suitable travel destinations, sightseeing spots, and itineraries.

[1324] Step 9:

[1325] The server retrieves the generated travel plan and sends it to the terminal to present to the user. The generated travel plan is configured as data and transferred to the terminal via the network. The output data may be in the form of, for example, "Day 1: Kiyomizu-dera Temple, Day 2: Kinkaku-ji Temple."

[1326] Step 10:

[1327] Users can request information about available stores through their devices while working remotely. The user's current location information is acquired and sent to the server.

[1328] Step 11:

[1329] The server uses an external service (e.g., Google Maps API) to obtain information about nearby cafes and coworking spaces based on the user's current location. The server sends an API request and stores the store information obtained from the external service in a database.

[1330] Step 12:

[1331] The server presents store information to the user's device based on the acquired store information. By also displaying the store's reservation status and usage status, the user can select an appropriate store while working remotely. The output data will be information such as "Nearby Cafe A, reservation status is available."

[1332] 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.

[1333] The system of the present invention centrally manages the efficiency of users' remote work and travel planning, and also provides the function of recognizing and dynamically responding to users' emotions. Each component of the system and its specific operation are described below.

[1334] Components:

[1335] 1. A means of receiving task information for a user's remote work

[1336] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[1337] Server: Receives task information sent from the device.

[1338] 2. A way to tokenize task information and store it in a database

[1339] Server: Tokenizes received task information and stores it securely in a database.

[1340] 3. A way to manage task progress based on saved task information

[1341] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[1342] Terminal: Provides the user with a visual indication of task progress.

[1343] 4. Means for receiving travel planning condition information from a user

[1344] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[1345] Server: Receives travel condition information sent from the terminal.

[1346] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[1347] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1348] 6. Means of presenting the generated travel plan to the user

[1349] Server: Retrieves the generated travel plan and sends it to the device.

[1350] Terminal: Visually displays the generated itinerary to the user.

[1351] 7. Emotion engine that recognizes user emotions

[1352] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine.

[1353] Server: Receives and manages emotion data recognized by the emotion engine.

[1354] 8. A method for automatically adjusting task and travel plan content based on recognized emotional information

[1355] Server: Dynamically adjusts task priorities and travel plan suggestions based on recognized emotion data.

[1356] 9. A means of analyzing emotional information and providing advice

[1357] Server: Analyzes emotional data and generates advice aimed at reducing stress and improving motivation.

[1358] Terminal: Notifies the user of advice from the server.

[1359] Specific operation explanation:

[1360] User task management

[1361] 1. User enters a task:

[1362] The user accesses the task management interface, enters detailed information about the task, and submits it.

[1363] 2. The device sends task information to the server:

[1364] The terminal transmits the input task information to the server.

[1365] 3. The server receives the task information and tokenizes it:

[1366] The server tokenizes the received task information and stores it securely in a database.

[1367] 4. The server manages the task progress:

[1368] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[1369] 5. The device will display the task progress:

[1370] Users can visually check task progress on a dashboard.

[1371] User travel planning

[1372] 1. User enters travel requirements:

[1373] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[1374] 2. The device sends travel condition information to the server:

[1375] The terminal transmits the input travel condition information to the server.

[1376] 3. The server receives the travel condition information and provides it to the AI ​​model:

[1377] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[1378] 4. The server retrieves the generated itinerary:

[1379] The server retrieves the itinerary generated by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1380] 5. The device displays your travel plan:

[1381] Users can visually check the generated travel plan on a dashboard.

[1382] User Emotion Recognition and Dynamic Adjustment

[1383] 1. Recognize user emotions:

[1384] The emotion engine analyzes the user's facial expressions and voice in real time to identify the user's current emotion (e.g., stress, happiness, anxiety, etc.).

[1385] 2. The device sends emotional information to the server:

[1386] The device transmits the recognized emotion data to the server.

[1387] 3. The server manages emotional information and adjusts tasks and travel plans:

[1388] The server dynamically adjusts task priorities and travel plan suggestions based on emotion data. For example, if a user is feeling stressed, it may lower task priorities or suggest additional breaks to reduce task load.

[1389] 4. Analyze sentiment information and generate advice:

[1390] The server analyzes the emotional data and generates advice aimed at reducing the user's stress and increasing their motivation.

[1391] 5. The device notifies the user of the advice:

[1392] The device notifies the user of the generated advice, such as "Take a break" or "Take a deep breath and relax."

[1393] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[1394] The processing flow will be explained below.

[1395] Task management process flow

[1396] User task management

[1397] Step 1:

[1398] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[1399] Step 2:

[1400] The terminal sends the entered task information to the server as an AJAX request.

[1401] Step 3:

[1402] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[1403] Step 4:

[1404] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[1405] Step 5:

[1406] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[1407] Step 6:

[1408] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[1409] Step 7:

[1410] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[1411] Step 8:

[1412] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[1413] Trip planning process flow

[1414] User travel planning

[1415] Step 1:

[1416] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[1417] Step 2:

[1418] The terminal sends the entered travel condition information to the server as an AJAX request.

[1419] Step 3:

[1420] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[1421] Step 4:

[1422] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[1423] Step 5:

[1424] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[1425] Step 6:

[1426] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1427] Step 7:

[1428] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[1429] Step 8:

[1430] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[1431] Emotion recognition and dynamic adjustment processing flow

[1432] User Emotion Recognition and Dynamic Adjustment

[1433] Step 1:

[1434] While the user is using the system, the emotion engine analyzes the user's facial expressions and voice in real time to identify their current emotion (e.g., stress, happiness, anxiety, etc.).

[1435] Step 2:

[1436] The terminal transmits the emotion information recognized by the emotion engine to the server.

[1437] Step 3:

[1438] The server manages the received emotion information.

[1439] Step 4:

[1440] The server dynamically adjusts remote work task priorities and travel plan suggestions based on the recognized emotional information. For example, if the user is feeling stressed, it may lower the priority of a task to reduce the burden or suggest additional breaks.

[1441] Step 5:

[1442] The server stores the adjusted task information and travel plans in a database.

[1443] Step 6:

[1444] The terminal retrieves the adjustment information from the server and visually displays it to the user.

[1445] Step 7:

[1446] The server analyzes the emotional information and generates advice aimed at reducing the user's stress and improving their motivation.

[1447] Step 8:

[1448] The device notifies the user of advice generated by the server, such as "Take a break" or "Take a deep breath and relax."

[1449] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[1450] Example 2

[1451] 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."

[1452] Conventional remote work and travel planning management systems have difficulty providing distributed functions in an integrated manner. Furthermore, they lack the ability to recognize and dynamically respond to users' emotions in real time, which hinders the improvement of users' work-life balance. This leaves users without a means to efficiently manage tasks and create optimal travel plans.

[1453] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving remote work task information input by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for recognizing the user's emotions, and means for dynamically adjusting the content of the task or travel plan based on the recognized emotion information. This enables efficient, unified management of the user's remote work and travel planning, and also enables appropriate responses according to the user's emotions.

[1454] "Remote work" refers to work done over a communications network such as the internet.

[1455] "Task information" is detailed information about a task item that a user must perform, and includes a title, description, priority, deadline, and the like.

[1456] "Tokenization" refers to the process of analyzing information and breaking it down into smaller units (tokens) based on meaning and structure.

[1457] "Database" means an electronic system for efficiently and securely storing and managing digital data.

[1458] "Task progress management" refers to the process of monitoring and updating the progress of a task (not started, in progress, completed, etc.) based on stored task information.

[1459] "Travel planning" refers to creating a plan based on conditions such as the travel destination, budget, and number of days.

[1460] A "generative AI model" refers to a computer program that uses artificial intelligence technology to provide generated content or answers based on input conditions.

[1461] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state (e.g., stress, happiness, anxiety, etc.).

[1462] "Dynamic adjustment" refers to the process of changing content and settings in real time based on the situation.

[1463] A "dashboard" refers to an interface for visually and comprehensively displaying various information.

[1464] The system according to the present invention provides a unified management system for improving the efficiency of remote work and travel planning for users, and also provides a function for recognizing and dynamically responding to user emotions. The system of the present invention includes the following components.

[1465] 1. A means of receiving task information for a user's remote work

[1466] Terminal: The user accesses a task management interface and enters the task title, description, priority, due date, etc. For example, the user adds a task called "Write a progress report for Project X" and sets the priority to high and the due date to the end of this week.

[1467] Server: Receives task information sent from the device.

[1468] 2. A way to tokenize task information and store it in a database

[1469] Server: Tokenizes the received task information and stores it securely in a database. Specifically, the task information is split into tokens such as "Project X," "Progress Report," "Created," "High," and "This weekend," and stored in a DBMS (e.g., MySQL).

[1470] 3. A way to manage task progress based on saved task information

[1471] Server: Manages task information appropriately and tracks task progress status (not started, in progress, completed, etc.) When a user updates a task, the server updates the corresponding record in the database.

[1472] 4. How the device displays task progress

[1473] On the device: Users can visually see the progress of their tasks on a dashboard, with incomplete tasks displayed in red, in progress in yellow, and completed in green.

[1474] 5. Means for receiving travel planning condition information from a user

[1475] User: Accesses a travel planning interface and inputs travel destination, budget, number of days, etc. For example, a user might set the conditions as "Tokyo," "300,000 yen," and "5 days."

[1476] Server: Receives travel condition information sent from the terminal.

[1477] 6. A means of generating a travel plan based on received travel condition information via an external generative AI model

[1478] Server: Provides the received travel condition information to an external generative AI model and generates a travel plan. Specifically, it sends the following prompt to the generative AI model:

[1479] "Please create a five-day travel plan for Tokyo with a budget of 300,000 yen."

[1480] 7. Means of presenting the generated travel plan to the user

[1481] Server: Retrieves the generated itinerary, formats it as needed, and sends it to the device.

[1482] Device: The user can visually check the generated travel plan on a dashboard, for example, displaying the itinerary and cost list.

[1483] 8. How to Recognize User Emotions

[1484] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine. For example, a facial expression recognition API can be used to determine "stress" or "happiness."

[1485] 9. A means of dynamically adjusting the content of a task or itinerary based on recognized emotional information

[1486] Server: Dynamically adjust task priorities and travel plan suggestions based on recognized emotion data. For example, if the user is feeling stressed, lower the priority or suggest additional breaks to reduce task load.

[1487] These components enable the system of the present invention to comprehensively support users in improving the efficiency of remote work and travel planning, and also to flexibly respond to users' emotions. Users can efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[1488] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1489] Processing flow and specific operations

[1490] Task Management

[1491] Step 1:

[1492] The user accesses the task management interface and inputs the task title, description, priority, deadline, etc. The task information is sent to the server as input data. Specifically, the user inputs information such as "Create a progress report for Project X," "High," and "This weekend."

[1493] Step 2:

[1494] The device sends the entered task information to the server's API endpoint via an HTTP POST request. The input is the task information entered by the user, and the output is the status of successful submission to the server.

[1495] Step 3:

[1496] The server receives an HTTP request and tokenizes the task information. Specifically, it splits the task information into tokens such as "Project X," "Progress Report," "Create," "High," and "This Weekend." The input is the received task information, and the output is the tokenized task data.

[1497] Step 4:

[1498] The server stores the tokenized task data in a database (e.g., MySQL). The input is the tokenized task data, and the output is the task information stored in the database.

[1499] Step 5:

[1500] The server manages the task progress and tracks and updates the progress status (not started, in progress, completed, etc.). For example, when a user marks a task as progressed, the server updates the corresponding record in the database. The input is the current task information and the user's actions, and the output is the updated task progress status.

[1501] Step 6:

[1502] The terminal periodically retrieves task progress information from the server and displays it visually on a dashboard. Specifically, tasks that have not been started are displayed in red, tasks in progress in yellow, and completed tasks in green. The input is the progress data retrieved from the server, and the output is the visual display to the user.

[1503] Travel Planning

[1504] Step 1:

[1505] The user accesses the trip planning interface and inputs travel conditions such as destination, budget, and number of days. The travel condition information is sent as input data to the server. Specifically, the user enters the conditions "Tokyo," "300,000 yen," and "5 days."

[1506] Step 2:

[1507] The device sends the entered travel condition information to the server's API endpoint via an HTTP POST request. The input is the travel condition information entered by the user, and the output is the status of successful transmission to the server.

[1508] Step 3:

[1509] The server receives the HTTP request and provides the received travel condition information to an external generative AI model. Specifically, it sends the following prompt to the generative AI model: "Please create a 5-day travel plan for Tokyo. The budget is 300,000 yen." The input is the received travel condition information, and the output is the prompt sent to the generative AI model.

[1510] Step 4:

[1511] The server retrieves the itinerary from the generative AI model and formats it as needed. The input is the generated itinerary, and the output is the formatted itinerary data.

[1512] Step 5:

[1513] The server sends the travel plan data to the terminal. The input is the formatted travel plan data, and the output is the status of successful transmission to the terminal.

[1514] Step 6:

[1515] The terminal visually displays the travel plan on a dashboard, specifically showing the itinerary, cost list, etc. The input is the travel plan data sent from the server, and the output is the visual display to the user.

[1516] Emotion Recognition and Dynamic Regulation

[1517] Step 1:

[1518] The device uses an emotion engine to analyze the user's facial expressions and voice in real time and recognize their emotions. Specifically, it uses a facial expression recognition API to determine "stress" and "happiness." The input is the user's video and audio data, and the output is recognized emotional data.

[1519] Step 2:

[1520] The device sends the recognized emotion data to the server via an HTTP POST request. The input is the recognized emotion data, and the output is the status of successful transmission to the server.

[1521] Step 3:

[1522] The server receives emotional information and dynamically adjusts task priorities and travel plan suggestions based on that information. For example, if the user is feeling stressed, the server lowers task priorities to reduce the task load. The input is the received emotional information, and the output is the adjusted task or travel plan data.

[1523] Step 4:

[1524] The server sends the adjusted task or travel plan data to the terminal, where the input is the adjusted task or travel plan data and the output is a transmission success status to the terminal.

[1525] Step 5:

[1526] The device generates advice based on the emotion data and notifies the user. For example, it displays advice such as "Take a deep breath" or "We recommend taking a short break." The input is the advice data sent from the server, and the output is a visual display to the user.

[1527] (Application example 2)

[1528] 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."

[1529] While modern factory robots efficiently perform a variety of tasks, their long working hours and complex operations have led to problems with declining operational efficiency and reliability. In particular, the lack of emotion-based maintenance or dynamic task adjustments increases the risk of unexpected malfunctions and operational shutdowns. Furthermore, the lack of a means to comprehensively manage robots' operational efficiency and maintenance plans in real time makes it difficult for managers to respond appropriately. Given these circumstances, there is a growing need for a system that improves the operational efficiency and reliability of factory robots.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1531] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from a user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for receiving robot emotion data using an emotion recognition engine, means for dynamically adjusting the robot's task priority based on the emotion data, and means for presenting the generated travel plan to the user. This enables centralized management of factory robot work efficiency and maintenance plans, and dynamic adjustment of tasks based on emotion data.

[1532] A "user" is an entity that uses this system to input task information and set travel conditions.

[1533] "Remote work task information" refers to detailed task information entered by a user to manage remote work, including the task title, description, priority, deadline, etc.

[1534] "Tokenization" is a method of securely storing received data in a database using methods such as encryption and hashing.

[1535] "Database" means a collection of data that securely stores tokenized task information and makes it accessible as needed.

[1536] "Task progress management" is the process of tracking and updating the progress status of a task based on stored task information.

[1537] "Travel planning condition information" is condition information such as the travel destination, budget, number of days, etc. that the user sets when planning a trip.

[1538] An "external generative AI model" is an artificial intelligence model that receives travel condition information set by the user and generates a travel plan based on that information.

[1539] A "travel plan" is a detailed travel schedule or itinerary created by a generative AI model based on travel planning condition information.

[1540] An "emotion recognition engine" is an engine that analyzes a robot's emotional data (such as vibrations and temperature) in real time and identifies its emotional state.

[1541] "Emotion data" is data that indicates the current emotional state of the robot, obtained by the emotion recognition engine.

[1542] "Dynamic adjustment of task priorities" is a process that automatically changes task priorities based on acquired emotional data to optimize the robot's workload.

[1543] A "maintenance plan" is a plan to create a maintenance schedule based on the robot's emotional data and maintain the robot's performance.

[1544] "Integrated display" means that users can see the progress of remote work tasks and the status of travel plans all in one dashboard.

[1545] This invention relates to a system that manages the work efficiency and maintenance plans of factory robots in an integrated manner and dynamically adjusts task priorities based on emotion data. The specific configuration and operation of the system are described below.

[1546] The system includes the following major hardware and software components:

[1547] Hardware

[1548] Factory robots: Robots equipped with emotion recognition sensors and controlled remotely.

[1549] Server: A central server that manages tasks, generates travel plans, and manages emotion data.

[1550] software

[1551] Task Management API: An API for receiving task information, tokenizing it, and storing it in a database.

[1552] Emotion recognition engine: An engine that analyzes the robot's emotional data (e.g., vibration and temperature) and identifies its emotional state.

[1553] Generative AI model: An AI model for generating optimal travel plans based on received travel condition information.

[1554] System Operation

[1555] 1. User task management

[1556] Users access the task management interface remotely and enter detailed task information (title, description, priority, deadline, etc.). The entered task information is sent to the server via the terminal. The server tokenizes the received task information, stores it in a database, and manages the task progress.

[1557] 2. Generate a travel plan

[1558] The user accesses a trip planning interface and inputs travel conditions (destination, budget, number of days, etc.). The input information is sent to the server via the device, and the server provides this information to an external generative AI model to generate a travel plan. The generated travel plan is then presented to the user via the server.

[1559] 3. Acquiring Emotional Data and Dynamic Task Adjustment

[1560] The robot's emotion recognition sensors monitor the robot's condition (e.g., vibration and temperature) in real time, and the emotion recognition engine analyzes this to generate emotion data. The generated emotion data is sent to the server, and task priorities are automatically adjusted. For example, if the robot is feeling "stressed," the task priority will be changed to "urgent" and a maintenance notification will be issued immediately.

[1561] Specific examples

[1562] For example, consider the case where a manager assigns a task called "Routine Maintenance" to a factory robot. This task information is sent to the server via an input terminal, tokenized, and stored in a database. Meanwhile, if the robot's emotion recognition sensor detects an emotional state of "stress," the server will use this emotional data to adjust the task priority to "urgent" and immediately send a maintenance notification to the manager.

[1563] Prompt Sentence Examples

[1564] An example of a prompt to be input to the generative AI model is as follows:

[1565] Robot ID: 1

[1566] Emotional state: Stress

[1567] Recommended action: Prompt maintenance

[1568] Task Priority: Urgent

[1569] This prompt is then fed into a generative AI model and used to generate an optimal plan of action or set of actions.

[1570] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1571] Step 1:

[1572] The user inputs task information for remote work. The terminal receives the input information such as the task title, description, priority, and deadline, and sends it to the server. Input: Task information (title, description, priority, deadline). Output: Task information sent to the server.

[1573] Step 2:

[1574] The server receives task information and tokenizes each task. The tokenized task information is saved in a database. Input: Task information received from the device. Output: Tokenized task information saved in a database.

[1575] Step 3:

[1576] The server manages task progress based on task information stored in the database. It tracks task progress status (e.g. not started, in progress, completed) and updates it as needed. Input: Task information stored in the database. Output: Updated task progress status.

[1577] Step 4:

[1578] The user inputs travel plan condition information. The terminal receives condition information such as travel destination, budget, number of days, etc. and sends it to the server. Input: Travel plan condition information (travel destination, budget, number of days). Output: Travel condition information sent to the server.

[1579] Step 5:

[1580] The server receives travel condition information and provides it to an external generative AI model to generate a travel plan. The generated travel plan is organized and saved in a database. Input: Travel condition information provided to the external generative AI model. Output: Generated travel plan.

[1581] Step 6:

[1582] The generated itinerary is sent from the server to the terminal and presented to the user. Input: Generated itinerary. Output: Itinerary visually displayed on the terminal.

[1583] Step 7:

[1584] The robot's emotion recognition sensor acquires the robot's emotion data in real time, and the emotion recognition engine analyzes this emotion data. Input: Emotion data acquired from the robot. Output: Analyzed emotional state.

[1585] Step 8:

[1586] The emotion recognition engine sends the analyzed emotion data to the server, which then dynamically adjusts task priorities based on the emotion data. Input: Analyzed emotion data. Output: Adjusted task priorities.

[1587] Step 9:

[1588] The server analyzes the emotion data and sends appropriate maintenance notifications to the user or administrator. For example, if the robot's emotional state is "stressed," it issues a notification saying "Perform prompt maintenance." Input: Analyzed emotion data. Output: Maintenance notification sent to the user or administrator.

[1589] 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.

[1590] 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.

[1591] 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.

[1592] [Fourth embodiment]

[1593] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1594] 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.

[1595] 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).

[1596] 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.

[1597] 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.

[1598] 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).

[1599] 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.

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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.

[1604] 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.

[1605] 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."

[1606] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[1607] Components:

[1608] 1. A means of receiving task information for a user's remote work

[1609] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[1610] Server: Receives task information sent from the device.

[1611] 2. A way to tokenize task information and store it in a database

[1612] Server: Tokenizes received task information and stores it securely in a database.

[1613] 3. A way to manage task progress based on saved task information

[1614] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[1615] Terminal: Provides the user with a visual indication of task progress.

[1616] 4. Means for receiving travel planning condition information from a user

[1617] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[1618] Server: Receives travel condition information sent from the terminal.

[1619] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[1620] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1621] 6. Means of presenting the generated travel plan to the user

[1622] Server: Retrieves the generated travel plan and sends it to the device.

[1623] Terminal: Visually displays the generated itinerary to the user.

[1624] Specific operation explanation:

[1625] User task management

[1626] 1. User enters a task:

[1627] The user accesses the task management interface, enters detailed information about the task, and submits it.

[1628] 2. The device sends task information to the server:

[1629] The terminal transmits the input task information to the server.

[1630] 3. The server receives the task information and tokenizes it:

[1631] The server tokenizes the received task information and stores it securely in a database.

[1632] 4. The server manages the task progress:

[1633] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[1634] 5. The device will display the task progress:

[1635] Users can visually check task progress on a dashboard.

[1636] User travel planning

[1637] 1. User enters travel requirements:

[1638] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[1639] 2. The device sends travel condition information to the server:

[1640] The terminal transmits the input travel condition information to the server.

[1641] 3. The server receives the travel condition information and provides it to the AI ​​model:

[1642] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[1643] 4. The server retrieves the generated itinerary:

[1644] The server retrieves the travel plan generated from the AI ​​model and sends it to the device.

[1645] 5. The device displays your travel plan:

[1646] Users can visually check the generated travel plan on a dashboard.

[1647] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[1648] The processing flow will be explained below.

[1649] Task management process flow

[1650] User task management

[1651] Step 1:

[1652] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[1653] Step 2:

[1654] The terminal sends the entered task information to the server as an AJAX request.

[1655] Step 3:

[1656] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[1657] Step 4:

[1658] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[1659] Step 5:

[1660] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[1661] Step 6:

[1662] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[1663] Step 7:

[1664] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[1665] Step 8:

[1666] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[1667] Trip planning process flow

[1668] User travel planning

[1669] Step 1:

[1670] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[1671] Step 2:

[1672] The terminal sends the entered travel condition information to the server as an AJAX request.

[1673] Step 3:

[1674] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[1675] Step 4:

[1676] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[1677] Step 5:

[1678] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[1679] Step 6:

[1680] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1681] Step 7:

[1682] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[1683] Step 8:

[1684] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[1685] In this way, the roles of the user, terminal, and server work together to manage tasks and plan trips, thereby improving the user's work-life balance.

[1686] Example 1

[1687] 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."

[1688] In today's remote work environment, effective task management and trip planning are essential to maximize work efficiency. However, there are few platforms that centrally manage these functions, forcing users to use multiple tools. As a result, it is difficult to integrate task management and trip planning, making it difficult to achieve work-life balance.

[1689] 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.

[1690] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, and means for integrating and displaying the task progress and travel plan in real time on a user dashboard. This allows users to centrally manage remote work tasks and travel planning, enabling an efficient work-life balance.

[1691] "Remote work task information" is information about the specific work that a user needs to accomplish when working remotely and the progress of that work.

[1692] "Tokenization" is the process of breaking down input information into smaller units and converting each unit into a separately identifiable form.

[1693] A "database" is a system for safely and efficiently storing information so that it can be searched and retrieved later.

[1694] "Task progress status" is information indicating the progress and completion status of tasks that a user performs while working remotely.

[1695] "Planning condition information" is information relating to conditions such as travel destination, budget, number of days, etc. that a user specifies when planning a trip.

[1696] A "generative AI model" is an artificial intelligence model that has the ability to generate new information or plans based on given input.

[1697] A "travel plan" is a plan that includes details of a trip, such as a specific schedule, places to visit, and accommodation.

[1698] A "dashboard" is an interface that displays information in a format that allows users to easily view it visually.

[1699] "Real-time" means that information is reflected immediately and there is almost no time delay in updating.

[1700] The system according to the present invention provides functions for improving the efficiency of remote work and for centrally managing travel planning. The following describes each component of the system and its specific operation.

[1701] Components:

[1702] 1. A means for receiving task information for a user's remote work:

[1703] Terminal: The user accesses the task management interface and enters the task title, description, priority, deadline, etc. For example, the user enters information such as "Create presentation materials," "Complete by the deadline," "High," and "2023-04-30."

[1704] 2. How to tokenize task information and store it in the database:

[1705] Server: Receives task information sent from the device, tokenizes it, and stores it in a database such as MongoDB.

[1706] 3. How to manage task progress based on saved task information:

[1707] Server: Tracks and manages the progress status (not started, in progress, completed, etc.) based on task information, and monitors the user's progress.

[1708] 4. How to display task progress based on saved task information:

[1709] On the device: Users can visually check task progress on a dashboard, which is visualized in graphs and lists.

[1710] 5. Means for receiving travel planning requirements information from a user:

[1711] User: Accesses a trip planning interface and enters travel destination, budget, number of days, etc. For example, the user enters "Tokyo as destination," "100,000 yen as budget," and "3 days as number of days."

[1712] 6. A means for generating a travel plan via an external generative AI model based on the received travel condition information:

[1713] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan. The generative AI model used is OpenAI's GPT-3. An example of a prompt is "Please create a three-day travel plan to Tokyo. The budget is 100,000 yen."

[1714] 7. Means for presenting the generated travel plan to the user:

[1715] Server: Takes the generated itinerary, formats it appropriately, and sends it to the device.

[1716] Terminal: The user visually checks the generated itinerary on a dashboard.

[1717] 8. Integrated display of task progress and travel plans:

[1718] Terminal: Task progress and travel plans retrieved from the server are displayed in a unified manner, allowing users to simultaneously manage their remote work progress and travel plans.

[1719] This system allows users to centrally manage remote work tasks and plan trips, enabling them to efficiently achieve a work-life balance.The present invention provides a consistent platform that solves the challenges of remote work while simultaneously resolving the problems of travel planning.

[1720] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1721] System program processing flow

[1722] Step 1:

[1723] User enters task

[1724] User: Accesses the task management interface and enters the task title, description, priority, due date, etc.

[1725] Input: "Create presentation materials" "Complete by deadline" "Expensive" "2023-04-30"

[1726] What happens: A user fills out a form and clicks the "Submit" button. The data is converted from the form into JSON format data.

[1727] Step 2:

[1728] The device sends task information to the server

[1729] Terminal: Sends the entered task information to the server.

[1730] Input: Task information entered by the user (JSON format)

[1731] Output: HTTP POST request to the server

[1732] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[1733] Step 3:

[1734] The server receives and tokenizes the task information.

[1735] Server: Tokenizes the received task information and stores it in the database.

[1736] Input: Task information sent from the device (JSON format)

[1737] Output: Tokenized task information (database format)

[1738] Specific operation: Parse the JSON data, tokenize each element of the task (break it down into keywords and tags), and store it in a database such as MongoDB.

[1739] Step 4:

[1740] The server manages the task progress

[1741] Server: Manages the progress status of tasks (not started, in progress, completed, etc.) based on the saved task information.

[1742] Input: Tokenized task information stored in a database

[1743] Output: Updated task progress status

[1744] Specific behavior: Periodically check the status of each task and update the status according to user actions.

[1745] Step 5:

[1746] The device displays task progress

[1747] Terminal: Visually display task progress retrieved from the server on a dashboard.

[1748] Input: Task progress status obtained from the server

[1749] Output: Visual display of task progress

[1750] What it does: View task progress on a dashboard in graph, list, or calendar format.

[1751] Step 6:

[1752] User enters travel conditions

[1753] User: Accesses a trip planning interface and enters travel destination, budget, number of days, and other travel criteria.

[1754] Input: "Destination: Tokyo" "Budget: 100,000 yen" "Number of days: 3 days"

[1755] Specific Actions: The user fills out the form with the necessary travel requirements and clicks the "Submit" button again.

[1756] Step 7:

[1757] The device sends travel condition information to the server

[1758] Terminal: Sends the entered travel conditions information to the server.

[1759] Input: Travel conditions information entered by the user (JSON format)

[1760] Output: HTTP POST request to the server

[1761] Specific behavior: Creates an HTTP request containing form data and sends it to the server.

[1762] Step 8:

[1763] The server receives travel condition information and provides it to the AI ​​model

[1764] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1765] Input: Travel conditions information sent from the device (JSON format)

[1766] Output: A trip plan from the generative AI model

[1767] Specific behavior: Generate prompts for the AI ​​model and receive travel plans via API. Example: "Please create a three-day travel plan for Tokyo with a budget of 100,000 yen."

[1768] Step 9:

[1769] The server retrieves the generated itinerary

[1770] Server: Retrieves the itinerary generated by the AI ​​model, formats it appropriately, and sends it to the device.

[1771] Input: Travel itinerary from a generative AI model

[1772] Output: A formatted itinerary

[1773] Specific operation: Organize the obtained travel plans into a format that is easy for the user to understand.

[1774] Step 10:

[1775] The device displays the travel plan

[1776] Terminal: Visually displays the generated travel plan received from the server to the user.

[1777] Input: Formatted itinerary

[1778] Output: A visual representation of the itinerary

[1779] Specific operation: Display travel schedule, destination details, budget allocation, etc. on a dashboard.

[1780] integrated management

[1781] By following these steps, users can manage remote work tasks and travel planning in a unified manner, enabling them to efficiently achieve a work-life balance.

[1782] (Application example 1)

[1783] 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."

[1784] With the spread of remote work, there is a demand for tools to improve remote work efficiency, but conventional travel planning tools have difficulty providing plans that are linked to remote work schedules. For this reason, there is a need for a system that provides information on cafes and coworking spaces that users can use while working remotely, and can also centrally manage on-site remote work and travel planning.

[1785] 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.

[1786] In this invention, the server includes means for receiving remote work task information entered by a user via a task management interface, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel planning condition information from the user via a travel planning interface, means for generating a travel plan via a generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for providing store information available during remote work, and means for obtaining store reservations and usage status using an external service based on the user's current location information. This allows users to centrally manage their remote work and travel plans, further improving the efficiency of remote work.

[1787] The "task management interface" is a user interface that allows a user to input and send task information for remote work.

[1788] "Task information" is data about remote work, including detailed information such as the task title, description, priority, and deadline.

[1789] "Tokenization" is the process of converting received information into a format that can be securely processed and stored, for example by encrypting or encoding it.

[1790] A "database" is a digital warehouse for safely storing and managing users' task information, progress, and so on.

[1791] "Task progress" is status data that tracks and manages the status of a task, such as not started, in progress, or completed, based on saved task information.

[1792] The "interface for travel planning" is a user interface that allows a user to input and transmit travel planning condition information.

[1793] "Travel planning condition information" is condition data necessary when planning a trip, such as the travel destination, budget, number of days, etc.

[1794] A "generative AI model" is an artificial intelligence model that generates optimal travel plans based on travel planning condition information received from a user.

[1795] A "travel plan" is a specific plan that includes the travel destination, itinerary, places to visit, accommodation, etc.

[1796] "Store information available for use while working remotely" refers to information about facilities that can be used while working remotely, such as cafes and coworking spaces.

[1797] "User's current location information" means current geographic location data obtained from a user's smartphone or other device.

[1798] "External Services" are external software services, such as APIs and databases provided by third parties, that are used to extend the functionality of an application.

[1799] "Obtaining store reservations and usage status" refers to the process of using the provided API or database to obtain information such as the reservation status and current congestion level of a specific cafe or coworking space.

[1800] The system "Remote Cafe & Trip" of the present invention provides functions for improving the efficiency of users' remote work and centrally managing travel planning. Each component of the system and its specific operation are described below.

[1801] Components:

[1802] Task management interface

[1803] The user inputs remote task information through a task management interface. The device then sends the received task information to the server. The task information entered by the user includes details such as the task title, description, priority, and deadline.

[1804] Tokenized data storage

[1805] The server tokenizes the received task information and stores it securely in a database. The tokenization process ensures data security.

[1806] Task progress management

[1807] The server manages the progress of tasks based on the saved task information. It tracks the progress status (not started, in progress, completed, etc.) and displays it on the user's device. The user can visually check the progress of the task.

[1808] Trip planning interface

[1809] The user uses a trip planning interface to input conditions such as the travel destination, budget, and number of days, and sends the input to the server.

[1810] Travel plan generation using generative AI models

[1811] The server sends prompts to the generative AI model based on the received travel condition information to generate a travel plan. This generative AI model uses OpenAI's API.

[1812] Presenting your travel plan

[1813] The server acquires the generated itinerary and sends it to the user's terminal, where the user can visually display the generated itinerary.

[1814] Providing store information that can be used while working remotely

[1815] The server uses external services (such as Google Maps API) based on the user's current location information to obtain information about nearby cafes and coworking spaces, allowing users to easily find stores they can use while working remotely.

[1816] Obtaining store reservations and usage status

[1817] The server uses external services to obtain reservation and usage status for specific cafes and coworking spaces and provides this information to users.

[1818] Examples:

[1819] Task Management

[1820] For example, when a user enters a task to create a monthly report, they enter the following information into the interface: "Create monthly report," "Create monthly sales performance report," "High," "2023-10-31." The device sends this to the server, where it is tokenized and stored in the database. The task progress is then displayed on the dashboard.

[1821] Travel plan generation

[1822] If a user inputs travel criteria such as "Kyoto," "budget of 100,000 yen," and "3 days," the server sends the following prompt to the generative AI model:

[1823] "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[1824] The answer from the AI ​​model is

[1825] Day 1: After arriving at Kyoto Station, visit Kiyomizu-dera Temple and Gion. Visit Fushimi Inari Taisha Shrine, and have dinner around Kyoto Station in the evening.

[1826] Day 2: Visit Kinkakuji Temple and Ryoanji Temple. Visit Arashiyama in the evening and stroll through the bamboo forest. Dinner in Arashiyama.

[1827] Day 3: Visit the Kyoto National Museum. In the afternoon, stroll through Kyoto Gyoen National Garden and have lunch along the Kamo River. In the evening, return to Kyoto Station for the return journey.

[1828] The plan is generated and presented to the user.

[1829] This system allows users to centrally manage their remote work and travel plans, improving the efficiency of remote work.

[1830] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1831] Step 1:

[1832] The user enters remote work task information through a task management interface. The task information entered by the user includes the task title, description, priority, and deadline. For example, input data such as "Create monthly report," "Create monthly sales performance report," "High," and "2023-10-31" is sent.

[1833] Step 2:

[1834] The device sends the task information entered by the user to the server. At this time, the entered task information is configured as a data packet and passed to the server via the network. The input data is JSON format data of the task information.

[1835] Step 3:

[1836] The server tokenizes the received task information. Tokenization is the process of encrypting or encoding input data to make it safe to handle. For example, input data such as "Create monthly report" is converted to "token1234."

[1837] Step 4:

[1838] The server stores the tokenized task information in the database. At this time, the tokenized information is inserted into the appropriate field in the database and the index information is updated. For example, "token1234" is stored in the task information table in the database.

[1839] Step 5:

[1840] The server manages the progress of tasks based on the stored task information and tracks their progress status. The server uses an algorithm to manage the task state (not started, in progress, completed) and updates the progress in conjunction with the database. For example, "in progress" may be updated to "completed."

[1841] Step 6:

[1842] The user accesses the trip planning interface, inputs travel information (destination, budget, number of days), and sends it to the server via the terminal. The input data sent is "Kyoto," "budget of 100,000 yen," and "3 days."

[1843] Step 7:

[1844] The server sends a prompt to the generative AI model based on the received travel condition information. This prompt is composed of a natural language sentence that includes the travel condition information. An example of a prompt sentence is, "Travel conditions: Destination is Kyoto, budget is 100,000 yen, number of days is 3. Please generate a recommended travel plan."

[1845] Step 8:

[1846] The generative AI model takes a prompt as input and generates a travel plan using natural language processing and machine learning algorithms. Based on the input, the AI ​​model suggests suitable travel destinations, sightseeing spots, and itineraries.

[1847] Step 9:

[1848] The server retrieves the generated travel plan and sends it to the terminal to present to the user. The generated travel plan is configured as data and transferred to the terminal via the network. The output data may be in the form of, for example, "Day 1: Kiyomizu-dera Temple, Day 2: Kinkaku-ji Temple."

[1849] Step 10:

[1850] Users can request information about available stores through their devices while working remotely. The user's current location information is acquired and sent to the server.

[1851] Step 11:

[1852] The server uses an external service (e.g., Google Maps API) to obtain information about nearby cafes and coworking spaces based on the user's current location. The server sends an API request and stores the store information obtained from the external service in a database.

[1853] Step 12:

[1854] The server presents store information to the user's device based on the acquired store information. By also displaying the store's reservation status and usage status, the user can select an appropriate store while working remotely. The output data will be information such as "Nearby Cafe A, reservation status is available."

[1855] 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.

[1856] The system of the present invention centrally manages the efficiency of users' remote work and travel planning, and also provides the function of recognizing and dynamically responding to users' emotions. Each component of the system and its specific operation are described below.

[1857] Components:

[1858] 1. A means of receiving task information for a user's remote work

[1859] Terminal: The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and submits it.

[1860] Server: Receives task information sent from the device.

[1861] 2. A way to tokenize task information and store it in a database

[1862] Server: Tokenizes received task information and stores it securely in a database.

[1863] 3. A way to manage task progress based on saved task information

[1864] Server: Properly manages task information and tracks task progress status (not started, in progress, completed, etc.).

[1865] Terminal: Provides the user with a visual indication of task progress.

[1866] 4. Means for receiving travel planning condition information from a user

[1867] User: Accesses a trip planning interface, enters travel destination, budget, number of days, and other information, and submits it.

[1868] Server: Receives travel condition information sent from the terminal.

[1869] 5. A means of generating a travel plan based on received travel condition information via an external generative AI model

[1870] Server: Provides the received travel condition information to an external generative AI model to generate a travel plan.

[1871] 6. Means of presenting the generated travel plan to the user

[1872] Server: Retrieves the generated travel plan and sends it to the device.

[1873] Terminal: Visually displays the generated itinerary to the user.

[1874] 7. Emotion engine that recognizes user emotions

[1875] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine.

[1876] Server: Receives and manages emotion data recognized by the emotion engine.

[1877] 8. A method for automatically adjusting task and travel plan content based on recognized emotional information

[1878] Server: Dynamically adjusts task priorities and travel plan suggestions based on recognized emotion data.

[1879] 9. A means of analyzing emotional information and providing advice

[1880] Server: Analyzes emotional data and generates advice aimed at reducing stress and improving motivation.

[1881] Terminal: Notifies the user of advice from the server.

[1882] Specific operation explanation:

[1883] User task management

[1884] 1. User enters a task:

[1885] The user accesses the task management interface, enters detailed information about the task, and submits it.

[1886] 2. The device sends task information to the server:

[1887] The terminal transmits the input task information to the server.

[1888] 3. The server receives the task information and tokenizes it:

[1889] The server tokenizes the received task information and stores it securely in a database.

[1890] 4. The server manages the task progress:

[1891] Based on the saved task information, the server manages the progress of the task and updates it as necessary.

[1892] 5. The device will display the task progress:

[1893] Users can visually check task progress on a dashboard.

[1894] User travel planning

[1895] 1. User enters travel requirements:

[1896] Users access a trip planning interface, enter conditions such as destination, budget, and number of days, and submit the information.

[1897] 2. The device sends travel condition information to the server:

[1898] The terminal transmits the input travel condition information to the server.

[1899] 3. The server receives the travel condition information and provides it to the AI ​​model:

[1900] The server provides the received travel condition information to an external generative AI model to generate a travel plan.

[1901] 4. The server retrieves the generated itinerary:

[1902] The server retrieves the itinerary generated by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1903] 5. The device displays your travel plan:

[1904] Users can visually check the generated travel plan on a dashboard.

[1905] User Emotion Recognition and Dynamic Adjustment

[1906] 1. Recognize user emotions:

[1907] The emotion engine analyzes the user's facial expressions and voice in real time to identify the user's current emotion (e.g., stress, happiness, anxiety, etc.).

[1908] 2. The device sends emotional information to the server:

[1909] The device transmits the recognized emotion data to the server.

[1910] 3. The server manages emotional information and adjusts tasks and travel plans:

[1911] The server dynamically adjusts task priorities and travel plan suggestions based on emotion data. For example, if a user is feeling stressed, it may lower task priorities or suggest additional breaks to reduce task load.

[1912] 4. Analyze sentiment information and generate advice:

[1913] The server analyzes the emotional data and generates advice aimed at reducing the user's stress and increasing their motivation.

[1914] 5. The device notifies the user of the advice:

[1915] The device notifies the user of the generated advice, such as "Take a break" or "Take a deep breath and relax."

[1916] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[1917] The processing flow will be explained below.

[1918] Task management process flow

[1919] User task management

[1920] Step 1:

[1921] The user accesses the task management interface, enters the task title, description, priority, deadline, etc., and presses the "Submit" button.

[1922] Step 2:

[1923] The terminal sends the entered task information to the server as an AJAX request.

[1924] Step 3:

[1925] The server validates the task information received, specifically checking whether it has a title, the number of characters in the description, the priority range, the due date format, etc.

[1926] Step 4:

[1927] The server tokenizes the validated task information and stores it securely in a database. Tokenization is a security measure to protect personal information.

[1928] Step 5:

[1929] The server returns a message to the terminal indicating that the task was successfully saved, or an error message if the save fails.

[1930] Step 6:

[1931] The device receives a successful save message from the server and notifies the user that the task was added successfully. If an error message was returned, it is displayed to the user.

[1932] Step 7:

[1933] The server updates the task progress status (not started, in progress, completed, etc.) as appropriate based on the saved task information. When the task progress is updated, the information is also reflected in the database.

[1934] Step 8:

[1935] The device displays task progress to the user in real time, allowing the user to view the current task status on a dashboard.

[1936] Trip planning process flow

[1937] User travel planning

[1938] Step 1:

[1939] The user accesses the travel planning interface, inputs travel condition information such as travel destination, budget, number of days, purpose, etc., and presses the "Submit" button.

[1940] Step 2:

[1941] The terminal sends the entered travel condition information to the server as an AJAX request.

[1942] Step 3:

[1943] The server validates the travel conditions information received, specifically checking the accuracy of the travel destination, budget range, and the format of the number of days.

[1944] Step 4:

[1945] The server provides the travel condition information that has passed validation to an external generative AI model to generate a travel plan.

[1946] Step 5:

[1947] The generative AI model creates a travel plan based on the user's requirements and returns the created travel plan to the server.

[1948] Step 6:

[1949] The server receives the itinerary returned by the AI ​​model, formats it as needed, and sends the formatted itinerary information to the device.

[1950] Step 7:

[1951] The terminal visually displays the travel plan received from the server to the user, allowing the user to check the proposed travel plan on a dashboard.

[1952] Step 8:

[1953] The user can review the displayed itinerary and make any necessary modifications, which are then sent back to the server, where the AI ​​model creates an updated itinerary.

[1954] Emotion recognition and dynamic adjustment processing flow

[1955] User Emotion Recognition and Dynamic Adjustment

[1956] Step 1:

[1957] While the user is using the system, the emotion engine analyzes the user's facial expressions and voice in real time to identify their current emotion (e.g., stress, happiness, anxiety, etc.).

[1958] Step 2:

[1959] The terminal transmits the emotion information recognized by the emotion engine to the server.

[1960] Step 3:

[1961] The server manages the received emotion information.

[1962] Step 4:

[1963] The server dynamically adjusts remote work task priorities and travel plan suggestions based on the recognized emotional information. For example, if the user is feeling stressed, it may lower the priority of a task to reduce the burden or suggest additional breaks.

[1964] Step 5:

[1965] The server stores the adjusted task information and travel plans in a database.

[1966] Step 6:

[1967] The terminal retrieves the adjustment information from the server and visually displays it to the user.

[1968] Step 7:

[1969] The server analyzes the emotional information and generates advice aimed at reducing the user's stress and improving their motivation.

[1970] Step 8:

[1971] The device notifies the user of advice generated by the server, such as "Take a break" or "Take a deep breath and relax."

[1972] In this way, the system of the present invention contributes to improving the user's work-life balance by unifying the management of the user's remote work efficiency and travel planning, and by recognizing and dynamically responding to the user's emotions in real time. This system allows users to efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[1973] Example 2

[1974] 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."

[1975] Conventional remote work and travel planning management systems have difficulty providing distributed functions in an integrated manner. Furthermore, they lack the ability to recognize and dynamically respond to users' emotions in real time, which hinders the improvement of users' work-life balance. This leaves users without a means to efficiently manage tasks and create optimal travel plans.

[1976] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving remote work task information input by a user, means for tokenizing the received task information and storing it in a database, means for managing task progress based on the stored task information, means for receiving travel plan condition information from the user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for presenting the generated travel plan to the user, means for recognizing the user's emotions, and means for dynamically adjusting the content of the task or travel plan based on the recognized emotion information. This enables efficient, unified management of the user's remote work and travel planning, and also enables appropriate responses according to the user's emotions.

[1977] "Remote work" refers to work done over a communications network such as the internet.

[1978] "Task information" is detailed information about a task item that a user must perform, and includes a title, description, priority, deadline, and the like.

[1979] "Tokenization" refers to the process of analyzing information and breaking it down into smaller units (tokens) based on meaning and structure.

[1980] "Database" means an electronic system for efficiently and securely storing and managing digital data.

[1981] "Task progress management" refers to the process of monitoring and updating the progress of a task (not started, in progress, completed, etc.) based on stored task information.

[1982] "Travel planning" refers to creating a plan based on conditions such as the travel destination, budget, and number of days.

[1983] A "generative AI model" refers to a computer program that uses artificial intelligence technology to provide generated content or answers based on input conditions.

[1984] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state (e.g., stress, happiness, anxiety, etc.).

[1985] "Dynamic adjustment" refers to the process of changing content and settings in real time based on the situation.

[1986] A "dashboard" refers to an interface for visually and comprehensively displaying various information.

[1987] The system according to the present invention provides a unified management system for improving the efficiency of remote work and travel planning for users, and also provides a function for recognizing and dynamically responding to user emotions. The system of the present invention includes the following components.

[1988] 1. A means of receiving task information for a user's remote work

[1989] Terminal: The user accesses a task management interface and enters the task title, description, priority, due date, etc. For example, the user adds a task called "Write a progress report for Project X" and sets the priority to high and the due date to the end of this week.

[1990] Server: Receives task information sent from the device.

[1991] 2. A way to tokenize task information and store it in a database

[1992] Server: Tokenizes the received task information and stores it securely in a database. Specifically, the task information is split into tokens such as "Project X," "Progress Report," "Created," "High," and "This weekend," and stored in a DBMS (e.g., MySQL).

[1993] 3. A way to manage task progress based on saved task information

[1994] Server: Manages task information appropriately and tracks task progress status (not started, in progress, completed, etc.) When a user updates a task, the server updates the corresponding record in the database.

[1995] 4. How the device displays task progress

[1996] On the device: Users can visually see the progress of their tasks on a dashboard, with incomplete tasks displayed in red, in progress in yellow, and completed in green.

[1997] 5. Means for receiving travel planning condition information from a user

[1998] User: Accesses a travel planning interface and inputs travel destination, budget, number of days, etc. For example, a user might set the conditions as "Tokyo," "300,000 yen," and "5 days."

[1999] Server: Receives travel condition information sent from the terminal.

[2000] 6. A means of generating a travel plan based on received travel condition information via an external generative AI model

[2001] Server: Provides the received travel condition information to an external generative AI model and generates a travel plan. Specifically, it sends the following prompt to the generative AI model:

[2002] "Please create a five-day travel plan for Tokyo with a budget of 300,000 yen."

[2003] 7. Means of presenting the generated travel plan to the user

[2004] Server: Retrieves the generated itinerary, formats it as needed, and sends it to the device.

[2005] Device: The user can visually check the generated travel plan on a dashboard, for example, displaying the itinerary and cost list.

[2006] 8. How to Recognize User Emotions

[2007] Device: Analyzes the user's facial expressions and voice in real time and recognizes emotions using an emotion engine. For example, a facial expression recognition API can be used to determine "stress" or "happiness."

[2008] 9. A means of dynamically adjusting the content of a task or itinerary based on recognized emotional information

[2009] Server: Dynamically adjust task priorities and travel plan suggestions based on recognized emotion data. For example, if the user is feeling stressed, lower the priority or suggest additional breaks to reduce task load.

[2010] These components enable the system of the present invention to comprehensively support users in improving the efficiency of remote work and travel planning, and also to flexibly respond to users' emotions. Users can efficiently manage tasks, create optimal travel plans, and maintain a healthy lifestyle.

[2011] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2012] Processing flow and specific operations

[2013] Task Management

[2014] Step 1:

[2015] The user accesses the task management interface and inputs the task title, description, priority, deadline, etc. The task information is sent to the server as input data. Specifically, the user inputs information such as "Create a progress report for Project X," "High," and "This weekend."

[2016] Step 2:

[2017] The device sends the entered task information to the server's API endpoint via an HTTP POST request. The input is the task information entered by the user, and the output is the status of successful submission to the server.

[2018] Step 3:

[2019] The server receives an HTTP request and tokenizes the task information. Specifically, it splits the task information into tokens such as "Project X," "Progress Report," "Create," "High," and "This Weekend." The input is the received task information, and the output is the tokenized task data.

[2020] Step 4:

[2021] The server stores the tokenized task data in a database (e.g., MySQL). The input is the tokenized task data, and the output is the task information stored in the database.

[2022] Step 5:

[2023] The server manages the task progress and tracks and updates the progress status (not started, in progress, completed, etc.). For example, when a user marks a task as progressed, the server updates the corresponding record in the database. The input is the current task information and the user's actions, and the output is the updated task progress status.

[2024] Step 6:

[2025] The terminal periodically retrieves task progress information from the server and displays it visually on a dashboard. Specifically, tasks that have not been started are displayed in red, tasks in progress in yellow, and completed tasks in green. The input is the progress data retrieved from the server, and the output is the visual display to the user.

[2026] Travel Planning

[2027] Step 1:

[2028] The user accesses the trip planning interface and inputs travel conditions such as destination, budget, and number of days. The travel condition information is sent as input data to the server. Specifically, the user enters the conditions "Tokyo," "300,000 yen," and "5 days."

[2029] Step 2:

[2030] The device sends the entered travel condition information to the server's API endpoint via an HTTP POST request. The input is the travel condition information entered by the user, and the output is the status of successful transmission to the server.

[2031] Step 3:

[2032] The server receives the HTTP request and provides the received travel condition information to an external generative AI model. Specifically, it sends the following prompt to the generative AI model: "Please create a 5-day travel plan for Tokyo. The budget is 300,000 yen." The input is the received travel condition information, and the output is the prompt sent to the generative AI model.

[2033] Step 4:

[2034] The server retrieves the itinerary from the generative AI model and formats it as needed. The input is the generated itinerary, and the output is the formatted itinerary data.

[2035] Step 5:

[2036] The server sends the travel plan data to the terminal. The input is the formatted travel plan data, and the output is the status of successful transmission to the terminal.

[2037] Step 6:

[2038] The terminal visually displays the travel plan on a dashboard, specifically showing the itinerary, cost list, etc. The input is the travel plan data sent from the server, and the output is the visual display to the user.

[2039] Emotion Recognition and Dynamic Regulation

[2040] Step 1:

[2041] The device uses an emotion engine to analyze the user's facial expressions and voice in real time and recognize their emotions. Specifically, it uses a facial expression recognition API to determine "stress" and "happiness." The input is the user's video and audio data, and the output is recognized emotional data.

[2042] Step 2:

[2043] The device sends the recognized emotion data to the server via an HTTP POST request. The input is the recognized emotion data, and the output is the status of successful transmission to the server.

[2044] Step 3:

[2045] The server receives emotional information and dynamically adjusts task priorities and travel plan suggestions based on that information. For example, if the user is feeling stressed, the server lowers task priorities to reduce the task load. The input is the received emotional information, and the output is the adjusted task or travel plan data.

[2046] Step 4:

[2047] The server sends the adjusted task or travel plan data to the terminal, where the input is the adjusted task or travel plan data and the output is a transmission success status to the terminal.

[2048] Step 5:

[2049] The device generates advice based on the emotion data and notifies the user. For example, it displays advice such as "Take a deep breath" or "We recommend taking a short break." The input is the advice data sent from the server, and the output is a visual display to the user.

[2050] (Application example 2)

[2051] 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."

[2052] While modern factory robots efficiently perform a variety of tasks, their long working hours and complex operations have led to problems with declining operational efficiency and reliability. In particular, the lack of emotion-based maintenance or dynamic task adjustments increases the risk of unexpected malfunctions and operational shutdowns. Furthermore, the lack of a means to comprehensively manage robots' operational efficiency and maintenance plans in real time makes it difficult for managers to respond appropriately. Given these circumstances, there is a growing need for a system that improves the operational efficiency and reliability of factory robots.

[2053] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2054] In this invention, the server includes means for receiving remote work task information entered by a user, means for tokenizing the received task information and saving it in a database, means for managing task progress based on the saved task information, means for receiving travel plan condition information from a user, means for generating a travel plan via an external generative AI model based on the received travel condition information, means for receiving robot emotion data using an emotion recognition engine, means for dynamically adjusting the robot's task priority based on the emotion data, and means for presenting the generated travel plan to the user. This enables centralized management of factory robot work efficiency and maintenance plans, and dynamic adjustment of tasks based on emotion data.

[2055] A "user" is an entity that uses this system to input task information and set travel conditions.

[2056] "Remote work task information" refers to detailed task information entered by a user to manage remote work, including the task title, description, priority, deadline, etc.

[2057] "Tokenization" is a method of securely storing received data in a database using methods such as encryption and hashing.

[2058] "Database" means a collection of data that securely stores tokenized task information and makes it accessible as needed.

[2059] "Task progress management" is the process of tracking and updating the progress status of a task based on stored task information.

[2060] "Travel planning condition information" is condition information such as the travel destination, budget, number of days, etc. that the user sets when planning a trip.

[2061] An "external generative AI model" is an artificial intelligence model that receives travel condition information set by the user and generates a travel plan based on that information.

[2062] A "travel plan" is a detailed travel schedule or itinerary created by a generative AI model based on travel planning condition information.

[2063] An "emotion recognition engine" is an engine that analyzes a robot's emotional data (such as vibrations and temperature) in real time and identifies its emotional state.

[2064] "Emotion data" is data that indicates the current emotional state of the robot, obtained by the emotion recognition engine.

[2065] "Dynamic adjustment of task priorities" is a process that automatically changes task priorities based on acquired emotional data to optimize the robot's workload.

[2066] A "maintenance plan" is a plan to create a maintenance schedule based on the robot's emotional data and maintain the robot's performance.

[2067] "Integrated display" means that users can see the progress of remote work tasks and the status of travel plans all in one dashboard.

[2068] This invention relates to a system that manages the work efficiency and maintenance plans of factory robots in an integrated manner and dynamically adjusts task priorities based on emotion data. The specific configuration and operation of the system are described below.

[2069] The system includes the following major hardware and software components:

[2070] Hardware

[2071] Factory robots: Robots equipped with emotion recognition sensors and controlled remotely.

[2072] Server: A central server that manages tasks, generates travel plans, and manages emotion data.

[2073] software

[2074] Task Management API: An API for receiving task information, tokenizing it, and storing it in a database.

[2075] Emotion recognition engine: An engine that analyzes the robot's emotional data (e.g., vibration and temperature) and identifies its emotional state.

[2076] Generative AI model: An AI model for generating optimal travel plans based on received travel condition information.

[2077] System Operation

[2078] 1. User task management

[2079] Users access the task management interface remotely and enter detailed task information (title, description, priority, deadline, etc.). The entered task information is sent to the server via the terminal. The server tokenizes the received task information, stores it in a database, and manages the task progress.

[2080] 2. Generate a travel plan

[2081] The user accesses a trip planning interface and inputs travel conditions (destination, budget, number of days, etc.). The input information is sent to the server via the device, and the server provides this information to an external generative AI model to generate a travel plan. The generated travel plan is then presented to the user via the server.

[2082] 3. Acquiring Emotional Data and Dynamic Task Adjustment

[2083] The robot's emotion recognition sensors monitor the robot's condition (e.g., vibration and temperature) in real time, and the emotion recognition engine analyzes this to generate emotion data. The generated emotion data is sent to the server, and task priorities are automatically adjusted. For example, if the robot is feeling "stressed," the task priority will be changed to "urgent" and a maintenance notification will be issued immediately.

[2084] Specific examples

[2085] For example, consider the case where a manager assigns a task called "Routine Maintenance" to a factory robot. This task information is sent to the server via an input terminal, tokenized, and stored in a database. Meanwhile, if the robot's emotion recognition sensor detects an emotional state of "stress," the server will use this emotional data to adjust the task priority to "urgent" and immediately send a maintenance notification to the manager.

[2086] Prompt Sentence Examples

[2087] An example of a prompt to be input to the generative AI model is as follows:

[2088] Robot ID: 1

[2089] Emotional state: Stress

[2090] Recommended action: Prompt maintenance

[2091] Task Priority: Urgent

[2092] This prompt is then fed into a generative AI model and used to generate an optimal plan of action or set of actions.

[2093] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2094] Step 1:

[2095] The user inputs task information for remote work. The terminal receives the input information such as the task title, description, priority, and deadline, and sends it to the server. Input: Task information (title, description, priority, deadline). Output: Task information sent to the server.

[2096] Step 2:

[2097] The server receives task information and tokenizes each task. The tokenized task information is saved in a database. Input: Task information received from the device. Output: Tokenized task information saved in a database.

[2098] Step 3:

[2099] The server manages task progress based on task information stored in the database. It tracks task progress status (e.g. not started, in progress, completed) and updates it as needed. Input: Task information stored in the database. Output: Updated task progress status.

[2100] Step 4:

[2101] The user inputs travel plan condition information. The terminal receives condition information such as travel destination, budget, number of days, etc. and sends it to the server. Input: Travel plan condition information (travel destination, budget, number of days). Output: Travel condition information sent to the server.

[2102] Step 5:

[2103] The server receives travel condition information and provides it to an external generative AI model to generate a travel plan. The generated travel plan is organized and saved in a database. Input: Travel condition information provided to the external generative AI model. Output: Generated travel plan.

[2104] Step 6:

[2105] The generated itinerary is sent from the server to the terminal and presented to the user. Input: Generated itinerary. Output: Itinerary visually displayed on the terminal.

[2106] Step 7:

[2107] The robot's emotion recognition sensor acquires the robot's emotion data in real time, and the emotion recognition engine analyzes this emotion data. Input: Emotion data acquired from the robot. Output: Analyzed emotional state.

[2108] Step 8:

[2109] The emotion recognition engine sends the analyzed emotion data to the server, which then dynamically adjusts task priorities based on the emotion data. Input: Analyzed emotion data. Output: Adjusted task priorities.

[2110] Step 9:

[2111] The server analyzes the emotion data and sends appropriate maintenance notifications to the user or administrator. For example, if the robot's emotional state is "stressed," it issues a notification saying "Perform prompt maintenance." Input: Analyzed emotion data. Output: Maintenance notification sent to the user or administrator.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] 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.

[2117] 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.

[2118] 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).

[2119] 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.

[2120] 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."

[2121] 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.

[2122] 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).

[2123] 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.

[2124] 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.

[2125] 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.

[2126] 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.

[2127] 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.

[2128] 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.

[2129] 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.

[2130] 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.

[2131] 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.

[2132] 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.

[2133] The following is further disclosed regarding the above embodiment.

[2134] (Claim 1)

[2135] means for receiving remote work task information input by a user;

[2136] A means for tokenizing received task information and storing it in a database;

[2137] A means for managing task progress based on the saved task information;

[2138] means for receiving travel planning condition information from a user;

[2139] A means for generating a travel plan based on the received travel condition information through an external generation AI model;

[2140] means for presenting the generated travel plan to a user;

[2141] A system including:

[2142] (Claim 2)

[2143] 10. The system of claim 1, further comprising means for updating or modifying the travel plan using the travel plan requirement information.

[2144] (Claim 3)

[2145] 10. The system of claim 1, further comprising means for displaying an integrated display of remote work task progress and travel plan status on a user dashboard.

[2146] "Example 1"

[2147] (Claim 1)

[2148] means for receiving remote work task information input by a user;

[2149] A means for tokenizing received task information and storing it in a database;

[2150] A means for managing task progress based on the saved task information;

[2151] means for recei...

Claims

1. means for receiving remote work task information input by a user; A means for tokenizing received task information and storing it in a database; A means for managing task progress based on the saved task information; means for receiving travel planning condition information from a user; A means for generating a travel plan based on the received travel condition information through an external generation AI model; means for presenting the generated travel plan to a user; A system including:

2. 10. The system of claim 1, further comprising means for updating or modifying the travel plan using the travel plan requirement information.

3. 10. The system of claim 1, further comprising means for displaying an integrated display of remote work task progress and travel plan status on a user dashboard.

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