System

Abstract

To provide a system.SOLUTION: A system is provided, comprising means of collecting tasks to be executed, means of generating a task schedule, means of setting and notifying task reminders, and means of generating and obtaining a report at scheduled times of the tasks using generative artificial intelligence.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional task management systems require a series of tasks, such as collecting tasks, managing schedules, and creating reports, to be performed manually, which reduces work efficiency. [Means for solving the problem]

[0005] The system of the present invention collects instructions, manages the execution schedule of the collected tasks, creates and acquires reports on multiple tasks at the scheduled time using generative AI, and reports the materials output by the generative AI. This automates the flow of tasks and improves work efficiency. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention provides a to-do list that can be directly input into iPaaS as a means of collecting instructions from users. Specifically, when a user inputs a task into the to-do list, the system collects it and manages the task execution schedule. For example, if a user inputs the task "Create a report by 10:00 AM tomorrow," the system collects this task and schedules the task of creating the report by 10:00 AM tomorrow.

[0029] "Example 2"

[0030] At the scheduled time, the system uses generative AI to create and retrieve the report. Specifically, the generative AI collects the necessary information and creates a report based on that information. For example, the generative AI collects information from the internet and creates a report based on that information.

[0031] "Example 3"

[0032] As a means of reporting the materials output by the generative AI, the system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report created by the generative AI by sending it to the user's email address, etc.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters a task into the to-do list directly in the iPaaS. For example, the user enters a task such as "Create a report by 10:00 AM tomorrow."

[0036] Step 2: The system collects input from the user and manages the task execution schedule. Specifically, the system collects the task "Create a report by 10:00 AM tomorrow" and schedules the task to create the report by 10:00 AM tomorrow. "Example 2"

[0037] Step 1: At the scheduled time, the system uses generative AI to generate a report. Specifically, the generative AI collects the necessary information and generates a report based on that information.

[0038] Step 2: The system retrieves the report created by the generative AI. For example, the generative AI collects information from the internet, creates a report based on that information, and the system retrieves that report.

[0039] "Example 3"

[0040] Step 1: The system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report by sending it to the user's email address.

[0041] Example 1

[0042] Next, a description will be given of Example 1 of Form 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."

[0043] Conventional task management systems required users to manually input tasks and manage schedules, resulting in problems that reduced efficiency. Task reminder settings and notifications were also insufficient, meaning users could miss deadlines. Furthermore, report creation using generative artificial intelligence was not automated, placing a heavy burden on users.

[0044] 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.

[0045] In this invention, the server includes means for collecting instructions, means for managing the collected task execution schedules, means for creating and acquiring reports for multiple tasks at scheduled times using generative artificial intelligence, means for reporting materials output by the generative artificial intelligence, means for setting and notifying task reminders, means for saving task data in a database, and means for generating task schedules. This allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and automatically create reports using generative artificial intelligence.

[0046] The "means for collecting instructions" is an interface for inputting tasks and instructions from the user and sending them to the system.

[0047] The "means for managing execution schedules of collected tasks" is a function for creating and managing execution schedules based on collected tasks.

[0048] "Generative AI" is an AI technology that automatically generates reports and documents based on input data.

[0049] "Means for creating and obtaining reports" refers to a function for creating reports using generative artificial intelligence and obtaining those reports.

[0050] "Means for reporting materials output by generative artificial intelligence" is a function for providing users with materials created by generative artificial intelligence.

[0051] The "means for setting and notifying task reminders" is a function for setting reminders based on task deadlines and notifying the user.

[0052] The "means for saving task data in a database" is a function for saving collected task data in a database.

[0053] The "means for generating a task schedule" is a function for generating an execution schedule based on collected task data.

[0054] The "worklist with direct input from the integrated platform" is a worklist on an integrated platform that allows users to directly input tasks.

[0055] A "communication tool" is a tool that a user uses to send tasks or instructions to the system.

[0056] The present invention relates to a system that allows a user to efficiently manage tasks and automatically create reports by utilizing generative artificial intelligence. Specific embodiments of this system will be described below.

[0057] First, the user inputs a task into the task list directly input on the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The user's device (PC or smartphone) then sends this task to the server. The device sends the task data using an HTTP request.

[0058] The server receives HTTP requests sent from devices and retrieves task data. The server processes the requests using a web framework such as Flask or Django. The retrieved task data is then stored in a database using SQL queries. For example, a relational database such as MySQL (registered trademark) or PostgreSQL is used.

[0059] Next, the server generates a task execution schedule based on the saved task data. The server adds the task's deadline to the calendar using the Google® Calendar API. The server also sets a task reminder and notifies the user. For example, the server sets a reminder one hour before the task and notifies the user via email or push notification.

[0060] Furthermore, the server utilizes generative artificial intelligence to create reports at scheduled times. The generative artificial intelligence automatically generates reports and materials based on the input data. The generated reports are provided to the user.

[0061] As a concrete example, consider the case where a user inputs a task such as "Create a report by 10:00 AM tomorrow." When the user enters this task in the integrated platform's direct input to-do list, the device sends the task data to the server as an HTTP request. The server receives the request and saves the task data in a database. The server then uses the Google Calendar API to add the task's deadline to the calendar and set a reminder. It then sends the user an email notification one hour before the task. Furthermore, generative artificial intelligence is used to automatically create the report at the scheduled time and provide it to the user.

[0062] Examples of prompts to be input to a generative AI model include:

[0063] Enter the task "Create a report by 10 AM tomorrow" into the task list of the integrated platform. The system will collect this task and schedule a task to create a report by 10 AM tomorrow.

[0064] In this way, the invention allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and leverage generative artificial intelligence to automatically generate reports.

[0065] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0066] Step 1:

[0067] The user enters a task

[0068] The user inputs tasks into the task list directly into the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The input task data is sent to the terminal.

[0069] Step 2:

[0070] The device sends the task

[0071] The terminal sends the task data entered by the user to the server. Specifically, the task data is sent using an HTTP POST request. The input is the task data, and the output is a request sent to the server.

[0072] Step 3:

[0073] The server receives the task

[0074] The server receives the HTTP POST request sent from the terminal and retrieves the task data. For example, it processes the request using a web framework such as Flask or Django. The input is the HTTP request, and the output is the retrieved task data.

[0075] Step 4:

[0076] The server saves the task in a database

[0077] The server saves the acquired task data in a database. Specifically, it uses SQL queries to insert data into a relational database such as MySQL or PostgreSQL. The input is task data, and the output is data saved in the database.

[0078] Step 5:

[0079] The server generates a schedule of tasks

[0080] The server generates a task execution schedule based on the stored task data. For example, it uses the Google Calendar API to add task deadlines to a calendar. The input is the task data, and the output is the creation of a calendar event.

[0081] Step 6:

[0082] Server sets reminder

[0083] The server sets a reminder based on the task's due date, for example, using the Google Calendar API to set a reminder one hour before the task. The input is the task's due date data, and the output is the reminder setting.

[0084] Step 7:

[0085] The server notifies the user of the reminder

[0086] The server sends notifications to users based on the set reminders. Specifically, it sends reminders to users using email or push notifications. The input is the reminder setting data, and the output is the notification to the user.

[0087] Step 8:

[0088] The server creates reports using generative artificial intelligence

[0089] The server utilizes generative artificial intelligence to generate reports at scheduled times, with the input being the task data and the output being the generated report.

[0090] Step 9:

[0091] The server provides the generated report to the user.

[0092] The server provides the user with the report created by the generative AI. Specifically, it sends the report to the user's terminal. The input is the generated report, and the output is the report provided to the user.

[0093] (Application example 1)

[0094] Next, a description will be given of Application Example 1 of Embodiment 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."

[0095] In conventional factory work management systems, work task input and schedule management were often done manually, resulting in inefficiencies. Furthermore, the system lacked the ability to monitor task progress in real time and adjust schedules as needed, which led to delays and errors.

[0096] 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.

[0097] In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, a means for reporting materials output by the generative AI, a means for inputting work tasks to machinery in a factory, a means for collecting the input tasks and automatically managing the execution schedule, and a means for monitoring the progress of tasks in real time and adjusting the schedule as necessary. This enables efficient management of work tasks in a factory, and real-time progress monitoring and schedule adjustment.

[0098] A "means for collecting instructions" is a device or software for inputting tasks or instructions from a user and collecting them as data.

[0099] The "means for managing the execution schedule of the collected tasks" is a device or software for planning the execution timing of the collected tasks and automatically adjusting the schedule.

[0100] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports based on specified tasks.

[0101] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative artificial intelligence in report format.

[0102] The "means for inputting work tasks to machinery in a factory" refers to a device or software for inputting work tasks and giving instructions to machinery in a factory.

[0103] The "means for collecting input tasks and automatically managing the execution schedule" refers to a device or software for collecting tasks input by a user and automatically managing the execution schedule of those tasks.

[0104] The "means for monitoring the progress of tasks in real time and adjusting the schedule as necessary" refers to a device or software for monitoring the progress of tasks in real time and dynamically adjusting the schedule according to the progress.

[0105] A system for carrying out the present invention is for efficiently managing work tasks in a factory and monitoring progress in real time. A specific embodiment of this system will be described below.

[0106] 1. System Configuration

[0107] The system consists of the following main components:

[0108] Server: Collects tasks, manages schedules, and creates reports using generative AI.

[0109] Terminal: A device (e.g., tablet, PC) used to input work tasks to machinery in a factory.

[0110] Users: Factory workers and managers.

[0111] 2. Hardware and Software Used

[0112] Hardware: Factory robots (e.g. KUKA, Fanuc, etc.), tablets, PCs.

[0113] Software: Python, APScheduler (scheduling library), generative AI model.

[0114] 3. Data processing and calculation

[0115] Server Processing

[0116] The server collects tasks entered by users and manages the execution schedule. Specifically, it performs the following processes:

[0117] 1. Task collection: Tasks entered by users through the terminal are saved in a database.

[0118] 2. Schedule management: Using APScheduler, the execution timing of collected tasks is planned and the schedule is automatically adjusted.

[0119] 3. Report Generation: Use generative AI models to automatically generate and retrieve reports based on specified tasks.

[0120] Terminal handling

[0121] The terminal is a device for inputting work tasks to machines in a factory. A user inputs a task using the terminal, and the task is sent to a server.

[0122] User operations

[0123] Users use terminals to input work tasks for machines in a factory. The input tasks are sent to a server, which collects the tasks and manages the schedule.

[0124] 4. Specific Examples

[0125] For example, a user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." This task is sent to the server, which uses APScheduler to schedule the task to run at the specified time. Once the task is completed, a report is automatically generated using a generative AI model.

[0126] 5. Examples of prompts

[0127] The user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00". The system collects this task and schedules it to run at the specified time. Once the task is complete, the status is updated to "completed".

[0128] The above is a specific embodiment for carrying out the present invention. This system enables efficient management of work tasks within a factory, progress monitoring in real time, and schedule adjustment.

[0129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0130] Step 1:

[0131] The user inputs a work task using a terminal. For example, the user inputs a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." The input task is sent from the terminal to the server. The input data consists of the task name and deadline.

[0132] Step 2:

[0133] The server receives the task sent from the terminal and stores it in the database. The server analyzes the received task data and extracts the task name and deadline time. This stores the basic information of the task in the database.

[0134] Step 3:

[0135] The server uses APScheduler to plan the execution timing of the collected tasks and automatically adjust the schedule. The server schedules jobs to execute the tasks based on the task deadlines. This determines the execution timing of the tasks.

[0136] Step 4:

[0137] The server executes the task at the specified time. For example, it sends an instruction to a machine in a factory to execute the task "Inspect Machine A" at the specified time. This executes the task.

[0138] Step 5:

[0139] The server monitors the progress of the task in real time. The server receives feedback from the machinery in the factory and updates the progress of the task, allowing the progress of the task to be monitored in real time.

[0140] Step 6:

[0141] The server uses a generative AI model to automatically create a report after the task is completed. The server inputs the results of the task execution into the generative AI model and generates a report. This outputs the results of the task execution as a report.

[0142] Step 7:

[0143] The server provides the generated report to the user. The server sends the generated report to the user's terminal so that the user can check the report. This allows the user to check the results of the task execution.

[0144] Example 2

[0145] Next, a description will be given of Example 2 of Form 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."

[0146] Conventional report creation systems require users to manually collect information and create reports, which is time-consuming and labor-intensive. Furthermore, the information collection and report creation often lack accuracy and consistency. Furthermore, they lack the functionality to automatically generate reports based on a schedule, making it difficult to provide timely information. To solve these issues, a system that can efficiently and automatically generate reports and provide them to users is needed.

[0147] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0148] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for collecting information using a generative AI model at the scheduled time and creating a report based on a prompt sentence, means for saving the generated report and notifying the user, and means for the user to obtain the report through a terminal. This eliminates the need for the user to manually collect information and enables efficient, automatic, and timely acquisition of highly accurate reports.

[0149] The "means for collecting instructions" is a function for collecting tasks and requests from users.

[0150] The "means for managing the execution schedule of collected tasks" is a function for managing the execution timing of collected tasks and requests and executing them at the appropriate time.

[0151] A "generative AI model" is a model for generating data using artificial intelligence, such as a model that performs natural language processing.

[0152] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[0153] "Means for creating reports" refers to a function that automatically creates reports using a generative AI model based on collected information.

[0154] The "means for saving the generated report" is a function for saving the generated report in a database or a file system.

[0155] "Means for notifying the user" is a function for notifying the user that a generated report is available.

[0156] "Means for users to retrieve reports through a terminal" refers to the functionality that allows users to access and retrieve saved reports using a terminal such as a computer or mobile device.

[0157] The present invention provides a system for allowing users to efficiently and automatically generate and obtain reports. Specific embodiments of this system will be described below.

[0158] System configuration

[0159] This system is mainly composed of three elements: a server, a terminal, and a user. The server plays a central role in collecting information and creating reports using a generative AI model. The terminal is a device that allows the user to access the server and obtain the generated reports. The user is the entity that uses the system to generate and obtain reports.

[0160] Hardware and software used

[0161] The server is a high-performance computer with sufficient computing power to run the generative AI model. Specifically, it requires a CPU, GPU, memory, and storage. As for software, a framework (e.g., TENSORFLOW (registered trademark) or PyTorch) for running the generative AI model (e.g., a model that performs natural language processing) is used.

[0162] A terminal is a device that allows a user to access a server, and includes PCs, tablets, smartphones, etc. A web browser and dedicated applications are installed on the terminal, providing an interface for communicating with the server.

[0163] Data processing and calculation

[0164] The server first collects instructions from users via task lists and communication tools, then manages the execution schedule of the collected tasks and executes the generative AI model at the specified time.

[0165] The generative AI model collects the necessary information from the internet based on a prompt, such as "Please write a report on the latest AI technology." The collected information is temporarily stored on the server.

[0166] The server then re-enters the generative AI model with prompts based on the collected information to generate a report, which is then stored in a database or file system on the server.

[0167] Specific examples

[0168] For example, if a user wants a "report on the latest AI technology," the server inputs the following prompt into the generative AI model:

[0169] Example prompt sentence:

[0170] "Please write a report on the latest AI technologies, detailing the major innovations and their applications announced in 2023."

[0171] The generative AI model collects relevant information from the internet based on the prompt and creates a report. The report is then saved on a server and sent to the user. The user can access the server via their device and download and view the generated report.

[0172] In this way, the server automatically generates reports based on a schedule, enabling users to obtain the information they need in a timely manner.

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

[0174] Step 1:

[0175] The server collects instructions from users. The inputs are tasks and requests provided by users through task lists and communication tools. The server stores these instructions in a database. Specifically, the server retrieves data from task lists and communication tools via APIs and stores it in the database.

[0176] Step 2:

[0177] The server manages the execution schedule of the collected tasks. The input is task information stored in a database. The server uses this information to schedule the execution timing of the tasks. Specifically, the server uses a scheduler to set the execution time of each task and set a timer.

[0178] Step 3:

[0179] At the scheduled time, the server uses the generative AI model to collect information. The inputs are a prompt and scheduled task information. The server inputs the prompt into the generative AI model and collects the necessary information from the Internet. Specifically, the server inputs the prompt "Please create a report on the latest AI technology" into the generative AI model and uses web scraping technology to collect related information.

[0180] Step 4:

[0181] The server then inputs a prompt to the generative AI model based on the collected information and generates a report. The inputs are the collected information and the prompt. The server inputs the prompt to the generative AI model, saying, "Please create a detailed report on the latest AI technology based on the collected information," and receives the generated report. Specifically, the server retrieves the collected information from the database, inputs it into the generative AI model, and generates a report.

[0182] Step 5:

[0183] The server saves the generated report and notifies the user. The input is the generated report. The server saves the report in a database or file system and notifies the user via email or push notification. Specifically, the server saves the generated report in a specific directory and sends a notification based on the user's contact information.

[0184] Step 6:

[0185] The user accesses the server through their device and retrieves the generated report. The input is a notification from the server. The user accesses the server using a web browser or a dedicated application on their device and downloads the saved report. Specifically, the user clicks the link in the notification, logs in to the server, and downloads the report.

[0186] (Application example 2)

[0187] Next, a description will be given of Application Example 2 of Form 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."

[0188] Logistics centers are required to be able to grasp operational and inventory status in a timely manner and operate efficiently. However, with conventional methods, collecting information and creating reports requires a great deal of time and effort, making it difficult to provide information in real time.

[0189] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at the scheduled time using generative AI, means for reporting materials output by the generative AI, means for collecting logistics-related information, means for generating reports based on the collected logistics-related information, and means for notifying the generated reports. This makes it possible to grasp the operating status and inventory status of the logistics center in real time, enabling efficient operation.

[0190] A "means for collecting instructions" is a device or software for collecting instructions or tasks from a user.

[0191] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[0192] "Means for utilizing generative AI to generate and obtain reports based on multiple tasks at scheduled times" refers to a device or software that uses generative AI to generate and obtain reports based on multiple tasks at set times.

[0193] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative AI in report format.

[0194] "Means for collecting logistics-related information" means devices or software for collecting logistics-related data and news from the Internet and other sources.

[0195] The "means for generating a report based on the collected logistics-related information" refers to a device or software for generating a report based on the collected logistics-related information.

[0196] The "means for notifying the user of the generated report" is a device or software for notifying the user of the generated report.

[0197] To implement the present invention, the following system configuration and program are required.

[0198] System Configuration

[0199] 1. Hardware

[0200] Server: Collects data, runs generative AI, and generates reports.

[0201] Smartphone: The device on which the user views the report.

[0202] 2. Software

[0203] Generative AI model: Uses generative AI such as OpenAI (registered trademark) GPT-3 (registered trademark).

[0204] Data Collection Library: Collects logistics-related information from the Internet using the Requests library.

[0205] Scheduling library: Use the Schedule library to manage task execution schedules.

[0206] Program processing explanation

[0207] 1. Means of collecting instructions

[0208] The server uses a task list and communication tools directly input from the cloud service to collect instructions and tasks from users, allowing users to easily input tasks.

[0209] 2. A method for managing the execution schedule of collected tasks

[0210] The server uses a scheduling library to manage the timing and order of execution of collected tasks, so that tasks are executed at the appropriate time.

[0211] 3. A method to generate and obtain reports using AI that generates multiple tasks at scheduled times

[0212] The server uses generative AI to create and retrieve reports based on multiple tasks at set times. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet.

[0213] 4. A means of reporting materials output by generative AI

[0214] The server outputs the materials created by the generative AI in report format and notifies the user on their smartphone, allowing them to receive the latest information in real time.

[0215] 5. Means of collecting logistics-related information

[0216] The server uses a data collection library to collect logistics-related data and news from the Internet, ensuring that the latest logistics-related information is always available.

[0217] 6. A means of generating reports based on collected logistics-related information

[0218] The server generates reports based on the collected logistics-related information using generative AI models, resulting in an informed and detailed report.

[0219] 7. Means of notification of generated reports

[0220] The server then sends the generated report to the smartphone, allowing the user to view the report in real time.

[0221] Specific examples

[0222] Every morning at 9 a.m., the logistics center manager receives a report containing the latest logistics news and inventory status. The report includes the previous day's shipping status, inventory fluctuations, and the latest news in the logistics industry.

[0223] Prompt Sentence Examples

[0224] Write a report based on the following logistics news stories:

[0225] News 1: Latest trends in the logistics industry

[0226] News 2: Introducing new logistics technology

[0227] News 3: Fluctuations in market supply and demand

[0228] In this way, a system can be created that streamlines logistics center operations and provides the latest information in a timely manner.

[0229] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0230] Step 1:

[0231] The server collects instructions and tasks from users. Users input tasks using a task list entered directly into the cloud service or using communication tools. The server receives this input and stores it in a database. The input data includes the task content, priority, scheduled execution time, etc.

[0232] Step 2:

[0233] The server manages the execution schedule of the collected tasks. It uses a scheduling library to set the execution timing and order of the tasks. The input data is the scheduled execution time of the tasks, and the output data is a list of scheduled tasks.

[0234] Step 3:

[0235] The server generates and retrieves reports at scheduled times using generative AI. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet. The input data is the collected logistics-related information, and the output data is the generated report.

[0236] Step 4:

[0237] The server outputs the materials generated by the generative AI in report format and notifies the smartphone. The generated report is sent to the user's smartphone, where the user can check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[0238] Step 5:

[0239] The server uses a data collection library to collect logistics-related data and news from the Internet. This ensures that the latest logistics-related information is always available. The input data is logistics-related information available on the Internet, and the output data is the collected logistics-related information.

[0240] Step 6:

[0241] The server generates reports using a generative AI model based on the collected logistics-related information, resulting in a detailed report based on the information. The input data is the collected logistics-related information, and the output data is the generated report.

[0242] Step 7:

[0243] The server notifies the smartphone of the generated report, allowing the user to check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[0244] Example 3

[0245] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0246] Conventional report creation systems require users to manually collect information and create reports, which takes time and effort. Furthermore, there are limited ways to provide generated reports to users, making it difficult to efficiently communicate information.

[0247] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for utilizing the generative AI to create and obtain reports for multiple tasks at the scheduled time, means for providing the user with materials output by the generative AI, means for receiving user input and inputting prompt statements to the generative AI, means for temporarily saving the generated report, means for obtaining the user's contact information, and means for sending the generated report to the user's contact information. This enables the user to create reports efficiently and receive information quickly.

[0248] A "means for collecting instructions" is a device or method that receives instructions or requests from a user and collects information for processing within the system.

[0249] The "means for managing the execution schedule of collected tasks" refers to a device or method for planning and managing the time and order of the collected tasks in order to execute them efficiently.

[0250] "Generative AI" refers to an AI system that has the ability to automatically generate information such as text or reports based on user input.

[0251] "Means for creating and obtaining reports" refers to a device or method for creating reports using generative artificial intelligence and obtaining the created reports.

[0252] "Means for providing a user with materials output by a generative artificial intelligence" refers to a device or method for providing a user with materials created by a generative artificial intelligence.

[0253] "Means for receiving user input and inputting a prompt sentence to the generative AI" refers to a device or method for receiving input from a user and inputting the input as a prompt sentence to the generative AI.

[0254] "Means for temporarily storing generated reports" refers to a device or method for temporarily storing reports generated by generative artificial intelligence.

[0255] The "means for acquiring user contact information" refers to a device or method for acquiring contact information such as a user's email address or phone number.

[0256] The "means for sending the generated report to the user's contact information" refers to a device or method for sending the report generated by the generative artificial intelligence based on the user's contact information.

[0257] The present invention relates to a system for creating reports using generative artificial intelligence and providing the reports to users. Specific embodiments of this system will be described below.

[0258] System configuration

[0259] The system consists of the following main components:

[0260] 1. Server

[0261] 2. Terminal

[0262] 3. Users

[0263] Hardware and software used

[0264] The server provides the computational resources to run a generative artificial intelligence model (e.g., OpenAI's GPT-4 (registered trademark)). It also temporarily stores the generated reports using a database or file system. It also sends the reports to the user's contacts using the SMTP protocol.

[0265] The terminal provides an interface for the user to input the prompt sentence. This can be a device such as a PC or smartphone, and accesses the server through a browser.

[0266] The user uses the system to input a prompt to generate a report and receives the generated report.

[0267] Data processing and calculation

[0268] The server inputs the prompt received from the user into a generative AI model to generate a report, which is temporarily stored on the server and then sent based on the user's contact information.

[0269] Specific examples

[0270] For example, if a user enters the prompt "Write a report on the latest technology trends," the following happens:

[0271] 1. The user enters a prompt:

[0272] The user opens a browser, accesses the system's web page, and types "Write a report on the latest technology trends" into the text box.

[0273] 2. The terminal sends the prompt to the server:

[0274] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text.

[0275] 3. The server receives the prompt and inputs it into the generative AI model:

[0276] The server analyzes the received prompt sentence and inputs it into a generative artificial intelligence model (GPT-4).

[0277] 4. The generative AI model generates the report:

[0278] Based on the prompt, GPT-4 generates a report stating, "Emerging technology trends in 2023 include the evolution of artificial intelligence, the widespread adoption of 5G, and the application of blockchain technology. These technologies are bringing about revolutionary changes in various industries."

[0279] 5. The server temporarily stores the generated report:

[0280] The server stores the generated reports in a database.

[0281] 6. The server gets the user's email address:

[0282] The server obtains the email address from the user's registration information.

[0283] 7. The server sends the generated report to the user's email address:

[0284] The server uses the SMTP protocol to send the generated report to the user's email address.

[0285] 8. User receives email and checks report:

[0286] The user receives a new email in their email client and sees the attached report.

[0287] In this way, the user can create reports efficiently and receive information quickly. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0288] Step 1:

[0289] The user enters a prompt statement.

[0290] A user accesses the system interface from their own device (PC, smartphone, etc.) and inputs a prompt statement indicating the content of the report they want to generate. For example, they might input, "Please create a report on the latest technological trends." The input data is the prompt statement, and the output data is an input confirmation message displayed on the device.

[0291] Step 2:

[0292] The terminal sends the prompt to the server.

[0293] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text. The input data is the prompt text, and the output data is the prompt text sent to the server.

[0294] Step 3:

[0295] The server receives the prompt sentence and inputs it into the generative AI model.

[0296] The server receives the prompt sentence sent from the device and inputs it into a generative AI model (e.g., GPT-4). The input data is the prompt sentence, and the output data is the input result to the generative AI model.

[0297] Step 4:

[0298] A generative AI model generates the report.

[0299] The generative AI model generates a report based on the input prompt, which contains detailed information depending on the content of the prompt. The input data is the prompt, and the output data is the generated report.

[0300] Step 5:

[0301] The server temporarily stores the generated report.

[0302] The server temporarily stores the reports output from the generative AI model. This storage is done using a database or file system. The input data is the generated report, and the output data is the saved report.

[0303] Step 6:

[0304] The server retrieves the user's email address.

[0305] The server obtains the user's email address, which was provided when the user registered with the system. The input data is the user's identification information, and the output data is the obtained email address.

[0306] Step 7:

[0307] The server will send the generated report to the user's email address.

[0308] The server sends the saved report to the user's email address using the SMTP protocol. The input data are the saved report and the email address, and the output data is the email sent.

[0309] Step 8:

[0310] The user receives an email and reviews the report.

[0311] The user receives the email sent from the server in their email client. The generated report is attached to the email or is included in the body of the email. The user checks it and uses it as needed. The input data is the sent email, and the output data is the checked report.

[0312] (Application example 3)

[0313] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0314] Logistics center operators need to efficiently grasp data such as inventory status, shipping status, arrival status, and work efficiency in their daily operations, and make appropriate decisions. However, manually collecting this data and creating reports takes time and effort, hindering efficient business operations. Furthermore, there is a lack of a way to quickly share the generated reports with relevant parties, which can lead to delays in information transmission. To solve these issues, a system that uses generative AI to automatically generate reports and quickly share them is needed.

[0315] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for sending the generated reports by email, and means for generating reports for the logistics center operations manager. This enables the logistics center operations manager to efficiently collect the necessary data and quickly receive the automatically generated reports.

[0316] A "means for collecting instructions" is a device or software for collecting instructions or requests from a user.

[0317] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[0318] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports.

[0319] "Means for reporting materials output by generative AI" refers to a device or software for providing materials output by generative artificial intelligence in report format.

[0320] A "means for emailing a generated report" is a device or software for sending a generated report via email to a designated recipient.

[0321] The "means for generating a report for the logistics center operator" is a device or software for generating a report containing information required by the logistics center operator.

[0322] As an embodiment of the present invention, a report generation system utilizing generative AI is provided for logistics center operators. A specific embodiment of the system is described below.

[0323] 1. System Program

[0324] The system consists of the following main components:

[0325] A means of collecting instructions

[0326] A means to manage the execution schedule of collected tasks

[0327] A means of creating and obtaining reports using generative AI

[0328] A means of reporting materials output by generative AI

[0329] A means to email the generated report

[0330] A means of generating reports for distribution center operations managers

[0331] 2. Program Processing

[0332] The server first collects instructions from users, which are entered via a smartphone application or a web interface. The collected instructions are registered as tasks and their execution schedules are managed.

[0333] Next, the generative AI creates a report based on the scheduled time. The generative AI uses OpenAI's API to generate a report based on the specified prompt. The generated report is saved on the server.

[0334] The generated report is then emailed to the specified email address using Python's smtplib library.

[0335] 3. Hardware and Software Used

[0336] Hardware: Smartphones, servers

[0337] Software: Python, OpenAI API, SMTP server

[0338] 4. Specific Examples

[0339] For example, if a logistics center manager wants to know today's inventory and shipping status, he or she opens a smartphone application and requests report generation. The generative AI generates a report like this:

[0340] Availability:

[0341] Product A: 500 pieces

[0342] Product B: 300 pieces

[0343] Shipping Status:

[0344] Product A: 200 units shipped

[0345] Product B: 100 units shipped

[0346] Availability:

[0347] Product A: 100 units expected to arrive

[0348] Product B: 50 units expected to arrive

[0349] Work efficiency:

[0350] Average work time: 2 hours

[0351] Work efficiency: 85%

[0352] This report will be automatically sent to the administrator's email address.

[0353] 5. Examples of prompts

[0354] An example of a prompt to input to a generative AI model is as follows:

[0355] Prepare a report for the distribution center operations manager. Please include the following information:

[0356] Availability

[0357] Shipping Status

[0358] Stock availability

[0359] Work efficiency

[0360] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0361] Step 1:

[0362] The user inputs report generation instructions via a smartphone application or web interface. The input instructions include the information to be included in the report (inventory status, shipping status, arrival status, work efficiency, etc.), and the user's request is transmitted to the system.

[0363] Step 2:

[0364] The server receives instructions from the user and registers them as tasks. The registered tasks are managed based on an execution schedule. Specifically, the timing and order of task execution are determined. The input is the user's instructions, and the output is the registered tasks.

[0365] Step 3:

[0366] Based on the scheduled time, the server sends a prompt to the generative AI, which contains instructions for generating a report containing the information specified by the user. The input is the scheduled task, and the output is the prompt to the generative AI.

[0367] Step 4:

[0368] The generative AI generates a report based on the prompt. The generated report is sent to the server. The input is the prompt, and the output is the generated report. Specifically, the report is generated using OpenAI's API.

[0369] Step 5:

[0370] The server receives the generated report and sends it as an email to the specified email address. The Python smtplib library is used to send the email. The input is the generated report and the output is the email sent.

[0371] Step 6:

[0372] A user receives an email on a smartphone or other device and views the generated report. The input is the email that was sent, and the output is the report that the user views. The specific behavior is to view the report using the email application.

[0373] 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.

[0374] "Example 1"

[0375] In one embodiment of the present invention, the generative AI includes an emotion engine that recognizes a user's emotions. The emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, text input, etc. For example, if the user senses that they are stressed, the emotion engine communicates that information to the generative AI.

[0376] "Example 2"

[0377] Furthermore, the emotion engine adjusts task priorities based on the user's emotions. For example, if the user feels stressed, the emotion engine communicates this information to the generative AI, which then prioritizes tasks that may reduce stress. Specifically, it prioritizes tasks related to relaxation and tasks that the user is expected to enjoy.

[0378] "Example 3"

[0379] The emotion engine also adjusts the content of the report based on the user's emotions. For example, if the user feels happy, the emotion engine communicates this information to the generative AI, which then adjusts the report content to reflect the user's happiness. Specifically, the report will include information related to the user's happiness.

[0380] The processing flow of each embodiment will be described below.

[0381] "Example 1"

[0382] Step 1: The emotion engine recognizes the user's emotions based on their tone of voice, facial expressions, text input, etc.

[0383] Step 2: The emotion engine communicates the recognized emotion information to the generative AI.

[0384] "Example 2"

[0385] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts task priorities based on the emotional information. Specifically, it prioritizes tasks that may reduce stress.

[0386] "Example 3"

[0387] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts the report content based on the emotion information. Specifically, it includes information related to what makes the user happy.

[0388] Example 1

[0389] Next, a description will be given of Example 1 of Form 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."

[0390] Conventional task management systems provide schedule management and reminder functions for tasks entered by users, but lack consideration for user emotions. Furthermore, there is a need for systems that not only manage task execution schedules but also respond to user emotions. Furthermore, there is a need for a function to automate document creation using generative artificial intelligence. A system that can solve these issues is needed.

[0391] 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.

[0392] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring documents for multiple tasks at scheduled times using generative artificial intelligence, means for documenting materials output by the generative artificial intelligence, means including an emotion engine for recognizing user emotions, and means for responding according to the user's emotions based on information obtained from the emotion engine. This makes it possible to improve the efficiency of user task management and to respond appropriately according to emotions.

[0393] "Means for collecting instructions" refers to the means for inputting tasks and instructions from users and incorporating them into the system.

[0394] The "means for managing the execution schedule of collected tasks" refers to a means for managing the execution timing and deadline of collected tasks and notifying the user at an appropriate time.

[0395] "Generative AI" is an AI technology that automatically generates documents and reports based on user instructions and data.

[0396] "Means for creating and obtaining documents" refers to the use of generative artificial intelligence to create task-based documents and obtain the necessary information.

[0397] "Means of documentation" refers to the means of organizing the materials output by the generative artificial intelligence and compiling them into a formal document.

[0398] The "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, text input, etc.

[0399] "Means for responding according to emotions" refers to means for providing appropriate responses and advice according to the user's emotions based on information obtained from the emotion engine.

[0400] "Worklists entered directly on an integrated platform" refers to a list on an integrated platform where users can enter tasks directly.

[0401] "Communication Tools" are tools that allow users to communicate with the system and are used to gather instructions.

[0402] MODE FOR CARRYING OUT THE INVENTION

[0403] The present invention is a system that allows a user to input a task, manages the execution schedule of the task, and responds according to the user's emotions. A specific embodiment of this system will be described below.

[0404] 1. Task input by user

[0405] Users can use their terminals to input tasks into a task list directly into the integrated platform. For example, a user can input a task such as "Create a report by 10:00 AM tomorrow."

[0406] 2. Task collection by the server

[0407] The server collects tasks entered by users in real time, stores them in a database, and analyzes task details (task name, deadline, priority, etc.).

[0408] 3. Task scheduling by the server

[0409] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on the task deadlines and sends notifications to the user at the appropriate time. For example, when a task deadline is approaching, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow."

[0410] 4. Emotion Recognition by Emotion Engine

[0411] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expressions, text input, etc. For example, if a user inputs the text "I'm very tired today," the emotion engine will recognize that the user is tired.

[0412] 5. Emotion-based responses using generative AI

[0413] The generative AI responds to the user's emotions based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be good to take a short break to relax."

[0414] Specific examples

[0415] Example 1: Task entry and schedule management

[0416] A user enters a task in their to-do list, "Create a report by 10 AM tomorrow." The server collects this task and stores it in a database. The server sets a reminder based on the task's due date, and notifies the user at 9 AM tomorrow, "You have a task to create a report by 10 AM tomorrow."

[0417] Example 2: Emotion recognition and response

[0418] A user enters text such as "I feel very tired today." The emotion engine recognizes that the user is tired and relays this information to the generative AI, which then offers advice such as "It would be good to take a short break to relax."

[0419] Prompt Sentence Examples

[0420] Task input prompt

[0421] "Please add a task to your to-do list to prepare the report by 10:00 AM tomorrow."

[0422] Emotion recognition prompts

[0423] "If the user feels tired, offer them some tips on how to relax."

[0424] The above is a specific embodiment for carrying out the present invention.

[0425] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0426] Step 1:

[0427] A user uses a terminal to input tasks into the integrated platform's direct input task list. The input task includes detailed information such as the task name, deadline, and priority. For example, a task is input as "Create a report by 10:00 AM tomorrow." The input data is the task name "Create report," the deadline "10:00 AM tomorrow," and the priority "High."

[0428] Step 2:

[0429] The server collects tasks entered by users in real time. The collected tasks are stored in a database. The server analyzes detailed information such as task name, deadline, and priority and stores it in the database. The input data is the task information entered by the user, and the output data is the task information stored in the database.

[0430] Step 3:

[0431] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on task deadlines and sends notifications to users at appropriate times. For example, when a task deadline approaches, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow." The input data is the task information stored in the database, and the output data is the notification sent to the user.

[0432] Step 4:

[0433] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expression, text input, etc. For example, if a user enters the text "I'm very tired today," the emotion engine recognizes that the user is tired. The input data is the user's tone of voice, facial expression, text input, etc., and the output data is the user's emotional information.

[0434] Step 5:

[0435] The generative AI responds according to the user's emotions based on the information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be a good idea to take a short break to relax." The input data is the user's emotional information obtained from the emotion engine, and the output data is advice to the user.

[0436] (Application example 1)

[0437] Next, a description will be given of Application Example 1 of Embodiment 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."

[0438] Conventional factory robot systems lack sufficient task schedule management and worker emotional monitoring, resulting in problems such as reduced work efficiency and worker stress. Furthermore, if task instructions are not given properly, the robot's behavior can become unstable. This can lead to a decline in productivity throughout the factory and potentially affect quality control.

[0439] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using a generative AI, a means for reporting materials output by the generative AI, a means for recognizing the emotions of workers using an emotion engine, a means for adjusting the task schedule based on the emotions of workers, and a means for instructing robots to perform tasks. This allows for efficient task schedule management and flexible schedule adjustment based on the emotions of workers. Furthermore, appropriate task instructions are given to robots, improving productivity and quality control throughout the factory.

[0440] A "means for collecting instructions" is an interface or system for collecting tasks or instructions from the user.

[0441] The "means for managing the execution schedule of collected tasks" is a system that creates and manages a schedule for efficiently executing collected tasks.

[0442] "Means for creating and obtaining reports using generative AI" refers to a system that uses generative artificial intelligence to automatically create and obtain task-based reports.

[0443] "Means for reporting materials output by generative AI" refers to a system that compiles and reports materials created by generative artificial intelligence.

[0444] The "means for recognizing a worker's emotions using an emotion engine" is an engine for recognizing emotions from the worker's tone of voice, facial expressions, text input, etc.

[0445] The "means for adjusting task schedules based on worker emotions" is a system that flexibly adjusts task schedules according to the recognized emotions of workers.

[0446] The "means for instructing robots to perform tasks" is a system for instructing factory robots to perform scheduled tasks and have them execute them.

[0447] A system for carrying out this invention is configured as follows: The server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports using generative AI, means for reporting materials output by the generative AI, means for recognizing the emotions of workers using an emotion engine, means for adjusting the task schedule based on the emotions of workers, and means for instructing robots on tasks.

[0448] Program processing explanation

[0449] The server processes and calculates data using the following hardware and software.

[0450] Hardware: Factory robots, emotion-recognition cameras, microphones

[0451] Software: EmotionEngine, TaskScheduler, RobotController

[0452] 1. A means of collecting instructions: The server provides an interface for collecting tasks and instructions from users, for example, via a to-do list or communication tool directly input into the iPaaS.

[0453] 2. A means for managing task execution schedules: The server creates and manages schedules for efficiently executing collected tasks. It uses TaskScheduler to generate schedules that take into account task deadlines and priorities.

[0454] 3. Using generative AI to create and retrieve reports: The server uses generative AI to automatically create and retrieve task-based reports. For example, if a user inputs a task such as "Create a report by 10:00 AM tomorrow," the generative AI will create a report based on that task.

[0455] 4. A means of reporting the materials output by the generative AI: The server compiles and reports the materials created by the generative AI, allowing users to efficiently check the progress of their tasks.

[0456] 5. Means of recognizing worker emotions using an emotion engine: The server uses an emotion engine to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The Emotion Engine is responsible for this, and can detect when a worker is feeling stressed.

[0457] 6. Adjusting task schedules based on worker emotions: The server flexibly adjusts task schedules according to the worker's recognized emotions. For example, if a worker is feeling stressed, it can change the priority of tasks or adjust the schedule to include breaks.

[0458] 7. Means for instructing robots to carry out tasks: The server instructs factory robots to carry out scheduled tasks. RobotController is used to issue specific work instructions to the robots.

[0459] Specific examples

[0460] For example, if a factory manager enters the tasks "Maintain Machine A" and "Assemble Part B" into a to-do list, the server collects them and creates a task schedule. Generative AI creates reports based on the tasks, and Emotion Engine monitors the emotions of workers. If a worker is feeling stressed, Task Scheduler adjusts the schedule, and Robot Controller issues appropriate instructions to the robot.

[0461] Prompt Sentence Examples

[0462] "The factory manager has entered tasks into the to-do list. Collect task descriptions and deadlines and issue instructions to the robot. Also, monitor the emotions of the workers and adjust their schedules if they are feeling stressed."

[0463] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0464] Step 1:

[0465] The user inputs tasks into the ToDo list. For example, the user inputs tasks such as "Maintain machine A" or "Assemble part B." The input tasks are sent to the server. The input data includes a task description and a deadline.

[0466] Step 2:

[0467] The server collects instructions. The server collects tasks from the to-do list submitted by the user and stores them in a database. The collected data includes task descriptions and deadlines.

[0468] Step 3:

[0469] The server manages the task execution schedule. The server passes the collected tasks to the TaskScheduler, which generates a schedule that takes into account the task deadlines and priorities. The input data are task descriptions and deadlines, and the output data is a list of scheduled tasks.

[0470] Step 4:

[0471] The server uses generative AI to create and retrieve reports. The server inputs the task details into the generative AI, which then automatically creates the report. The input data is the task description, and the output data is the generated report.

[0472] Step 5:

[0473] The server reports the materials output by the generative AI. The server provides the report created by the generative AI to the user. The input data is the generated report, and the output data is the report provided to the user.

[0474] Step 6:

[0475] The server uses an emotion engine to recognize the worker's emotions. The server uses an emotion recognition camera and microphone to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The input data is the worker's voice and video, and the output data is the recognized emotional information.

[0476] Step 7:

[0477] The server adjusts the task schedule based on the worker's emotions. The server flexibly adjusts the task schedule using TaskScheduler based on the recognized emotion information. The input data is the recognized emotion information, and the output data is the adjusted task schedule.

[0478] Step 8:

[0479] The server issues tasks to the robots. The server then passes the scheduled tasks to the RobotController, which issues specific work instructions to the factory robots. The input data is the scheduled task list, and the output data is the work instructions for the robots.

[0480] Example 2

[0481] Next, a description will be given of Example 2 of Form 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."

[0482] Conventional task management systems prioritize tasks without considering the user's emotional state, which can have a negative impact on user stress and efficiency. Furthermore, report creation using generative AI does not provide information based on the user's emotions, so it cannot fully meet user needs. This leads to issues such as reduced user satisfaction and productivity.

[0483] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0484] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for acquiring user emotional data, means for analyzing the acquired emotional data, means for adjusting task priorities based on the analysis results, and means for making final adjustments to the report based on the adjusted task priorities. This makes it possible to adjust task priorities according to the user's emotional state and create reports using generative AI.

[0485] A "means for collecting instructions" is a device or software for collecting tasks or requests from a user.

[0486] The "means for managing the execution schedule of the collected tasks" is a device or software that sets and manages a schedule for efficiently executing the collected tasks.

[0487] "Means for creating and obtaining reports using generative AI" refers to devices or software that automatically create reports using generative AI technology and obtain them.

[0488] "Means for reporting materials output by generative AI" refers to a device or software for providing users with materials generated by generative AI.

[0489] The "means for acquiring user emotional data" refers to a device or software for detecting the user's emotional state and collecting that data.

[0490] The "means for analyzing acquired emotional data" refers to a device or software for analyzing collected emotional data of users and obtaining the results.

[0491] The "means for adjusting task priorities based on analysis results" refers to a device or software for dynamically changing task priorities based on the analysis results of emotion data.

[0492] The "means for finalizing the report based on the priority of the adjusted task" is a device or software for finalizing the content of the report by taking into account the priority of the adjusted task.

[0493] MODE FOR CARRYING OUT THE INVENTION

[0494] This invention is a system that adjusts task priorities based on the user's emotional state and creates reports using generative AI. Specific embodiments of this system are described below.

[0495] System configuration

[0496] Server Configuration

[0497] The server contains several modules with the following functions:

[0498] 1. Instruction collection module: Collects tasks and requests from users, for example, providing a task management list through a cloud service.

[0499] 2. Schedule Management Module: Set and manage schedules to efficiently execute collected tasks.

[0500] 3. Generative AI module: Uses generative AI technology (e.g., GPT-4) to automatically generate and retrieve reports.

[0501] 4. Report delivery module: Provides users with materials generated by generative AI.

[0502] Device configuration

[0503] The terminal has the following features:

[0504] 1. Emotion Data Acquisition Module: Detects the user's emotional state and collects that data. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice, and sends them to emotion analysis software (e.g., Affectiva).

[0505] Emotion engine configuration

[0506] The emotion engine has the following functions:

[0507] 1. Emotion analysis module: Analyzes the acquired emotion data and obtains the results, for example, determining whether the user is feeling stressed.

[0508] 2. Priority adjustment module: Dynamically changes task priorities based on the analysis results of emotion data.

[0509] Specific examples

[0510] If a user is feeling stressed at work, the emotion engine analyzes that information and relays it to the generative AI, which then collects information related to relaxation (e.g., meditation techniques and relaxation music) and creates a report based on that information.

[0511] Prompt Sentence Examples

[0512] "If the user is stressed, collect information related to relaxation and create a report."

[0513] The system aims to reduce stress for users by responding flexibly to their emotional state and providing optimal information.

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

[0515] Program processing flow

[0516] Step 1: Check the schedule

[0517] The server uses a schedule management module to start processing at a specified time. It receives pre-configured schedule information as input and generates a trigger to proceed to the next processing step as output. Specifically, it uses a Cron job to start the report creation process every day at 9:00 AM.

[0518] Step 2: Start creating reports

[0519] The server launches the generative AI module and starts the report creation process. It receives a trigger from the schedule management module as input and initializes the generative AI model as output. Specifically, it runs a Python script to launch the generative AI model (e.g., GPT-4).

[0520] Step 3: Gather information

[0521] The generative AI model collects information from the internet. As input, it receives prompts required for creating a report, and as output, it generates the collected information. Specifically, it uses BeautifulSoup to scrape the latest economic news from news sites.

[0522] Step 4: Generate a report

[0523] A generative AI model generates a report based on collected information. It receives collected information as input and generates a generated report as output. Specifically, it uses natural language processing technology to organize the information and create a report in an easy-to-understand format.

[0524] Step 5: Obtaining emotion data

[0525] The device acquires the user's emotional data. It captures the user's facial expressions and voice as input and generates emotional data as output. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice and sends them to emotion analysis software (e.g., Affectiva).

[0526] Step 6: Sentiment Analysis

[0527] The emotion engine analyzes the acquired emotion data. It receives the emotion data sent from the device as input and generates the analysis results as output. Specifically, it analyzes the data from Affectiva and determines whether the user is feeling stressed.

[0528] Step 7: Adjust task priorities

[0529] The server receives data from the emotion engine and adjusts task priorities. It receives the results of emotion analysis as input and generates adjusted task priorities as output. Specific behavior is to increase the priority of relaxation-related tasks (e.g., meditation suggestions).

[0530] Step 8: Finalize and distribute the report

[0531] The generative AI model finalizes the report based on information from the emotion engine. It receives the adjusted task priorities as input and generates the final report as output. Specifically, it adds relaxation-related information to the report and sends the final report to the user's device via email.

[0532] In this way, task prioritization based on the user's emotional state and report creation using generative AI are achieved.

[0533] (Application example 2)

[0534] Next, a description will be given of Application Example 2 of Form 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."

[0535] While conventional systems can generate reports at scheduled times using generative AI, they lack the ability to adjust task priorities based on user emotions. This makes it difficult to reduce user stress and fatigue, and productivity improvements cannot be expected.

[0536] 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.

[0537] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine and adjusting task priorities, and means for increasing the priority of relaxation tasks based on the analysis results of the emotion engine. This makes it possible to adjust task priorities based on the user's emotions and reduce stress and fatigue.

[0538] A "means for collecting instructions" is a device or software for collecting tasks or instructions from a user.

[0539] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[0540] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative AI to create reports based on data and obtain them.

[0541] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative AI as a report.

[0542] The "means for analyzing a user's emotions using an emotion engine and adjusting task priorities" refers to a device or software for analyzing a user's emotions using an emotion engine and adjusting task priorities based on the results of the analysis.

[0543] The "means for increasing the priority of a relaxation task based on the analysis results of the emotion engine" is a device or software for increasing the priority of a relaxation task for reducing stress and fatigue of a user based on the analysis results of the emotion engine.

[0544] A system for implementing the present invention has the following configuration.

[0545] 1. System Program

[0546] The system includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at scheduled times using a generative AI, means for reporting materials output by the generative AI, means for analyzing a user's emotions using an emotion engine and adjusting the priority of tasks, and means for increasing the priority of relaxation tasks based on the analysis results of the emotion engine.

[0547] 2. Program processing explanation

[0548] The server uses the following hardware and software:

[0549] Hardware: Factory robots, sensors (to detect worker emotions)

[0550] Software: EmotionEngine (emotion engine), AIReportGenerator (generative AI), requests (for data collection)

[0551] The server uses the requests library to collect factory data from the Internet. It then uses AIReportGenerator to generate and save reports based on the collected data. It also uses EmotionEngine to analyze workers' emotions and adjust task priorities based on the results. For example, if a worker feels fatigued, it increases the priority of relaxation tasks.

[0552] 3. Specific Examples

[0553] As a concrete example, consider a usage scenario in a factory. If a worker in the factory feels fatigued, the emotion engine detects this information and the generative AI prioritizes relaxation tasks (e.g., short breaks or light stretching), thereby reducing worker fatigue and improving productivity.

[0554] Prompt Sentence Examples

[0555] Create a program that analyzes the emotions of workers in a factory and prioritizes relaxation tasks if they are feeling fatigued. Use generative AI to create production reports and analyze emotions using an emotion engine.

[0556] In this way, the system can adjust task priorities based on the user's emotions and support efficient production activities.

[0557] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0558] Step 1:

[0559] The server uses the requests library to collect factory data from the Internet. Specifically, it retrieves JSON-formatted data from a specified URL. The input is the URL, and the output is the retrieved JSON data. This data includes information about the factory's production status and the status of workers.

[0560] Step 2:

[0561] The server generates a report based on the collected data using AIReportGenerator. The input is the JSON data obtained in step 1, and the output is the generated report text. Specifically, AIReportGenerator parses the data, extracts important information, and formats it into a report.

[0562] Step 3:

[0563] The server saves the generated report. The input is the report text generated in step 2, and the output is the saved report file. Specifically, it writes the report text to a file and saves it in the specified directory.

[0564] Step 4:

[0565] The server uses EmotionEngine to analyze the worker's emotions. The input is the worker's biometric data acquired from sensors, and the output is the emotion analysis result. Specifically, EmotionEngine analyzes the biometric data and determines the worker's emotional state (e.g., fatigue, stress, relaxation).

[0566] Step 5:

[0567] The server adjusts task priorities based on the emotion engine's analysis results. The input is the emotion analysis result obtained in step 4, and the output is an adjusted task priority list. Specifically, if the emotion engine detects fatigue or stress, it updates the task list to increase the priority of relaxation tasks.

[0568] Step 6:

[0569] The server reflects the adjusted task priority list in the execution schedule. The input is the task priority list adjusted in step 5, and the output is the updated execution schedule. Specifically, the execution schedule is reorganized based on the task priorities, and the relaxation task is set to be executed with priority.

[0570] In this way, the server can adjust task priorities based on the user's emotions and support efficient production activities.

[0571] Example 3

[0572] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0573] Conventional report generation systems were unable to adjust report content based on user sentiment, making it difficult to increase user satisfaction. Furthermore, the means by which generated reports could be provided to users were limited, requiring more flexible responses.

[0574] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring a report using a generative AI model for multiple tasks at the scheduled time, means for reporting materials output by the generative AI model, means for analyzing user emotions, means for adjusting the content of the report based on the analyzed emotion information, and means for providing the adjusted report to the user. This makes it possible to generate and provide a report according to the user's emotions.

[0575] "Instruction collection means" refers to the interface or system used to receive tasks or requests from users.

[0576] "Means for managing the execution schedule of collected tasks" refers to a system that sets and manages schedules for executing received tasks and requests at the appropriate time.

[0577] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to generate reports and materials based on user instructions.

[0578] "Means for creating and obtaining reports" refers to a system for creating reports using a generative AI model and obtaining those reports.

[0579] "Means for reporting materials output by a generative AI model" refers to a system for providing users with reports and materials created by a generative AI model.

[0580] "Means for analyzing user emotions" refers to a system that analyzes a user's emotional state using user feedback, facial expression recognition data, etc.

[0581] "Means for adjusting the content of the report based on the analyzed emotional information" refers to a system that appropriately changes and adjusts the content of the generated report based on the user's emotional information.

[0582] "Means for providing a user with a tailored report" means a system for sending and providing a user with a tailored report based on emotional information.

[0583] This invention is a system that uses a generative AI model to generate and provide reports based on user emotions. Specific embodiments of this system are described below.

[0584] Hardware and software used

[0585] Hardware: Servers, user devices (PCs, smartphones, etc.)

[0586] Software: Generative AI models (e.g., GPT-4), emotion engines, email delivery systems

[0587] System Operation Overview

[0588] A user requests a report

[0589] The user uses a terminal to access the system interface, enters a prompt specifying the content of the report, and submits the request. For example, the user enters "Please create a report on the Japanese IT market in 2023" and clicks the submit button.

[0590] The server runs the generative AI model and generates a report.

[0591] The server receives the request and launches a generative AI model (e.g., GPT-4). The server inputs the user's prompt into the generative AI model and generates a report. For example, the server inputs the prompt "Please write a report on Japan's IT market in 2023" into GPT-4 and obtains the generated report.

[0592] The server starts the emotion engine and analyzes the user's emotions.

[0593] The server starts the emotion engine and collects the user's emotion data. The emotion data is obtained from user feedback and facial expression recognition data. For example, if a user sends feedback such as "I'm really looking forward to it," the server inputs that feedback into the emotion engine and analyzes the user's emotion as "joy."

[0594] The server communicates emotional information to the generative AI model and adjusts the report.

[0595] The server transmits the emotion information obtained from the emotion engine to the generative AI model, which then adjusts the content of the report based on the user's emotion. For example, if the emotion engine analyzes the user's emotion as "joy," the server transmits that information to the generative AI model, which then regenerates a report that includes more positive elements.

[0596] The server provides the report to the user

[0597] The server finally sends the generated report to the user's email address, and the user receives the email and checks the report on their device. For example, the server sends the generated report to the email address specified by the user, and the user receives the email and checks the report.

[0598] Specific examples

[0599] Prompt Sentence Examples

[0600] "Please create the following market analysis report, focusing on the Japanese IT market in 2023."

[0601] In this way, the system can provide a report that is adjusted based on the user's emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0602] Step 1:

[0603] A user requests a report

[0604] Input: A user uses a terminal to access the system's interface and enters prompt statements.

[0605] Specific behavior: The user enters "Please create a report on Japan's IT market in 2023" and clicks the submit button.

[0606] Output: The user's request is sent to the server.

[0607] Step 2:

[0608] The server runs the generative AI model and generates a report.

[0609] Input: The server receives the user's prompt.

[0610] Specific operation: The server launches a generative AI model (e.g., GPT-4) and inputs a prompt.

[0611] Data processing: A generative AI model generates a report based on the prompt.

[0612] Output: The generated report is returned to the server.

[0613] Step 3:

[0614] The server starts the emotion engine and analyzes the user's emotions.

[0615] Input: The server receives user feedback and facial recognition data.

[0616] Specific behavior: The user sends feedback such as "I'm really looking forward to it." The server inputs that feedback into the emotion engine.

[0617] Data calculation: The emotion engine analyzes the feedback and interprets the user's emotion as "joy."

[0618] Output: The analyzed emotion information is returned to the server.

[0619] Step 4:

[0620] The server communicates emotional information to the generative AI model and adjusts the report.

[0621] Input: The server receives emotion information obtained from the emotion engine.

[0622] Specific operation: The server conveys emotional information to the generative AI model.

[0623] Data processing: Generative AI models adjust report content based on sentiment information.

[0624] Output: The adjusted report is returned to the server.

[0625] Step 5:

[0626] The server provides the report to the user

[0627] Input: The server receives the final generated report.

[0628] What happens: The server sends the generated report to the user's email address.

[0629] Output: User receives email on device and checks report.

[0630] In this way, the system can provide tailored reports based on the user's emotions.

[0631] (Application example 3)

[0632] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0633] Conventional report creation systems using generative AI lacked personalization based on user emotions, making it difficult to increase user satisfaction. Furthermore, there were limited ways to provide generated reports to users at the right time.

[0634] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at the scheduled time using a generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine, means for adjusting the content of the report based on the user emotions, and means for providing the adjusted report to the user. This makes it possible to provide a personalized report according to the user's emotions at an appropriate time.

[0635] An "instruction collection means" is a device or software that receives and records tasks or requests from a user.

[0636] The "means for managing the execution schedule of collected tasks" refers to a device or software that creates and manages a plan for executing received tasks or requests at the appropriate time.

[0637] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to create and obtain reports based on specified tasks.

[0638] "Means for reporting materials output by generative AI" refers to a device or software for providing users with materials created by generative AI.

[0639] The "means for analyzing a user's emotions using an emotion engine" is a device or software for analyzing a user's emotional state.

[0640] A "means for adjusting report content based on user emotion" is a device or software for modifying the content of a generated report in response to the user's emotional state.

[0641] A "means for providing a user with an adjusted report" is a device or software for sending or displaying an adjusted report to a user based on emotions.

[0642] The following system configuration is used as an embodiment of this invention: The server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports using generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine, means for adjusting the content of the report based on the user emotions, and means for providing the adjusted report to the user.

[0643] Hardware and software used

[0644] Hardware: Smartphone

[0645] software:

[0646] Generative AI models (e.g., GPT-4)

[0647] Emotion engines (e.g., Affectiva)

[0648] Email sending service (e.g. SendGrid)

[0649] Processing flow

[0650] 1. Means of collecting instructions:

[0651] Users use their smartphones to input tasks and requests, including direct task lists to cloud services and collecting instructions via communication tools.

[0652] 2. How to manage the execution schedule of collected tasks:

[0653] The server plans and manages the execution of received tasks and requests in a timely manner, thereby ensuring efficient task processing.

[0654] 3. How to create and retrieve reports using generative AI:

[0655] The server uses a generative AI model (e.g., GPT-4) to generate and retrieve reports based on the specified tasks.

[0656] 4. Means of reporting materials generated by generative AI:

[0657] The server provides the user with the materials generated by the generative AI, including instructions for sending the report to the user's email address using an email sending service (e.g., SendGrid).

[0658] 5. How to analyze user sentiment using an emotion engine:

[0659] The server uses an emotion engine (e.g., Affectiva) to analyze emotions from the user's text. For example, if a user types, "I'm feeling very happy today!", the emotion engine will detect "joy."

[0660] 6. How to tailor report content based on user sentiment:

[0661] The server changes the content of the generated report depending on the user's emotional state. For example, if the user is feeling "joy," the generative AI generates a report with content related to "joy."

[0662] 7. Means of providing tailored reports to users:

[0663] The server sends or displays the report adjusted based on the emotion to the user, thereby providing a personalized report according to the user's emotion.

[0664] Specific examples

[0665] If a user types "I'm feeling very happy today!", the emotion engine will detect "joy" and the generative AI will generate a report on content related to "joy." The generated report will be sent to the user's email address using an email sending service.

[0666] Prompt Sentence Examples

[0667] Generate a report that makes the user feel joy. Include positive news and uplifting stories.

[0668] In this way, reports tailored to the user's emotions can be provided, enabling more personalized content delivery.

[0669] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0670] Step 1:

[0671] Users input tasks and requests using their smartphones. These tasks and requests are sent to the server via a task list or communication tool directly input to the cloud service. The server collects these instructions and stores them in a database.

[0672] Step 2:

[0673] The server manages the execution schedule based on the collected tasks and requests. Specifically, it takes into account the priority and deadlines of the tasks and creates a plan to execute them at the appropriate time. The schedule information is stored in a database.

[0674] Step 3:

[0675] At the scheduled time, the server uses a generative AI model (e.g., GPT-4) to generate a report based on the specified task. The server inputs the prompt sentence into the generative AI model and retrieves the generated report. The generated report is temporarily stored in memory.

[0676] Step 4:

[0677] The server uses an email sending service (e.g., SendGrid) to provide the user with the materials output by the generative AI model. It creates and sends an email to send the generated report to the user's email address.

[0678] Step 5:

[0679] A user inputs emotional text using a smartphone, for example, "I feel very happy today!" The input text is sent to the server.

[0680] Step 6:

[0681] The server uses an emotion engine (e.g., Affectiva) to analyze the emotion from the user's text. The input text is passed to the emotion engine and the emotion analysis result is obtained. The emotion analysis result is temporarily stored in memory.

[0682] Step 7:

[0683] The server adjusts the content of the generated report based on the results of the sentiment analysis. Specifically, it inputs new prompts into the generative AI model according to the user's emotional state and generates an adjusted report. The adjusted report is temporarily stored in memory.

[0684] Step 8:

[0685] The server again uses the email sending service to provide the adjusted report to the user, creating and sending an email to send the adjusted report to the user's email address.

[0686] In this way, it is possible to provide a personalized report according to the user's emotions at an appropriate time.

[0687] 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.

[0688] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0689] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0690] 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.

[0691] [Second embodiment]

[0692] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0693] 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.

[0694] 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).

[0695] 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.

[0696] 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.

[0697] 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).

[0698] 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.

[0699] 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.

[0700] 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.

[0701] 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.

[0702] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0703] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0704] "Example 1"

[0705] The system of the present invention provides a to-do list that can be directly input into iPaaS as a means of collecting instructions from users. Specifically, when a user inputs a task into the to-do list, the system collects it and manages the task execution schedule. For example, if a user inputs the task "Create a report by 10:00 AM tomorrow," the system collects this task and schedules the task of creating the report by 10:00 AM tomorrow.

[0706] "Example 2"

[0707] At the scheduled time, the system uses generative AI to create and retrieve the report. Specifically, the generative AI collects the necessary information and creates a report based on that information. For example, the generative AI collects information from the internet and creates a report based on that information.

[0708] "Example 3"

[0709] As a means of reporting the materials output by the generative AI, the system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report created by the generative AI by sending it to the user's email address, etc.

[0710] The processing flow of each embodiment will be described below.

[0711] "Example 1"

[0712] Step 1: The user enters a task into the to-do list directly into the iPaaS. For example, the user enters a task such as "Create a report by 10:00 AM tomorrow."

[0713] Step 2: The system collects input from the user and manages the task execution schedule. Specifically, the system collects the task "Create a report by 10:00 AM tomorrow" and schedules the task to create the report by 10:00 AM tomorrow. "Example 2"

[0714] Step 1: At the scheduled time, the system uses generative AI to generate a report. Specifically, the generative AI collects the necessary information and generates a report based on that information.

[0715] Step 2: The system retrieves the report created by the generative AI. For example, the generative AI collects information from the internet, creates a report based on that information, and the system retrieves that report.

[0716] "Example 3"

[0717] Step 1: The system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report by sending it to the user's email address.

[0718] Example 1

[0719] Next, a description will be given of Example 1 of Form 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."

[0720] Conventional task management systems required users to manually input tasks and manage schedules, resulting in problems that reduced efficiency. Task reminder settings and notifications were also insufficient, meaning users could miss deadlines. Furthermore, report creation using generative artificial intelligence was not automated, placing a heavy burden on users.

[0721] 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.

[0722] In this invention, the server includes means for collecting instructions, means for managing the collected task execution schedules, means for creating and acquiring reports for multiple tasks at scheduled times using generative artificial intelligence, means for reporting materials output by the generative artificial intelligence, means for setting and notifying task reminders, means for saving task data in a database, and means for generating task schedules. This allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and automatically create reports using generative artificial intelligence.

[0723] The "means for collecting instructions" is an interface for inputting tasks and instructions from the user and sending them to the system.

[0724] The "means for managing execution schedules of collected tasks" is a function for creating and managing execution schedules based on collected tasks.

[0725] "Generative AI" is an AI technology that automatically generates reports and documents based on input data.

[0726] "Means for creating and obtaining reports" refers to a function for creating reports using generative artificial intelligence and obtaining those reports.

[0727] "Means for reporting materials output by generative artificial intelligence" is a function for providing users with materials created by generative artificial intelligence.

[0728] The "means for setting and notifying task reminders" is a function for setting reminders based on task deadlines and notifying the user.

[0729] The "means for saving task data in a database" is a function for saving collected task data in a database.

[0730] The "means for generating a task schedule" is a function for generating an execution schedule based on collected task data.

[0731] The "worklist with direct input from the integrated platform" is a worklist on an integrated platform that allows users to directly input tasks.

[0732] A "communication tool" is a tool that a user uses to send tasks or instructions to the system.

[0733] The present invention relates to a system that allows a user to efficiently manage tasks and automatically create reports by utilizing generative artificial intelligence. Specific embodiments of this system will be described below.

[0734] First, the user inputs a task into the task list directly input on the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The user's device (PC or smartphone) then sends this task to the server. The device sends the task data using an HTTP request.

[0735] The server receives HTTP requests sent from devices and retrieves task data. The server processes the requests using a web framework such as Flask or Django. The retrieved task data is then stored in a database using SQL queries. For example, a relational database such as MySQL or PostgreSQL is used.

[0736] Next, the server generates a task execution schedule based on the saved task data. The server adds the task's due date to the calendar using the Google Calendar API. The server also sets a task reminder and notifies the user. For example, it sets a reminder one hour before the task and notifies the user via email or push notification.

[0737] Furthermore, the server utilizes generative artificial intelligence to create reports at scheduled times. The generative artificial intelligence automatically generates reports and materials based on the input data. The generated reports are provided to the user.

[0738] As a concrete example, consider the case where a user inputs a task such as "Create a report by 10:00 AM tomorrow." When the user enters this task in the integrated platform's direct input to-do list, the device sends the task data to the server as an HTTP request. The server receives the request and saves the task data in a database. The server then uses the Google Calendar API to add the task's deadline to the calendar and set a reminder. It then sends the user an email notification one hour before the task. Furthermore, generative artificial intelligence is used to automatically create the report at the scheduled time and provide it to the user.

[0739] Examples of prompts to be input to a generative AI model include:

[0740] Enter the task "Create a report by 10 AM tomorrow" into the task list of the integrated platform. The system will collect this task and schedule a task to create a report by 10 AM tomorrow.

[0741] In this way, the invention allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and leverage generative artificial intelligence to automatically generate reports.

[0742] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0743] Step 1:

[0744] The user enters a task

[0745] The user inputs tasks into the task list directly into the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The input task data is sent to the terminal.

[0746] Step 2:

[0747] The device sends the task

[0748] The terminal sends the task data entered by the user to the server. Specifically, the task data is sent using an HTTP POST request. The input is the task data, and the output is a request sent to the server.

[0749] Step 3:

[0750] The server receives the task

[0751] The server receives the HTTP POST request sent from the terminal and retrieves the task data. For example, it processes the request using a web framework such as Flask or Django. The input is the HTTP request, and the output is the retrieved task data.

[0752] Step 4:

[0753] The server saves the task in a database

[0754] The server saves the acquired task data in a database. Specifically, it uses SQL queries to insert data into a relational database such as MySQL or PostgreSQL. The input is task data, and the output is data saved in the database.

[0755] Step 5:

[0756] The server generates a schedule of tasks

[0757] The server generates a task execution schedule based on the stored task data. For example, it uses the Google Calendar API to add task deadlines to a calendar. The input is the task data, and the output is the creation of a calendar event.

[0758] Step 6:

[0759] Server sets reminder

[0760] The server sets a reminder based on the task's due date, for example, using the Google Calendar API to set a reminder one hour before the task. The input is the task's due date data, and the output is the reminder setting.

[0761] Step 7:

[0762] The server notifies the user of the reminder

[0763] The server sends notifications to users based on the set reminders. Specifically, it sends reminders to users using email or push notifications. The input is the reminder setting data, and the output is the notification to the user.

[0764] Step 8:

[0765] The server creates reports using generative artificial intelligence

[0766] The server utilizes generative artificial intelligence to generate reports at scheduled times, with the input being the task data and the output being the generated report.

[0767] Step 9:

[0768] The server provides the generated report to the user.

[0769] The server provides the user with the report created by the generative AI. Specifically, it sends the report to the user's terminal. The input is the generated report, and the output is the report provided to the user.

[0770] (Application example 1)

[0771] Next, a description will be given of Application Example 1 of Form 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."

[0772] In conventional factory work management systems, work task input and schedule management were often done manually, resulting in inefficiencies. Furthermore, the system lacked the ability to monitor task progress in real time and adjust schedules as needed, which led to delays and errors.

[0773] 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.

[0774] In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, a means for reporting materials output by the generative AI, a means for inputting work tasks to machinery in a factory, a means for collecting the input tasks and automatically managing the execution schedule, and a means for monitoring the progress of tasks in real time and adjusting the schedule as necessary. This enables efficient management of work tasks in a factory, and real-time progress monitoring and schedule adjustment.

[0775] A "means for collecting instructions" is a device or software for inputting tasks or instructions from a user and collecting them as data.

[0776] The "means for managing the execution schedule of the collected tasks" is a device or software for planning the execution timing of the collected tasks and automatically adjusting the schedule.

[0777] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports based on specified tasks.

[0778] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative artificial intelligence in report format.

[0779] The "means for inputting work tasks to machinery in a factory" refers to a device or software for inputting work tasks and giving instructions to machinery in a factory.

[0780] The "means for collecting input tasks and automatically managing the execution schedule" refers to a device or software for collecting tasks input by a user and automatically managing the execution schedule of those tasks.

[0781] The "means for monitoring the progress of tasks in real time and adjusting the schedule as necessary" refers to a device or software for monitoring the progress of tasks in real time and dynamically adjusting the schedule according to the progress.

[0782] A system for carrying out the present invention is for efficiently managing work tasks in a factory and monitoring progress in real time. A specific embodiment of this system will be described below.

[0783] 1. System Configuration

[0784] The system consists of the following main components:

[0785] Server: Collects tasks, manages schedules, and creates reports using generative AI.

[0786] Terminal: A device (e.g., tablet, PC) used to input work tasks to machinery in a factory.

[0787] Users: Factory workers and managers.

[0788] 2. Hardware and Software Used

[0789] Hardware: Factory robots (e.g. KUKA, Fanuc, etc.), tablets, PCs.

[0790] Software: Python, APScheduler (scheduling library), generative AI model.

[0791] 3. Data processing and calculation

[0792] Server Processing

[0793] The server collects tasks entered by users and manages the execution schedule. Specifically, it performs the following processes:

[0794] 1. Task collection: Tasks entered by users through the terminal are saved in a database.

[0795] 2. Schedule management: Using APScheduler, the execution timing of collected tasks is planned and the schedule is automatically adjusted.

[0796] 3. Report Generation: Use generative AI models to automatically generate and retrieve reports based on specified tasks.

[0797] Terminal handling

[0798] The terminal is a device for inputting work tasks to machines in a factory. A user inputs a task using the terminal, and the task is sent to a server.

[0799] User operations

[0800] Users use terminals to input work tasks for machines in a factory. The input tasks are sent to a server, which collects the tasks and manages the schedule.

[0801] 4. Specific Examples

[0802] For example, a user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." This task is sent to the server, which uses APScheduler to schedule the task to run at the specified time. Once the task is completed, a report is automatically generated using a generative AI model.

[0803] 5. Examples of prompts

[0804] The user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00". The system collects this task and schedules it to run at the specified time. Once the task is complete, the status is updated to "completed".

[0805] The above is a specific embodiment for carrying out the present invention. This system enables efficient management of work tasks within a factory, progress monitoring in real time, and schedule adjustment.

[0806] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0807] Step 1:

[0808] The user inputs a work task using a terminal. For example, the user inputs a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." The input task is sent from the terminal to the server. The input data consists of the task name and deadline.

[0809] Step 2:

[0810] The server receives the task sent from the terminal and stores it in the database. The server analyzes the received task data and extracts the task name and deadline time. This stores the basic information of the task in the database.

[0811] Step 3:

[0812] The server uses APScheduler to plan the execution timing of the collected tasks and automatically adjust the schedule. The server schedules jobs to execute the tasks based on the task deadlines. This determines the execution timing of the tasks.

[0813] Step 4:

[0814] The server executes the task at the specified time. For example, it sends an instruction to a machine in a factory to execute the task "Inspect Machine A" at the specified time. This executes the task.

[0815] Step 5:

[0816] The server monitors the progress of the task in real time. The server receives feedback from the machinery in the factory and updates the progress of the task, allowing the progress of the task to be monitored in real time.

[0817] Step 6:

[0818] The server uses a generative AI model to automatically create a report after the task is completed. The server inputs the results of the task execution into the generative AI model and generates a report. This outputs the results of the task execution as a report.

[0819] Step 7:

[0820] The server provides the generated report to the user. The server sends the generated report to the user's terminal so that the user can check the report. This allows the user to check the results of the task execution.

[0821] Example 2

[0822] Next, a description will be given of Example 2 of Form 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."

[0823] Conventional report creation systems require users to manually collect information and create reports, which is time-consuming and labor-intensive. Furthermore, the information collection and report creation often lack accuracy and consistency. Furthermore, they lack the functionality to automatically generate reports based on a schedule, making it difficult to provide timely information. To solve these issues, a system that can efficiently and automatically generate reports and provide them to users is needed.

[0824] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0825] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for collecting information using a generative AI model at the scheduled time and creating a report based on a prompt sentence, means for saving the generated report and notifying the user, and means for the user to obtain the report through a terminal. This eliminates the need for the user to manually collect information and enables efficient, automatic, and timely acquisition of highly accurate reports.

[0826] The "means for collecting instructions" is a function for collecting tasks and requests from users.

[0827] The "means for managing the execution schedule of collected tasks" is a function for managing the execution timing of collected tasks and requests and executing them at the appropriate time.

[0828] A "generative AI model" is a model for generating data using artificial intelligence, such as a model that performs natural language processing.

[0829] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[0830] "Means for creating reports" refers to a function that automatically creates reports using a generative AI model based on collected information.

[0831] The "means for saving the generated report" is a function for saving the generated report in a database or a file system.

[0832] "Means for notifying the user" is a function for notifying the user that a generated report is available.

[0833] "Means for users to retrieve reports through a terminal" refers to the functionality that allows users to access and retrieve saved reports using a terminal such as a computer or mobile device.

[0834] The present invention provides a system for allowing users to efficiently and automatically generate and obtain reports. Specific embodiments of this system will be described below.

[0835] System configuration

[0836] This system is mainly composed of three elements: a server, a terminal, and a user. The server plays a central role in collecting information and creating reports using a generative AI model. The terminal is a device that allows the user to access the server and obtain the generated reports. The user is the entity that uses the system to generate and obtain reports.

[0837] Hardware and software used

[0838] The server is a high-performance computer with sufficient computing power to run generative AI models. Specifically, it requires a CPU, GPU, memory, and storage. For software, a framework (such as TensorFlow or PyTorch) for running generative AI models (e.g., models that perform natural language processing) is used.

[0839] A terminal is a device that allows a user to access a server, and includes PCs, tablets, smartphones, etc. A web browser and dedicated applications are installed on the terminal, providing an interface for communicating with the server.

[0840] Data processing and calculation

[0841] The server first collects instructions from users via task lists and communication tools, then manages the execution schedule of the collected tasks and executes the generative AI model at the specified time.

[0842] The generative AI model collects the necessary information from the internet based on a prompt, such as "Please write a report on the latest AI technology." The collected information is temporarily stored on the server.

[0843] The server then re-enters the generative AI model with prompts based on the collected information to generate a report, which is then stored in a database or file system on the server.

[0844] Specific examples

[0845] For example, if a user wants a "report on the latest AI technology," the server inputs the following prompt into the generative AI model:

[0846] Example prompt sentence:

[0847] "Please write a report on the latest AI technologies. In particular, please provide details on the major innovations and their applications announced in 2023."

[0848] The generative AI model collects relevant information from the internet based on the prompt and creates a report. The report is then saved on a server and sent to the user. The user can access the server via their device and download and view the generated report.

[0849] In this way, the server automatically generates reports based on a schedule, enabling users to obtain the information they need in a timely manner.

[0850] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0851] Step 1:

[0852] The server collects instructions from users. The inputs are tasks and requests provided by users through task lists and communication tools. The server stores these instructions in a database. Specifically, the server retrieves data from task lists and communication tools via APIs and stores it in the database.

[0853] Step 2:

[0854] The server manages the execution schedule of the collected tasks. The input is task information stored in a database. The server uses this information to schedule the execution timing of the tasks. Specifically, the server uses a scheduler to set the execution time of each task and set a timer.

[0855] Step 3:

[0856] At the scheduled time, the server uses the generative AI model to collect information. The inputs are a prompt and scheduled task information. The server inputs the prompt into the generative AI model and collects the necessary information from the Internet. Specifically, the server inputs the prompt "Please create a report on the latest AI technology" into the generative AI model and uses web scraping technology to collect related information.

[0857] Step 4:

[0858] The server then inputs a prompt to the generative AI model based on the collected information and generates a report. The inputs are the collected information and the prompt. The server inputs the prompt to the generative AI model, saying, "Please create a detailed report on the latest AI technology based on the collected information," and receives the generated report. Specifically, the server retrieves the collected information from the database, inputs it into the generative AI model, and generates a report.

[0859] Step 5:

[0860] The server saves the generated report and notifies the user. The input is the generated report. The server saves the report in a database or file system and notifies the user via email or push notification. Specifically, the server saves the generated report in a specific directory and sends a notification based on the user's contact information.

[0861] Step 6:

[0862] The user accesses the server through their device and retrieves the generated report. The input is a notification from the server. The user accesses the server using a web browser or a dedicated application on their device and downloads the saved report. Specifically, the user clicks the link in the notification, logs in to the server, and downloads the report.

[0863] (Application example 2)

[0864] Next, a description will be given of Application Example 2 of Form 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."

[0865] Logistics centers are required to be able to grasp operational and inventory status in a timely manner and operate efficiently. However, with conventional methods, collecting information and creating reports requires a great deal of time and effort, making it difficult to provide information in real time.

[0866] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at the scheduled time using generative AI, means for reporting materials output by the generative AI, means for collecting logistics-related information, means for generating reports based on the collected logistics-related information, and means for notifying the generated reports. This makes it possible to grasp the operating status and inventory status of the logistics center in real time, enabling efficient operation.

[0867] A "means for collecting instructions" is a device or software for collecting instructions or tasks from a user.

[0868] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[0869] "Means for utilizing generative AI to generate and obtain reports based on multiple tasks at scheduled times" refers to a device or software that uses generative AI to generate and obtain reports based on multiple tasks at set times.

[0870] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative AI in report format.

[0871] "Means for collecting logistics-related information" means devices or software for collecting logistics-related data and news from the Internet and other sources.

[0872] The "means for generating a report based on the collected logistics-related information" refers to a device or software for generating a report based on the collected logistics-related information.

[0873] The "means for notifying the user of the generated report" is a device or software for notifying the user of the generated report.

[0874] To implement the present invention, the following system configuration and program are required.

[0875] System Configuration

[0876] 1. Hardware

[0877] Server: Collects data, runs generative AI, and generates reports.

[0878] Smartphone: The device on which the user views the report.

[0879] 2. Software

[0880] Generative AI model: Use generative AI such as OpenAI GPT-3.

[0881] Data Collection Library: Collects logistics-related information from the Internet using the Requests library.

[0882] Scheduling library: Use the Schedule library to manage task execution schedules.

[0883] Program processing explanation

[0884] 1. Means of collecting instructions

[0885] The server uses a task list and communication tools directly input from the cloud service to collect instructions and tasks from users, allowing users to easily input tasks.

[0886] 2. A method for managing the execution schedule of collected tasks

[0887] The server uses a scheduling library to manage the timing and order of execution of collected tasks, so that tasks are executed at the appropriate time.

[0888] 3. A method to generate and obtain reports using AI that generates multiple tasks at scheduled times

[0889] The server uses generative AI to create and retrieve reports based on multiple tasks at set times. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet.

[0890] 4. A means of reporting materials output by generative AI

[0891] The server outputs the materials created by the generative AI in report format and notifies the user on their smartphone, allowing them to receive the latest information in real time.

[0892] 5. Means of collecting logistics-related information

[0893] The server uses a data collection library to collect logistics-related data and news from the Internet, ensuring that the latest logistics-related information is always available.

[0894] 6. A means of generating reports based on collected logistics-related information

[0895] The server generates reports based on the collected logistics-related information using generative AI models, resulting in an informed and detailed report.

[0896] 7. Means of notification of generated reports

[0897] The server then sends the generated report to the smartphone, allowing the user to view the report in real time.

[0898] Specific examples

[0899] Every morning at 9 a.m., the logistics center manager receives a report containing the latest logistics news and inventory status. The report includes the previous day's shipping status, inventory fluctuations, and the latest news in the logistics industry.

[0900] Prompt Sentence Examples

[0901] Write a report based on the following logistics news stories:

[0902] News 1: Latest trends in the logistics industry

[0903] News 2: Introducing new logistics technology

[0904] News 3: Fluctuations in market supply and demand

[0905] In this way, a system can be created that streamlines logistics center operations and provides the latest information in a timely manner.

[0906] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0907] Step 1:

[0908] The server collects instructions and tasks from users. Users input tasks using a task list entered directly into the cloud service or using communication tools. The server receives this input and stores it in a database. The input data includes the task content, priority, scheduled execution time, etc.

[0909] Step 2:

[0910] The server manages the execution schedule of the collected tasks. It uses a scheduling library to set the execution timing and order of the tasks. The input data is the scheduled execution time of the tasks, and the output data is a list of scheduled tasks.

[0911] Step 3:

[0912] The server generates and retrieves reports at scheduled times using generative AI. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet. The input data is the collected logistics-related information, and the output data is the generated report.

[0913] Step 4:

[0914] The server outputs the materials generated by the generative AI in report format and notifies the smartphone. The generated report is sent to the user's smartphone, where the user can check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[0915] Step 5:

[0916] The server uses a data collection library to collect logistics-related data and news from the Internet. This ensures that the latest logistics-related information is always available. The input data is logistics-related information available on the Internet, and the output data is the collected logistics-related information.

[0917] Step 6:

[0918] The server generates reports using a generative AI model based on the collected logistics-related information, resulting in a detailed report based on the information. The input data is the collected logistics-related information, and the output data is the generated report.

[0919] Step 7:

[0920] The server notifies the smartphone of the generated report, allowing the user to check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[0921] Example 3

[0922] Next, a description will be given of Example 3 of Form Example 3. 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."

[0923] Conventional report creation systems require users to manually collect information and create reports, which takes time and effort. Furthermore, there are limited ways to provide generated reports to users, making it difficult to efficiently communicate information.

[0924] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for utilizing the generative AI to create and obtain reports for multiple tasks at the scheduled time, means for providing the user with materials output by the generative AI, means for receiving user input and inputting prompt statements to the generative AI, means for temporarily saving the generated report, means for obtaining the user's contact information, and means for sending the generated report to the user's contact information. This enables the user to create reports efficiently and receive information quickly.

[0925] A "means for collecting instructions" is a device or method that receives instructions or requests from a user and collects information for processing within the system.

[0926] The "means for managing the execution schedule of collected tasks" refers to a device or method for planning and managing the time and order of the collected tasks in order to execute them efficiently.

[0927] "Generative AI" refers to an AI system that has the ability to automatically generate information such as text or reports based on user input.

[0928] "Means for creating and obtaining reports" refers to a device or method for creating reports using generative artificial intelligence and obtaining the created reports.

[0929] "Means for providing a user with materials output by a generative artificial intelligence" refers to a device or method for providing a user with materials created by a generative artificial intelligence.

[0930] "Means for receiving user input and inputting a prompt sentence to the generative AI" refers to a device or method for receiving input from a user and inputting the input as a prompt sentence to the generative AI.

[0931] "Means for temporarily storing generated reports" refers to a device or method for temporarily storing reports generated by generative artificial intelligence.

[0932] The "means for acquiring user contact information" refers to a device or method for acquiring contact information such as a user's email address or phone number.

[0933] The "means for sending the generated report to the user's contact information" refers to a device or method for sending the report generated by the generative artificial intelligence based on the user's contact information.

[0934] The present invention relates to a system for creating reports using generative artificial intelligence and providing the reports to users. Specific embodiments of this system will be described below.

[0935] System configuration

[0936] The system consists of the following main components:

[0937] 1. Server

[0938] 2. Terminal

[0939] 3. Users

[0940] Hardware and software used

[0941] The server provides the computational resources to run generative artificial intelligence models (e.g., OpenAI's GPT-4), temporarily stores the generated reports using a database or file system, and sends the reports to the user's contacts using the SMTP protocol.

[0942] The terminal provides an interface for the user to input the prompt sentence. This can be a device such as a PC or smartphone, and accesses the server through a browser.

[0943] The user uses the system to input a prompt to generate a report and receives the generated report.

[0944] Data processing and calculation

[0945] The server inputs the prompt received from the user into a generative AI model to generate a report, which is temporarily stored on the server and then sent based on the user's contact information.

[0946] Specific examples

[0947] For example, if a user enters the prompt "Write a report on the latest technology trends," the following happens:

[0948] 1. The user enters a prompt:

[0949] The user opens a browser, accesses the system's web page, and types "Write a report on the latest technology trends" into the text box.

[0950] 2. The terminal sends the prompt to the server:

[0951] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text.

[0952] 3. The server receives the prompt and inputs it into the generative AI model:

[0953] The server analyzes the received prompt sentence and inputs it into a generative artificial intelligence model (GPT-4).

[0954] 4. The generative AI model generates the report:

[0955] Based on the prompt, GPT-4 generates a report stating, "Emerging technology trends in 2023 include the evolution of artificial intelligence, the widespread adoption of 5G, and the application of blockchain technology. These technologies are bringing about revolutionary changes in various industries."

[0956] 5. The server temporarily stores the generated report:

[0957] The server stores the generated reports in a database.

[0958] 6. The server gets the user's email address:

[0959] The server obtains the email address from the user's registration information.

[0960] 7. The server sends the generated report to the user's email address:

[0961] The server uses the SMTP protocol to send the generated report to the user's email address.

[0962] 8. User receives email and checks report:

[0963] The user receives a new email in their email client and sees the attached report.

[0964] In this way, the user can create reports efficiently and receive information quickly. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0965] Step 1:

[0966] The user enters a prompt statement.

[0967] A user accesses the system interface from their own device (PC, smartphone, etc.) and inputs a prompt statement indicating the content of the report they want to generate. For example, they might input, "Please create a report on the latest technological trends." The input data is the prompt statement, and the output data is an input confirmation message displayed on the device.

[0968] Step 2:

[0969] The terminal sends the prompt to the server.

[0970] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text. The input data is the prompt text, and the output data is the prompt text sent to the server.

[0971] Step 3:

[0972] The server receives the prompt sentence and inputs it into the generative AI model.

[0973] The server receives the prompt sentence sent from the device and inputs it into a generative AI model (e.g., GPT-4). The input data is the prompt sentence, and the output data is the input result to the generative AI model.

[0974] Step 4:

[0975] A generative AI model generates the report.

[0976] The generative AI model generates a report based on the input prompt, which contains detailed information depending on the content of the prompt. The input data is the prompt, and the output data is the generated report.

[0977] Step 5:

[0978] The server temporarily stores the generated report.

[0979] The server temporarily stores the reports output from the generative AI model. This storage is done using a database or file system. The input data is the generated report, and the output data is the saved report.

[0980] Step 6:

[0981] The server retrieves the user's email address.

[0982] The server obtains the user's email address, which was provided when the user registered with the system. The input data is the user's identification information, and the output data is the obtained email address.

[0983] Step 7:

[0984] The server will send the generated report to the user's email address.

[0985] The server sends the saved report to the user's email address using the SMTP protocol. The input data are the saved report and the email address, and the output data is the email sent.

[0986] Step 8:

[0987] The user receives an email and reviews the report.

[0988] The user receives the email sent from the server in their email client. The generated report is attached to the email or is included in the body of the email. The user checks it and uses it as needed. The input data is the sent email, and the output data is the checked report.

[0989] (Application example 3)

[0990] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0991] Logistics center operators need to efficiently grasp data such as inventory status, shipping status, arrival status, and work efficiency in their daily operations, and make appropriate decisions. However, manually collecting this data and creating reports takes time and effort, hindering efficient business operations. Furthermore, there is a lack of a way to quickly share the generated reports with relevant parties, which can lead to delays in information transmission. To solve these issues, a system that uses generative AI to automatically generate reports and quickly share them is needed.

[0992] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for sending the generated reports by email, and means for generating reports for the logistics center operations manager. This enables the logistics center operations manager to efficiently collect the necessary data and quickly receive the automatically generated reports.

[0993] A "means for collecting instructions" is a device or software for collecting instructions or requests from a user.

[0994] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[0995] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports.

[0996] "Means for reporting materials output by generative AI" refers to a device or software for providing materials output by generative artificial intelligence in report format.

[0997] A "means for emailing a generated report" is a device or software for sending a generated report via email to a designated recipient.

[0998] The "means for generating a report for the logistics center operator" is a device or software for generating a report containing information required by the logistics center operator.

[0999] As an embodiment of the present invention, a report generation system utilizing generative AI is provided for logistics center operators. A specific embodiment of the system is described below.

[1000] 1. System Program

[1001] The system consists of the following main components:

[1002] A means of collecting instructions

[1003] A means to manage the execution schedule of collected tasks

[1004] A means of creating and obtaining reports using generative AI

[1005] A means of reporting materials output by generative AI

[1006] A means to email the generated report

[1007] A means of generating reports for distribution center operations managers

[1008] 2. Program Processing

[1009] The server first collects instructions from users, which are entered via a smartphone application or a web interface. The collected instructions are registered as tasks and their execution schedules are managed.

[1010] Next, the generative AI creates a report based on the scheduled time. The generative AI uses OpenAI's API to generate a report based on the specified prompt. The generated report is saved on the server.

[1011] The generated report is then emailed to the specified email address using Python's smtplib library.

[1012] 3. Hardware and Software Used

[1013] Hardware: Smartphones, servers

[1014] Software: Python, OpenAI API, SMTP server

[1015] 4. Specific Examples

[1016] For example, if a logistics center manager wants to know today's inventory and shipping status, he or she opens a smartphone application and requests report generation. The generative AI generates a report like this:

[1017] Availability:

[1018] Product A: 500 pieces

[1019] Product B: 300 pieces

[1020] Shipping Status:

[1021] Product A: 200 units shipped

[1022] Product B: 100 units shipped

[1023] Availability:

[1024] Product A: 100 units expected to arrive

[1025] Product B: 50 units expected to arrive

[1026] Work efficiency:

[1027] Average work time: 2 hours

[1028] Work efficiency: 85%

[1029] This report will be automatically sent to the administrator's email address.

[1030] 5. Examples of prompts

[1031] An example of a prompt to input to a generative AI model is as follows:

[1032] Prepare a report for the distribution center operations manager. Please include the following information:

[1033] Availability

[1034] Shipping Status

[1035] Stock availability

[1036] Work efficiency

[1037] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1038] Step 1:

[1039] The user inputs report generation instructions via a smartphone application or web interface. The input instructions include the information to be included in the report (inventory status, shipping status, arrival status, work efficiency, etc.), and the user's request is transmitted to the system.

[1040] Step 2:

[1041] The server receives instructions from the user and registers them as tasks. The registered tasks are managed based on an execution schedule. Specifically, the timing and order of task execution are determined. The input is the user's instructions, and the output is the registered tasks.

[1042] Step 3:

[1043] Based on the scheduled time, the server sends a prompt to the generative AI, which contains instructions for generating a report containing the information specified by the user. The input is the scheduled task, and the output is the prompt to the generative AI.

[1044] Step 4:

[1045] The generative AI generates a report based on the prompt. The generated report is sent to the server. The input is the prompt, and the output is the generated report. Specifically, the report is generated using OpenAI's API.

[1046] Step 5:

[1047] The server receives the generated report and sends it as an email to the specified email address. The Python smtplib library is used to send the email. The input is the generated report and the output is the email sent.

[1048] Step 6:

[1049] A user receives an email on a smartphone or other device and views the generated report. The input is the email that was sent, and the output is the report that the user views. The specific behavior is to view the report using the email application.

[1050] 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.

[1051] "Example 1"

[1052] In one embodiment of the present invention, the generative AI includes an emotion engine that recognizes a user's emotions. The emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, text input, etc. For example, if the user senses that they are stressed, the emotion engine communicates that information to the generative AI.

[1053] "Example 2"

[1054] Furthermore, the emotion engine adjusts task priorities based on the user's emotions. For example, if the user feels stressed, the emotion engine communicates this information to the generative AI, which then prioritizes tasks that may reduce stress. Specifically, it prioritizes tasks related to relaxation and tasks that the user is expected to enjoy.

[1055] "Example 3"

[1056] The emotion engine also adjusts the content of the report based on the user's emotions. For example, if the user feels happy, the emotion engine communicates this information to the generative AI, which then adjusts the report content to reflect the user's happiness. Specifically, the report will include information related to the user's happiness.

[1057] The processing flow of each embodiment will be described below.

[1058] "Example 1"

[1059] Step 1: The emotion engine recognizes the user's emotions based on their tone of voice, facial expressions, text input, etc.

[1060] Step 2: The emotion engine communicates the recognized emotion information to the generative AI.

[1061] "Example 2"

[1062] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts task priorities based on the emotional information. Specifically, it prioritizes tasks that may reduce stress.

[1063] "Example 3"

[1064] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts the report content based on the emotion information. Specifically, it includes information related to what makes the user happy.

[1065] Example 1

[1066] Next, a description will be given of Example 1 of Form 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."

[1067] Conventional task management systems provide schedule management and reminder functions for tasks entered by users, but lack consideration for user emotions. Furthermore, there is a need for systems that not only manage task execution schedules but also respond to user emotions. Furthermore, there is a need for a function to automate document creation using generative artificial intelligence. A system that can solve these issues is needed.

[1068] 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.

[1069] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring documents for multiple tasks at scheduled times using generative artificial intelligence, means for documenting materials output by the generative artificial intelligence, means including an emotion engine for recognizing user emotions, and means for responding according to the user's emotions based on information obtained from the emotion engine. This makes it possible to improve the efficiency of user task management and to respond appropriately according to emotions.

[1070] "Means for collecting instructions" refers to the means for inputting tasks and instructions from users and incorporating them into the system.

[1071] The "means for managing the execution schedule of collected tasks" refers to a means for managing the execution timing and deadline of collected tasks and notifying the user at an appropriate time.

[1072] "Generative AI" is an AI technology that automatically generates documents and reports based on user instructions and data.

[1073] "Means for creating and obtaining documents" refers to the use of generative artificial intelligence to create task-based documents and obtain the necessary information.

[1074] "Means of documentation" refers to the means of organizing the materials output by the generative artificial intelligence and compiling them into a formal document.

[1075] The "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, text input, etc.

[1076] "Means for responding according to emotions" refers to means for providing appropriate responses and advice according to the user's emotions based on information obtained from the emotion engine.

[1077] "Worklists entered directly on an integrated platform" refers to a list on an integrated platform where users can enter tasks directly.

[1078] "Communication Tools" are tools that allow users to communicate with the system and are used to gather instructions.

[1079] MODE FOR CARRYING OUT THE INVENTION

[1080] The present invention is a system that allows a user to input a task, manages the execution schedule of the task, and responds according to the user's emotions. A specific embodiment of this system will be described below.

[1081] 1. Task input by user

[1082] Users can use their terminals to input tasks into a task list directly into the integrated platform. For example, a user can input a task such as "Create a report by 10:00 AM tomorrow."

[1083] 2. Task collection by the server

[1084] The server collects tasks entered by users in real time, stores them in a database, and analyzes task details (task name, deadline, priority, etc.).

[1085] 3. Task scheduling by the server

[1086] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on the task deadlines and sends notifications to the user at the appropriate time. For example, when a task deadline is approaching, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow."

[1087] 4. Emotion Recognition by Emotion Engine

[1088] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expressions, text input, etc. For example, if a user inputs the text "I'm very tired today," the emotion engine will recognize that the user is tired.

[1089] 5. Emotion-based responses using generative AI

[1090] The generative AI responds to the user's emotions based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be good to take a short break to relax."

[1091] Specific examples

[1092] Example 1: Task entry and schedule management

[1093] A user enters a task in their to-do list, "Create a report by 10 AM tomorrow." The server collects this task and stores it in a database. The server sets a reminder based on the task's due date, and notifies the user at 9 AM tomorrow, "You have a task to create a report by 10 AM tomorrow."

[1094] Example 2: Emotion recognition and response

[1095] A user enters text such as "I feel very tired today." The emotion engine recognizes that the user is tired and relays this information to the generative AI, which then offers advice such as "It would be good to take a short break to relax."

[1096] Prompt Sentence Examples

[1097] Task input prompt

[1098] "Please add a task to your to-do list to prepare the report by 10:00 AM tomorrow."

[1099] Emotion recognition prompts

[1100] "If the user feels tired, offer them some tips on how to relax."

[1101] The above is a specific embodiment for carrying out the present invention.

[1102] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1103] Step 1:

[1104] A user uses a terminal to input tasks into the integrated platform's direct input task list. The input task includes detailed information such as the task name, deadline, and priority. For example, a task is input as "Create a report by 10:00 AM tomorrow." The input data is the task name "Create report," the deadline "10:00 AM tomorrow," and the priority "High."

[1105] Step 2:

[1106] The server collects tasks entered by users in real time. The collected tasks are stored in a database. The server analyzes detailed information such as task name, deadline, and priority and stores it in the database. The input data is the task information entered by the user, and the output data is the task information stored in the database.

[1107] Step 3:

[1108] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on task deadlines and sends notifications to users at appropriate times. For example, when a task deadline approaches, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow." The input data is the task information stored in the database, and the output data is the notification sent to the user.

[1109] Step 4:

[1110] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expression, text input, etc. For example, if a user enters the text "I'm very tired today," the emotion engine recognizes that the user is tired. The input data is the user's tone of voice, facial expression, text input, etc., and the output data is the user's emotional information.

[1111] Step 5:

[1112] The generative AI responds according to the user's emotions based on the information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be a good idea to take a short break to relax." The input data is the user's emotional information obtained from the emotion engine, and the output data is advice to the user.

[1113] (Application example 1)

[1114] Next, a description will be given of Application Example 1 of Form 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."

[1115] Conventional factory robot systems lack sufficient task schedule management and worker emotional monitoring, resulting in problems such as reduced work efficiency and worker stress. Furthermore, if task instructions are not given properly, the robot's behavior can become unstable. This can lead to a decline in productivity throughout the factory and potentially affect quality control.

[1116] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using a generative AI, a means for reporting materials output by the generative AI, a means for recognizing the emotions of workers using an emotion engine, a means for adjusting the task schedule based on the emotions of workers, and a means for instructing robots to perform tasks. This allows for efficient task schedule management and flexible schedule adjustment based on the emotions of workers. Furthermore, appropriate task instructions are given to robots, improving productivity and quality control throughout the factory.

[1117] A "means for collecting instructions" is an interface or system for collecting tasks or instructions from the user.

[1118] The "means for managing execution schedules of collected tasks" is a system that creates and manages schedules for efficiently executing collected tasks.

[1119] "Means for creating and obtaining reports using generative AI" refers to a system that uses generative artificial intelligence to automatically create and obtain task-based reports.

[1120] "Means for reporting materials output by generative AI" refers to a system that compiles and reports materials created by generative artificial intelligence.

[1121] The "means for recognizing a worker's emotions using an emotion engine" is an engine for recognizing emotions from the worker's tone of voice, facial expressions, text input, etc.

[1122] The "means for adjusting task schedules based on worker emotions" is a system that flexibly adjusts task schedules according to the recognized emotions of workers.

[1123] The "means for instructing robots to perform tasks" is a system for instructing factory robots to perform scheduled tasks and have them execute them.

[1124] A system for carrying out this invention is configured as follows: The server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports using generative AI, means for reporting materials output by the generative AI, means for recognizing the emotions of workers using an emotion engine, means for adjusting the task schedule based on the emotions of workers, and means for instructing robots on tasks.

[1125] Program processing explanation

[1126] The server processes and calculates data using the following hardware and software.

[1127] Hardware: Factory robots, emotion-recognition cameras, microphones

[1128] Software: EmotionEngine, TaskScheduler, RobotController

[1129] 1. A means of collecting instructions: The server provides an interface for collecting tasks and instructions from users, for example, via a to-do list or communication tool directly input into the iPaaS.

[1130] 2. A means for managing task execution schedules: The server creates and manages schedules for efficiently executing collected tasks. It uses TaskScheduler to generate schedules that take into account task deadlines and priorities.

[1131] 3. Using generative AI to create and retrieve reports: The server uses generative AI to automatically create and retrieve task-based reports. For example, if a user inputs a task such as "Create a report by 10:00 AM tomorrow," the generative AI will create a report based on that task.

[1132] 4. A means of reporting the materials output by the generative AI: The server compiles and reports the materials created by the generative AI, allowing users to efficiently check the progress of their tasks.

[1133] 5. Means of recognizing worker emotions using an emotion engine: The server uses an emotion engine to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The Emotion Engine is responsible for this, and can detect when a worker is feeling stressed.

[1134] 6. Adjusting task schedules based on worker emotions: The server flexibly adjusts task schedules according to the worker's recognized emotions. For example, if a worker is feeling stressed, it can change the priority of tasks or adjust the schedule to include breaks.

[1135] 7. Means for instructing robots to carry out tasks: The server instructs factory robots to carry out scheduled tasks. RobotController is used to issue specific work instructions to the robots.

[1136] Specific examples

[1137] For example, if a factory manager enters the tasks "Maintain Machine A" and "Assemble Part B" into a to-do list, the server collects them and creates a task schedule. Generative AI creates reports based on the tasks, and Emotion Engine monitors the emotions of workers. If a worker is feeling stressed, Task Scheduler adjusts the schedule, and Robot Controller issues appropriate instructions to the robot.

[1138] Prompt Sentence Examples

[1139] "The factory manager has entered tasks into the to-do list. Collect task descriptions and deadlines and issue instructions to the robot. Also, monitor the emotions of the workers and adjust their schedules if they are feeling stressed."

[1140] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1141] Step 1:

[1142] The user inputs tasks into the ToDo list. For example, the user inputs tasks such as "Maintain machine A" or "Assemble part B." The input tasks are sent to the server. The input data includes a task description and a deadline.

[1143] Step 2:

[1144] The server collects instructions. The server collects tasks from the to-do list submitted by the user and stores them in a database. The collected data includes task descriptions and deadlines.

[1145] Step 3:

[1146] The server manages the task execution schedule. The server passes the collected tasks to the TaskScheduler, which generates a schedule that takes into account the task deadlines and priorities. The input data are task descriptions and deadlines, and the output data is a list of scheduled tasks.

[1147] Step 4:

[1148] The server uses generative AI to create and retrieve reports. The server inputs the task details into the generative AI, which then automatically creates the report. The input data is the task description, and the output data is the generated report.

[1149] Step 5:

[1150] The server reports the materials output by the generative AI. The server provides the report created by the generative AI to the user. The input data is the generated report, and the output data is the report provided to the user.

[1151] Step 6:

[1152] The server uses an emotion engine to recognize the worker's emotions. The server uses an emotion recognition camera and microphone to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The input data is the worker's voice and video, and the output data is the recognized emotional information.

[1153] Step 7:

[1154] The server adjusts the task schedule based on the worker's emotions. The server flexibly adjusts the task schedule using TaskScheduler based on the recognized emotion information. The input data is the recognized emotion information, and the output data is the adjusted task schedule.

[1155] Step 8:

[1156] The server issues tasks to the robots. The server then passes the scheduled tasks to the RobotController, which issues specific work instructions to the factory robots. The input data is the scheduled task list, and the output data is the work instructions for the robots.

[1157] Example 2

[1158] Next, a description will be given of Example 2 of Form 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."

[1159] Conventional task management systems prioritize tasks without considering the user's emotional state, which can have a negative impact on user stress and efficiency. Furthermore, report creation using generative AI does not provide information based on the user's emotions, so it cannot fully meet user needs. This leads to issues such as reduced user satisfaction and productivity.

[1160] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1161] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for acquiring user emotional data, means for analyzing the acquired emotional data, means for adjusting task priorities based on the analysis results, and means for making final adjustments to the report based on the adjusted task priorities. This makes it possible to adjust task priorities according to the user's emotional state and create reports using generative AI.

[1162] A "means for collecting instructions" is a device or software for collecting tasks or requests from a user.

[1163] The "means for managing the execution schedule of the collected tasks" is a device or software that sets and manages a schedule for efficiently executing the collected tasks.

[1164] "Means for creating and obtaining reports using generative AI" refers to devices or software that automatically create reports using generative AI technology and obtain them.

[1165] "Means for reporting materials output by generative AI" refers to a device or software for providing users with materials generated by generative AI.

[1166] The "means for acquiring user emotional data" refers to a device or software for detecting the user's emotional state and collecting that data.

[1167] The "means for analyzing acquired emotional data" refers to a device or software for analyzing collected emotional data of users and obtaining the results.

[1168] The "means for adjusting task priorities based on analysis results" refers to a device or software for dynamically changing task priorities based on the analysis results of emotion data.

[1169] The "means for finalizing the report based on the priority of the adjusted task" is a device or software for finalizing the content of the report by taking into account the priority of the adjusted task.

[1170] MODE FOR CARRYING OUT THE INVENTION

[1171] This invention is a system that adjusts task priorities based on the user's emotional state and creates reports using generative AI. Specific embodiments of this system are described below.

[1172] System configuration

[1173] Server Configuration

[1174] The server contains several modules with the following functions:

[1175] 1. Instruction collection module: Collects tasks and requests from users, for example, providing a task management list through a cloud service.

[1176] 2. Schedule Management Module: Set and manage schedules to efficiently execute collected tasks.

[1177] 3. Generative AI module: Uses generative AI technology (e.g., GPT-4) to automatically generate and retrieve reports.

[1178] 4. Report delivery module: Provides users with materials generated by generative AI.

[1179] Device configuration

[1180] The terminal has the following features:

[1181] 1. Emotion Data Acquisition Module: Detects the user's emotional state and collects that data. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice, and sends them to emotion analysis software (e.g., Affectiva).

[1182] Emotion engine configuration

[1183] The emotion engine has the following functions:

[1184] 1. Emotion analysis module: Analyzes the acquired emotion data and obtains the results, for example, determining whether the user is feeling stressed.

[1185] 2. Priority adjustment module: Dynamically changes task priorities based on the results of emotion data analysis.

[1186] Specific examples

[1187] If a user is feeling stressed at work, the emotion engine analyzes that information and relays it to the generative AI, which then collects information related to relaxation (e.g., meditation techniques and relaxation music) and creates a report based on that information.

[1188] Prompt Sentence Examples

[1189] "If the user is stressed, collect information related to relaxation and create a report."

[1190] The system aims to reduce stress for users by responding flexibly to their emotional state and providing the most appropriate information.

[1191] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1192] Program processing flow

[1193] Step 1: Check the schedule

[1194] The server uses a schedule management module to start processing at a specified time. It receives pre-configured schedule information as input and generates a trigger to proceed to the next processing step as output. Specifically, it uses a Cron job to start the report creation process every day at 9:00 AM.

[1195] Step 2: Start creating reports

[1196] The server launches the generative AI module and starts the report creation process. It receives a trigger from the schedule management module as input and initializes the generative AI model as output. Specifically, it runs a Python script to launch the generative AI model (e.g., GPT-4).

[1197] Step 3: Gather information

[1198] The generative AI model collects information from the internet. As input, it receives prompts required for creating a report, and as output, it generates the collected information. Specifically, it uses BeautifulSoup to scrape the latest economic news from news sites.

[1199] Step 4: Generate a report

[1200] A generative AI model generates a report based on collected information. It receives collected information as input and generates a generated report as output. Specifically, it uses natural language processing technology to organize the information and create a report in an easy-to-understand format.

[1201] Step 5: Obtaining emotion data

[1202] The device acquires the user's emotional data. It captures the user's facial expressions and voice as input and generates emotional data as output. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice and sends them to emotion analysis software (e.g., Affectiva).

[1203] Step 6: Sentiment Analysis

[1204] The emotion engine analyzes the acquired emotion data. It receives the emotion data sent from the device as input and generates the analysis results as output. Specifically, it analyzes the data from Affectiva and determines whether the user is feeling stressed.

[1205] Step 7: Adjust task priorities

[1206] The server receives data from the emotion engine and adjusts task priorities. It receives the results of emotion analysis as input and generates adjusted task priorities as output. Specific behavior is to increase the priority of relaxation-related tasks (e.g., meditation suggestions).

[1207] Step 8: Finalize and distribute the report

[1208] The generative AI model finalizes the report based on information from the emotion engine. It receives the adjusted task priorities as input and generates the final report as output. Specifically, it adds relaxation-related information to the report and sends the final report to the user's device via email.

[1209] In this way, task prioritization based on the user's emotional state and report creation using generative AI are achieved.

[1210] (Application example 2)

[1211] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1212] While conventional systems can generate reports at scheduled times using generative AI, they lack the ability to adjust task priorities based on user emotions. This makes it difficult to reduce user stress and fatigue, and productivity improvements cannot be expected.

[1213] 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.

[1214] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine and adjusting task priorities, and means for increasing the priority of relaxation tasks based on the analysis results of the emotion engine. This makes it possible to adjust task priorities based on the user's emotions and reduce stress and fatigue.

[1215] A "means for collecting instructions" is a device or software for collecting tasks or instructions from a user.

[1216] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[1217] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative AI to create reports based on data and obtain them.

[1218] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative AI as a report.

[1219] The "means for analyzing a user's emotions using an emotion engine and adjusting task priorities" refers to a device or software for analyzing a user's emotions using an emotion engine and adjusting task priorities based on the results of the analysis.

[1220] The "means for increasing the priority of a relaxation task based on the analysis results of the emotion engine" is a device or software for increasing the priority of a relaxation task for reducing stress and fatigue of a user based on the analysis results of the emotion engine.

[1221] A system for implementing the present invention has the following configuration.

[1222] 1. System Program

[1223] The system includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at scheduled times using a generative AI, means for reporting materials output by the generative AI, means for analyzing a user's emotions using an emotion engine and adjusting the priority of tasks, and means for increasing the priority of relaxation tasks based on the analysis results of the emotion engine.

[1224] 2. Program processing explanation

[1225] The server uses the following hardware and software:

[1226] Hardware: Factory robots, sensors (to detect worker emotions)

[1227] Software: EmotionEngine (emotion engine), AIReportGenerator (generative AI), requests (for data collection)

[1228] The server uses the requests library to collect factory data from the Internet. It then uses AIReportGenerator to generate and save reports based on the collected data. It also uses EmotionEngine to analyze workers' emotions and adjust task priorities based on the results. For example, if a worker feels fatigued, it increases the priority of relaxation tasks.

[1229] 3. Specific Examples

[1230] As a concrete example, consider a usage scenario in a factory. If a worker in the factory feels fatigued, the emotion engine detects this information and the generative AI prioritizes relaxation tasks (e.g., short breaks or light stretching), thereby reducing worker fatigue and improving productivity.

[1231] Prompt Sentence Examples

[1232] Create a program that analyzes the emotions of workers in a factory and prioritizes relaxation tasks if they are feeling fatigued. Use generative AI to create production reports and analyze emotions using an emotion engine.

[1233] In this way, the system can adjust task priorities based on the user's emotions and support efficient production activities.

[1234] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1235] Step 1:

[1236] The server uses the requests library to collect factory data from the Internet. Specifically, it retrieves JSON-formatted data from a specified URL. The input is the URL, and the output is the retrieved JSON data. This data includes information about the factory's production status and the status of workers.

[1237] Step 2:

[1238] The server generates a report based on the collected data using AIReportGenerator. The input is the JSON data obtained in step 1, and the output is the generated report text. Specifically, AIReportGenerator parses the data, extracts important information, and formats it into a report.

[1239] Step 3:

[1240] The server saves the generated report. The input is the report text generated in step 2, and the output is the saved report file. Specifically, it writes the report text to a file and saves it in the specified directory.

[1241] Step 4:

[1242] The server uses EmotionEngine to analyze the worker's emotions. The input is the worker's biometric data acquired from sensors, and the output is the emotion analysis result. Specifically, EmotionEngine analyzes the biometric data and determines the worker's emotional state (e.g., fatigue, stress, relaxation).

[1243] Step 5:

[1244] The server adjusts task priorities based on the emotion engine's analysis results. The input is the emotion analysis result obtained in step 4, and the output is an adjusted task priority list. Specifically, if the emotion engine detects fatigue or stress, it updates the task list to increase the priority of relaxation tasks.

[1245] Step 6:

[1246] The server reflects the adjusted task priority list in the execution schedule. The input is the task priority list adjusted in step 5, and the output is the updated execution schedule. Specifically, the execution schedule is reorganized based on the task priorities, and the relaxation task is set to be executed with priority.

[1247] In this way, the server can adjust task priorities based on the user's emotions and support efficient production activities.

[1248] Example 3

[1249] Next, a description will be given of Example 3 of Form Example 3. 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."

[1250] Conventional report generation systems were unable to adjust report content based on user sentiment, making it difficult to increase user satisfaction. Furthermore, the means by which generated reports could be provided to users were limited, requiring more flexible responses.

[1251] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring a report using a generative AI model for multiple tasks at the scheduled time, means for reporting materials output by the generative AI model, means for analyzing user emotions, means for adjusting the content of the report based on the analyzed emotion information, and means for providing the adjusted report to the user. This makes it possible to generate and provide a report according to the user's emotions.

[1252] "Instruction collection means" refers to the interface or system used to receive tasks or requests from users.

[1253] "Means for managing the execution schedule of collected tasks" refers to a system that sets and manages schedules for executing received tasks and requests at the appropriate time.

[1254] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to generate reports and materials based on user instructions.

[1255] "Means for creating and obtaining reports" refers to a system for creating reports using a generative AI model and obtaining those reports.

[1256] "Means for reporting materials output by a generative AI model" refers to a system for providing users with reports and materials created by a generative AI model.

[1257] "Means for analyzing user emotions" refers to a system that analyzes a user's emotional state using user feedback, facial expression recognition data, etc.

[1258] "Means for adjusting the content of the report based on the analyzed emotional information" refers to a system that appropriately changes and adjusts the content of the generated report based on the user's emotional information.

[1259] "Means for providing a user with a tailored report" means a system for sending and providing a user with a tailored report based on emotional information.

[1260] This invention is a system that uses a generative AI model to generate and provide reports based on user emotions. Specific embodiments of this system are described below.

[1261] Hardware and software used

[1262] Hardware: Servers, user devices (PCs, smartphones, etc.)

[1263] Software: Generative AI models (e.g., GPT-4), emotion engines, email delivery systems

[1264] System Operation Overview

[1265] A user requests a report

[1266] The user uses a terminal to access the system interface, enters a prompt specifying the content of the report, and submits the request. For example, the user enters "Please create a report on the Japanese IT market in 2023" and clicks the submit button.

[1267] The server runs the generative AI model and generates a report.

[1268] The server receives the request and launches a generative AI model (e.g., GPT-4). The server inputs the user's prompt into the generative AI model and generates a report. For example, the server inputs the prompt "Please write a report on Japan's IT market in 2023" into GPT-4 and obtains the generated report.

[1269] The server starts the emotion engine and analyzes the user's emotions.

[1270] The server starts the emotion engine and collects the user's emotion data. The emotion data is obtained from user feedback and facial expression recognition data. For example, if a user sends feedback such as "I'm really looking forward to it," the server inputs that feedback into the emotion engine and analyzes the user's emotion as "joy."

[1271] The server communicates emotional information to the generative AI model and adjusts the report.

[1272] The server transmits the emotion information obtained from the emotion engine to the generative AI model, which then adjusts the content of the report based on the user's emotion. For example, if the emotion engine analyzes the user's emotion as "joy," the server transmits that information to the generative AI model, which then regenerates a report that includes more positive elements.

[1273] The server provides the report to the user

[1274] The server finally sends the generated report to the user's email address, and the user receives the email and checks the report on their device. For example, the server sends the generated report to the email address specified by the user, and the user receives the email and checks the report.

[1275] Specific examples

[1276] Prompt Sentence Examples

[1277] "Please create the following market analysis report, focusing on the Japanese IT market in 2023."

[1278] In this way, the system can provide a report that is adjusted based on the user's emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1279] Step 1:

[1280] A user requests a report

[1281] Input: A user uses a terminal to access the system's interface and enters prompt statements.

[1282] Specific behavior: The user enters "Please create a report on Japan's IT market in 2023" and clicks the submit button.

[1283] Output: The user's request is sent to the server.

[1284] Step 2:

[1285] The server runs the generative AI model and generates a report.

[1286] Input: The server receives the user's prompt.

[1287] Specific operation: The server launches a generative AI model (e.g., GPT-4) and inputs a prompt.

[1288] Data processing: A generative AI model generates a report based on the prompt.

[1289] Output: The generated report is returned to the server.

[1290] Step 3:

[1291] The server starts the emotion engine and analyzes the user's emotions.

[1292] Input: The server receives user feedback and facial recognition data.

[1293] Specific behavior: The user sends feedback such as "I'm really looking forward to it." The server inputs that feedback into the emotion engine.

[1294] Data calculation: The emotion engine analyzes the feedback and interprets the user's emotion as "joy."

[1295] Output: The analyzed emotion information is returned to the server.

[1296] Step 4:

[1297] The server communicates emotional information to the generative AI model and adjusts the report.

[1298] Input: The server receives emotion information obtained from the emotion engine.

[1299] Specific operation: The server conveys emotional information to the generative AI model.

[1300] Data processing: Generative AI models adjust report content based on sentiment information.

[1301] Output: The adjusted report is returned to the server.

[1302] Step 5:

[1303] The server provides the report to the user

[1304] Input: The server receives the final generated report.

[1305] What happens: The server sends the generated report to the user's email address.

[1306] Output: User receives email on device and checks report.

[1307] In this way, the system can provide tailored reports based on the user's emotions.

[1308] (Application example 3)

[1309] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1310] Conventional report creation systems using generative AI lacked personalization based on user emotions, making it difficult to increase user satisfaction. Furthermore, there were limited ways to provide generated reports to users at the right time.

[1311] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at the scheduled time using a generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine, means for adjusting the content of the report based on the user emotions, and means for providing the adjusted report to the user. This makes it possible to provide a personalized report according to the user's emotions at an appropriate time.

[1312] An "instruction collection means" is a device or software that receives and records tasks or requests from a user.

[1313] The "means for managing the execution schedule of collected tasks" refers to a device or software that creates and manages a plan for executing received tasks or requests at the appropriate time.

[1314] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to create and obtain reports based on specified tasks.

[1315] "Means for reporting materials output by generative AI" refers to a device or software for providing users with materials created by generative AI.

[1316] The "means for analyzing a user's emotions using an emotion engine" is a device or software for analyzing a user's emotional state.

[1317] A "means for adjusting report content based on user emotion" is a device or software for modifying the content of a generated report in response to the user's emotional state.

[1318] A "means for providing a user with an adjusted report" is a device or software for sending or displaying an adjusted report to a user based on emotions.

[1319] The following system configuration is used as an embodiment of this invention: The server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports using generative AI, means for reporting materials output by the generative AI, means for analyzing user emotions using an emotion engine, means for adjusting the content of the report based on the user emotions, and means for providing the adjusted report to the user.

[1320] Hardware and software used

[1321] Hardware: Smartphone

[1322] software:

[1323] Generative AI models (e.g., GPT-4)

[1324] Emotion engines (e.g., Affectiva)

[1325] Email sending service (e.g. SendGrid)

[1326] Processing flow

[1327] 1. Means of collecting instructions:

[1328] Users use their smartphones to input tasks and requests, including direct task lists to cloud services and collecting instructions via communication tools.

[1329] 2. How to manage the execution schedule of collected tasks:

[1330] The server plans and manages the execution of received tasks and requests in a timely manner, thereby ensuring efficient task processing.

[1331] 3. How to create and retrieve reports using generative AI:

[1332] The server uses a generative AI model (e.g., GPT-4) to generate and retrieve reports based on the specified tasks.

[1333] 4. Means of reporting materials generated by generative AI:

[1334] The server provides the user with the materials generated by the generative AI, including instructions for sending the report to the user's email address using an email sending service (e.g., SendGrid).

[1335] 5. How to analyze user sentiment using an emotion engine:

[1336] The server uses an emotion engine (e.g., Affectiva) to analyze emotions from the user's text. For example, if a user types, "I'm feeling very happy today!", the emotion engine will detect "joy."

[1337] 6. How to tailor report content based on user sentiment:

[1338] The server changes the content of the generated report depending on the user's emotional state. For example, if the user is feeling "joy," the generative AI generates a report with content related to "joy."

[1339] 7. Means of providing tailored reports to users:

[1340] The server sends or displays the report adjusted based on the emotion to the user, thereby providing a personalized report according to the user's emotion.

[1341] Specific examples

[1342] If a user types "I'm feeling very happy today!", the emotion engine will detect "joy" and the generative AI will generate a report on content related to "joy." The generated report will be sent to the user's email address using an email sending service.

[1343] Prompt Sentence Examples

[1344] Generate a report that makes the user feel joy. Include positive news and uplifting stories.

[1345] In this way, reports tailored to the user's emotions can be provided, enabling more personalized content delivery.

[1346] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1347] Step 1:

[1348] Users input tasks and requests using their smartphones. These tasks and requests are sent to the server via a task list or communication tool directly input to the cloud service. The server collects these instructions and stores them in a database.

[1349] Step 2:

[1350] The server manages the execution schedule based on the collected tasks and requests. Specifically, it takes into account the priority and deadlines of the tasks and creates a plan to execute them at the appropriate time. The schedule information is stored in a database.

[1351] Step 3:

[1352] At the scheduled time, the server uses a generative AI model (e.g., GPT-4) to generate a report based on the specified task. The server inputs the prompt sentence into the generative AI model and retrieves the generated report. The generated report is temporarily stored in memory.

[1353] Step 4:

[1354] The server uses an email sending service (e.g., SendGrid) to provide the user with the materials output by the generative AI model. It creates and sends an email to send the generated report to the user's email address.

[1355] Step 5:

[1356] A user inputs emotional text using a smartphone, for example, "I feel very happy today!" The input text is sent to the server.

[1357] Step 6:

[1358] The server uses an emotion engine (e.g., Affectiva) to analyze the emotion from the user's text. The input text is passed to the emotion engine and the emotion analysis result is obtained. The emotion analysis result is temporarily stored in memory.

[1359] Step 7:

[1360] The server adjusts the content of the generated report based on the results of the sentiment analysis. Specifically, it inputs new prompts into the generative AI model according to the user's emotional state and generates an adjusted report. The adjusted report is temporarily stored in memory.

[1361] Step 8:

[1362] The server again uses the email sending service to provide the adjusted report to the user, creating and sending an email to send the adjusted report to the user's email address.

[1363] In this way, it is possible to provide a personalized report according to the user's emotions at an appropriate time.

[1364] 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.

[1365] 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> ) 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.

[1366] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1367] 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.

[1368] [Third embodiment]

[1369] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1370] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1371] 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).

[1372] 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.

[1373] 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.

[1374] 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).

[1375] 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.

[1376] 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.

[1377] 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.

[1378] 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.

[1379] In the headset type terminal 314, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. 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 executed by the processor 46 on the RAM 48.

[1380] This is realized by operating as the control unit 46A in accordance with the reception output program 60.

[1381] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1382] "Example 1"

[1383] The system of the present invention provides a to-do list that can be directly input into iPaaS as a means of collecting instructions from users. Specifically, when a user inputs a task into the to-do list, the system collects it and manages the task execution schedule. For example, if a user inputs the task "Create a report by 10:00 AM tomorrow," the system collects this task and schedules the task of creating the report by 10:00 AM tomorrow.

[1384] "Example 2"

[1385] At the scheduled time, the system uses generative AI to create and retrieve the report. Specifically, the generative AI collects the necessary information and creates a report based on that information. For example, the generative AI collects information from the internet and creates a report based on that information.

[1386] "Example 3"

[1387] As a means of reporting the materials output by the generative AI, the system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report created by the generative AI by sending it to the user's email address, etc.

[1388] The processing flow of each embodiment will be described below.

[1389] "Example 1"

[1390] Step 1: The user enters a task into the to-do list directly in the iPaaS. For example, the user enters a task such as "Create a report by 10:00 AM tomorrow."

[1391] Step 2: The system collects input from the user and manages the task execution schedule. Specifically, the system collects the task "Create a report by 10:00 AM tomorrow" and schedules the task to create the report by 10:00 AM tomorrow. "Example 2"

[1392] Step 1: At the scheduled time, the system uses generative AI to generate a report. Specifically, the generative AI collects the necessary information and generates a report based on that information.

[1393] Step 2: The system retrieves the report created by the generative AI. For example, the generative AI collects information from the internet, creates a report based on that information, and the system retrieves that report.

[1394] "Example 3"

[1395] Step 1: The system provides the user with the report created by the generative AI. Specifically, the system provides the user with the report by sending it to the user's email address.

[1396] Example 1

[1397] Next, a description will be given of Example 1 of Form 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."

[1398] Conventional task management systems required users to manually input tasks and manage schedules, resulting in problems that reduced efficiency. Task reminder settings and notifications were also insufficient, meaning users could miss deadlines. Furthermore, report creation using generative artificial intelligence was not automated, placing a heavy burden on users.

[1399] 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.

[1400] In this invention, the server includes means for collecting instructions, means for managing the collected task execution schedules, means for creating and acquiring reports for multiple tasks at scheduled times using generative artificial intelligence, means for reporting materials output by the generative artificial intelligence, means for setting and notifying task reminders, means for saving task data in a database, and means for generating task schedules. This allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and automatically create reports using generative artificial intelligence.

[1401] The "means for collecting instructions" is an interface for inputting tasks and instructions from the user and sending them to the system.

[1402] The "means for managing execution schedules of collected tasks" is a function for creating and managing execution schedules based on collected tasks.

[1403] "Generative AI" is an AI technology that automatically generates reports and documents based on input data.

[1404] "Means for creating and obtaining reports" refers to a function for creating reports using generative artificial intelligence and obtaining those reports.

[1405] "Means for reporting materials output by generative artificial intelligence" is a function for providing users with materials created by generative artificial intelligence.

[1406] The "means for setting and notifying task reminders" is a function for setting reminders based on task deadlines and notifying the user.

[1407] The "means for saving task data in a database" is a function for saving collected task data in a database.

[1408] The "means for generating a task schedule" is a function for generating an execution schedule based on collected task data.

[1409] The "worklist with direct input from the integrated platform" is a worklist on an integrated platform that allows users to directly input tasks.

[1410] A "communication tool" is a tool that a user uses to send tasks or instructions to the system.

[1411] The present invention relates to a system that allows a user to efficiently manage tasks and automatically create reports by utilizing generative artificial intelligence. Specific embodiments of this system will be described below.

[1412] First, the user inputs a task into the task list directly input on the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The user's device (PC or smartphone) then sends this task to the server. The device sends the task data using an HTTP request.

[1413] The server receives HTTP requests sent from devices and retrieves task data. The server processes the requests using a web framework such as Flask or Django. The retrieved task data is then stored in a database using SQL queries. For example, a relational database such as MySQL or PostgreSQL is used.

[1414] Next, the server generates a task execution schedule based on the saved task data. The server adds the task's due date to the calendar using the Google Calendar API. The server also sets a task reminder and notifies the user. For example, it sets a reminder one hour before the task and notifies the user via email or push notification.

[1415] Furthermore, the server utilizes generative artificial intelligence to create reports at scheduled times. The generative artificial intelligence automatically generates reports and materials based on the input data. The generated reports are provided to the user.

[1416] As a concrete example, consider the case where a user inputs a task such as "Create a report by 10:00 AM tomorrow." When the user enters this task in the integrated platform's direct input to-do list, the device sends the task data to the server as an HTTP request. The server receives the request and saves the task data in a database. The server then uses the Google Calendar API to add the task's deadline to the calendar and set a reminder. It then sends the user an email notification one hour before the task. Furthermore, generative artificial intelligence is used to automatically create the report at the scheduled time and provide it to the user.

[1417] Examples of prompts to be input to a generative AI model include:

[1418] Enter the task "Create a report by 10 AM tomorrow" into the task list of the integrated platform. The system will collect this task and schedule a task to create a report by 10 AM tomorrow.

[1419] In this way, the invention allows users to efficiently manage tasks, receive reminder notifications so they don't miss task deadlines, and leverage generative artificial intelligence to automatically generate reports.

[1420] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1421] Step 1:

[1422] The user enters a task

[1423] The user inputs tasks into the task list directly into the integrated platform. For example, the user inputs a task such as "Create a report by 10:00 AM tomorrow." The input task data is sent to the terminal.

[1424] Step 2:

[1425] The device sends the task

[1426] The terminal sends the task data entered by the user to the server. Specifically, the task data is sent using an HTTP POST request. The input is the task data, and the output is a request sent to the server.

[1427] Step 3:

[1428] The server receives the task

[1429] The server receives the HTTP POST request sent from the terminal and retrieves the task data. For example, it processes the request using a web framework such as Flask or Django. The input is the HTTP request, and the output is the retrieved task data.

[1430] Step 4:

[1431] The server saves the task in a database

[1432] The server saves the acquired task data in a database. Specifically, it uses SQL queries to insert data into a relational database such as MySQL or PostgreSQL. The input is task data, and the output is data saved in the database.

[1433] Step 5:

[1434] The server generates a schedule of tasks

[1435] The server generates a task execution schedule based on the stored task data. For example, it uses the Google Calendar API to add task deadlines to a calendar. The input is the task data, and the output is the creation of a calendar event.

[1436] Step 6:

[1437] Server sets reminder

[1438] The server sets a reminder based on the task's due date, for example, using the Google Calendar API to set a reminder one hour before the task. The input is the task's due date data, and the output is the reminder setting.

[1439] Step 7:

[1440] The server notifies the user of the reminder

[1441] The server sends notifications to users based on the set reminders. Specifically, it sends reminders to users using email or push notifications. The input is the reminder setting data, and the output is the notification to the user.

[1442] Step 8:

[1443] The server creates reports using generative artificial intelligence

[1444] The server utilizes generative artificial intelligence to generate reports at scheduled times, with the input being the task data and the output being the generated report.

[1445] Step 9:

[1446] The server provides the generated report to the user.

[1447] The server provides the user with the report created by the generative AI. Specifically, it sends the report to the user's terminal. The input is the generated report, and the output is the report provided to the user.

[1448] (Application example 1)

[1449] Next, a description will be given of Application Example 1 of Form 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."

[1450] In conventional factory work management systems, work task input and schedule management were often done manually, resulting in inefficiencies. Furthermore, the system lacked the ability to monitor task progress in real time and adjust schedules as needed, which led to delays and errors.

[1451] 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.

[1452] In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, a means for reporting materials output by the generative AI, a means for inputting work tasks to machinery in a factory, a means for collecting the input tasks and automatically managing the execution schedule, and a means for monitoring the progress of tasks in real time and adjusting the schedule as necessary. This enables efficient management of work tasks in a factory, and real-time progress monitoring and schedule adjustment.

[1453] A "means for collecting instructions" is a device or software for inputting tasks or instructions from a user and collecting them as data.

[1454] The "means for managing the execution schedule of the collected tasks" is a device or software for planning the execution timing of the collected tasks and automatically adjusting the schedule.

[1455] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports based on specified tasks.

[1456] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative artificial intelligence in report format.

[1457] The "means for inputting work tasks to machinery in a factory" refers to a device or software for inputting work tasks and giving instructions to machinery in a factory.

[1458] The "means for collecting input tasks and automatically managing the execution schedule" refers to a device or software for collecting tasks input by a user and automatically managing the execution schedule of those tasks.

[1459] The "means for monitoring the progress of tasks in real time and adjusting the schedule as necessary" refers to a device or software for monitoring the progress of tasks in real time and dynamically adjusting the schedule according to the progress.

[1460] A system for carrying out the present invention is for efficiently managing work tasks in a factory and monitoring progress in real time. A specific embodiment of this system will be described below.

[1461] 1. System Configuration

[1462] The system consists of the following main components:

[1463] Server: Collects tasks, manages schedules, and creates reports using generative AI.

[1464] Terminal: A device (e.g., tablet, PC) used to input work tasks to machinery in a factory.

[1465] Users: Factory workers and managers.

[1466] 2. Hardware and Software Used

[1467] Hardware: Factory robots (e.g. KUKA, Fanuc, etc.), tablets, PCs.

[1468] Software: Python, APScheduler (scheduling library), generative AI model.

[1469] 3. Data processing and calculation

[1470] Server Processing

[1471] The server collects tasks entered by users and manages the execution schedule. Specifically, it performs the following processes:

[1472] 1. Task collection: Tasks entered by users through the terminal are saved in a database.

[1473] 2. Schedule management: Using APScheduler, the execution timing of collected tasks is planned and the schedule is automatically adjusted.

[1474] 3. Report Generation: Use generative AI models to automatically generate and retrieve reports based on specified tasks.

[1475] Terminal handling

[1476] The terminal is a device for inputting work tasks to machines in a factory. A user inputs a task using the terminal, and the task is sent to a server.

[1477] User operations

[1478] Users use terminals to input work tasks for machines in a factory. The input tasks are sent to a server, which collects the tasks and manages the schedule.

[1479] 4. Specific Examples

[1480] For example, a user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." This task is sent to the server, which uses APScheduler to schedule the task to run at the specified time. Once the task is completed, a report is automatically generated using a generative AI model.

[1481] 5. Examples of prompts

[1482] The user enters a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00". The system collects this task and schedules it to run at the specified time. Once the task is complete, the status is updated to "completed".

[1483] The above is a specific embodiment for carrying out the present invention. This system enables efficient management of work tasks within a factory, progress monitoring in real time, and schedule adjustment.

[1484] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1485] Step 1:

[1486] The user inputs a work task using a terminal. For example, the user inputs a task called "Inspect Machine A" to be completed by "2023-10-01 10:00:00." The input task is sent from the terminal to the server. The input data consists of the task name and deadline.

[1487] Step 2:

[1488] The server receives the task sent from the terminal and stores it in the database. The server analyzes the received task data and extracts the task name and deadline time. This stores the basic information of the task in the database.

[1489] Step 3:

[1490] The server uses APScheduler to plan the execution timing of the collected tasks and automatically adjust the schedule. The server schedules jobs to execute the tasks based on the task deadlines. This determines the execution timing of the tasks.

[1491] Step 4:

[1492] The server executes the task at the specified time. For example, it sends an instruction to a machine in a factory to execute the task "Inspect Machine A" at the specified time. This executes the task.

[1493] Step 5:

[1494] The server monitors the progress of the task in real time. The server receives feedback from the machinery in the factory and updates the progress of the task, allowing the progress of the task to be monitored in real time.

[1495] Step 6:

[1496] The server uses a generative AI model to automatically create a report after the task is completed. The server inputs the results of the task execution into the generative AI model and generates a report. This outputs the results of the task execution as a report.

[1497] Step 7:

[1498] The server provides the generated report to the user. The server sends the generated report to the user's terminal so that the user can check the report. This allows the user to check the results of the task execution.

[1499] Example 2

[1500] Next, a description will be given of Example 2 of Form 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."

[1501] Conventional report creation systems require users to manually collect information and create reports, which is time-consuming and labor-intensive. Furthermore, the information collection and report creation often lack accuracy and consistency. Furthermore, they lack the functionality to automatically generate reports based on a schedule, making it difficult to provide timely information. To solve these issues, a system that can efficiently and automatically generate reports and provide them to users is needed.

[1502] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1503] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for collecting information using a generative AI model at the scheduled time and creating a report based on a prompt sentence, means for saving the generated report and notifying the user, and means for the user to obtain the report through a terminal. This eliminates the need for the user to manually collect information and enables efficient, automatic, and timely acquisition of highly accurate reports.

[1504] The "means for collecting instructions" is a function for collecting tasks and requests from users.

[1505] The "means for managing the execution schedule of collected tasks" is a function for managing the execution timing of collected tasks and requests and executing them at the appropriate time.

[1506] A "generative AI model" is a model for generating data using artificial intelligence, such as a model that performs natural language processing.

[1507] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[1508] "Means for creating reports" refers to a function that automatically creates reports using a generative AI model based on collected information.

[1509] The "means for saving the generated report" is a function for saving the generated report in a database or a file system.

[1510] "Means for notifying the user" is a function for notifying the user that a generated report is available.

[1511] "Means for users to retrieve reports through a terminal" refers to the functionality that allows users to access and retrieve saved reports using a terminal such as a computer or mobile device.

[1512] The present invention provides a system for allowing users to efficiently and automatically generate and obtain reports. Specific embodiments of this system will be described below.

[1513] System configuration

[1514] This system is mainly composed of three elements: a server, a terminal, and a user. The server plays a central role in collecting information and creating reports using a generative AI model. The terminal is a device that allows the user to access the server and obtain the generated reports. The user is the entity that uses the system to generate and obtain reports.

[1515] Hardware and software used

[1516] The server is a high-performance computer with sufficient computing power to run generative AI models. Specifically, it requires a CPU, GPU, memory, and storage. For software, a framework (such as TensorFlow or PyTorch) for running generative AI models (e.g., models that perform natural language processing) is used.

[1517] A terminal is a device that allows a user to access a server, and includes PCs, tablets, smartphones, etc. A web browser and dedicated applications are installed on the terminal, providing an interface for communicating with the server.

[1518] Data processing and calculation

[1519] The server first collects instructions from users via task lists and communication tools, then manages the execution schedule of the collected tasks and executes the generative AI model at the specified time.

[1520] The generative AI model collects the necessary information from the internet based on a prompt, such as "Please write a report on the latest AI technology." The collected information is temporarily stored on the server.

[1521] The server then re-enters the generative AI model with prompts based on the collected information to generate a report, which is then stored in a database or file system on the server.

[1522] Specific examples

[1523] For example, if a user wants a "report on the latest AI technology," the server inputs the following prompt into the generative AI model:

[1524] Example prompt sentence:

[1525] "Please write a report on the latest AI technologies, detailing the major innovations and their applications announced in 2023."

[1526] The generative AI model collects relevant information from the internet based on the prompt and creates a report. The report is then saved on a server and sent to the user. The user can access the server via their device and download and view the generated report.

[1527] In this way, the server automatically generates reports based on a schedule, enabling users to obtain the information they need in a timely manner.

[1528] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1529] Step 1:

[1530] The server collects instructions from users. The inputs are tasks and requests provided by users through task lists and communication tools. The server stores these instructions in a database. Specifically, the server retrieves data from task lists and communication tools via APIs and stores it in the database.

[1531] Step 2:

[1532] The server manages the execution schedule of the collected tasks. The input is task information stored in a database. The server uses this information to schedule the execution timing of the tasks. Specifically, the server uses a scheduler to set the execution time of each task and set a timer.

[1533] Step 3:

[1534] At the scheduled time, the server uses the generative AI model to collect information. The inputs are a prompt and scheduled task information. The server inputs the prompt into the generative AI model and collects the necessary information from the Internet. Specifically, the server inputs the prompt "Please create a report on the latest AI technology" into the generative AI model and uses web scraping technology to collect related information.

[1535] Step 4:

[1536] The server then inputs a prompt to the generative AI model based on the collected information and generates a report. The inputs are the collected information and the prompt. The server inputs the prompt to the generative AI model, saying, "Please create a detailed report on the latest AI technology based on the collected information," and receives the generated report. Specifically, the server retrieves the collected information from the database, inputs it into the generative AI model, and generates a report.

[1537] Step 5:

[1538] The server saves the generated report and notifies the user. The input is the generated report. The server saves the report in a database or file system and notifies the user via email or push notification. Specifically, the server saves the generated report in a specific directory and sends a notification based on the user's contact information.

[1539] Step 6:

[1540] The user accesses the server through their device and retrieves the generated report. The input is a notification from the server. The user accesses the server using a web browser or a dedicated application on their device and downloads the saved report. Specifically, the user clicks the link in the notification, logs in to the server, and downloads the report.

[1541] (Application example 2)

[1542] Next, a description will be given of Application Example 2 of Form 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."

[1543] Logistics centers are required to be able to grasp operational and inventory status in a timely manner and operate efficiently. However, with conventional methods, collecting information and creating reports requires a great deal of time and effort, making it difficult to provide information in real time.

[1544] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at the scheduled time using generative AI, means for reporting materials output by the generative AI, means for collecting logistics-related information, means for generating reports based on the collected logistics-related information, and means for notifying the generated reports. This makes it possible to grasp the operating status and inventory status of the logistics center in real time, enabling efficient operation.

[1545] A "means for collecting instructions" is a device or software for collecting instructions or tasks from a user.

[1546] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[1547] "Means for utilizing generative AI to generate and obtain reports based on multiple tasks at scheduled times" refers to a device or software that uses generative AI to generate and obtain reports based on multiple tasks at set times.

[1548] "Means for reporting materials output by generative AI" refers to a device or software for outputting materials created by generative AI in report format.

[1549] "Means for collecting logistics-related information" means devices or software for collecting logistics-related data and news from the Internet and other sources.

[1550] The "means for generating a report based on the collected logistics-related information" refers to a device or software for generating a report based on the collected logistics-related information.

[1551] The "means for notifying the user of the generated report" is a device or software for notifying the user of the generated report.

[1552] To implement the present invention, the following system configuration and program are required.

[1553] System Configuration

[1554] 1. Hardware

[1555] Server: Collects data, runs generative AI, and generates reports.

[1556] Smartphone: The device on which the user views the report.

[1557] 2. Software

[1558] Generative AI model: Use generative AI such as OpenAI GPT-3.

[1559] Data Collection Library: Collects logistics-related information from the Internet using the Requests library.

[1560] Scheduling library: Use the Schedule library to manage task execution schedules.

[1561] Program processing explanation

[1562] 1. Means of collecting instructions

[1563] The server uses a task list and communication tools directly input from the cloud service to collect instructions and tasks from users, allowing users to easily input tasks.

[1564] 2. A method for managing the execution schedule of collected tasks

[1565] The server uses a scheduling library to manage the timing and order of execution of collected tasks, so that tasks are executed at the appropriate time.

[1566] 3. A method to generate and obtain reports using AI that generates multiple tasks at scheduled times

[1567] The server uses generative AI to create and retrieve reports based on multiple tasks at set times. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet.

[1568] 4. A means of reporting materials output by generative AI

[1569] The server outputs the materials created by the generative AI in report format and notifies the user on their smartphone, allowing them to receive the latest information in real time.

[1570] 5. Means of collecting logistics-related information

[1571] The server uses a data collection library to collect logistics-related data and news from the Internet, ensuring that the latest logistics-related information is always available.

[1572] 6. A means of generating reports based on collected logistics-related information

[1573] The server generates reports based on the collected logistics-related information using generative AI models, resulting in an informed and detailed report.

[1574] 7. Means of notification of generated reports

[1575] The server then sends the generated report to the smartphone, allowing the user to view the report in real time.

[1576] Specific examples

[1577] Every morning at 9 a.m., the logistics center manager receives a report containing the latest logistics news and inventory status. The report includes the previous day's shipping status, inventory fluctuations, and the latest news in the logistics industry.

[1578] Prompt Sentence Examples

[1579] Write a report based on the following logistics news stories:

[1580] News 1: Latest trends in the logistics industry

[1581] News 2: Introducing new logistics technology

[1582] News 3: Fluctuations in market supply and demand

[1583] In this way, a system can be created that streamlines logistics center operations and provides the latest information in a timely manner.

[1584] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1585] Step 1:

[1586] The server collects instructions and tasks from users. Users input tasks using a task list entered directly into the cloud service or using communication tools. The server receives this input and stores it in a database. The input data includes the task content, priority, scheduled execution time, etc.

[1587] Step 2:

[1588] The server manages the execution schedule of the collected tasks. It uses a scheduling library to set the execution timing and order of the tasks. The input data is the scheduled execution time of the tasks, and the output data is a list of scheduled tasks.

[1589] Step 3:

[1590] The server generates and retrieves reports at scheduled times using generative AI. It uses a generative AI model (e.g., OpenAI GPT-3) to generate reports based on logistics-related information collected from the internet. The input data is the collected logistics-related information, and the output data is the generated report.

[1591] Step 4:

[1592] The server outputs the materials generated by the generative AI in report format and notifies the smartphone. The generated report is sent to the user's smartphone, where the user can check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[1593] Step 5:

[1594] The server uses a data collection library to collect logistics-related data and news from the Internet. This ensures that the latest logistics-related information is always available. The input data is logistics-related information available on the Internet, and the output data is the collected logistics-related information.

[1595] Step 6:

[1596] The server generates reports using a generative AI model based on the collected logistics-related information, resulting in a detailed report based on the information. The input data is the collected logistics-related information, and the output data is the generated report.

[1597] Step 7:

[1598] The server notifies the smartphone of the generated report, allowing the user to check the report in real time. The input data is the generated report, and the output data is the report displayed on the user's smartphone.

[1599] Example 3

[1600] Next, a third embodiment of the third embodiment will be described. 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."

[1601] Conventional report creation systems require users to manually collect information and create reports, which takes time and effort. Furthermore, there are limited ways to provide generated reports to users, making it difficult to efficiently communicate information.

[1602] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for utilizing the generative AI to create and obtain reports for multiple tasks at the scheduled time, means for providing the user with materials output by the generative AI, means for receiving user input and inputting prompt statements to the generative AI, means for temporarily saving the generated report, means for obtaining the user's contact information, and means for sending the generated report to the user's contact information. This enables the user to create reports efficiently and receive information quickly.

[1603] A "means for collecting instructions" is a device or method that receives instructions or requests from a user and collects information for processing within the system.

[1604] The "means for managing the execution schedule of collected tasks" refers to a device or method for planning and managing the time and order of the collected tasks in order to execute them efficiently.

[1605] "Generative AI" refers to an AI system that has the ability to automatically generate information such as text or reports based on user input.

[1606] "Means for creating and obtaining reports" refers to a device or method for creating reports using generative artificial intelligence and obtaining the created reports.

[1607] "Means for providing a user with materials output by a generative artificial intelligence" refers to a device or method for providing a user with materials created by a generative artificial intelligence.

[1608] "Means for receiving user input and inputting a prompt sentence to the generative AI" refers to a device or method for receiving input from a user and inputting the input as a prompt sentence to the generative AI.

[1609] "Means for temporarily storing generated reports" refers to a device or method for temporarily storing reports generated by generative artificial intelligence.

[1610] The "means for acquiring user contact information" refers to a device or method for acquiring contact information such as a user's email address or phone number.

[1611] The "means for sending the generated report to the user's contact information" refers to a device or method for sending the report generated by the generative artificial intelligence based on the user's contact information.

[1612] The present invention relates to a system for creating reports using generative artificial intelligence and providing the reports to users. Specific embodiments of this system will be described below.

[1613] System configuration

[1614] The system consists of the following main components:

[1615] 1. Server

[1616] 2. Terminal

[1617] 3. Users

[1618] Hardware and software used

[1619] The server provides the computational resources to run generative artificial intelligence models (e.g., OpenAI's GPT-4), temporarily stores the generated reports using a database or file system, and sends the reports to the user's contacts using the SMTP protocol.

[1620] The terminal provides an interface for the user to input the prompt sentence. This can be a device such as a PC or smartphone, and accesses the server through a browser.

[1621] The user uses the system to input a prompt to generate a report and receives the generated report.

[1622] Data processing and calculation

[1623] The server inputs the prompt received from the user into a generative AI model to generate a report, which is temporarily stored on the server and then sent based on the user's contact information.

[1624] Specific examples

[1625] For example, if a user enters the prompt "Write a report on the latest technology trends," the following happens:

[1626] 1. The user enters a prompt:

[1627] The user opens a browser, accesses the system's web page, and types "Write a report on the latest technology trends" into the text box.

[1628] 2. The terminal sends the prompt to the server:

[1629] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text.

[1630] 3. The server receives the prompt and inputs it into the generative AI model:

[1631] The server analyzes the received prompt sentence and inputs it into a generative artificial intelligence model (GPT-4).

[1632] 4. The generative AI model generates the report:

[1633] Based on the prompt, GPT-4 generates a report stating, "Emerging technology trends in 2023 include the evolution of artificial intelligence, the widespread adoption of 5G, and the application of blockchain technology. These technologies are bringing about revolutionary changes in various industries."

[1634] 5. The server temporarily stores the generated report:

[1635] The server stores the generated reports in a database.

[1636] 6. The server gets the user's email address:

[1637] The server obtains the email address from the user's registration information.

[1638] 7. The server sends the generated report to the user's email address:

[1639] The server uses the SMTP protocol to send the generated report to the user's email address.

[1640] 8. User receives email and checks report:

[1641] The user receives a new email in their email client and sees the attached report.

[1642] In this way, the user can create reports efficiently and receive information quickly. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1643] Step 1:

[1644] The user enters a prompt statement.

[1645] A user accesses the system interface from their own device (PC, smartphone, etc.) and inputs a prompt statement indicating the content of the report they want to generate. For example, they might input, "Please create a report on the latest technological trends." The input data is the prompt statement, and the output data is an input confirmation message displayed on the device.

[1646] Step 2:

[1647] The terminal sends the prompt to the server.

[1648] When the user clicks the "Submit" button, the terminal sends an HTTP POST request to the server and sends data including the prompt text. The input data is the prompt text, and the output data is the prompt text sent to the server.

[1649] Step 3:

[1650] The server receives the prompt sentence and inputs it into the generative AI model.

[1651] The server receives the prompt sentence sent from the device and inputs it into a generative AI model (e.g., GPT-4). The input data is the prompt sentence, and the output data is the input result to the generative AI model.

[1652] Step 4:

[1653] A generative AI model generates the report.

[1654] The generative AI model generates a report based on the input prompt, which contains detailed information depending on the content of the prompt. The input data is the prompt, and the output data is the generated report.

[1655] Step 5:

[1656] The server temporarily stores the generated report.

[1657] The server temporarily stores the reports output from the generative AI model. This storage is done using a database or file system. The input data is the generated report, and the output data is the saved report.

[1658] Step 6:

[1659] The server retrieves the user's email address.

[1660] The server obtains the user's email address, which was provided when the user registered with the system. The input data is the user's identification information, and the output data is the obtained email address.

[1661] Step 7:

[1662] The server will send the generated report to the user's email address.

[1663] The server sends the saved report to the user's email address using the SMTP protocol. The input data are the saved report and the email address, and the output data is the email sent.

[1664] Step 8:

[1665] The user receives an email and reviews the report.

[1666] The user receives the email sent from the server in their email client. The generated report is attached to the email or is included in the body of the email. The user checks it and uses it as needed. The input data is the sent email, and the output data is the checked report.

[1667] (Application example 3)

[1668] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1669] Logistics center operators need to efficiently grasp data such as inventory status, shipping status, arrival status, and work efficiency in their daily operations, and make appropriate decisions. However, manually collecting this data and creating reports takes time and effort, hindering efficient business operations. Furthermore, there is a lack of a way to quickly share the generated reports with relevant parties, which can lead to delays in information transmission. To solve these issues, a system that uses generative AI to automatically generate reports and quickly share them is needed.

[1670] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for sending the generated reports by email, and means for generating reports for the logistics center operations manager. This enables the logistics center operations manager to efficiently collect the necessary data and quickly receive the automatically generated reports.

[1671] A "means for collecting instructions" is a device or software for collecting instructions or requests from a user.

[1672] The "means for managing the execution schedule of the collected tasks" refers to a device or software for managing the execution timing and order of the collected tasks.

[1673] "Means for creating and obtaining reports using generative AI" refers to devices or software that use generative artificial intelligence to automatically create and obtain reports.

[1674] "Means for reporting materials output by generative AI" refers to a device or software for providing materials output by generative artificial intelligence in report format.

[1675] A "means for emailing a generated report" is a device or software for sending a generated report via email to a designated recipient.

[1676] The "means for generating a report for the logistics center operator" is a device or software for generating a report containing information required by the logistics center operator.

[1677] As an embodiment of the present invention, a report generation system utilizing generative AI is provided for logistics center operators. A specific embodiment of the system is described below.

[1678] 1. System Program

[1679] The system consists of the following main components:

[1680] A means of collecting instructions

[1681] A means to manage the execution schedule of collected tasks

[1682] A means of creating and obtaining reports using generative AI

[1683] A means of reporting materials output by generative AI

[1684] A means to email the generated report

[1685] A means of generating reports for distribution center operations managers

[1686] 2. Program Processing

[1687] The server first collects instructions from users, which are entered via a smartphone application or a web interface. The collected instructions are registered as tasks, and their execution schedules are managed.

[1688] Next, the generative AI creates a report based on the scheduled time. The generative AI uses OpenAI's API to generate a report based on the specified prompt. The generated report is saved on the server.

[1689] The generated report is then emailed to the specified email address using Python's smtplib library.

[1690] 3. Hardware and Software Used

[1691] Hardware: Smartphones, servers

[1692] Software: Python, OpenAI API, SMTP server

[1693] 4. Specific Examples

[1694] For example, if a logistics center manager wants to know today's inventory and shipping status, he or she opens a smartphone application and requests report generation. The generative AI generates a report like this:

[1695] Availability:

[1696] Product A: 500 pieces

[1697] Product B: 300 pieces

[1698] Shipping Status:

[1699] Product A: 200 units shipped

[1700] Product B: 100 units shipped

[1701] Availability:

[1702] Product A: 100 units expected to arrive

[1703] Product B: 50 units expected to arrive

[1704] Work efficiency:

[1705] Average work time: 2 hours

[1706] Work efficiency: 85%

[1707] This report will be automatically sent to the administrator's email address.

[1708] 5. Examples of prompts

[1709] An example of a prompt to input to a generative AI model is as follows:

[1710] Prepare a report for the distribution center operations manager. Please include the following information:

[1711] Availability

[1712] Shipping Status

[1713] Stock availability

[1714] Work efficiency

[1715] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1716] Step 1:

[1717] The user inputs report generation instructions via a smartphone application or web interface. The input instructions include the information to be included in the report (inventory status, shipping status, arrival status, work efficiency, etc.), and the user's request is transmitted to the system.

[1718] Step 2:

[1719] The server receives instructions from the user and registers them as tasks. The registered tasks are managed based on an execution schedule. Specifically, the timing and order of task execution are determined. The input is the user's instructions, and the output is the registered tasks.

[1720] Step 3:

[1721] Based on the scheduled time, the server sends a prompt to the generative AI, which contains instructions for generating a report containing the information specified by the user. The input is the scheduled task, and the output is the prompt to the generative AI.

[1722] Step 4:

[1723] The generative AI generates a report based on the prompt. The generated report is sent to the server. The input is the prompt, and the output is the generated report. Specifically, the report is generated using OpenAI's API.

[1724] Step 5:

[1725] The server receives the generated report and sends it as an email to the specified email address. The Python smtplib library is used to send the email. The input is the generated report and the output is the email sent.

[1726] Step 6:

[1727] A user receives an email on a smartphone or other device and views the generated report. The input is the email that was sent, and the output is the report that the user views. The specific behavior is to view the report using the email application.

[1728] 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.

[1729] "Example 1"

[1730] In one embodiment of the present invention, the generative AI includes an emotion engine that recognizes a user's emotions. The emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, text input, etc. For example, if the user senses that they are stressed, the emotion engine communicates that information to the generative AI.

[1731] "Example 2"

[1732] Furthermore, the emotion engine adjusts task priorities based on the user's emotions. For example, if the user feels stressed, the emotion engine communicates this information to the generative AI, which then prioritizes tasks that may reduce stress. Specifically, it prioritizes tasks related to relaxation and tasks that the user is expected to enjoy.

[1733] "Example 3"

[1734] The emotion engine also adjusts the content of the report based on the user's emotions. For example, if the user feels happy, the emotion engine communicates this information to the generative AI, which then adjusts the report content to reflect the user's happiness. Specifically, the report will include information related to the user's happiness.

[1735] The processing flow of each embodiment will be described below.

[1736] "Example 1"

[1737] Step 1: The emotion engine recognizes the user's emotions based on their tone of voice, facial expressions, text input, etc.

[1738] Step 2: The emotion engine communicates the recognized emotion information to the generative AI.

[1739] "Example 2"

[1740] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts task priorities based on the emotional information. Specifically, it prioritizes tasks that may reduce stress.

[1741] "Example 3"

[1742] Step 1: The emotion engine recognizes the user's emotions and conveys that information to the generative AI. Step 2: The generative AI adjusts the report content based on the emotion information. Specifically, it includes information related to what makes the user happy.

[1743] Example 1

[1744] Next, a description will be given of Example 1 of Form 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."

[1745] Conventional task management systems provide schedule management and reminder functions for tasks entered by users, but lack consideration for user emotions. Furthermore, there is a need for systems that not only manage task execution schedules but also respond to user emotions. Furthermore, there is a need for a function to automate document creation using generative artificial intelligence. A system that can solve these issues is needed.

[1746] 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.

[1747] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring documents for multiple tasks at scheduled times using generative artificial intelligence, means for documenting materials output by the generative artificial intelligence, means including an emotion engine for recognizing user emotions, and means for responding according to the user's emotions based on information obtained from the emotion engine. This makes it possible to improve the efficiency of user task management and to respond appropriately according to emotions.

[1748] "Means for collecting instructions" refers to the means for inputting tasks and instructions from users and incorporating them into the system.

[1749] The "means for managing the execution schedule of collected tasks" refers to a means for managing the execution timing and deadline of collected tasks and notifying the user at an appropriate time.

[1750] "Generative AI" is an AI technology that automatically generates documents and reports based on user instructions and data.

[1751] "Means for creating and obtaining documents" refers to the use of generative artificial intelligence to create task-based documents and obtain the necessary information.

[1752] "Means of documentation" refers to the means of organizing the materials output by the generative artificial intelligence and compiling them into a formal document.

[1753] The "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, text input, etc.

[1754] "Means for responding according to emotions" refers to means for providing appropriate responses and advice according to the user's emotions based on information obtained from the emotion engine.

[1755] "Worklists entered directly on an integrated platform" refers to a list on an integrated platform where users can enter tasks directly.

[1756] "Communication Tools" are tools that allow users to communicate with the system and are used to gather instructions.

[1757] MODE FOR CARRYING OUT THE INVENTION

[1758] The present invention is a system that allows a user to input a task, manages the execution schedule of the task, and responds according to the user's emotions. A specific embodiment of this system will be described below.

[1759] 1. Task input by user

[1760] Users can use their terminals to input tasks into a task list directly into the integrated platform. For example, a user can input a task such as "Create a report by 10:00 AM tomorrow."

[1761] 2. Task collection by the server

[1762] The server collects tasks entered by users in real time, stores them in a database, and analyzes task details (task name, deadline, priority, etc.).

[1763] 3. Task scheduling by the server

[1764] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on the task deadlines and sends notifications to the user at the appropriate time. For example, when a task deadline is approaching, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow."

[1765] 4. Emotion Recognition by Emotion Engine

[1766] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expressions, text input, etc. For example, if a user inputs the text "I'm very tired today," the emotion engine will recognize that the user is tired.

[1767] 5. Emotion-based responses using generative AI

[1768] The generative AI responds to the user's emotions based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be good to take a short break to relax."

[1769] Specific examples

[1770] Example 1: Task entry and schedule management

[1771] A user enters a task in their to-do list, "Create a report by 10 AM tomorrow." The server collects this task and stores it in a database. The server sets a reminder based on the task's due date, and notifies the user at 9 AM tomorrow, "You have a task to create a report by 10 AM tomorrow."

[1772] Example 2: Emotion recognition and response

[1773] A user enters text such as "I feel very tired today." The emotion engine recognizes that the user is tired and relays this information to the generative AI, which then offers advice such as "It would be good to take a short break to relax."

[1774] Prompt Sentence Examples

[1775] Task input prompt

[1776] "Please add a task to your to-do list to prepare the report by 10:00 AM tomorrow."

[1777] Emotion recognition prompts

[1778] "If the user feels tired, offer them some tips on how to relax."

[1779] The above is a specific embodiment for carrying out the present invention.

[1780] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1781] Step 1:

[1782] A user uses a terminal to input tasks into the integrated platform's direct input task list. The input task includes detailed information such as the task name, deadline, and priority. For example, a task is input as "Create a report by 10:00 AM tomorrow." The input data is the task name "Create report," the deadline "10:00 AM tomorrow," and the priority "High."

[1783] Step 2:

[1784] The server collects tasks entered by users in real time. The collected tasks are stored in a database. The server analyzes detailed information such as task name, deadline, and priority and stores it in the database. The input data is the task information entered by the user, and the output data is the task information stored in the database.

[1785] Step 3:

[1786] The server manages the execution schedule of the collected tasks. Specifically, the server sets reminders based on task deadlines and sends notifications to users at appropriate times. For example, when a task deadline approaches, the server notifies the user, "You have a task to create a report by 10:00 AM tomorrow." The input data is the task information stored in the database, and the output data is the notification sent to the user.

[1787] Step 4:

[1788] The emotion engine included in generative AI recognizes a user's emotions from their tone of voice, facial expression, text input, etc. For example, if a user enters the text "I'm very tired today," the emotion engine recognizes that the user is tired. The input data is the user's tone of voice, facial expression, text input, etc., and the output data is the user's emotional information.

[1789] Step 5:

[1790] The generative AI responds according to the user's emotions based on the information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is tired, the generative AI will provide advice such as, "It would be a good idea to take a short break to relax." The input data is the user's emotional information obtained from the emotion engine, and the output data is advice to the user.

[1791] (Application example 1)

[1792] Next, a description will be given of Application Example 1 of Form 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."

[1793] Conventional factory robot systems lack sufficient task schedule management and worker emotional monitoring, resulting in problems such as reduced work efficiency and worker stress. Furthermore, if task instructions are not given properly, the robot's behavior can become unstable. This can lead to a decline in productivity throughout the factory and potentially affect quality control.

[1794] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for collecting instructions, a means for managing the execution schedule of the collected tasks, a means for creating and acquiring reports on multiple tasks at scheduled times using a generative AI, a means for reporting materials output by the generative AI, a means for recognizing the emotions of workers using an emotion engine, a means for adjusting the task schedule based on the emotions of workers, and a means for instructing robots to perform tasks. This allows for efficient task schedule management and flexible schedule adjustment based on the emotions of workers. Furthermore, appropriate task instructions are given to robots, improving productivity and quality control throughout the factory.

[1795] A "means for collecting instructions" is an interface or system for collecting tasks or instructions from the user.

[1796] The "means for managing execution schedules of collected tasks" is a system that creates and manages schedules for efficiently executing collected tasks.

[1797] "Means for creating and obtaining reports using generative AI" refers to a system that uses generative artificial intelligence to automatically create and obtain task-based reports.

[1798] "Means for reporting materials output by generative AI" refers to a system that compiles and reports materials created by generative artificial intelligence.

[1799] The "means for recognizing a worker's emotions using an emotion engine" is an engine for recognizing emotions from the worker's tone of voice, facial expressions, text input, etc.

[1800] The "means for adjusting task schedules based on worker emotions" is a system that flexibly adjusts task schedules according to the recognized emotions of workers.

[1801] The "means for instructing robots to perform tasks" is a system for instructing factory robots to perform scheduled tasks and have them execute them.

[1802] A system for carrying out this invention is configured as follows: The server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and obtaining reports using generative AI, means for reporting materials output by the generative AI, means for recognizing the emotions of workers using an emotion engine, means for adjusting the task schedule based on the emotions of workers, and means for instructing robots on tasks.

[1803] Program processing explanation

[1804] The server processes and calculates data using the following hardware and software.

[1805] Hardware: Factory robots, emotion-recognition cameras, microphones

[1806] Software: EmotionEngine, TaskScheduler, RobotController

[1807] 1. A means of collecting instructions: The server provides an interface for collecting tasks and instructions from users, for example, via a to-do list or communication tool directly input into the iPaaS.

[1808] 2. A means for managing task execution schedules: The server creates and manages schedules for efficiently executing collected tasks. It uses TaskScheduler to generate schedules that take into account task deadlines and priorities.

[1809] 3. Using generative AI to create and retrieve reports: The server uses generative AI to automatically create and retrieve task-based reports. For example, if a user inputs a task such as "Create a report by 10:00 AM tomorrow," the generative AI will create a report based on that task.

[1810] 4. A means of reporting the materials output by the generative AI: The server compiles and reports the materials created by the generative AI, allowing users to efficiently check the progress of their tasks.

[1811] 5. Means of recognizing worker emotions using an emotion engine: The server uses an emotion engine to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The Emotion Engine is responsible for this, and can detect when a worker is feeling stressed.

[1812] 6. Adjusting task schedules based on worker emotions: The server flexibly adjusts task schedules according to the worker's recognized emotions. For example, if a worker is feeling stressed, it can change the priority of tasks or adjust the schedule to include breaks.

[1813] 7. Means for instructing robots to carry out tasks: The server instructs factory robots to carry out scheduled tasks. RobotController is used to issue specific work instructions to the robots.

[1814] Specific examples

[1815] For example, if a factory manager enters the tasks "Maintain Machine A" and "Assemble Part B" into a to-do list, the server collects them and creates a task schedule. Generative AI creates reports based on the tasks, and Emotion Engine monitors the emotions of workers. If a worker is feeling stressed, Task Scheduler adjusts the schedule, and Robot Controller issues appropriate instructions to the robot.

[1816] Prompt Sentence Examples

[1817] "The factory manager has entered tasks into the to-do list. Collect task descriptions and deadlines and issue instructions to the robot. Also, monitor the emotions of the workers and adjust their schedules if they are feeling stressed."

[1818] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1819] Step 1:

[1820] The user inputs tasks into the ToDo list. For example, the user inputs tasks such as "Maintain machine A" or "Assemble part B." The input tasks are sent to the server. The input data includes a task description and a deadline.

[1821] Step 2:

[1822] The server collects instructions. The server collects tasks from the to-do list submitted by the user and stores them in a database. The collected data includes task descriptions and deadlines.

[1823] Step 3:

[1824] The server manages the task execution schedule. The server passes the collected tasks to the TaskScheduler, which generates a schedule that takes into account the task deadlines and priorities. The input data are task descriptions and deadlines, and the output data is a list of scheduled tasks.

[1825] Step 4:

[1826] The server uses generative AI to create and retrieve reports. The server inputs the task details into the generative AI, which then automatically creates the report. The input data is the task description, and the output data is the generated report.

[1827] Step 5:

[1828] The server reports the materials output by the generative AI. The server provides the report created by the generative AI to the user. The input data is the generated report, and the output data is the report provided to the user.

[1829] Step 6:

[1830] The server uses an emotion engine to recognize the worker's emotions. The server uses an emotion recognition camera and microphone to recognize emotions from the worker's tone of voice, facial expressions, text input, etc. The input data is the worker's voice and video, and the output data is the recognized emotional information.

[1831] Step 7:

[1832] The server adjusts the task schedule based on the worker's emotions. The server flexibly adjusts the task schedule using TaskScheduler based on the recognized emotion information. The input data is the recognized emotion information, and the output data is the adjusted task schedule.

[1833] Step 8:

[1834] The server issues tasks to the robots. The server then passes the scheduled tasks to the RobotController, which issues specific work instructions to the factory robots. The input data is the scheduled task list, and the output data is the work instructions for the robots.

[1835] Example 2

[1836] Next, a description will be given of Example 2 of Form 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."

[1837] Conventional task management systems prioritize tasks without considering the user's emotional state, which can have a negative impact on user stress and efficiency. Furthermore, report creation using generative AI does not provide information based on the user's emotions, so it cannot fully meet user needs. This leads to issues such as reduced user satisfaction and productivity.

[1838] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1839] In this invention, the server includes means for collecting instructions, means for managing the execution schedule of the collected tasks, means for creating and acquiring reports on multiple tasks at scheduled times using generative AI, means for reporting materials output by the generative AI, means for acquiring user emotional data, means for analyzing the acquired emotional data, means for adjusting task priorities based on the analysis results, and means for making final adjustments to the report based on the adjusted task priorities. This makes it possible to adjust task priorities according to the user's emotional state and create reports using generative AI.

[1840] A "means for collecting instructions" is a device or software for collecting tasks or requests from a user.

[1841] The "means for managing the execution schedule of the collected tasks" is a device or software that sets and manages a schedule for efficiently executing the collected tasks.

[1842] "Means for creating and obtaining reports using generative AI" refers to devices or software that automatically create reports using generative AI technology and obtain them.

[1843] "Means for reporting materials output by generative AI" refers to a device or software for providing users with materials generated by generative AI.

[1844] The "means for acquiring user emotional data" refers to a device or software for detecting the user's emotional state and collecting that data.

[1845] The "means for analyzing acquired emotional data" refers to a device or software f...

Claims

1. A means for collecting tasks to be performed; A means to generate a schedule for tasks A way to set and receive task reminders, Generate tasks at scheduled times; Create and obtain reports using artificial intelligence; A system including:

2. A means for collecting work tasks; A means for planning the timing of execution of the collected work tasks; means for transmitting instructions to the machine to perform the task at the scheduled time; A means to monitor task progress in real time; means for generating a report upon completion of a task using the generative AI model; A system including:

3. A means for collecting tasks to be performed; A means for generating an execution schedule for the collected tasks; A method to generate and obtain reports using AI that generates tasks at scheduled times, A means for acquiring user emotion data; A means for analyzing the acquired emotion data; A means for adjusting task priorities based on the analysis results; and A means for finalizing the report based on the adjusted task priorities; and A system including:

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