system

Abstract

We provide the system. [Solution] A terminal device for collecting schedule information from participants, A processing device that integrates collected schedule information and generates an optimal activity schedule for operation, A notification device means that notifies participants of the generated activity schedule and provides reminders as needed, A processing mechanism that supports communication between participants using natural language processing, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] [There is a need to reduce the burden of schedule management and communication management in modern busy home environments and small-scale group operations and achieve efficient operation. In particular, in the case of a group that frequently requires schedule adjustment, problems such as friction between participants and stagnation of operation may occur due to sudden schedule changes and insufficient communication.]

Means for Solving the Problems

[0005] This invention provides a system that automatically generates an overall schedule by using a terminal means to aggregate schedule information from participants, and efficiently transmits information to participants using a notification device means. Furthermore, it enables smooth communication among participants by using a communication support means that utilizes natural language processing. In addition, it includes a real-time adjustment function that takes environmental information into account and an improvement suggestion function that utilizes operational data, thereby improving schedule flexibility and operational efficiency.

[0006] "Participant" refers to [all individuals who participate in practices or matches within the operation of a sports team].

[0007] "Schedule information" refers to information provided by participants, including their schedules, available times, and any restrictions regarding specific dates.

[0008] "Terminal" refers to an electronic device used by participants to input schedule information.

[0009] A "processing device" refers to a computing device that integrates collected information and performs tasks such as automatic schedule generation and data analysis.

[0010] A "notification device" refers to a component of a system that communicates generated schedules and important information to participants.

[0011] "Natural language processing" refers to the technology of analyzing human language and converting it into a format that is easy for computers to understand.

[0012] "Environmental information" refers to external information that can affect activities, such as weather and location conditions.

[0013] "Real-time adjustment" refers to a function that dynamically revises the schedule to respond immediately to sudden changes in plans or unforeseen circumstances.

[0014] "Operational data" refers to [recorded information and statistical data related to the activities of a sports team].

[0015] "Improvement proposal" refers to [a specific proposal for improving the efficiency and quality of activities based on the analysis of operation data].

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The system for implementing this invention effectively manages participants' schedule information, automatically generates schedules, and facilitates smooth communication. The following describes the program processing of this system in natural language with specific examples.

[0038] First, the user enters their schedule information using the terminal. The terminal has the function of formatting this input information and sending it to the server. For example, a parent might enter, "I will be unavailable in the evening next Friday."

[0039] The server receives various participant schedule information submitted by users and integrates it into a database. Next, the server analyzes the aggregated information to determine the schedules of all participants and automatically generates an optimal activity schedule. This generated schedule is then combined to allow as many participants as possible to attend. For example, a practice session might be scheduled for Saturday morning that everyone can attend.

[0040] The generated schedule is notified to all participants from the server. The notification is displayed on the device and, if necessary, is relayed to participants again through the reminder function. For example, a reminder such as "There will be practice tomorrow at 9 AM" will be sent the day before practice.

[0041] Furthermore, the server utilizes natural language processing to support communication between users. When a user enters a specific question or message through their device, the system automatically analyzes it and generates an appropriate response. For example, if a parent asks, "Where is the next game?", the system will respond, "The next game will be held at the community center."

[0042] Furthermore, the server acquires environmental information in real time and has the capability to respond to sudden schedule changes. If changes in weather or venue availability necessitate changes to the activity schedule, adjustments are made quickly. For example, if heavy rain is forecast, the system will automatically change the location to an indoor facility.

[0043] Finally, the server analyzes operational data and generates improvement suggestions to further streamline operations. This allows stakeholders to obtain information to improve the quality of operations. For example, based on historical data analysis, the most efficient practice time is suggested.

[0044] In this way, this invention significantly reduces the burden on participants and enables smooth and efficient sports team management.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user uses a terminal to enter their schedule information. The terminal receives the schedule information from the user and prepares to send that data to the server.

[0048] Step 2:

[0049] The terminal converts the schedule information entered by the user into a specified data format and sends it to the server. For example, information such as "Unable to attend on the afternoon of July 15th" might be entered.

[0050] Step 3:

[0051] The server receives schedule information sent from terminals and stores it in a database. The server aggregates this data and integrates the schedule information of all participants.

[0052] Step 4:

[0053] The server executes a comprehensive schedule generation algorithm, taking into account all participants' schedules, to automatically generate the optimal activity date. This selects a date and time that allows as many participants as possible to gather.

[0054] Step 5:

[0055] The server composes a message to notify participants of the generated schedule and sends it to the terminal. The terminal receives the notification and displays it to the user.

[0056] Step 6:

[0057] The device uses a reminder function to send additional notifications to the user as the scheduled activity date approaches. This helps the user not forget their appointments.

[0058] Step 7:

[0059] When a user enters additional questions or information from their device, the device uses natural language processing to analyze the content and send it to the server.

[0060] Step 8:

[0061] The server analyzes the user's inquiry and generates an appropriate response. The server then sends that response back to the terminal and displays it to the user.

[0062] Step 9:

[0063] The server periodically retrieves external environmental information (such as weather information) and readjusts the schedule if sudden changes are required.

[0064] Step 10:

[0065] The server analyzes operational data and generates suggestions for further improvement and optimization. These suggestions are then communicated to the user via their terminal.

[0066] (Example 1)

[0067] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0068] In recent years, there has been a growing need to coordinate participants' schedules and manage schedules efficiently and effectively in various activities. However, problems exist, such as difficulties in smooth communication among participants and the inability to respond quickly to sudden changes in circumstances. Furthermore, a significant amount of time and effort is required to run these activities, and efficiency is needed. Against this backdrop, there is a need for a system that integrates participants' schedule information, generates optimal activity schedules, and supports communication.

[0069] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0070] In this invention, the server includes an information terminal means for collecting and integrating schedule information from participants, an information processing device means for generating an optimal activity schedule, a communication device means for notifying participants of the generated activity schedule and providing reminders, a data processing mechanism means for supporting information exchange among participants using natural language processing, an information processing device means for acquiring external environmental information and making immediate adjustments, and a data processing device means for analyzing aggregated operation-related information and generating suggestions for improving operations. This enables efficient operation and smooth communication by automatically adjusting the schedules of all participants.

[0071] An "information terminal" is an electronic device used to input and collect schedule information from participants.

[0072] An "information processing device" is a computer system that integrates collected schedule information and generates an optimal activity schedule.

[0073] A "communication device" is an electronic device used to notify participants of the generated activity schedule and to send reminders as needed.

[0074] A "data processing mechanism" is a system that uses natural language processing technology to support information exchange among participants and facilitate communication.

[0075] "External environmental information" refers to information about external conditions that may affect the activity schedule, such as weather and facility usage.

[0076] "Compiled operational information" refers to data collected and analyzed regarding the operational status of activities.

[0077] This invention is a system aimed at efficient schedule management and smooth communication among participants. The system utilizes information terminals, servers, and various software technologies.

[0078] The device provides an interface for users to input their schedule information. This includes smartphones, tablets, and personal computers, and utilizes a dedicated schedule management application. Through this application, users can register dates, times, and detailed schedule information.

[0079] The server receives schedule information sent from terminals and stores it in a database. Here, the server uses a generative AI model to analyze the data. This model automatically generates the optimal activity schedule from a vast dataset. For example, it identifies a time slot on Saturday morning when everyone can participate.

[0080] The generated schedule is notified to each participant from the server. This notification is sent via push notifications or email using communication devices, providing visual reminders on their devices. The notification also includes a reminder function; for example, a message such as "There is practice tomorrow at 9 AM" is sent the day before the scheduled event.

[0081] Furthermore, the server utilizes natural language processing technology to support communication between users. When a user enters a question or message through their device, the server analyzes the content and automatically generates an appropriate reply. For example, in response to the question, "Where is the next match?", it would reply, "The next match will be held at the Civic Center."

[0082] The server also uses external APIs to retrieve real-time weather information and facility usage status, allowing for quick responses to sudden changes in plans. For example, if an outdoor activity is canceled due to bad weather, it can be immediately changed to an indoor activity.

[0083] This system reduces the burden on participants and allows for efficient and smooth scheduling. An example of a prompt for the generating AI model is, "Please suggest the best date for the next activity."

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] Users enter their schedule information using a terminal. This input involves filling in the date, time, and details through a dedicated application. The terminal converts this information into a standardized format and sends it to the server. The input is the user's individual schedule, and the output is formatted data.

[0087] Step 2:

[0088] The server aggregates the schedule information received from the terminals and records it in the database. The server integrates the received data and checks which schedules are conflicting. The data processing used here involves saving data to tables and executing queries. The input is formatted data, and the output is integrated schedule information.

[0089] Step 3:

[0090] The server analyzes the information stored in the database and generates an optimal activity schedule that maximizes participant attendance. A generation AI model is used to create the schedule, taking multiple conditions into account. The input is integrated schedule information, and the output is the generated activity schedule.

[0091] Step 4:

[0092] The server notifies participants of the generated activity schedule. This notification is sent via email or push notification. The server also sends additional notifications at pre-configured times if reminders are needed. The input is the generated activity schedule, and the output is the notification message.

[0093] Step 5:

[0094] Users can input questions or messages through their terminal. The server automatically parses these messages and generates appropriate responses using natural language processing techniques. The input is the user's question or message, and the output is the generated response.

[0095] Step 6:

[0096] The server retrieves real-time data from an external API (e.g., weather information) and determines whether the planned activity schedule needs to be changed. If necessary, the server generates a new schedule and immediately notifies participants. At this stage, the input is real-time environmental information, and the output is the adjusted activity schedule.

[0097] Step 7:

[0098] The server analyzes past operational data and generates suggestions for improvement. This includes data analysis regarding participation levels and optimal time slots. The input is past operational data, and the output is improvement suggestions.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] In recent years, factories and facilities have been required to efficiently utilize the available time and resources of workers and machinery, and to implement dynamic schedule management. However, conventional systems have struggled to consider multiple factors in real time and quickly adjust to the optimal schedule. Therefore, there is a need for technology that can flexibly respond to unexpected environmental changes and changes in working conditions.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes an input device means for collecting schedule information from participants, an information processing device means for integrating the collected schedule information and generating an optimal activity schedule for operation, an output device means for notifying participants of the generated activity schedule and providing notifications as necessary, an adjustment device means for acquiring external information and quickly adjusting the activity schedule according to conditions, and an assignment device means for optimizing the schedule considering the available time and capacity of workers or machines. This enables optimal utilization of resources in factories and facilities and flexible adjustment of schedules in response to dynamic changes in conditions.

[0104] "Participants" refers to all individual units or elements involved in a plan or activity, primarily including workers and machinery.

[0105] "Schedule information" refers to data related to participants' available time, capabilities, and other planning-related information.

[0106] An "input device" is a means of collecting participants' schedule information and providing it to the system.

[0107] An "information processing device" is a means of optimizing activity schedules based on collected data.

[0108] An "output device" is a means of notifying participants of the generated activity schedule and providing information as needed.

[0109] "External information" refers to data about external factors that affect the environment or situation.

[0110] A "coordination device" is a means of adjusting the activity schedule based on external information.

[0111] An "allocation device" is a means of creating an appropriate schedule that takes into account the available time and capabilities of the participants.

[0112] To implement this invention, a system combining multiple functions is required. First, the server operates as an information processing device, aggregating participants' schedule information. Terminals are used as input devices, and participant information is collected. For example, workers can use their smartphones to input their available time.

[0113] The server analyzes collected data using artificial intelligence technology to generate an optimal activity schedule. Specifically, it utilizes scheduling algorithms written in programming languages ​​such as Python. Furthermore, it incorporates natural language processing software, enabling it to understand questions from participants and automatically provide detailed schedule answers.

[0114] The generated activity schedule is notified to the output device, which is a terminal. The terminal informs participants of the schedule through its notification function and sends reminders as needed. For example, a reminder such as "There is a meeting tomorrow at 9 AM" is sent to the participant's terminal.

[0115] Furthermore, the server constantly monitors external information and adjusts schedules based on weather and facility usage. This allows for quick responses to sudden changes. For example, if outdoor work is canceled due to bad weather, it will be moved indoors.

[0116] An example of a prompt message is, "To optimize the factory schedule, please input the available time for each worker to suggest the optimal allocation." Based on this prompt, the generating AI model will suggest the optimal allocation of resources. This will help participants plan efficiently.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The terminal is used as an input device, and the user enters their schedule information. Specifically, the entered data includes the participant's ID, available time slots, and information about specific skills or roles. This data is formatted by the terminal and sent to the server.

[0120] Step 2:

[0121] The server stores the received participant schedule information in a database. This database aggregates the schedule information of all participants. The server uses this data to analyze each participant's available time and calculate the optimal activity schedule. Specifically, it uses a scheduling algorithm to efficiently combine available time slots.

[0122] Step 3:

[0123] The server notifies each participant of the generated activity schedule as output. At this time, the server generates a notification message and sends it to the terminal. The notification includes the date, time, and location of the activity, as well as a list of participants. If necessary, a reminder function will activate, and participants will be notified again.

[0124] Step 4:

[0125] The server retrieves status data from an external environmental information system. This information includes weather forecasts and facility usage status. Based on the retrieved information, the server re-evaluates the schedule and adjusts the activity dates if necessary. The adjusted dates are then notified to each participant again.

[0126] Step 5:

[0127] When a user enters a question through their device, the server uses natural language processing to analyze the content. Based on the analysis, the server generates an appropriate response and informs the user. For example, to the question "Where is the next meeting?", the server automatically responds "The next meeting will be held in Conference Room B."

[0128] Step 6:

[0129] The server collects and analyzes historical operational data to generate suggestions for improving operational efficiency. Using a generation AI model, it proposes the most efficient activity schedules and other strategies. These suggestions are provided to administrators, contributing to operational improvements.

[0130] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0131] This invention is a system using terminals and a server to collect participants' schedule information and generate an efficient activity schedule. This system incorporates an emotion engine that recognizes the user's emotions and adjusts communication accordingly.

[0132] Users input their schedule information using a device. The device sends this information to a server, which generates an optimal schedule based on the aggregated data. The generated schedule is notified to all participants, and reminders are sent as needed. For example, if a parent inputs "I'm available next Tuesday except in the evening" into their device, that information is used by the server.

[0133] This system uses natural language processing to facilitate communication between participants. When a user enters a question or request via their device, the server analyzes the content and automatically generates an appropriate response. For example, if there is a question about the match schedule, the server will provide an answer such as, "The next match is this weekend, Saturday."

[0134] Of particular note is the use of an emotion engine. The device analyzes the user's text and voice input to identify emotions. Based on the identified emotions, the server dynamically adjusts the content of notifications and communications. For example, if a user enters a dissatisfied comment, the server responds by sending a friendly and supportive message such as, "Is there anything we can do to resolve the issue?"

[0135] Furthermore, the emotion engine adjusts the timing and method of reminders. For example, if it detects that the user is feeling stressed, it might send a reminder a little earlier in a softer tone. This allows the user to prepare for their next appointment without feeling overwhelmed.

[0136] In this way, this invention achieves the optimization of operations and communication that take emotions into consideration, making it possible to build a system that can be used with peace of mind by all stakeholders.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user uses the terminal to enter their schedule information. The terminal converts the entered data into a predetermined format and prepares to send it to the server.

[0140] Step 2:

[0141] The device sends the scheduled information it has prepared to the server. For example, this information might include "I have an appointment next Wednesday afternoon."

[0142] Step 3:

[0143] The server receives schedule information from the terminal, stores it in a database, and integrates it.

[0144] Step 4:

[0145] The server generates an activity schedule based on aggregated schedule information. In this process, a schedule is created that takes into account the ability of as many participants as possible to attend.

[0146] Step 5:

[0147] The server communicates the generated schedule to participants via email or app notifications.

[0148] Step 6:

[0149] The user uses their device to enter questions or comments. The device then sends them to the server, which prepares them for processing.

[0150] Step 7:

[0151] The server analyzes the received message using natural language processing, generates an appropriate response, and sends it back to the terminal. For example, in response to the question "What time does the match start?", it would reply "The match starts at 10:00 AM."

[0152] Step 8:

[0153] The device analyzes the user's emotions based on the text and voice input it receives, using an emotion engine.

[0154] Step 9:

[0155] The server uses the emotional state transmitted from the device to adjust the content of communications and notifications. For example, if the server determines that the user is feeling stressed, it will generate a support message such as, "Is there anything I can do to help?"

[0156] Step 10:

[0157] Reminder notifications sent to users are adjusted in timing and content according to their emotional state and are sent from their devices. Users with high stress levels will receive notifications a little earlier and with gentler content.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] In modern society, efficiently coordinating the schedules of multiple participants and ensuring smooth communication is crucial. However, this presents challenges, including the effort required for scheduling and communication management, as well as the difficulty of responding appropriately while considering the feelings of participants. Furthermore, maintaining an optimal activity schedule while adapting to a constantly changing external environment is another challenge.

[0161] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0162] In this invention, the server includes: an information terminal means for collecting schedule information from participants; a computing device means for integrating the collected schedule information and generating an optimal activity schedule for operation; and an emotion analysis device means for identifying the user's emotions and dynamically adjusting the content of notifications and communications based on the identified emotions. This makes scheduling participants more efficient, enables flexible and appropriate communication that takes participants' emotions into consideration, and allows for schedule management that responds quickly to changes in the environment.

[0163] An "information terminal" refers to a device used to collect schedule information from participants, and includes computing devices such as smartphones and personal computers.

[0164] A "computational device" refers to a machine that processes data based on collected information and generates an optimal activity schedule.

[0165] A "notification device" refers to a device that has communication capabilities and alert functions to inform participants of the generated activity schedule.

[0166] "Natural language processing" refers to technical methods for understanding and appropriately processing human language in order to facilitate communication among participants.

[0167] An "emotion analysis device" refers to a function that includes a processor and algorithms for analyzing user input and identifying emotions.

[0168] A "communication device" refers to a device used to transmit schedules, notifications, and other information to participants, and to update information in real time.

[0169] This invention is a unique system that efficiently manages participants' schedule information and enables flexible, emotion-based communication. The system utilizes terminals, servers, and a network to support smooth interaction among participants.

[0170] First, the user enters their schedule using an information terminal. This terminal includes internet-connected computing devices such as smartphones and PCs. The user enters their schedule into the terminal's interface and submits it, and that information is sent to the server. The software used includes dedicated applications and web browsers.

[0171] Next, the server takes on the role of a computing device, integrating the received schedule information. The server possesses advanced computing capabilities and applies scheduling algorithms to generate the optimal activity schedule. Cloud-based database management systems and big data processing technologies are utilized for data processing during this process.

[0172] Furthermore, the generated schedule is communicated to participants via notification devices, and reminders are sent as needed. These notifications include automated phone notification systems, email, and smartphone push notifications.

[0173] The server's natural language processing mechanism receives and parses user requests to generate appropriate responses. When a user enters a scheduling inquiry in natural language, the server responds based on the parsed results. The message generation uses prompts generated by a generative AI model. Examples of prompts include questions such as "When is the next match?" or "Please resend the schedule."

[0174] The emotion analysis device analyzes user messages and identifies emotions. Based on the identified emotions, the server dynamically adjusts the content of communication with the user. This enables a flexible communication strategy to improve user satisfaction through appropriate responses.

[0175] This invention realizes a system that facilitates and facilitates human-centered scheduling and communication among participants in activities involving multiple participants.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The user enters schedule information using an information terminal. The input screen has fields for date, time, location, and information about the people involved. After entering the necessary information, the user presses the submit button. This action sends the input data from the terminal to the server in a structured format. The input data is passed to the server, for example, in JSON format. The terminal confirms that the data has been sent and displays a confirmation message.

[0179] Step 2:

[0180] The server analyzes the received schedule data and stores it in a database. The server utilizes a database management system to sort user appointments chronologically and detect duplicates and inconsistencies. The input data is user appointment information, and the output is organized schedule information. If a duplicate is detected, the server generates a notification requesting confirmation from the user, and processing continues without interruption.

[0181] Step 3:

[0182] The server integrates the schedules of all participants and generates an optimal activity schedule. An algorithm is executed to coordinate individually scheduled appointments into a single optimized schedule. The input data is schedule information collected from multiple users, and the output is the most efficient activity schedule. The server stores this generated schedule until it is ready for notification.

[0183] Step 4:

[0184] The server uses an emotion analyzer to analyze text input from the user. A natural language processing model is used to extract emotions from the message. This analysis helps understand the user's emotional state and adjust the response accordingly. The input is the user's text message, and the output is identified emotion data. Based on the emotion, the server applies logic to dynamically change the tone and content of the reply.

[0185] Step 5:

[0186] The device receives notifications and reminders from the server and presents them to the user. The device notifies the user of schedules via push notifications and alerts, prompting confirmation or readjustment as needed. Input is notification data sent from the server, and output is notifications and suggestions displayed to the user. The device displays received messages in a manner tailored to the user's preferences and awaits user interaction.

[0187] (Application Example 2)

[0188] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0189] Managing staff shifts in physical stores requires flexible and efficient management that takes into account each staff member's schedule and emotional state. Traditional systems were unable to reflect staff emotional states in scheduling adjustments or provide flexible notification methods, making it difficult to reduce staff dissatisfaction and stress. Furthermore, communication was not smooth, and schedule changes were not effectively communicated.

[0190] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0191] In this invention, the server includes: an information terminal means for collecting schedule information from participants; an emotion analysis mechanism means for identifying the emotional state of participants and dynamically adjusting notifications and communication content based on the identified emotions; and means for adjusting the timing and content of reminders according to the identified emotions. This enables the generation of an optimal shift schedule that takes into account the emotions of staff, as well as flexible communication and notifications to reduce stress.

[0192] An "information terminal" is a device used to collect information from participants regarding their schedules and preferences.

[0193] A "processing mechanism" is a device that has the function of integrating collected information and generating an optimal schedule.

[0194] A "notification device" is a device that has the function of informing participants of the generated schedule and any changes.

[0195] An "information processing device" is a device that uses natural language processing to support communication between participants.

[0196] The "emotion analysis mechanism" is a device that analyzes participants' text and voice input to identify their emotional state.

[0197] A "reminder adjustment device" is a device that has the function of dynamically changing the timing and content of notifications in accordance with the identified emotions.

[0198] "Environmental information" refers to information obtained from external sources that may affect the planned schedule.

[0199] "Operational data" refers to data that collects information about the execution and activities of a system.

[0200] "Optimization suggestions" are recommendations aimed at improving operations and efficient scheduling.

[0201] This invention utilizes a system that combines an information terminal, a server, and a notification means to improve the efficiency of a staff shift management system for physical stores.

[0202] The user operates the information terminal, and each staff member inputs their desired shift and current emotional state into the terminal. The terminal sends the input information to the server. The server is built with Python and the Django framework and uses Google's Natural Language API to identify the user's emotional state. It also uses Scikit-learn to calculate and generate the optimal shift schedule based on each staff member's availability and emotional state. The generated schedule and notifications corresponding to the emotional state are sent from the server to each staff member via email or mobile notification.

[0203] Furthermore, the server collects and analyzes operational data from the entire system and generates suggestions for operational improvements and optimization of scheduling. Scikit-learn is used in this process to identify areas for improvement through the analysis of historical data.

[0204] For example, if a staff member is feeling stressed on a given day, the server will send a reminder early, along with a relaxing message and a schedule notification. This approach reduces the burden on staff members and ensures smooth shift management.

[0205] An example of a prompt might be: "Identify the emotion from the text entered by the user and suggest an appropriate message based on that emotion. 'I'm very tired today.'" This prompt prompts the generative AI model to generate an emotion-based message, providing communication that is appropriate to the user's feelings.

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] Users input their shift preferences and current emotional state via an information terminal. This input includes information such as desired shift times, days of the week, and emotional state. The terminal receives this information, converts it to a digital format, and sends it to the server.

[0209] Step 2:

[0210] The server receives shift request information and emotional state data from the terminal. Next, it analyzes the emotional state using Google's Natural Language API. The analysis results output the type of emotion (e.g., stress, fatigue, joy). This analysis result is used for subsequent schedule adjustments.

[0211] Step 3:

[0212] The server uses Scikit-learn to generate an optimal shift schedule based on the received schedule information and analyzed sentiment data. The input data also includes similar information collected from other staff members. This results in a balanced schedule that takes into account the wishes and emotional states of all staff members.

[0213] Step 4:

[0214] The generated shift schedules are organized by the server and sent to notification systems. Specifically, the content of reminders and schedule notifications is adjusted according to the user's emotional state. For example, users who are feeling stressed will receive notifications with added relaxing messages.

[0215] Step 5:

[0216] The server also collects system operation data. This data is analyzed, and Scikit-learn is used to generate suggestions for optimizing schedules and improving operations. The input data consists of past operation records, and the output is the suggested content.

[0217] Step 6:

[0218] The server notifies users of the generated proposals and shift schedules. The final notification content is distributed through the system, and users can receive it on their smartphones, email, etc. Notifications are made in real time or at pre-set times.

[0219] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0220] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0221] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0225] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0226] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0227] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0228] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0229] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0230] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0231] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0232] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0233] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0234] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0235] The system for implementing this invention effectively manages participants' schedule information, automatically generates schedules, and facilitates smooth communication. The following describes the program processing of this system in natural language with specific examples.

[0236] First, the user enters their schedule information using the terminal. The terminal has the function of formatting this input information and sending it to the server. For example, a parent might enter, "I will be unavailable in the evening next Friday."

[0237] The server receives various participant schedule information submitted by users and integrates it into a database. Next, the server analyzes the aggregated information to determine the schedules of all participants and automatically generates an optimal activity schedule. This generated schedule is then combined to allow as many participants as possible to attend. For example, a practice session might be scheduled for Saturday morning that everyone can attend.

[0238] The generated schedule is notified to all participants from the server. The notification is displayed on the device and, if necessary, is relayed to participants again through the reminder function. For example, a reminder such as "There will be practice tomorrow at 9 AM" will be sent the day before practice.

[0239] Furthermore, the server utilizes natural language processing to support communication between users. When a user enters a specific question or message through their device, the system automatically analyzes it and generates an appropriate response. For example, if a parent asks, "Where is the next game?", the system will respond, "The next game will be held at the community center."

[0240] Furthermore, the server acquires environmental information in real time and has the capability to respond to sudden schedule changes. If changes in weather or venue availability necessitate changes to the activity schedule, adjustments are made quickly. For example, if heavy rain is forecast, the system will automatically change the location to an indoor facility.

[0241] Finally, the server analyzes operational data and generates improvement suggestions to further streamline operations. This allows stakeholders to obtain information to improve the quality of operations. For example, based on historical data analysis, the most efficient practice time is suggested.

[0242] In this way, this invention significantly reduces the burden on participants and enables smooth and efficient sports team management.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The user uses a terminal to enter their schedule information. The terminal receives the schedule information from the user and prepares to send that data to the server.

[0246] Step 2:

[0247] The terminal converts the schedule information entered by the user into a specified data format and sends it to the server. For example, information such as "Unable to attend on the afternoon of July 15th" might be entered.

[0248] Step 3:

[0249] The server receives schedule information sent from terminals and stores it in a database. The server aggregates this data and integrates the schedule information of all participants.

[0250] Step 4:

[0251] The server executes a comprehensive schedule generation algorithm, taking into account all participants' schedules, to automatically generate the optimal activity date. This selects a date and time that allows as many participants as possible to gather.

[0252] Step 5:

[0253] The server composes a message to notify participants of the generated schedule and sends it to the terminal. The terminal receives the notification and displays it to the user.

[0254] Step 6:

[0255] The device uses a reminder function to send additional notifications to the user as the scheduled activity date approaches. This helps the user not forget their appointments.

[0256] Step 7:

[0257] When a user enters additional questions or information from their device, the device uses natural language processing to analyze the content and send it to the server.

[0258] Step 8:

[0259] The server analyzes the user's inquiry and generates an appropriate response. The server then sends that response back to the terminal and displays it to the user.

[0260] Step 9:

[0261] The server periodically retrieves external environmental information (such as weather information) and readjusts the schedule if sudden changes are required.

[0262] Step 10:

[0263] The server analyzes operational data and generates suggestions for further improvement and optimization. These suggestions are then communicated to the user via their terminal.

[0264] (Example 1)

[0265] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0266] In recent years, there has been a growing need to coordinate participants' schedules and manage schedules efficiently and effectively in various activities. However, problems exist, such as difficulties in smooth communication among participants and the inability to respond quickly to sudden changes in circumstances. Furthermore, a significant amount of time and effort is required to run these activities, and efficiency is needed. Against this backdrop, there is a need for a system that integrates participants' schedule information, generates optimal activity schedules, and supports communication.

[0267] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0268] In this invention, the server includes an information terminal means for collecting and integrating schedule information from participants, an information processing device means for generating an optimal activity schedule, a communication device means for notifying participants of the generated activity schedule and providing reminders, a data processing mechanism means for supporting information exchange among participants using natural language processing, an information processing device means for acquiring external environmental information and making immediate adjustments, and a data processing device means for analyzing aggregated operation-related information and generating suggestions for improving operations. This enables efficient operation and smooth communication by automatically adjusting the schedules of all participants.

[0269] An "information terminal" is an electronic device used to input and collect schedule information from participants.

[0270] An "information processing device" is a computer system that integrates collected schedule information and generates an optimal activity schedule.

[0271] A "communication device" is an electronic device used to notify participants of the generated activity schedule and to send reminders as needed.

[0272] A "data processing mechanism" is a system that uses natural language processing technology to support information exchange among participants and facilitate communication.

[0273] "External environmental information" refers to information about external conditions that may affect the activity schedule, such as weather and facility usage.

[0274] "Compiled operational information" refers to data collected and analyzed regarding the operational status of activities.

[0275] This invention is a system aimed at efficient schedule management and smooth communication among participants. The system utilizes information terminals, servers, and various software technologies.

[0276] The device provides an interface for users to input their schedule information. This includes smartphones, tablets, and personal computers, and utilizes a dedicated schedule management application. Through this application, users can register dates, times, and detailed schedule information.

[0277] The server receives schedule information sent from terminals and stores it in a database. Here, the server uses a generative AI model to analyze the data. This model automatically generates the optimal activity schedule from a vast dataset. For example, it identifies a time slot on Saturday morning when everyone can participate.

[0278] The generated schedule is notified to each participant from the server. This notification is sent via push notifications or email using communication devices, providing visual reminders on their devices. The notification also includes a reminder function; for example, a message such as "There is practice tomorrow at 9 AM" is sent the day before the scheduled event.

[0279] Furthermore, the server utilizes natural language processing technology to support communication between users. When a user enters a question or message through their device, the server analyzes the content and automatically generates an appropriate reply. For example, in response to the question, "Where is the next match?", it would reply, "The next match will be held at the Civic Center."

[0280] The server also uses external APIs to retrieve real-time weather information and facility usage status, allowing for quick responses to sudden changes in plans. For example, if an outdoor activity is canceled due to bad weather, it can be immediately changed to an indoor activity.

[0281] This system reduces the burden on participants and allows for efficient and smooth scheduling. An example of a prompt for the generating AI model is, "Please suggest the best date for the next activity."

[0282] The flow of the specific process in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The user uses the terminal to input their schedule information. In this input, the date, time, and details are entered through a dedicated application. The terminal converts this information into a unified format and sends it to the server. The input is the user's individual schedule, and the output is the formatted data.

[0285] Step 2:

[0286] The server aggregates the schedule information received from the terminal and records it in the database. The server integrates the received data and checks for any conflicting schedules. The data processing used here is data storage in a table and query execution. The input is the formatted data, and the output is the integrated schedule information.

[0287] Step 3:

[0288] The server analyzes the information stored in the database and generates an optimal activity schedule that enables the maximum participation rate of the participants. Here, an AI model is used to generate the schedule considering multiple conditions. The input is the integrated schedule information, and the output is the generated activity schedule.

[0289] Step 4:

[0290] The server notifies the participants of the generated activity schedule. This notification is sent using email or push notifications. The server sends additional notifications at pre-set timings if reminders are required. The input is the generated activity schedule, and the output is the notification message.

[0291] Step 5:

[0292] Users can input questions or messages through their terminal. The server automatically parses these messages and generates appropriate responses using natural language processing techniques. The input is the user's question or message, and the output is the generated response.

[0293] Step 6:

[0294] The server retrieves real-time data from an external API (e.g., weather information) and determines whether the planned activity schedule needs to be changed. If necessary, the server generates a new schedule and immediately notifies participants. At this stage, the input is real-time environmental information, and the output is the adjusted activity schedule.

[0295] Step 7:

[0296] The server analyzes past operational data and generates suggestions for improvement. This includes data analysis regarding participation levels and optimal time slots. The input is past operational data, and the output is improvement suggestions.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] In recent years, factories and facilities have been required to efficiently utilize the available time and resources of workers and machinery, and to implement dynamic schedule management. However, conventional systems have struggled to consider multiple factors in real time and quickly adjust to the optimal schedule. Therefore, there is a need for technology that can flexibly respond to unexpected environmental changes and changes in working conditions.

[0300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes an input device means for collecting schedule information from participants, an information processing device means for integrating the collected schedule information and generating an optimal activity schedule for operation, an output device means for notifying the participants of the generated activity schedule and providing notifications as necessary, an adjustment device means for obtaining external information and quickly adjusting the activity schedule according to conditions, and an allocation device means for optimizing the schedule considering the available time and capabilities of workers or machines. As a result, it becomes possible to optimally utilize resources in a factory or facility and flexibly adjust the schedule according to dynamic condition changes.

[0302] "Participants" refers to all individual units or elements involved in plans and activities, mainly including workers and machinery and equipment.

[0303] "Schedule information" refers to data related to the available time and capabilities of participants and other relevant plans.

[0304] "Input device" is a means for collecting participants' schedule information and providing it to the system.

[0305] "Information processing device" is a means for optimizing the activity schedule based on the collected data.

[0306] "Output device" is a means for notifying the participants of the generated activity schedule and providing information as necessary.

[0307] "External information" refers to data related to external factors that affect the environment and situation.

[0308] "Adjustment device" is a means for adjusting the activity schedule based on external information.

[0309] "Allocation device" is a means for constructing an appropriate schedule considering the available time and capabilities of participants.

[0310] To implement this invention, a system combining multiple functions is required. First, the server operates as an information processing device, aggregating participants' schedule information. Terminals are used as input devices, and participant information is collected. For example, workers can use their smartphones to input their available time.

[0311] The server analyzes collected data using artificial intelligence technology to generate an optimal activity schedule. Specifically, it utilizes scheduling algorithms written in programming languages ​​such as Python. Furthermore, it incorporates natural language processing software, enabling it to understand questions from participants and automatically provide detailed schedule answers.

[0312] The generated activity schedule is notified to the output device, which is a terminal. The terminal informs participants of the schedule through its notification function and sends reminders as needed. For example, a reminder such as "There is a meeting tomorrow at 9 AM" is sent to the participant's terminal.

[0313] Furthermore, the server constantly monitors external information and adjusts schedules based on weather and facility usage. This allows for quick responses to sudden changes. For example, if outdoor work is canceled due to bad weather, it will be moved indoors.

[0314] An example of a prompt message is, "To optimize the factory schedule, please input the available time for each worker to suggest the optimal allocation." Based on this prompt, the generating AI model will suggest the optimal allocation of resources. This will help participants plan efficiently.

[0315] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0316] Step 1:

[0317] The terminal is used as an input device, and the user enters their schedule information. Specifically, the entered data includes the participant's ID, available time slots, and information about specific skills or roles. This data is formatted by the terminal and sent to the server.

[0318] Step 2:

[0319] The server stores the received participant schedule information in a database. This database aggregates the schedule information of all participants. The server uses this data to analyze each participant's available time and calculate the optimal activity schedule. Specifically, it uses a scheduling algorithm to efficiently combine available time slots.

[0320] Step 3:

[0321] The server notifies each participant of the generated activity schedule as output. At this time, the server generates a notification message and sends it to the terminal. The notification includes the date, time, and location of the activity, as well as a list of participants. If necessary, a reminder function will activate, and participants will be notified again.

[0322] Step 4:

[0323] The server retrieves status data from an external environmental information system. This information includes weather forecasts and facility usage status. Based on the retrieved information, the server re-evaluates the schedule and adjusts the activity dates if necessary. The adjusted dates are then notified to each participant again.

[0324] Step 5:

[0325] When a user enters a question through their device, the server uses natural language processing to analyze the content. Based on the analysis, the server generates an appropriate response and informs the user. For example, to the question "Where is the next meeting?", the server automatically responds "The next meeting will be held in Conference Room B."

[0326] Step 6:

[0327] The server collects and analyzes historical operational data to generate suggestions for improving operational efficiency. Using a generation AI model, it proposes the most efficient activity schedules and other strategies. These suggestions are provided to administrators, contributing to operational improvements.

[0328] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0329] This invention is a system using terminals and a server to collect participants' schedule information and generate an efficient activity schedule. This system incorporates an emotion engine that recognizes the user's emotions and adjusts communication accordingly.

[0330] Users input their schedule information using a device. The device sends this information to a server, which generates an optimal schedule based on the aggregated data. The generated schedule is notified to all participants, and reminders are sent as needed. For example, if a parent inputs "I'm available next Tuesday except in the evening" into their device, that information is used by the server.

[0331] This system uses natural language processing to facilitate communication between participants. When a user enters a question or request via their device, the server analyzes the content and automatically generates an appropriate response. For example, if there is a question about the match schedule, the server will provide an answer such as, "The next match is this weekend, Saturday."

[0332] Of particular note is the use of an emotion engine. The device analyzes the user's text and voice input to identify emotions. Based on the identified emotions, the server dynamically adjusts the content of notifications and communications. For example, if a user enters a dissatisfied comment, the server responds by sending a friendly and supportive message such as, "Is there anything we can do to resolve the issue?"

[0333] Furthermore, the emotion engine adjusts the timing and method of reminders. For example, if it detects that the user is feeling stressed, it might send a reminder a little earlier in a softer tone. This allows the user to prepare for their next appointment without feeling overwhelmed.

[0334] In this way, this invention achieves the optimization of operations and communication that take emotions into consideration, making it possible to build a system that can be used with peace of mind by all stakeholders.

[0335] The following describes the processing flow.

[0336] Step 1:

[0337] The user uses the terminal to enter their schedule information. The terminal converts the entered data into a predetermined format and prepares to send it to the server.

[0338] Step 2:

[0339] The device sends the scheduled information it has prepared to the server. For example, this information might include "I have an appointment next Wednesday afternoon."

[0340] Step 3:

[0341] The server receives schedule information from the terminal, stores it in a database, and integrates it.

[0342] Step 4:

[0343] The server generates an activity schedule based on aggregated schedule information. In this process, a schedule is created that takes into account the ability of as many participants as possible to attend.

[0344] Step 5:

[0345] The server communicates the generated schedule to participants via email or app notifications.

[0346] Step 6:

[0347] The user uses their device to enter questions or comments. The device then sends them to the server, which prepares them for processing.

[0348] Step 7:

[0349] The server analyzes the received message using natural language processing, generates an appropriate response, and sends it back to the terminal. For example, in response to the question "What time does the match start?", it would reply "The match starts at 10:00 AM."

[0350] Step 8:

[0351] The device analyzes the user's emotions based on the text and voice input it receives, using an emotion engine.

[0352] Step 9:

[0353] The server uses the emotional state transmitted from the device to adjust the content of communications and notifications. For example, if the server determines that the user is feeling stressed, it will generate a support message such as, "Is there anything I can do to help?"

[0354] Step 10:

[0355] Reminder notifications sent to users are adjusted in timing and content according to their emotional state and are sent from their devices. Users with high stress levels will receive notifications a little earlier and with gentler content.

[0356] (Example 2)

[0357] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0358] In modern society, efficiently coordinating the schedules of multiple participants and ensuring smooth communication is crucial. However, this presents challenges, including the effort required for scheduling and communication management, as well as the difficulty of responding appropriately while considering the feelings of participants. Furthermore, maintaining an optimal activity schedule while adapting to a constantly changing external environment is another challenge.

[0359] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0360] In this invention, the server includes: an information terminal means for collecting schedule information from participants; a computing device means for integrating the collected schedule information and generating an optimal activity schedule for operation; and an emotion analysis device means for identifying the user's emotions and dynamically adjusting the content of notifications and communications based on the identified emotions. This makes scheduling participants more efficient, enables flexible and appropriate communication that takes participants' emotions into consideration, and allows for schedule management that responds quickly to changes in the environment.

[0361] An "information terminal" refers to a device used to collect schedule information from participants, and includes computing devices such as smartphones and personal computers.

[0362] A "computational device" refers to a machine that processes data based on collected information and generates an optimal activity schedule.

[0363] A "notification device" refers to a device that has communication capabilities and alert functions to inform participants of the generated activity schedule.

[0364] "Natural language processing" refers to technical methods for understanding and appropriately processing human language in order to facilitate communication among participants.

[0365] An "emotion analysis device" refers to a function that includes a processor and algorithms for analyzing user input and identifying emotions.

[0366] A "communication device" refers to a device used to transmit schedules, notifications, and other information to participants, and to update information in real time.

[0367] This invention is a unique system that efficiently manages participants' schedule information and enables flexible, emotion-based communication. The system utilizes terminals, servers, and a network to support smooth interaction among participants.

[0368] First, the user enters their schedule using an information terminal. This terminal includes internet-connected computing devices such as smartphones and PCs. The user enters their schedule into the terminal's interface and submits it, and that information is sent to the server. The software used includes dedicated applications and web browsers.

[0369] Next, the server takes on the role of a computing device, integrating the received schedule information. The server possesses advanced computing capabilities and applies scheduling algorithms to generate the optimal activity schedule. Cloud-based database management systems and big data processing technologies are utilized for data processing during this process.

[0370] Furthermore, the generated schedule is communicated to participants via notification devices, and reminders are sent as needed. These notifications include automated phone notification systems, email, and smartphone push notifications.

[0371] The server's natural language processing mechanism receives and parses user requests to generate appropriate responses. When a user enters a scheduling inquiry in natural language, the server responds based on the parsed results. The message generation uses prompts generated by a generative AI model. Examples of prompts include questions such as "When is the next match?" or "Please resend the schedule."

[0372] The emotion analysis device analyzes user messages and identifies emotions. Based on the identified emotions, the server dynamically adjusts the content of communication with the user. This enables a flexible communication strategy to improve user satisfaction through appropriate responses.

[0373] This invention realizes a system that facilitates and facilitates human-centered scheduling and communication among participants in activities involving multiple participants.

[0374] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0375] Step 1:

[0376] The user enters schedule information using an information terminal. The input screen has fields for date, time, location, and information about the people involved. After entering the necessary information, the user presses the submit button. This action sends the input data from the terminal to the server in a structured format. The input data is passed to the server, for example, in JSON format. The terminal confirms that the data has been sent and displays a confirmation message.

[0377] Step 2:

[0378] The server analyzes the received schedule data and stores it in a database. The server utilizes a database management system to sort user appointments chronologically and detect duplicates and inconsistencies. The input data is user appointment information, and the output is organized schedule information. If a duplicate is detected, the server generates a notification requesting confirmation from the user, and processing continues without interruption.

[0379] Step 3:

[0380] The server integrates the schedules of all participants and generates an optimal activity schedule. An algorithm is executed to coordinate individually scheduled appointments into a single optimized schedule. The input data is schedule information collected from multiple users, and the output is the most efficient activity schedule. The server stores this generated schedule until it is ready for notification.

[0381] Step 4:

[0382] The server uses an emotion analyzer to analyze text input from the user. A natural language processing model is used to extract emotions from the message. This analysis helps understand the user's emotional state and adjust the response accordingly. The input is the user's text message, and the output is identified emotion data. Based on the emotion, the server applies logic to dynamically change the tone and content of the reply.

[0383] Step 5:

[0384] The device receives notifications and reminders from the server and presents them to the user. The device notifies the user of schedules via push notifications and alerts, prompting confirmation or readjustment as needed. Input is notification data sent from the server, and output is notifications and suggestions displayed to the user. The device displays received messages in a manner tailored to the user's preferences and awaits user interaction.

[0385] (Application Example 2)

[0386] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0387] Managing staff shifts in physical stores requires flexible and efficient management that takes into account each staff member's schedule and emotional state. Traditional systems were unable to reflect staff emotional states in scheduling adjustments or provide flexible notification methods, making it difficult to reduce staff dissatisfaction and stress. Furthermore, communication was not smooth, and schedule changes were not effectively communicated.

[0388] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0389] In this invention, the server includes: an information terminal means for collecting schedule information from participants; an emotion analysis mechanism means for identifying the emotional state of participants and dynamically adjusting notifications and communication content based on the identified emotions; and means for adjusting the timing and content of reminders according to the identified emotions. This enables the generation of an optimal shift schedule that takes into account the emotions of staff, as well as flexible communication and notifications to reduce stress.

[0390] An "information terminal" is a device used to collect information from participants regarding their schedules and preferences.

[0391] A "processing mechanism" is a device that has the function of integrating collected information and generating an optimal schedule.

[0392] A "notification device" is a device that has the function of informing participants of the generated schedule and any changes.

[0393] An "information processing device" is a device that uses natural language processing to support communication between participants.

[0394] The "emotion analysis mechanism" is a device that analyzes participants' text and voice input to identify their emotional state.

[0395] A "reminder adjustment device" is a device that has the function of dynamically changing the timing and content of notifications in accordance with the identified emotions.

[0396] "Environmental information" refers to information obtained from external sources that may affect the planned schedule.

[0397] "Operational data" refers to data that collects information about the execution and activities of a system.

[0398] "Optimization suggestions" are recommendations aimed at improving operations and efficient scheduling.

[0399] This invention utilizes a system that combines an information terminal, a server, and a notification means to improve the efficiency of a staff shift management system for physical stores.

[0400] The user operates the information terminal, and each staff member inputs their desired shift and current emotional state into the terminal. The terminal sends the input information to the server. The server is built with Python and the Django framework and uses Google's Natural Language API to identify the user's emotional state. It also uses Scikit-learn to calculate and generate the optimal shift schedule based on each staff member's availability and emotional state. The generated schedule and emotional-based notifications are sent from the server to each staff member via email or mobile notification.

[0401] Furthermore, the server collects and analyzes operational data from the entire system and generates suggestions for operational improvements and optimization of scheduling. Scikit-learn is used in this process to identify areas for improvement through the analysis of historical data.

[0402] For example, if a staff member is feeling stressed on a given day, the server will send a reminder early, along with a relaxing message and a schedule notification. This approach reduces the burden on staff members and ensures smooth shift management.

[0403] An example of a prompt might be: "Identify the emotion from the text entered by the user and suggest an appropriate message based on that emotion. 'I'm very tired today.'" This prompt prompts the generative AI model to generate an emotion-based message, providing communication that is appropriate to the user's feelings.

[0404] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0405] Step 1:

[0406] Users input their shift preferences and current emotional state via an information terminal. This input includes information such as desired shift times, days of the week, and emotional state. The terminal receives this information, converts it to a digital format, and sends it to the server.

[0407] Step 2:

[0408] The server receives shift request information and emotional state data from the terminal. Next, it analyzes the emotional state using Google's Natural Language API. The analysis results output the type of emotion (e.g., stress, fatigue, joy). This analysis result is used for subsequent schedule adjustments.

[0409] Step 3:

[0410] The server uses Scikit-learn to generate an optimal shift schedule based on the received schedule information and analyzed sentiment data. The input data also includes similar information collected from other staff members. This results in a balanced schedule that takes into account the wishes and emotional states of all staff members.

[0411] Step 4:

[0412] The generated shift schedules are organized by the server and sent to notification systems. Specifically, the content of reminders and schedule notifications is adjusted according to the user's emotional state. For example, users who are feeling stressed will receive notifications with added relaxing messages.

[0413] Step 5:

[0414] The server also collects system operation data. This data is analyzed, and Scikit-learn is used to generate suggestions for optimizing schedules and improving operations. The input data consists of past operation records, and the output is the suggested content.

[0415] Step 6:

[0416] The server notifies users of the generated proposals and shift schedules. The final notification content is distributed through the system, and users can receive it on their smartphones, email, etc. Notifications are made in real time or at pre-set times.

[0417] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0418] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0419] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0423] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0424] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0425] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0426] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0427] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0428] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0429] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0430] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0431] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0432] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0433] The system for implementing this invention effectively manages participants' schedule information, automatically generates schedules, and facilitates smooth communication. The following describes the program processing of this system in natural language with specific examples.

[0434] First, the user enters their schedule information using the terminal. The terminal has the function of formatting this input information and sending it to the server. For example, a parent might enter, "I will be unavailable in the evening next Friday."

[0435] The server receives various participant schedule information submitted by users and integrates it into a database. Next, the server analyzes the aggregated information to determine the schedules of all participants and automatically generates an optimal activity schedule. This generated schedule is then combined to allow as many participants as possible to attend. For example, a practice session might be scheduled for Saturday morning that everyone can attend.

[0436] The generated schedule is notified to all participants from the server. The notification is displayed on the device and, if necessary, is relayed to participants again through the reminder function. For example, a reminder such as "There will be practice tomorrow at 9 AM" will be sent the day before practice.

[0437] Furthermore, the server utilizes natural language processing to support communication between users. When a user enters a specific question or message through their device, the system automatically analyzes it and generates an appropriate response. For example, if a parent asks, "Where is the next game?", the system will respond, "The next game will be held at the community center."

[0438] Furthermore, the server acquires environmental information in real time and has the capability to respond to sudden schedule changes. If changes in weather or venue availability necessitate changes to the activity schedule, adjustments are made quickly. For example, if heavy rain is forecast, the system will automatically change the location to an indoor facility.

[0439] Finally, the server analyzes operational data and generates improvement suggestions to further streamline operations. This allows stakeholders to obtain information to improve the quality of operations. For example, based on historical data analysis, the most efficient practice time is suggested.

[0440] In this way, this invention significantly reduces the burden on participants and enables smooth and efficient sports team management.

[0441] The following describes the processing flow.

[0442] Step 1:

[0443] The user uses a terminal to enter their schedule information. The terminal receives the schedule information from the user and prepares to send that data to the server.

[0444] Step 2:

[0445] The terminal converts the schedule information entered by the user into a specified data format and sends it to the server. For example, information such as "Unable to attend on the afternoon of July 15th" might be entered.

[0446] Step 3:

[0447] The server receives schedule information sent from terminals and stores it in a database. The server aggregates this data and integrates the schedule information of all participants.

[0448] Step 4:

[0449] The server executes a comprehensive schedule generation algorithm, taking into account all participants' schedules, to automatically generate the optimal activity date. This selects a date and time that allows as many participants as possible to gather.

[0450] Step 5:

[0451] The server composes a message to notify participants of the generated schedule and sends it to the terminal. The terminal receives the notification and displays it to the user.

[0452] Step 6:

[0453] The device uses a reminder function to send additional notifications to the user as the scheduled activity date approaches. This helps the user not forget their appointments.

[0454] Step 7:

[0455] When a user enters additional questions or information from their device, the device uses natural language processing to analyze the content and send it to the server.

[0456] Step 8:

[0457] The server analyzes the user's inquiry and generates an appropriate response. The server then sends that response back to the terminal and displays it to the user.

[0458] Step 9:

[0459] The server periodically retrieves external environmental information (such as weather information) and readjusts the schedule if sudden changes are required.

[0460] Step 10:

[0461] The server analyzes operational data and generates suggestions for further improvement and optimization. These suggestions are then communicated to the user via their terminal.

[0462] (Example 1)

[0463] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0464] In recent years, there has been a growing need to coordinate participants' schedules and manage schedules efficiently and effectively in various activities. However, problems exist, such as difficulties in smooth communication among participants and the inability to respond quickly to sudden changes in circumstances. Furthermore, a significant amount of time and effort is required to run these activities, and efficiency is needed. Against this backdrop, there is a need for a system that integrates participants' schedule information, generates optimal activity schedules, and supports communication.

[0465] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0466] In this invention, the server includes an information terminal means for collecting and integrating schedule information from participants, an information processing device means for generating an optimal activity schedule, a communication device means for notifying participants of the generated activity schedule and providing reminders, a data processing mechanism means for supporting information exchange among participants using natural language processing, an information processing device means for acquiring external environmental information and making immediate adjustments, and a data processing device means for analyzing aggregated operation-related information and generating suggestions for improving operations. This enables efficient operation and smooth communication by automatically adjusting the schedules of all participants.

[0467] An "information terminal" is an electronic device used to input and collect schedule information from participants.

[0468] An "information processing device" is a computer system that integrates collected schedule information and generates an optimal activity schedule.

[0469] A "communication device" is an electronic device used to notify participants of the generated activity schedule and to send reminders as needed.

[0470] A "data processing mechanism" is a system that uses natural language processing technology to support information exchange among participants and facilitate communication.

[0471] "External environmental information" refers to information about external conditions that may affect the activity schedule, such as weather and facility usage.

[0472] "Compiled operational information" refers to data collected and analyzed regarding the operational status of activities.

[0473] This invention is a system aimed at efficient schedule management and smooth communication among participants. The system utilizes information terminals, servers, and various software technologies.

[0474] The device provides an interface for users to input their schedule information. This includes smartphones, tablets, and personal computers, and utilizes a dedicated schedule management application. Through this application, users can register dates, times, and detailed schedule information.

[0475] The server receives schedule information sent from terminals and stores it in a database. Here, the server uses a generative AI model to analyze the data. This model automatically generates the optimal activity schedule from a vast dataset. For example, it identifies a time slot on Saturday morning when everyone can participate.

[0476] The generated schedule is notified to each participant from the server. This notification is sent via push notifications or email using communication devices, providing visual reminders on their devices. The notification also includes a reminder function; for example, a message such as "There is practice tomorrow at 9 AM" is sent the day before the scheduled event.

[0477] Furthermore, the server utilizes natural language processing technology to support communication between users. When a user enters a question or message through their device, the server analyzes the content and automatically generates an appropriate reply. For example, in response to the question, "Where is the next match?", it would reply, "The next match will be held at the Civic Center."

[0478] The server also uses external APIs to retrieve real-time weather information and facility usage status, allowing for quick responses to sudden changes in plans. For example, if an outdoor activity is canceled due to bad weather, it can be immediately changed to an indoor activity.

[0479] This system reduces the burden on participants and allows for efficient and smooth scheduling. An example of a prompt for the generating AI model is, "Please suggest the best date for the next activity."

[0480] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0481] Step 1:

[0482] Users enter their schedule information using a terminal. This input involves filling in the date, time, and details through a dedicated application. The terminal converts this information into a standardized format and sends it to the server. The input is the user's individual schedule, and the output is formatted data.

[0483] Step 2:

[0484] The server aggregates the schedule information received from the terminals and records it in the database. The server integrates the received data and checks which schedules are conflicting. The data processing used here involves saving data to tables and executing queries. The input is formatted data, and the output is integrated schedule information.

[0485] Step 3:

[0486] The server analyzes the information stored in the database and generates an optimal activity schedule that maximizes participant attendance. A generation AI model is used to create the schedule, taking multiple conditions into account. The input is integrated schedule information, and the output is the generated activity schedule.

[0487] Step 4:

[0488] The server notifies participants of the generated activity schedule. This notification is sent via email or push notification. The server also sends additional notifications at pre-configured times if reminders are needed. The input is the generated activity schedule, and the output is the notification message.

[0489] Step 5:

[0490] Users can input questions or messages through their terminal. The server automatically parses these messages and generates appropriate responses using natural language processing techniques. The input is the user's question or message, and the output is the generated response.

[0491] Step 6:

[0492] The server retrieves real-time data from an external API (e.g., weather information) and determines whether the planned activity schedule needs to be changed. If necessary, the server generates a new schedule and immediately notifies participants. At this stage, the input is real-time environmental information, and the output is the adjusted activity schedule.

[0493] Step 7:

[0494] The server analyzes past operational data and generates suggestions for improvement. This includes data analysis regarding participation levels and optimal time slots. The input is past operational data, and the output is improvement suggestions.

[0495] (Application Example 1)

[0496] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0497] In recent years, factories and facilities have been required to efficiently utilize the available time and resources of workers and machinery, and to implement dynamic schedule management. However, conventional systems have struggled to consider multiple factors in real time and quickly adjust to the optimal schedule. Therefore, there is a need for technology that can flexibly respond to unexpected environmental changes and changes in working conditions.

[0498] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0499] In this invention, the server includes an input device means for collecting schedule information from participants, an information processing device means for integrating the collected schedule information and generating an optimal activity schedule for operation, an output device means for notifying participants of the generated activity schedule and providing notifications as necessary, an adjustment device means for acquiring external information and quickly adjusting the activity schedule according to conditions, and an assignment device means for optimizing the schedule considering the available time and capacity of workers or machines. This enables optimal utilization of resources in factories and facilities and flexible adjustment of schedules in response to dynamic changes in conditions.

[0500] "Participants" refers to all individual units or elements involved in a plan or activity, primarily including workers and machinery.

[0501] "Schedule information" refers to data related to participants' available time, capabilities, and other planning-related information.

[0502] An "input device" is a means of collecting participants' schedule information and providing it to the system.

[0503] An "information processing device" is a means of optimizing activity schedules based on collected data.

[0504] An "output device" is a means of notifying participants of the generated activity schedule and providing information as needed.

[0505] "External information" refers to data about external factors that affect the environment or situation.

[0506] A "coordination device" is a means of adjusting the activity schedule based on external information.

[0507] An "allocation device" is a means of creating an appropriate schedule that takes into account the available time and capabilities of the participants.

[0508] To implement this invention, a system combining multiple functions is required. First, the server operates as an information processing device, aggregating participants' schedule information. Terminals are used as input devices, and participant information is collected. For example, workers can use their smartphones to input their available time.

[0509] The server analyzes collected data using artificial intelligence technology to generate an optimal activity schedule. Specifically, it utilizes scheduling algorithms written in programming languages ​​such as Python. Furthermore, it incorporates natural language processing software, enabling it to understand questions from participants and automatically provide detailed schedule answers.

[0510] The generated activity schedule is notified to the output device, which is a terminal. The terminal informs participants of the schedule through its notification function and sends reminders as needed. For example, a reminder such as "There is a meeting tomorrow at 9 AM" is sent to the participant's terminal.

[0511] Furthermore, the server constantly monitors external information and adjusts schedules based on weather and facility usage. This allows for quick responses to sudden changes. For example, if outdoor work is canceled due to bad weather, it will be moved indoors.

[0512] An example of a prompt message is, "To optimize the factory schedule, please input the available time for each worker to suggest the optimal allocation." Based on this prompt, the generating AI model will suggest the optimal allocation of resources. This will help participants plan efficiently.

[0513] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0514] Step 1:

[0515] The terminal is used as an input device, and the user enters their schedule information. Specifically, the entered data includes the participant's ID, available time slots, and information about specific skills or roles. This data is formatted by the terminal and sent to the server.

[0516] Step 2:

[0517] The server stores the received participant schedule information in a database. This database aggregates the schedule information of all participants. The server uses this data to analyze each participant's available time and calculate the optimal activity schedule. Specifically, it uses a scheduling algorithm to efficiently combine available time slots.

[0518] Step 3:

[0519] The server notifies each participant of the generated activity schedule as output. At this time, the server generates a notification message and sends it to the terminal. The notification includes the date, time, and location of the activity, as well as a list of participants. If necessary, a reminder function will activate, and participants will be notified again.

[0520] Step 4:

[0521] The server retrieves status data from an external environmental information system. This information includes weather forecasts and facility usage status. Based on the retrieved information, the server re-evaluates the schedule and adjusts the activity dates if necessary. The adjusted dates are then notified to each participant again.

[0522] Step 5:

[0523] When a user enters a question through their device, the server uses natural language processing to analyze the content. Based on the analysis, the server generates an appropriate response and informs the user. For example, to the question "Where is the next meeting?", the server automatically responds "The next meeting will be held in Conference Room B."

[0524] Step 6:

[0525] The server collects and analyzes historical operational data to generate suggestions for improving operational efficiency. Using a generation AI model, it proposes the most efficient activity schedules and other strategies. These suggestions are provided to administrators, contributing to operational improvements.

[0526] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0527] This invention is a system using terminals and a server to collect participants' schedule information and generate an efficient activity schedule. This system incorporates an emotion engine that recognizes the user's emotions and adjusts communication accordingly.

[0528] Users input their schedule information using a device. The device sends this information to a server, which generates an optimal schedule based on the aggregated data. The generated schedule is notified to all participants, and reminders are sent as needed. For example, if a parent inputs "I'm available next Tuesday except in the evening" into their device, that information is used by the server.

[0529] This system uses natural language processing to facilitate communication between participants. When a user enters a question or request via their device, the server analyzes the content and automatically generates an appropriate response. For example, if there is a question about the match schedule, the server will provide an answer such as, "The next match is this weekend, Saturday."

[0530] Of particular note is the use of an emotion engine. The device analyzes the user's text and voice input to identify emotions. Based on the identified emotions, the server dynamically adjusts the content of notifications and communications. For example, if a user enters a dissatisfied comment, the server responds by sending a friendly and supportive message such as, "Is there anything we can do to resolve the issue?"

[0531] Furthermore, the emotion engine adjusts the timing and method of reminders. For example, if it detects that the user is feeling stressed, it might send a reminder a little earlier in a softer tone. This allows the user to prepare for their next appointment without feeling overwhelmed.

[0532] In this way, this invention achieves the optimization of operations and communication that take emotions into consideration, making it possible to build a system that can be used with peace of mind by all stakeholders.

[0533] The following describes the processing flow.

[0534] Step 1:

[0535] The user uses the terminal to enter their schedule information. The terminal converts the entered data into a predetermined format and prepares to send it to the server.

[0536] Step 2:

[0537] The device sends the scheduled information it has prepared to the server. For example, this information might include "I have an appointment next Wednesday afternoon."

[0538] Step 3:

[0539] The server receives schedule information from the terminal, stores it in a database, and integrates it.

[0540] Step 4:

[0541] The server generates an activity schedule based on aggregated schedule information. In this process, a schedule is created that takes into account the ability of as many participants as possible to attend.

[0542] Step 5:

[0543] The server communicates the generated schedule to participants via email or app notifications.

[0544] Step 6:

[0545] The user uses their device to enter questions or comments. The device then sends them to the server, which prepares them for processing.

[0546] Step 7:

[0547] The server analyzes the received message using natural language processing, generates an appropriate response, and sends it back to the terminal. For example, in response to the question "What time does the match start?", it would reply "The match starts at 10:00 AM."

[0548] Step 8:

[0549] The device analyzes the user's emotions based on the text and voice input it receives, using an emotion engine.

[0550] Step 9:

[0551] The server uses the emotional state transmitted from the device to adjust the content of communications and notifications. For example, if the server determines that the user is feeling stressed, it will generate a support message such as, "Is there anything I can do to help?"

[0552] Step 10:

[0553] Reminder notifications sent to users are adjusted in timing and content according to their emotional state and are sent from their devices. Users with high stress levels will receive notifications a little earlier and with gentler content.

[0554] (Example 2)

[0555] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0556] In modern society, efficiently coordinating the schedules of multiple participants and ensuring smooth communication is crucial. However, this presents challenges, including the effort required for scheduling and communication management, as well as the difficulty of responding appropriately while considering the feelings of participants. Furthermore, maintaining an optimal activity schedule while adapting to a constantly changing external environment is another challenge.

[0557] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0558] In this invention, the server includes: an information terminal means for collecting schedule information from participants; a computing device means for integrating the collected schedule information and generating an optimal activity schedule for operation; and an emotion analysis device means for identifying the user's emotions and dynamically adjusting the content of notifications and communications based on the identified emotions. This makes scheduling participants more efficient, enables flexible and appropriate communication that takes participants' emotions into consideration, and allows for schedule management that responds quickly to changes in the environment.

[0559] An "information terminal" refers to a device used to collect schedule information from participants, and includes computing devices such as smartphones and personal computers.

[0560] A "computational device" refers to a machine that processes data based on collected information and generates an optimal activity schedule.

[0561] A "notification device" refers to a device that has communication capabilities and alert functions to inform participants of the generated activity schedule.

[0562] "Natural language processing" refers to technical methods for understanding and appropriately processing human language in order to facilitate communication among participants.

[0563] An "emotion analysis device" refers to a function that includes a processor and algorithms for analyzing user input and identifying emotions.

[0564] A "communication device" refers to a device used to transmit schedules, notifications, and other information to participants, and to update information in real time.

[0565] This invention is a unique system that efficiently manages participants' schedule information and enables flexible, emotion-based communication. The system utilizes terminals, servers, and a network to support smooth interaction among participants.

[0566] First, the user enters their schedule using an information terminal. This terminal includes internet-connected computing devices such as smartphones and PCs. The user enters their schedule into the terminal's interface and submits it, and that information is sent to the server. The software used includes dedicated applications and web browsers.

[0567] Next, the server takes on the role of a computing device, integrating the received schedule information. The server possesses advanced computing capabilities and applies scheduling algorithms to generate the optimal activity schedule. Cloud-based database management systems and big data processing technologies are utilized for data processing during this process.

[0568] Furthermore, the generated schedule is communicated to participants via notification devices, and reminders are sent as needed. These notifications include automated phone notification systems, email, and smartphone push notifications.

[0569] The server's natural language processing mechanism receives and parses user requests to generate appropriate responses. When a user enters a scheduling inquiry in natural language, the server responds based on the parsed results. The message generation uses prompts generated by a generative AI model. Examples of prompts include questions such as "When is the next match?" or "Please resend the schedule."

[0570] The emotion analysis device analyzes user messages and identifies emotions. Based on the identified emotions, the server dynamically adjusts the content of communication with the user. This enables a flexible communication strategy to improve user satisfaction through appropriate responses.

[0571] This invention realizes a system that facilitates and facilitates human-centered scheduling and communication among participants in activities involving multiple participants.

[0572] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0573] Step 1:

[0574] The user enters schedule information using an information terminal. The input screen has fields for date, time, location, and information about the people involved. After entering the necessary information, the user presses the submit button. This action sends the input data from the terminal to the server in a structured format. The input data is passed to the server, for example, in JSON format. The terminal confirms that the data has been sent and displays a confirmation message.

[0575] Step 2:

[0576] The server analyzes the received schedule data and stores it in a database. The server utilizes a database management system to sort user appointments chronologically and detect duplicates and inconsistencies. The input data is user appointment information, and the output is organized schedule information. If a duplicate is detected, the server generates a notification requesting confirmation from the user, and processing continues without interruption.

[0577] Step 3:

[0578] The server integrates the schedules of all participants and generates an optimal activity schedule. An algorithm is executed to coordinate individually scheduled appointments into a single optimized schedule. The input data is schedule information collected from multiple users, and the output is the most efficient activity schedule. The server stores this generated schedule until it is ready for notification.

[0579] Step 4:

[0580] The server uses an emotion analyzer to analyze text input from the user. A natural language processing model is used to extract emotions from the message. This analysis helps understand the user's emotional state and adjust the response accordingly. The input is the user's text message, and the output is identified emotion data. Based on the emotion, the server applies logic to dynamically change the tone and content of the reply.

[0581] Step 5:

[0582] The device receives notifications and reminders from the server and presents them to the user. The device notifies the user of schedules via push notifications and alerts, prompting confirmation or readjustment as needed. Input is notification data sent from the server, and output is notifications and suggestions displayed to the user. The device displays received messages in a manner tailored to the user's preferences and awaits user interaction.

[0583] (Application Example 2)

[0584] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0585] Managing staff shifts in physical stores requires flexible and efficient management that takes into account each staff member's schedule and emotional state. Traditional systems were unable to reflect staff emotional states in scheduling adjustments or provide flexible notification methods, making it difficult to reduce staff dissatisfaction and stress. Furthermore, communication was not smooth, and schedule changes were not effectively communicated.

[0586] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0587] In this invention, the server includes: an information terminal means for collecting schedule information from participants; an emotion analysis mechanism means for identifying the emotional state of participants and dynamically adjusting notifications and communication content based on the identified emotions; and means for adjusting the timing and content of reminders according to the identified emotions. This enables the generation of an optimal shift schedule that takes into account the emotions of staff, as well as flexible communication and notifications to reduce stress.

[0588] An "information terminal" is a device used to collect information from participants regarding their schedules and preferences.

[0589] A "processing mechanism" is a device that has the function of integrating collected information and generating an optimal schedule.

[0590] A "notification device" is a device that has the function of informing participants of the generated schedule and any changes.

[0591] An "information processing device" is a device that uses natural language processing to support communication between participants.

[0592] The "emotion analysis mechanism" is a device that analyzes participants' text and voice input to identify their emotional state.

[0593] A "reminder adjustment device" is a device that has the function of dynamically changing the timing and content of notifications in accordance with the identified emotions.

[0594] "Environmental information" refers to information obtained from external sources that may affect the planned schedule.

[0595] "Operational data" refers to data that collects information about the execution and activities of a system.

[0596] "Optimization suggestions" are recommendations aimed at improving operations and efficient scheduling.

[0597] This invention utilizes a system that combines an information terminal, a server, and a notification means to improve the efficiency of a staff shift management system for physical stores.

[0598] The user operates the information terminal, and each staff member inputs their desired shift and current emotional state into the terminal. The terminal sends the input information to the server. The server is built with Python and the Django framework and uses Google's Natural Language API to identify the user's emotional state. It also uses Scikit-learn to calculate and generate the optimal shift schedule based on each staff member's availability and emotional state. The generated schedule and emotional-based notifications are sent from the server to each staff member via email or mobile notification.

[0599] Furthermore, the server collects and analyzes operational data from the entire system and generates suggestions for operational improvements and optimization of scheduling. Scikit-learn is used in this process to identify areas for improvement through the analysis of historical data.

[0600] For example, if a staff member is feeling stressed on a given day, the server will send a reminder early, along with a relaxing message and a schedule notification. This approach reduces the burden on staff members and ensures smooth shift management.

[0601] An example of a prompt might be: "Identify the emotion from the text entered by the user and suggest an appropriate message based on that emotion. 'I'm very tired today.'" This prompt prompts the generative AI model to generate an emotion-based message, providing communication that is appropriate to the user's feelings.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] Users input their shift preferences and current emotional state via an information terminal. This input includes information such as desired shift times, days of the week, and emotional state. The terminal receives this information, converts it to a digital format, and sends it to the server.

[0605] Step 2:

[0606] The server receives shift request information and emotional state data from the terminal. Next, it analyzes the emotional state using Google's Natural Language API. The analysis results output the type of emotion (e.g., stress, fatigue, joy). This analysis result is used for subsequent schedule adjustments.

[0607] Step 3:

[0608] The server uses Scikit-learn to generate an optimal shift schedule based on the received schedule information and analyzed sentiment data. The input data also includes similar information collected from other staff members. This results in a balanced schedule that takes into account the wishes and emotional states of all staff members.

[0609] Step 4:

[0610] The generated shift schedules are organized by the server and sent to notification systems. Specifically, the content of reminders and schedule notifications is adjusted according to the user's emotional state. For example, users who are feeling stressed will receive notifications with added relaxing messages.

[0611] Step 5:

[0612] The server also collects system operation data. This data is analyzed, and Scikit-learn is used to generate suggestions for optimizing schedules and improving operations. The input data consists of past operation records, and the output is the suggested content.

[0613] Step 6:

[0614] The server notifies users of the generated proposals and shift schedules. The final notification content is distributed through the system, and users can receive it on their smartphones, email, etc. Notifications are made in real time or at pre-set times.

[0615] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0616] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0617] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0618] [Fourth Embodiment]

[0619] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0620] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0621] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0622] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0623] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0624] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0625] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0626] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0627] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0628] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0629] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0630] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0631] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0632] The system for implementing this invention effectively manages participants' schedule information, automatically generates schedules, and facilitates smooth communication. The following describes the program processing of this system in natural language with specific examples.

[0633] First, the user enters their schedule information using the terminal. The terminal has the function of formatting this input information and sending it to the server. For example, a parent might enter, "I will be unavailable in the evening next Friday."

[0634] The server receives various participant schedule information submitted by users and integrates it into a database. Next, the server analyzes the aggregated information to determine the schedules of all participants and automatically generates an optimal activity schedule. This generated schedule is then combined to allow as many participants as possible to attend. For example, a practice session might be scheduled for Saturday morning that everyone can attend.

[0635] The generated schedule is notified to all participants from the server. The notification is displayed on the device and, if necessary, is relayed to participants again through the reminder function. For example, a reminder such as "There will be practice tomorrow at 9 AM" will be sent the day before practice.

[0636] Furthermore, the server utilizes natural language processing to support communication between users. When a user enters a specific question or message through their device, the system automatically analyzes it and generates an appropriate response. For example, if a parent asks, "Where is the next game?", the system will respond, "The next game will be held at the community center."

[0637] Furthermore, the server acquires environmental information in real time and has the capability to respond to sudden schedule changes. If changes in weather or venue availability necessitate changes to the activity schedule, adjustments are made quickly. For example, if heavy rain is forecast, the system will automatically change the location to an indoor facility.

[0638] Finally, the server analyzes operational data and generates improvement suggestions to further streamline operations. This allows stakeholders to obtain information to improve the quality of operations. For example, based on historical data analysis, the most efficient practice time is suggested.

[0639] In this way, this invention significantly reduces the burden on participants and enables smooth and efficient sports team management.

[0640] The following describes the processing flow.

[0641] Step 1:

[0642] The user uses a terminal to enter their schedule information. The terminal receives the schedule information from the user and prepares to send that data to the server.

[0643] Step 2:

[0644] The terminal converts the schedule information entered by the user into a specified data format and sends it to the server. For example, information such as "Unable to attend on the afternoon of July 15th" might be entered.

[0645] Step 3:

[0646] The server receives schedule information sent from terminals and stores it in a database. The server aggregates this data and integrates the schedule information of all participants.

[0647] Step 4:

[0648] The server executes a comprehensive schedule generation algorithm, taking into account all participants' schedules, to automatically generate the optimal activity date. This selects a date and time that allows as many participants as possible to gather.

[0649] Step 5:

[0650] The server composes a message to notify participants of the generated schedule and sends it to the terminal. The terminal receives the notification and displays it to the user.

[0651] Step 6:

[0652] The device uses a reminder function to send additional notifications to the user as the scheduled activity date approaches. This helps the user not forget their appointments.

[0653] Step 7:

[0654] When a user enters additional questions or information from their device, the device uses natural language processing to analyze the content and send it to the server.

[0655] Step 8:

[0656] The server analyzes the user's inquiry and generates an appropriate response. The server then sends that response back to the terminal and displays it to the user.

[0657] Step 9:

[0658] The server periodically retrieves external environmental information (such as weather information) and readjusts the schedule if sudden changes are required.

[0659] Step 10:

[0660] The server analyzes operational data and generates suggestions for further improvement and optimization. These suggestions are then communicated to the user via their terminal.

[0661] (Example 1)

[0662] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] In recent years, there has been a growing need to coordinate participants' schedules and manage schedules efficiently and effectively in various activities. However, problems exist, such as difficulties in smooth communication among participants and the inability to respond quickly to sudden changes in circumstances. Furthermore, a significant amount of time and effort is required to run these activities, and efficiency is needed. Against this backdrop, there is a need for a system that integrates participants' schedule information, generates optimal activity schedules, and supports communication.

[0664] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0665] In this invention, the server includes an information terminal means for collecting and integrating schedule information from participants, an information processing device means for generating an optimal activity schedule, a communication device means for notifying participants of the generated activity schedule and providing reminders, a data processing mechanism means for supporting information exchange among participants using natural language processing, an information processing device means for acquiring external environmental information and making immediate adjustments, and a data processing device means for analyzing aggregated operation-related information and generating suggestions for improving operations. This enables efficient operation and smooth communication by automatically adjusting the schedules of all participants.

[0666] An "information terminal" is an electronic device used to input and collect schedule information from participants.

[0667] An "information processing device" is a computer system that integrates collected schedule information and generates an optimal activity schedule.

[0668] A "communication device" is an electronic device used to notify participants of the generated activity schedule and to send reminders as needed.

[0669] A "data processing mechanism" is a system that uses natural language processing technology to support information exchange among participants and facilitate communication.

[0670] "External environmental information" refers to information about external conditions that may affect the activity schedule, such as weather and facility usage.

[0671] "Compiled operational information" refers to data collected and analyzed regarding the operational status of activities.

[0672] This invention is a system aimed at efficient schedule management and smooth communication among participants. The system utilizes information terminals, servers, and various software technologies.

[0673] The device provides an interface for users to input their schedule information. This includes smartphones, tablets, and personal computers, and utilizes a dedicated schedule management application. Through this application, users can register dates, times, and detailed schedule information.

[0674] The server receives schedule information sent from terminals and stores it in a database. Here, the server uses a generative AI model to analyze the data. This model automatically generates the optimal activity schedule from a vast dataset. For example, it identifies a time slot on Saturday morning when everyone can participate.

[0675] The generated schedule is notified to each participant from the server. This notification is sent via push notifications or email using communication devices, providing visual reminders on their devices. The notification also includes a reminder function; for example, a message such as "There is practice tomorrow at 9 AM" is sent the day before the scheduled event.

[0676] Furthermore, the server utilizes natural language processing technology to support communication between users. When a user enters a question or message through their device, the server analyzes the content and automatically generates an appropriate reply. For example, in response to the question, "Where is the next match?", it would reply, "The next match will be held at the Civic Center."

[0677] The server also uses external APIs to retrieve real-time weather information and facility usage status, allowing for quick responses to sudden changes in plans. For example, if an outdoor activity is canceled due to bad weather, it can be immediately changed to an indoor activity.

[0678] This system reduces the burden on participants and allows for efficient and smooth scheduling. An example of a prompt for the generating AI model is, "Please suggest the best date for the next activity."

[0679] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0680] Step 1:

[0681] Users enter their schedule information using a terminal. This input involves filling in the date, time, and details through a dedicated application. The terminal converts this information into a standardized format and sends it to the server. The input is the user's individual schedule, and the output is formatted data.

[0682] Step 2:

[0683] The server aggregates the schedule information received from the terminals and records it in the database. The server integrates the received data and checks which schedules are conflicting. The data processing used here involves saving data to tables and executing queries. The input is formatted data, and the output is integrated schedule information.

[0684] Step 3:

[0685] The server analyzes the information stored in the database and generates an optimal activity schedule that maximizes participant attendance. A generation AI model is used to create the schedule, taking multiple conditions into account. The input is integrated schedule information, and the output is the generated activity schedule.

[0686] Step 4:

[0687] The server notifies participants of the generated activity schedule. This notification is sent via email or push notification. The server also sends additional notifications at pre-configured times if reminders are needed. The input is the generated activity schedule, and the output is the notification message.

[0688] Step 5:

[0689] Users can input questions or messages through their terminal. The server automatically parses these messages and generates appropriate responses using natural language processing techniques. The input is the user's question or message, and the output is the generated response.

[0690] Step 6:

[0691] The server retrieves real-time data from an external API (e.g., weather information) and determines whether the planned activity schedule needs to be changed. If necessary, the server generates a new schedule and immediately notifies participants. At this stage, the input is real-time environmental information, and the output is the adjusted activity schedule.

[0692] Step 7:

[0693] The server analyzes past operational data and generates suggestions for improvement. This includes data analysis regarding participation levels and optimal time slots. The input is past operational data, and the output is improvement suggestions.

[0694] (Application Example 1)

[0695] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0696] In recent years, factories and facilities have been required to efficiently utilize the available time and resources of workers and machinery, and to implement dynamic schedule management. However, conventional systems have struggled to consider multiple factors in real time and quickly adjust to the optimal schedule. Therefore, there is a need for technology that can flexibly respond to unexpected environmental changes and changes in working conditions.

[0697] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0698] In this invention, the server includes an input device means for collecting schedule information from participants, an information processing device means for integrating the collected schedule information and generating an optimal activity schedule for operation, an output device means for notifying participants of the generated activity schedule and providing notifications as necessary, an adjustment device means for acquiring external information and quickly adjusting the activity schedule according to conditions, and an assignment device means for optimizing the schedule considering the available time and capacity of workers or machines. This enables optimal utilization of resources in factories and facilities and flexible adjustment of schedules in response to dynamic changes in conditions.

[0699] "Participants" refers to all individual units or elements involved in a plan or activity, primarily including workers and machinery.

[0700] "Schedule information" refers to data related to participants' available time, capabilities, and other planning-related information.

[0701] An "input device" is a means of collecting participants' schedule information and providing it to the system.

[0702] An "information processing device" is a means of optimizing activity schedules based on collected data.

[0703] An "output device" is a means of notifying participants of the generated activity schedule and providing information as needed.

[0704] "External information" refers to data about external factors that affect the environment or situation.

[0705] A "coordination device" is a means of adjusting the activity schedule based on external information.

[0706] An "allocation device" is a means of creating an appropriate schedule that takes into account the available time and capabilities of the participants.

[0707] To implement this invention, a system combining multiple functions is required. First, the server operates as an information processing device, aggregating participants' schedule information. Terminals are used as input devices, and participant information is collected. For example, workers can use their smartphones to input their available time.

[0708] The server analyzes collected data using artificial intelligence technology to generate an optimal activity schedule. Specifically, it utilizes scheduling algorithms written in programming languages ​​such as Python. Furthermore, it incorporates natural language processing software, enabling it to understand questions from participants and automatically provide detailed schedule answers.

[0709] The generated activity schedule is notified to the output device, which is a terminal. The terminal informs participants of the schedule through its notification function and sends reminders as needed. For example, a reminder such as "There is a meeting tomorrow at 9 AM" is sent to the participant's terminal.

[0710] Furthermore, the server constantly monitors external information and adjusts schedules based on weather and facility usage. This allows for quick responses to sudden changes. For example, if outdoor work is canceled due to bad weather, it will be moved indoors.

[0711] An example of a prompt message is, "To optimize the factory schedule, please input the available time for each worker to suggest the optimal allocation." Based on this prompt, the generating AI model will suggest the optimal allocation of resources. This will help participants plan efficiently.

[0712] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0713] Step 1:

[0714] The terminal is used as an input device, and the user enters their schedule information. Specifically, the entered data includes the participant's ID, available time slots, and information about specific skills or roles. This data is formatted by the terminal and sent to the server.

[0715] Step 2:

[0716] The server stores the received participant schedule information in a database. This database aggregates the schedule information of all participants. The server uses this data to analyze each participant's available time and calculate the optimal activity schedule. Specifically, it uses a scheduling algorithm to efficiently combine available time slots.

[0717] Step 3:

[0718] The server notifies each participant of the generated activity schedule as output. At this time, the server generates a notification message and sends it to the terminal. The notification includes the date, time, and location of the activity, as well as a list of participants. If necessary, a reminder function will activate, and participants will be notified again.

[0719] Step 4:

[0720] The server retrieves status data from an external environmental information system. This information includes weather forecasts and facility usage status. Based on the retrieved information, the server re-evaluates the schedule and adjusts the activity dates if necessary. The adjusted dates are then notified to each participant again.

[0721] Step 5:

[0722] When a user enters a question through their device, the server uses natural language processing to analyze the content. Based on the analysis, the server generates an appropriate response and informs the user. For example, to the question "Where is the next meeting?", the server automatically responds "The next meeting will be held in Conference Room B."

[0723] Step 6:

[0724] The server collects and analyzes historical operational data to generate suggestions for improving operational efficiency. Using a generation AI model, it proposes the most efficient activity schedules and other strategies. These suggestions are provided to administrators, contributing to operational improvements.

[0725] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0726] This invention is a system using terminals and a server to collect participants' schedule information and generate an efficient activity schedule. This system incorporates an emotion engine that recognizes the user's emotions and adjusts communication accordingly.

[0727] Users input their schedule information using a device. The device sends this information to a server, which generates an optimal schedule based on the aggregated data. The generated schedule is notified to all participants, and reminders are sent as needed. For example, if a parent inputs "I'm available next Tuesday except in the evening" into their device, that information is used by the server.

[0728] This system uses natural language processing to facilitate communication between participants. When a user enters a question or request via their device, the server analyzes the content and automatically generates an appropriate response. For example, if there is a question about the match schedule, the server will provide an answer such as, "The next match is this weekend, Saturday."

[0729] Of particular note is the use of an emotion engine. The device analyzes the user's text and voice input to identify emotions. Based on the identified emotions, the server dynamically adjusts the content of notifications and communications. For example, if a user enters a dissatisfied comment, the server responds by sending a friendly and supportive message such as, "Is there anything we can do to resolve the issue?"

[0730] Furthermore, the emotion engine adjusts the timing and method of reminders. For example, if it detects that the user is feeling stressed, it might send a reminder a little earlier in a softer tone. This allows the user to prepare for their next appointment without feeling overwhelmed.

[0731] In this way, this invention achieves the optimization of operations and communication that take emotions into consideration, making it possible to build a system that can be used with peace of mind by all stakeholders.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] The user uses the terminal to enter their schedule information. The terminal converts the entered data into a predetermined format and prepares to send it to the server.

[0735] Step 2:

[0736] The device sends the scheduled information it has prepared to the server. For example, this information might include "I have an appointment next Wednesday afternoon."

[0737] Step 3:

[0738] The server receives schedule information from the terminal, stores it in a database, and integrates it.

[0739] Step 4:

[0740] The server generates an activity schedule based on aggregated schedule information. In this process, a schedule is created that takes into account the ability of as many participants as possible to attend.

[0741] Step 5:

[0742] The server communicates the generated schedule to participants via email or app notifications.

[0743] Step 6:

[0744] The user uses their device to enter questions or comments. The device then sends them to the server, which prepares them for processing.

[0745] Step 7:

[0746] The server analyzes the received message using natural language processing, generates an appropriate response, and sends it back to the terminal. For example, in response to the question "What time does the match start?", it would reply "The match starts at 10:00 AM."

[0747] Step 8:

[0748] The device analyzes the user's emotions based on the text and voice input it receives, using an emotion engine.

[0749] Step 9:

[0750] The server uses the emotional state transmitted from the device to adjust the content of communications and notifications. For example, if the server determines that the user is feeling stressed, it will generate a support message such as, "Is there anything I can do to help?"

[0751] Step 10:

[0752] Reminder notifications sent to users are adjusted in timing and content according to their emotional state and are sent from their devices. Users with high stress levels will receive notifications a little earlier and with gentler content.

[0753] (Example 2)

[0754] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0755] In modern society, efficiently coordinating the schedules of multiple participants and ensuring smooth communication is crucial. However, this presents challenges, including the effort required for scheduling and communication management, as well as the difficulty of responding appropriately while considering the feelings of participants. Furthermore, maintaining an optimal activity schedule while adapting to a constantly changing external environment is another challenge.

[0756] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0757] In this invention, the server includes: an information terminal means for collecting schedule information from participants; a computing device means for integrating the collected schedule information and generating an optimal activity schedule for operation; and an emotion analysis device means for identifying the user's emotions and dynamically adjusting the content of notifications and communications based on the identified emotions. This makes scheduling participants more efficient, enables flexible and appropriate communication that takes participants' emotions into consideration, and allows for schedule management that responds quickly to changes in the environment.

[0758] An "information terminal" refers to a device used to collect schedule information from participants, and includes computing devices such as smartphones and personal computers.

[0759] A "computational device" refers to a machine that processes data based on collected information and generates an optimal activity schedule.

[0760] A "notification device" refers to a device that has communication capabilities and alert functions to inform participants of the generated activity schedule.

[0761] "Natural language processing" refers to technical methods for understanding and appropriately processing human language in order to facilitate communication among participants.

[0762] An "emotion analysis device" refers to a function that includes a processor and algorithms for analyzing user input and identifying emotions.

[0763] A "communication device" refers to a device used to transmit schedules, notifications, and other information to participants, and to update information in real time.

[0764] This invention is a unique system that efficiently manages participants' schedule information and enables flexible, emotion-based communication. The system utilizes terminals, servers, and a network to support smooth interaction among participants.

[0765] First, the user enters their schedule using an information terminal. This terminal includes internet-connected computing devices such as smartphones and PCs. The user enters their schedule into the terminal's interface and submits it, and that information is sent to the server. The software used includes dedicated applications and web browsers.

[0766] Next, the server takes on the role of a computing device, integrating the received schedule information. The server possesses advanced computing capabilities and applies scheduling algorithms to generate the optimal activity schedule. Cloud-based database management systems and big data processing technologies are utilized for data processing during this process.

[0767] Furthermore, the generated schedule is communicated to participants via notification devices, and reminders are sent as needed. These notifications include automated phone notification systems, email, and smartphone push notifications.

[0768] The server's natural language processing mechanism receives and parses user requests to generate appropriate responses. When a user enters a scheduling inquiry in natural language, the server responds based on the parsed results. The message generation uses prompts generated by a generative AI model. Examples of prompts include questions such as "When is the next match?" or "Please resend the schedule."

[0769] The emotion analysis device analyzes user messages and identifies emotions. Based on the identified emotions, the server dynamically adjusts the content of communication with the user. This enables a flexible communication strategy to improve user satisfaction through appropriate responses.

[0770] This invention realizes a system that facilitates and facilitates human-centered scheduling and communication among participants in activities involving multiple participants.

[0771] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0772] Step 1:

[0773] The user enters schedule information using an information terminal. The input screen has fields for date, time, location, and information about the people involved. After entering the necessary information, the user presses the submit button. This action sends the input data from the terminal to the server in a structured format. The input data is passed to the server, for example, in JSON format. The terminal confirms that the data has been sent and displays a confirmation message.

[0774] Step 2:

[0775] The server analyzes the received schedule data and stores it in a database. The server utilizes a database management system to sort user appointments chronologically and detect duplicates and inconsistencies. The input data is user appointment information, and the output is organized schedule information. If a duplicate is detected, the server generates a notification requesting confirmation from the user, and processing continues without interruption.

[0776] Step 3:

[0777] The server integrates the schedules of all participants and generates an optimal activity schedule. An algorithm is executed to coordinate individually scheduled appointments into a single optimized schedule. The input data is schedule information collected from multiple users, and the output is the most efficient activity schedule. The server stores this generated schedule until it is ready for notification.

[0778] Step 4:

[0779] The server uses an emotion analyzer to analyze text input from the user. A natural language processing model is used to extract emotions from the message. This analysis helps understand the user's emotional state and adjust the response accordingly. The input is the user's text message, and the output is identified emotion data. Based on the emotion, the server applies logic to dynamically change the tone and content of the reply.

[0780] Step 5:

[0781] The device receives notifications and reminders from the server and presents them to the user. The device notifies the user of schedules via push notifications and alerts, prompting confirmation or readjustment as needed. Input is notification data sent from the server, and output is notifications and suggestions displayed to the user. The device displays received messages in a manner tailored to the user's preferences and awaits user interaction.

[0782] (Application Example 2)

[0783] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0784] Managing staff shifts in physical stores requires flexible and efficient management that takes into account each staff member's schedule and emotional state. Traditional systems were unable to reflect staff emotional states in scheduling adjustments or provide flexible notification methods, making it difficult to reduce staff dissatisfaction and stress. Furthermore, communication was not smooth, and schedule changes were not effectively communicated.

[0785] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0786] In this invention, the server includes: an information terminal means for collecting schedule information from participants; an emotion analysis mechanism means for identifying the emotional state of participants and dynamically adjusting notifications and communication content based on the identified emotions; and means for adjusting the timing and content of reminders according to the identified emotions. This enables the generation of an optimal shift schedule that takes into account the emotions of staff, as well as flexible communication and notifications to reduce stress.

[0787] An "information terminal" is a device used to collect information from participants regarding their schedules and preferences.

[0788] A "processing mechanism" is a device that has the function of integrating collected information and generating an optimal schedule.

[0789] A "notification device" is a device that has the function of informing participants of the generated schedule and any changes.

[0790] An "information processing device" is a device that uses natural language processing to support communication between participants.

[0791] The "emotion analysis mechanism" is a device that analyzes participants' text and voice input to identify their emotional state.

[0792] A "reminder adjustment device" is a device that has the function of dynamically changing the timing and content of notifications in accordance with the identified emotions.

[0793] "Environmental information" refers to information obtained from external sources that may affect the planned schedule.

[0794] "Operational data" refers to data that collects information about the execution and activities of a system.

[0795] "Optimization suggestions" are recommendations aimed at improving operations and efficient scheduling.

[0796] This invention utilizes a system that combines an information terminal, a server, and a notification means to improve the efficiency of a staff shift management system for physical stores.

[0797] The user operates the information terminal, and each staff member inputs their desired shift and current emotional state into the terminal. The terminal sends the input information to the server. The server is built with Python and the Django framework and uses Google's Natural Language API to identify the user's emotional state. It also uses Scikit-learn to calculate and generate the optimal shift schedule based on each staff member's availability and emotional state. The generated schedule and emotional-based notifications are sent from the server to each staff member via email or mobile notification.

[0798] Furthermore, the server collects and analyzes operational data from the entire system and generates suggestions for operational improvements and optimization of scheduling. Scikit-learn is used in this process to identify areas for improvement through the analysis of historical data.

[0799] For example, if a staff member is feeling stressed on a given day, the server will send a reminder early, along with a relaxing message and a schedule notification. This approach reduces the burden on staff members and ensures smooth shift management.

[0800] An example of a prompt might be: "Identify the emotion from the text entered by the user and suggest an appropriate message based on that emotion. 'I'm very tired today.'" This prompt prompts the generative AI model to generate an emotion-based message, providing communication that is appropriate to the user's feelings.

[0801] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0802] Step 1:

[0803] Users input their shift preferences and current emotional state via an information terminal. This input includes information such as desired shift times, days of the week, and emotional state. The terminal receives this information, converts it to a digital format, and sends it to the server.

[0804] Step 2:

[0805] The server receives shift request information and emotional state data from the terminal. Next, it analyzes the emotional state using Google's Natural Language API. The analysis results output the type of emotion (e.g., stress, fatigue, joy). This analysis result is used for subsequent schedule adjustments.

[0806] Step 3:

[0807] The server uses Scikit-learn to generate an optimal shift schedule based on the received schedule information and analyzed sentiment data. The input data also includes similar information collected from other staff members. This results in a balanced schedule that takes into account the wishes and emotional states of all staff members.

[0808] Step 4:

[0809] The generated shift schedules are organized by the server and sent to notification systems. Specifically, the content of reminders and schedule notifications is adjusted according to the user's emotional state. For example, users who are feeling stressed will receive notifications with added relaxing messages.

[0810] Step 5:

[0811] The server also collects system operation data. This data is analyzed, and Scikit-learn is used to generate suggestions for optimizing schedules and improving operations. The input data consists of past operation records, and the output is the suggested content.

[0812] Step 6:

[0813] The server notifies users of the generated proposals and shift schedules. The final notification content is distributed through the system, and users can receive it on their smartphones, email, etc. Notifications are made in real time or at pre-set times.

[0814] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0815] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0816] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0817] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0818] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0819] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0820] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0821] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0822] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0823] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0824] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0825] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0826] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0827] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0828] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0829] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0830] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0831] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0832] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0833] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0834] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0835] The following is further disclosed regarding the embodiments described above.

[0836] (Claim 1)

[0837] [A terminal device for collecting schedule information from participants,

[0838] [A processing device that integrates collected schedule information and generates an optimal activity schedule for operations,

[0839] [A notification device means that notifies participants of the generated activity schedule and provides reminders as needed,

[0840] [A processing mechanism that supports communication between participants using natural language processing,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] [A processing device that acquires environmental information from external sources and makes adjustments in real time if changes to the activity schedule are necessary,

[0844] The system according to claim 1, further comprising a notification device means for re-notifying the adjusted activity schedule.

[0845] (Claim 3)

[0846] The system according to claim 1, further comprising a processing device means for analyzing accumulated operational data and generating suggestions for improving operations or optimizing schedules.

[0847] "Example 1"

[0848] (Claim 1)

[0849] [An information terminal for collecting schedule information from participants,

[0850] [An information processing device that integrates collected schedule information and generates an optimal activity schedule for schedule management,

[0851] [A communication device means that notifies participants of the generated activity schedule and provides reminders,

[0852] [A data processing mechanism that supports information exchange among participants using natural language processing,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] [An information processing device that acquires external environmental information and performs immediate scheduling adjustments when required,

[0856] The system according to claim 1, further comprising communication device means for updating and re-notifying the adjusted activity schedule.

[0857] (Claim 3)

[0858] The system according to claim 1, further comprising a data processing device for analyzing aggregated operational information and generating suggestions for improving operations or streamlining scheduling.

[0859] "Application Example 1"

[0860] (Claim 1)

[0861] [An input device means for collecting schedule information from participants,

[0862] [An information processing device that integrates collected schedule information and generates an optimal activity schedule for operation,

[0863] [An output device means that notifies participants of the generated activity schedule and provides notifications as necessary,

[0864] [A processing device that supports communication between participants using natural language processing,

[0865] [An adjustment device means that acquires external information and quickly adjusts the activity schedule according to the conditions,

[0866] [An assignment device means that optimizes the schedule considering the available time and capacity of workers or machines,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, further comprising an output device means for re-notifying the adjusted activity schedule.

[0870] (Claim 3)

[0871] [The system according to claim 1, comprising information processing device means for analyzing aggregated operational data and generating suggestions for improving or streamlining operations.

[0872] "Example 2 of combining an emotion engine"

[0873] (Claim 1)

[0874] [An information terminal for collecting schedule information from participants,

[0875] [A computing device that integrates collected schedule information and generates an optimal activity schedule for operation,

[0876] [A notification device means that notifies participants of the generated activity schedule and sends reminders as needed,

[0877] [A processing mechanism that supports communication between participants using natural language processing,

[0878] [An emotion analysis device means for identifying the user's emotions and dynamically adjusting the content of notifications and communications based on the identified emotions,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] [A computing device that acquires environmental information from external sources and makes adjustments in real time if changes to the activity schedule are necessary,

[0882] The system according to claim 1, further comprising a communication device means for re-notifying the adjusted activity schedule.

[0883] (Claim 3)

[0884] The system according to claim 1, further comprising a computing device means for analyzing accumulated operational data and generating suggestions for improving operations or optimizing schedules.

[0885] "Application example 2 when combining with an emotional engine"

[0886] (Claim 1)

[0887] [An information terminal for collecting schedule information from participants,

[0888] [A processing mechanism that integrates collected schedule information and generates an optimal plan schedule for operation,

[0889] [A notification means that notifies participants of the generated schedule and sends reminders as needed,

[0890] [An information processing device that supports communication between participants using natural language processing,

[0891] [An emotion analysis mechanism that identifies the emotional state of participants and dynamically adjusts notifications and communication content based on the identified emotions,

[0892] [Means for adjusting the timing and content of reminders according to identified emotions,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] [A processing device that acquires environmental information from external sources and makes adjustments in real time if changes to the planned schedule are necessary,

[0896] [Notification means for re-notifying the adjusted schedule; system according to claim 1.

[0897] (Claim 3)

[0898] The system according to claim 1, further comprising an information processing mechanism means for analyzing accumulated operational data and generating suggestions for improving operations or optimizing schedules. [Explanation of Symbols]

[0899] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal device for collecting schedule information from participants, A processing device that integrates collected schedule information and generates an optimal activity schedule for operation, A notification device means that notifies participants of the generated activity schedule and provides reminders as needed, A processing mechanism that supports communication between participants using natural language processing, A system that includes this.

2. A processing device that acquires external environmental information and makes real-time adjustments when changes to the activity schedule are necessary, The system according to claim 1, further comprising a notification device means for re-notifying the adjusted activity schedule.

3. The system according to claim 1, further comprising a processing device means for analyzing accumulated operational data and generating suggestions for improving operations or optimizing schedules.

Images