system

Abstract

Provide a system. 【Solution means】 A means for the information processing device to receive schedule information from a user and store the schedule information in a storage device; A means for analyzing the schedule information stored in the storage device to determine an optimal activity time for each participant; A means for notifying other users of the optimal activity time; A means for receiving a selection of whether or not to participate in an activity from a user; A means for aggregating the received participation information and determining the final activity time; A means for strengthening communication in collective activity adjustment involving multiple participants and improving the efficiency of regional activities; A means for notifying the user of the final activity time; A system including the above.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 character of the chatbot, 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] In school events and PTA activities, efficiently making schedule adjustments and communicating is a burden for many people. Although it is desired to reduce this burden and simplify the decision-making process, in the conventional methods, it takes a long time to adjust the schedule, and there are often confusions in the adjustments and communications among the relevant parties. To solve such problems, a mechanism for realizing effective and efficient schedule management and communication is necessary.

Means for Solving the Problems

[0005] This invention provides an information processing device that receives schedule information from users and stores that information in a database. Furthermore, it has means for analyzing the schedule information in the database and determining the optimal event time for each user. This means includes a function to calculate the optimal date and time from multiple candidate dates using an optimization algorithm. After determining the optimal event time, the system notifies other users of this information and receives their responses regarding their ability to attend the event, thereby determining the final event time and notifying relevant parties. In addition, it provides a system that ensures thorough communication among participants by sending reminder notifications before the event. This achieves improved communication efficiency and simplified decision-making, which were difficult to solve with conventional methods.

[0006] An "information processing device" is a device used for inputting, processing, storing, and outputting data, and includes computer systems, among others.

[0007] "Users" refers to people who use this system to schedule appointments and communicate.

[0008] "Schedule information" refers to detailed information about the date, time, and content of events and meetings, which are created and entered by users.

[0009] A "database" is a system for managing, efficiently storing, and retrieving structured data.

[0010] "Analysis" is the process of organizing and analyzing data to derive information that is suitable for a specific purpose.

[0011] An "optimization algorithm" refers to a series of computational processes designed to find the best solution from multiple options.

[0012] The "final event time" is the date and time determined after users have been notified and their participation status has been compiled.

[0013] A "reminder notification" is a notification function that sends a reminder to the user before a scheduled event. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [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.

Embodiments for Carrying Out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered 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.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered 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.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention provides a system for streamlining the scheduling of events involving multiple users and for facilitating the smooth sharing of information. This system mainly consists of a server as an information processing device, terminals accessed by users, and the user's own interface.

[0036] The server is responsible for aggregating schedule information sent from each user. Schedule information entered by users via their terminals is stored in a database by the server. Based on this information, the server uses an optimization algorithm to calculate the optimal event time for each user. The calculated optimal date and time are then notified to all users.

[0037] The terminal functions as a means for users to input, confirm, and edit schedule information through an interface. After entering the schedule, the terminal performs the saving and transmission processes, passing the data to the server. It also receives notifications from the server and displays reminders and event change notifications to the user.

[0038] Users can input and modify appointments using their own devices and communicate smoothly with other users. Based on user selections, the final event time is determined, and this information is then notified to all users again.

[0039] As a concrete example, when scheduling a monthly PTA meeting using this system, each member first enters their available dates into a terminal. This information is collected on a server, and a candidate date is calculated through an optimization algorithm. The server notifies all members of the best candidate date, and members select their final attendance status on their terminals. The server compiles this attendance information, determines the final meeting date, and notifies the members. A reminder is automatically sent the day before the meeting, allowing users to prepare efficiently.

[0040] This format allows individual users to schedule activities with minimal burden, enabling the smooth operation of PTA and other organizational activities.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uses their device to enter possible dates for meetings they can attend. A scheduling form is provided on the device, and the user fills in the information in a timely manner.

[0044] Step 2:

[0045] The terminal checks the entered schedule information, verifies that there are no errors in the input, and then sends the data to the server. If there are errors, a message prompting the user to correct them will be displayed.

[0046] Step 3:

[0047] The server stores the received schedule information in a database. This database serves to store candidate dates and times for each user.

[0048] Step 4:

[0049] The server aggregates all user-submitted candidate dates stored in the database and applies an AI-based optimization algorithm to calculate the meeting date with the highest overall attendance rate.

[0050] Step 5:

[0051] The server generates a notification message with the calculated optimal date and time and sends it to all users.

[0052] Step 6:

[0053] The terminal displays a notification from the server indicating the optimal date and time for participation. The user reviews the notification and chooses whether or not to participate.

[0054] Step 7:

[0055] Based on the notification, the user specifies on their device whether or not they will participate. Once the selection is complete, the device sends that information back to the server.

[0056] Step 8:

[0057] The server compiles responses from all users indicating whether they can participate or not, and determines the final meeting date and time based on the number of available participants.

[0058] Step 9:

[0059] The server creates a message to notify all users of the final meeting date and time, and then executes the notification.

[0060] Step 10:

[0061] When the device receives notification of the final decision from the server, it displays the details to the user and automatically adds the event to the calendar.

[0062] Step 11:

[0063] The server sets a schedule to send reminders in advance as the meeting date approaches.

[0064] Step 12:

[0065] The device receives a reminder notification and displays a message prompting the user to reconfirm the event.

[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 modern society, coordinating the date and time of events involving many participants is difficult, as it requires selecting the most appropriate date and time to accommodate individual schedules. This is especially true when there are numerous possible dates and participants have diverse availability; manual coordination is time-consuming and laborious. Furthermore, delays in confirming and notifying participants of the chosen date and time can hinder the smooth running of the event. Efficient and effective solutions are needed to address these challenges.

[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 means for receiving schedule information from users and storing the schedule information in a storage area, means for analyzing the schedule information stored in the storage area and determining the optimal event time for each user, and means for notifying other users of the optimal event time. This enables efficient scheduling and smooth event management.

[0071] An "information processing device" is a device that receives, records, and analyzes data entered by a user.

[0072] A "user" is an individual or group that may use the system to input schedule information and potentially participate in an event.

[0073] "Schedule information" refers to data entered by users regarding their available time and participation time during a specific period.

[0074] "Memory area" refers to a part of data storage used to store received data.

[0075] "Analysis" refers to the processing activity of determining the optimal date and time based on the schedule information provided by the user.

[0076] The "optimal event time" is the date and time chosen to maximize efficiency and participation, taking into account the circumstances of all users.

[0077] "Notification" refers to communication activities aimed at conveying decided information to users.

[0078] "Participation status information" refers to information indicating whether a user is able to participate in the proposed event at the suggested time.

[0079] The "final event time" refers to the date and time after all participation confirmation information has been compiled and finalized.

[0080] A "communication domain" refers to the network environment or means of communication used when exchanging information.

[0081] "Optimization" refers to the application of calculations and algorithms to select the most appropriate date and time from the proposed candidate dates.

[0082] This invention is a system for efficiently coordinating the dates and times of events involving multiple users and for smoothly sharing information among users. The system mainly consists of a server acting as an information processing device, terminals accessed by users, and the users themselves.

[0083] The server plays the role of aggregating schedule information sent by users. Specifically, it receives schedule information entered by users via their terminals and stores it in data storage. A general database system can be used for this storage. For example, RDBMS (relational database management systems) such as MySQL® or PostgreSQL can be considered as databases.

[0084] Furthermore, the server performs optimization processing based on the stored information. This process uses the Python library Scikit-learn to select the optimal date and time. This allows the server to select the date and time that is most convenient for multiple users to participate. The determined date and time are automatically notified to all users, and the server aggregates the participation status information sent back by the users. Based on this, the final event date and time are determined. The server also has a function to send reminders to users the day before the event, and can send emails using an SMTP server or utilize push notification services.

[0085] The terminal functions as a means for users to access the system and input, confirm, and edit schedule information. Through the terminal's interface, users can select available days in a calendar format and fill in details in the input form. The entered information is sent from the terminal to the server and used for subsequent processing. The terminal also receives notifications from the server and informs the user via pop-up notifications or screen displays.

[0086] Users can input their schedules using their devices and communicate efficiently with other users. For example, when scheduling a PTA meeting, users input the days they are available into their devices. This information is collected on the server, and the optimal date is calculated and suggested to all users. Users then select whether they will attend or not using their devices, and the final meeting date is determined. An automatic reminder is sent to the user's device the day before the meeting, allowing them to prepare promptly.

[0087] As a concrete example, an example of a prompt message to the generating AI model is, "I would like to schedule a PTA meeting. Please let me know which days you are available next week." This prompt allows the AI ​​to assist the user in entering their schedule, enabling efficient scheduling.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The user accesses the interface through their device to open the schedule entry page. On the calendar-style screen, they select available dates and enter details such as time slots. They enter a prompt message such as "Please tell me which days you are available next week," and this information is collected and sent from their device as structured data in JSON format or similar.

[0091] Step 2:

[0092] The terminal sends the entered schedule information to the server. During this process, the terminal converts the data into a specific format (e.g., JSON format) and transmits it via the communication area. Once the information transmission to the server is complete, a notification indicating the success of the process is displayed on the terminal.

[0093] Step 3:

[0094] The server receives schedule information sent from the terminal and stores it in its storage. Based on this information, the server checks the schedules of all users and stores it in the database. During the saving process, the server checks the accuracy of the data and removes any inconsistent data.

[0095] Step 4:

[0096] The server analyzes the data stored in its memory and begins the optimization process. This analysis uses a generative AI model and optimization algorithms to calculate the optimal event date and time for all users. The algorithm clusters multidimensional data and selects candidate dates that are most likely to be attended. The results of this calculation are stored on the server as internal data.

[0097] Step 5:

[0098] The server generates a notification message with the calculated optimal event date and time and notifies all users. The notification is sent via email or push notification, and a record of the transmission is saved in the log. The server verifies that the notification was successfully delivered to each user.

[0099] Step 6:

[0100] The user receives a notification from the server and checks it on their device. A screen for selecting whether to participate or not appears on the device, and the user selects "Participate" or "Do not participate." Once the selection is confirmed, that information is sent back from the device to the server.

[0101] Step 7:

[0102] The server aggregates the attendance confirmation information submitted by users. This aggregation ultimately determines the event date and time that will ensure the optimal number of participants. The determined date and time are then notified to all users again as a reminder and registered as the final date.

[0103] Step 8:

[0104] The user receives a reminder notification sent from the server and confirms it on the notification screen on their device. By using the prompt message, "I would like to schedule a PTA meeting. Please let me know which days you are available next week," the user can quickly proceed with preparations.

[0105] (Application Example 1)

[0106] 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."

[0107] When coordinating group activities or events involving multiple participants, scheduling can become inefficient. This is especially true for community activities with many participants, where checking everyone's schedules and determining the optimal date is difficult. This challenge can lead to poor communication among participants, resulting in delays or inefficiencies in community activities.

[0108] 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.

[0109] In this invention, the server includes means for an information processing device to receive schedule information from a user and store the schedule information in a storage device, means for analyzing the schedule information stored in the storage device to determine the optimal activity time for each participant, and means for notifying other users of the optimal activity time. This makes it possible to quickly and effectively coordinate the optimal schedule for activities among multiple participants.

[0110] An "information processing device" is a device that has the function of receiving, storing, analyzing, and notifying users of data.

[0111] "User" refers to a person who provides schedule information to an information processing device and receives notification of the result.

[0112] "Schedule information" refers to data that indicates the dates on which a user is available to participate in a specific activity or event.

[0113] A "storage device" is a storage medium used by an information processing device to store scheduled information.

[0114] "Analysis" is the process of evaluating data based on collected schedule information and calculating the optimal activity time.

[0115] An "optimization calculation method" is an algorithm used to derive the optimal result that satisfies multiple conditions.

[0116] "Activity time" refers to the date and time of an activity or event, which is determined considering the participants' schedules.

[0117] "Collective activity coordination" is the process of efficiently combining schedules and plans for activities and events involving multiple participants.

[0118] To realize this system, servers responsible for information processing play a central role. These servers are deployed on cloud-based platforms such as AWS® and Google® Cloud, efficiently receiving scheduling information from users and storing it in storage devices. This allows the servers to manage large amounts of data while achieving a secure and scalable configuration.

[0119] The server uses programs implemented in programming languages ​​such as Python and Node.js to analyze the stored schedule information. These programs retrieve data from databases such as MongoDB and MySQL and use optimization calculation methods to determine the optimal activity times for each participant. Through such data calculations, a balanced activity schedule is created for all participants.

[0120] The analysis results are notified to the user's device in real time. The device is developed using cross-platform technologies such as React Native and Flutter® to ensure compatibility with various devices, including smartphones and personal computers. This allows users to enjoy convenience while maintaining a consistent user experience across different devices.

[0121] Another concrete example is how this system facilitates smooth scheduling for local residents participating in meetings organized by the local government. Residents can enter their available dates and times into the application, and the system will then suggest the most suitable schedule, allowing activities to proceed smoothly.

[0122] Examples of prompts for a generative AI model include: "I want to design a system that efficiently aggregates the schedules of multiple participants and calculates the optimal meeting time. This system also needs real-time notification and reminder sending capabilities. How should the program be structured?"

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The user opens the app on their smartphone and enters their available dates. The input data is converted to the appropriate format by the device and sent to the server. This allows the server to receive the user's available dates.

[0126] Step 2:

[0127] The server retrieves the received schedule information and stores it in the database. During this process, the format is standardized to ensure that the entered information is stored correctly, free from duplicates and errors. This process centralizes the management of schedule information in the database.

[0128] Step 3:

[0129] The server retrieves schedule information for all participants from the database and begins analysis using an optimization calculation method. Here, a Python-based algorithm is used to derive the optimal activity time. By comparing multiple candidate dates and times, the most convenient time for all participants is selected.

[0130] Step 4:

[0131] Once the optimal activity time is determined, the server notifies each participant's device of the result. The output is in real time, and users can check the results on their own devices. The notification includes important schedules for the next activity and information on how to prepare for the activity.

[0132] Step 5:

[0133] The user receives a notification, decides whether or not they can participate in the optimal activity time, and sends feedback to the server via their device. Here, the user reviews the details and makes an input to choose whether or not to participate.

[0134] Step 6:

[0135] The server collects participation confirmation information from users and determines the final activity time. Using an aggregation algorithm, it makes adjustments based on participant feedback to determine the time when the most participants can gather.

[0136] Step 7:

[0137] The server will re-notify all participants of the final confirmed activity time. This final notification, accompanied by a reminder function, is automatically sent before the activity date. The system makes it easier for participants to prepare for the activity.

[0138] 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.

[0139] This invention provides a system that streamlines event scheduling and enables more personalized notifications and decision-making by taking user emotions into consideration. The system includes a server as an information processing device, a terminal providing a user interface, and the user themselves. Furthermore, an emotion engine that analyzes user emotions is integrated.

[0140] The server aggregates and analyzes scheduling information and utilizes emotional data obtained by the emotion engine. For example, when a user enters potential meeting dates, the server stores the information in the database and uses the emotion engine to evaluate each user's emotional state. Based on this evaluation, the optimal date and time are selected, and notifications are adjusted accordingly.

[0141] The device allows users to input schedule information and provide emotional feedback through the user interface. When a user enters a schedule or receives a notification, the device collects the user's emotional data. This data is then sent to a server to help optimize notification methods.

[0142] Users can use their devices to input meeting schedules and communicate their feelings and feedback during those meetings. For example, a user's emotions such as stress or anticipation for a specific date and time are recorded and sent to a server, where they can be shared with other users.

[0143] As a concrete example, consider scheduling a PTA meeting. The user enters their available dates on their device and indicates their feelings about those dates using a simple slider or rating. This information is sent to the server. The server analyzes multiple candidate dates and the user's emotional state to determine the optimal meeting date. If there is a lot of positive feedback for a particular meeting date, that date and time will be given high priority and notified; if there is negative feedback, alternative dates can be suggested.

[0144] This format allows for adjustments that take into account the emotional state of the users, which is expected to facilitate smoother communication and improve satisfaction. As a result, it promotes increased overall participation and smoother operation in group meetings such as those of PTAs.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] Users use their devices to enter possible meeting dates. They also use a slider to indicate their feelings about those dates as emotional feedback.

[0148] Step 2:

[0149] The terminal verifies the format of the entered schedule information and sentiment feedback before sending it to the server, ensuring data integrity.

[0150] Step 3:

[0151] The server stores the received schedule information and emotional feedback in a database. The stored emotional data is then incorporated into the optimization algorithm.

[0152] Step 4:

[0153] The server uses an algorithm to analyze candidate date data and sentiment feedback collected from all users to calculate the meeting date that will generate the highest level of participation.

[0154] Step 5:

[0155] The server prepares the calculated optimal date and time as an emotionally sensitive message and notifies the user.

[0156] Step 6:

[0157] The terminal receives notifications from the server and displays them to the user. The user can then make a final decision on whether or not to participate in the event at the notified date and time.

[0158] Step 7:

[0159] The device resends the user's participation status information to the server. The transmitted data also includes re-evaluated sentiment feedback.

[0160] Step 8:

[0161] The server compiles the final attendance confirmation information, re-evaluates participation intentions, and then determines the final meeting date and time.

[0162] Step 9:

[0163] The server notifies all users of the finalized meeting date and time, and automatically updates their calendars.

[0164] Step 10:

[0165] The server schedules to send reminders at the optimal time, using an emotion engine, a few days before the meeting.

[0166] Step 11:

[0167] The device receives a reminder notification and displays it to the user to prompt them to prepare for the meeting.

[0168] (Example 2)

[0169] 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".

[0170] Traditional scheduling management systems fail to consider users' emotional states, leading to decreased user satisfaction during scheduling. Furthermore, they lack effective means of utilizing individual user emotional feedback when selecting the optimal date and time from multiple options. Additionally, notifications are delivered in a generic format, resulting in a lack of personalization for individual users.

[0171] 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.

[0172] In this invention, the server includes means for receiving schedule information from users and storing it in a memory area, means for evaluating each user's emotional state using sentiment analysis, and means for generating personalized notification text using a generative AI model. This enables optimal event adjustment that takes into account the user's emotional state and personalized notifications that are tailored to each individual user.

[0173] An "information processing device" is a device with electronic functions that receive input information from users and perform processing and analysis.

[0174] "Memory space" refers to digital storage used to store received data so that it can be retrieved when needed.

[0175] "Emotional analysis tools" refer to software or algorithms that analyze a user's emotions from data and evaluate their emotional state.

[0176] The "optimal event time" is the most appropriate date and time for an event, determined by considering user sentiment data and participation likelihood.

[0177] A "generative AI model" is a computer model that uses generative artificial intelligence technology to generate output based on specific inputs.

[0178] A "personalized notification message" is a notification message that is customized to reflect the attributes and status of each individual user.

[0179] An "optimization algorithm" is a computational procedure for deriving the best possible result from given options or data.

[0180] This invention is an information processing system for scheduling and notifying events. It primarily involves three parties: a server, a terminal, and a user, and optimizes events while considering the user's emotional state.

[0181] The server functions as a computer and information processing device. It receives scheduled information and sentiment data sent from users via terminals and stores this data in a database. The server also has sentiment analysis capabilities implemented to analyze the sentiment data obtained from users and select the optimal event date and time based on the results. In this process, it utilizes a generative AI model to generate personalized notification messages for users.

[0182] The terminal is a computer that provides a user interface. The user uses it to input schedule information and provides emotional feedback for each proposed date and time. For example, it can use a slider to select emotional states such as "neutral," "anticipatory," or "stressed." The terminal then sends this data to the server.

[0183] Users use this system to input potential event dates and whether they can attend. They also submit sentiment feedback at the same time, and the server analyzes this information to determine the most suitable date and time.

[0184] As a concrete example, consider scheduling PTA meetings. Users input their available dates using a terminal and evaluate their feelings towards each date and time. This information is sent to a server, where sentiment analysis and optimization algorithms select the optimal meeting date. By inputting information such as "I look forward to the meeting on Monday," the system makes appropriate adjustments.

[0185] Examples of prompt statements are as follows:

[0186] "To schedule the PTA meeting, please indicate your likelihood of attending and your feelings regarding the following possible dates. Friday: Highly optimistic, Saturday: Neutral, Sunday: Highly stressed."

[0187] This invention enables efficient schedule management that takes into account the emotions of users, and is expected to improve overall participation and facilitate communication.

[0188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0189] Step 1:

[0190] The user enters the event date on their device. Specifically, they use a date selection interface to select multiple possible dates. The entered dates are converted to a digital format and temporarily stored on the device.

[0191] Step 2:

[0192] Users rate their emotions for each scheduled date. They use sliders and options displayed on their device to specify emotional states such as "anticipated," "neutral," and "stressed." The emotional ratings are also converted into digital data and saved along with the scheduled information.

[0193] Step 3:

[0194] The device sends the user's entered schedule information and sentiment data to the server. The data is encrypted and transmitted over the network via a secure protocol. The transmitted data is received by the server and stored in a database.

[0195] Step 4:

[0196] The server analyzes the received schedule information and sentiment data. It processes the information retrieved from the database using sentiment analysis tools to quantify each user's emotional tendencies. For example, dates with a high level of expectation are given a higher rating.

[0197] Step 5:

[0198] The server executes an optimization algorithm based on the sentiment analysis results. This algorithm selects the date with the most positive responses based on sentiment evaluation. The algorithm uses sentiment data and candidate date information as input, and the output is the optimal event time.

[0199] Step 6:

[0200] The server uses a generative AI model to create personalized notification messages. It generates notification messages tailored to the selected optimal date and time, with different messages prepared for each user. This process ensures effective information delivery to users.

[0201] Step 7:

[0202] The server sends the generated personalized notification to the device. The device receives the notification and displays it to the user. The user can review the notification on the device and provide feedback or change their schedule as needed.

[0203] This enables optimal event scheduling that takes user emotions into consideration, resulting in highly satisfying schedule management.

[0204] (Application Example 2)

[0205] 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".

[0206] In coordinating events for individuals and communities, optimization is often not performed to take into account participants' feelings and schedules, which can result in decreased motivation to participate. This invention aims to enable event coordination that takes users' feelings into account, thereby improving participant satisfaction and the efficiency of event management.

[0207] 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.

[0208] In this invention, the server includes means for receiving and storing schedule information and sentiment data from users, means for analyzing the stored schedule information and sentiment data to calculate the optimal meeting time, and means for communicating the optimal meeting time to other users. This enables efficient event coordination that takes into account the sentiment of the users.

[0209] An "information processing device" is a computer system that receives data from users and performs processing and analysis.

[0210] "Schedule information" refers to time and date data related to future plans and events entered by the user.

[0211] "Emotional data" refers to data that shows the emotions and feelings that users have towards specific dates or events.

[0212] A "secure data storage location" is a data storage area designed to protect received data from leakage and unauthorized access.

[0213] "Analysis" is an information processing operation that calculates the optimal meeting time for each user based on the received data.

[0214] "Meeting time" refers to the start time or period decided upon for an event or gathering involving multiple users.

[0215] "To communicate" means to use means to transmit information to other users and make them understand it.

[0216] "Emotional analytics" is a technology that analyzes users' emotional data and draws conclusions based on that analysis.

[0217] An "optimization algorithm" is a mathematical method used to derive the most suitable result from among multiple options.

[0218] This application is implemented by the following system: A server receives scheduling information and sentiment data from users via smartphones or other devices to determine the optimal date for a meeting. The collected information is stored in Firebase, a cloud-based secure data storage location.

[0219] The server uses a sentiment engine that performs text sentiment analysis to analyze users' emotional data. The sentiment engine uses Google Cloud's Natural Language API to evaluate the participant's psychological state based on the emotional information extracted from the input text data.

[0220] Subsequently, an optimization algorithm is used to calculate the date that is most convenient for the most users and will elicit the most positive feedback, based on the data stored in Firebase. This calculation includes a predictive model and a feasible optimization plan.

[0221] On the device, a user interface including a user-specified emotion rating slider is built using the Flutter framework, allowing users to intuitively input their emotions when participating in an event. This makes emotional feedback and date selection easier.

[0222] For example, in coordinating a flea market event with citizen participation, users indicate the "dates they might be able to attend" and their "level of expectation" and "level of stress" using sliders. Based on the server's processing of this information, the date determined as the "day with the highest desire to participate" is notified to those who wish to attend.

[0223] A concrete example of a prompt message could be: "Residents, please help us coordinate the dates for this year's flea market. Please select a date you are available to attend and let us know your preference using the slider." This prompt message allows users to easily provide the necessary information, resulting in a more efficient functioning of the entire community.

[0224] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0225] Step 1:

[0226] The device receives the user's selected available dates and sentiment ratings. This input is performed through the user interface, and the device also obtains the user's sentiment data using a sentiment rating slider. The obtained data is sent to the server together as schedule information and sentiment data.

[0227] Step 2:

[0228] The server stores the received schedule and sentiment data in Firebase. This process securely stores the data that will serve as the basis for future analysis and calculations. In the database, each user's information is managed with a unique ID, ensuring efficient access.

[0229] Step 3:

[0230] The server analyzes sentiment data using Google Cloud's Natural Language API. In this step, based on the sentiment information collected from users, the server quantifies and visualizes the user's sentiment for each candidate event date. The analysis results in positive or negative feedback.

[0231] Step 4:

[0232] The server executes an optimization algorithm, combining sentiment ratings and scheduling information to calculate the optimal meeting time. This calculation uses aggregated user data to select the day when participants' happiness levels are maximized.

[0233] Step 5:

[0234] The server notifies eligible users of the calculated optimal meeting time. The notification is sent as a push message to the user's device, allowing them to confirm the determined meeting time. The notification includes a prompt message similar to, "The determined optimal date for the flea market is [Month] [Day]."

[0235] 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.

[0236] 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.

[0237] 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.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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".

[0251] This invention provides a system for streamlining the scheduling of events involving multiple users and for facilitating the smooth sharing of information. This system mainly consists of a server as an information processing device, terminals accessed by users, and the user's own interface.

[0252] The server is responsible for aggregating schedule information sent from each user. Schedule information entered by users via their terminals is stored in a database by the server. Based on this information, the server uses an optimization algorithm to calculate the optimal event time for each user. The calculated optimal date and time are then notified to all users.

[0253] The terminal functions as a means for users to input, confirm, and edit schedule information through an interface. After entering the schedule, the terminal performs the saving and transmission processes, passing the data to the server. It also receives notifications from the server and displays reminders and event change notifications to the user.

[0254] Users can input and modify appointments using their own devices and communicate smoothly with other users. Based on user selections, the final event time is determined, and this information is then notified to all users again.

[0255] As a concrete example, when scheduling a monthly PTA meeting using this system, each member first enters their available dates into a terminal. This information is collected on a server, and a candidate date is calculated through an optimization algorithm. The server notifies all members of the best candidate date, and members select their final attendance status on their terminals. The server compiles this attendance information, determines the final meeting date, and notifies the members. A reminder is automatically sent the day before the meeting, allowing users to prepare efficiently.

[0256] This format allows individual users to schedule activities with minimal burden, enabling the smooth operation of PTA and other organizational activities.

[0257] The following describes the processing flow.

[0258] Step 1:

[0259] The user uses their device to enter possible dates for meetings they can attend. A scheduling form is provided on the device, and the user fills in the information in a timely manner.

[0260] Step 2:

[0261] The terminal checks the entered schedule information, verifies that there are no errors in the input, and then sends the data to the server. If there are errors, a message prompting the user to correct them will be displayed.

[0262] Step 3:

[0263] The server stores the received schedule information in a database. This database serves to store candidate dates and times for each user.

[0264] Step 4:

[0265] The server aggregates all user-submitted candidate dates stored in the database and applies an AI-based optimization algorithm to calculate the meeting date with the highest overall attendance rate.

[0266] Step 5:

[0267] The server generates a notification message with the calculated optimal date and time and sends it to all users.

[0268] Step 6:

[0269] The terminal displays a notification from the server indicating the optimal date and time for participation. The user reviews the notification and chooses whether or not to participate.

[0270] Step 7:

[0271] Based on the notification, the user specifies on their device whether or not they will participate. Once the selection is complete, the device sends that information back to the server.

[0272] Step 8:

[0273] The server compiles responses from all users indicating whether they can participate or not, and determines the final meeting date and time based on the number of available participants.

[0274] Step 9:

[0275] The server creates a message for notifying all users of the determined final meeting date and time, and executes the notification.

[0276] Step 10:

[0277] When the terminal receives the notification of the final decision from the server, it displays the content to the user and automatically adds an event to the calendar.

[0278] Step 11:

[0279] When the meeting date approaches, the server sets a schedule for sending a reminder in advance.

[0280] Step 12:

[0281] The terminal receives the reminder notification and displays a message prompting the user to reconfirm the event.

[0282] (Example 1)

[0283] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0284] In modern society, when adjusting the date and time of an event attended by many users, it is difficult to select the most appropriate date and time according to individual schedules. In particular, when there are a large number of candidate dates and the circumstances of the participants are diverse, manual adjustment requires time and effort. Also, the confirmation and notification of the participants for the determined date and time may be delayed, hindering the smooth holding of the event. For these problems, an efficient and effective solution is required.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0286] In this invention, the server includes means for receiving schedule information from a user and storing the schedule information in a storage area, means for analyzing the schedule information stored in the storage area to determine an optimal event time for each user, and means for notifying other users of the optimal event time. This enables efficient schedule adjustment and smooth event management.

[0287] An "information processing device" is a device for receiving, recording, and analyzing data input by a user.

[0288] A "user" is an individual person or group who may input schedule information using the system and participate in events.

[0289] "Schedule information" is data input by a user regarding the free time or available participation time of an individual user during a specific period.

[0290] A "storage area" is a part of the data storage for storing received data.

[0291] "Analysis" is a processing activity for determining an optimal date and time based on schedule information from a user.

[0292] The "optimal event time" is the date and time selected considering the situations of all users to maximize efficiency and participation rate.

[0293] "Notification" is a communication activity for transmitting the determined information to a user.

[0294] "Participation availability information" is information indicating the availability of a user to participate in a proposed event time.

[0295] The "final event time" is the date and time determined after aggregating all participation availability information.

[0296] A "communication area" is a network environment or communication means used for information exchange.

[0297] "Optimization" refers to the application of calculations and algorithms to select the most appropriate date and time from the proposed candidate dates.

[0298] This invention is a system for efficiently coordinating the dates and times of events involving multiple users and for smoothly sharing information among users. The system mainly consists of a server acting as an information processing device, terminals accessed by users, and the users themselves.

[0299] The server plays the role of aggregating schedule information sent by users. Specifically, it receives schedule information entered by users via their terminals and stores it in data storage. A general-purpose database system can be used for this storage. For example, RDBMS (relational database management systems) such as MySQL or PostgreSQL can be considered as databases.

[0300] Furthermore, the server performs optimization processing based on the stored information. This process uses the Python library Scikit-learn to select the optimal date and time. This allows the server to select the date and time that is most convenient for multiple users to participate. The determined date and time are automatically notified to all users, and the server aggregates the participation status information sent back by the users. Based on this, the final event date and time are determined. The server also has a function to send reminders to users the day before the event, and can send emails using an SMTP server or utilize push notification services.

[0301] The terminal functions as a means for users to access the system and input, confirm, and edit schedule information. Through the terminal's interface, users can select available days in a calendar format and fill in details in the input form. The entered information is sent from the terminal to the server and used for subsequent processing. The terminal also receives notifications from the server and informs the user via pop-up notifications or screen displays.

[0302] The user can input their schedule using a terminal and communicate efficiently with other users. For example, in scheduling a PTA meeting, the user inputs the available days into the terminal. This information is aggregated on the server, and the calculated optimal day is proposed to all users. For the proposed schedule, the user selects whether to participate or not using the terminal, and the final meeting schedule is determined. On the day before the meeting, an automatic reminder is sent to the user's terminal, so the user can promptly proceed with preparations.

[0303] As a specific example, an example of a prompt sentence for a generative AI model is "I want to schedule a PTA meeting. Please tell me the available days next week." With this prompt, the AI assists the user in inputting their schedule and realizes efficient scheduling.

[0304] The flow of the specific process in Example 1 will be described using FIG. 11.

[0305] Step 1:

[0306] The user opens the schedule input page by accessing the interface through their terminal. On the calendar-formatted screen, the user selects the available dates and enters detailed information such as time slots. Entering "Please tell me the available days next week" as the prompt sentence, this information is aggregated and sent from the terminal as structured data in a format such as JSON.

[0307] Step 2:

[0308] The terminal sends the input schedule information to the server. At this time, the terminal converts the data into a specific format (e.g., JSON format) and executes the transmission via the communication area. When the information transmission to the server is completed, a notification indicating that the process was successful is displayed on the terminal.

[0309] Step 3:

[0310] The server receives schedule information sent from the terminal and stores it in its storage. Based on this information, the server checks the schedules of all users and stores it in the database. During the saving process, the server checks the accuracy of the data and removes any inconsistent data.

[0311] Step 4:

[0312] The server analyzes the data stored in its memory and begins the optimization process. This analysis uses a generative AI model and optimization algorithms to calculate the optimal event date and time for all users. The algorithm clusters multidimensional data and selects candidate dates that are most likely to be attended. The results of this calculation are stored on the server as internal data.

[0313] Step 5:

[0314] The server generates a notification message with the calculated optimal event date and time and notifies all users. The notification is sent via email or push notification, and a record of the transmission is saved in the log. The server verifies that the notification was successfully delivered to each user.

[0315] Step 6:

[0316] The user receives a notification from the server and checks it on their device. A screen for selecting whether to participate or not appears on the device, and the user selects "Participate" or "Do not participate." Once the selection is confirmed, that information is sent back from the device to the server.

[0317] Step 7:

[0318] The server aggregates the attendance confirmation information submitted by users. This aggregation ultimately determines the event date and time that will ensure the optimal number of participants. The determined date and time are then notified to all users again as a reminder and registered as the final date.

[0319] Step 8:

[0320] The user receives a reminder notification sent from the server and confirms it on the notification screen on their device. By using the prompt message, "I would like to schedule a PTA meeting. Please let me know which days you are available next week," the user can quickly proceed with preparations.

[0321] (Application Example 1)

[0322] 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."

[0323] When coordinating group activities or events involving multiple participants, scheduling can become inefficient. This is especially true for community activities with many participants, where checking everyone's schedules and determining the optimal date is difficult. This challenge can lead to poor communication among participants, resulting in delays or inefficiencies in community activities.

[0324] 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.

[0325] In this invention, the server includes means for an information processing device to receive schedule information from a user and store the schedule information in a storage device, means for analyzing the schedule information stored in the storage device to determine the optimal activity time for each participant, and means for notifying other users of the optimal activity time. This makes it possible to quickly and effectively coordinate the optimal schedule for activities among multiple participants.

[0326] An "information processing device" is a device that has the function of receiving, storing, analyzing, and notifying users of data.

[0327] "User" refers to a person who provides schedule information to an information processing device and receives notification of the result.

[0328] "Schedule information" refers to data that indicates the dates on which a user is available to participate in a specific activity or event.

[0329] A "storage device" is a storage medium used by an information processing device to store scheduled information.

[0330] "Analysis" is the process of evaluating data based on collected schedule information and calculating the optimal activity time.

[0331] An "optimization calculation method" is an algorithm used to derive the optimal result that satisfies multiple conditions.

[0332] "Activity time" refers to the date and time of an activity or event, which is determined considering the participants' schedules.

[0333] "Collective activity coordination" is the process of efficiently combining schedules and plans for activities and events involving multiple participants.

[0334] To realize this system, servers responsible for information processing play a central role. These servers are located on cloud-based platforms such as AWS and Google Cloud, efficiently receiving scheduling information from users and storing it in storage devices. This allows the servers to manage large amounts of data while achieving a secure and scalable configuration.

[0335] The server uses programs implemented in programming languages ​​such as Python and Node.js to analyze the stored schedule information. These programs retrieve data from databases such as MongoDB and MySQL and use optimization calculation methods to determine the optimal activity times for each participant. Through such data calculations, a balanced activity schedule is created for all participants.

[0336] The analysis results are notified to the user's device in real time. The system is developed using React Native and Flutter for cross-platform compatibility, allowing it to be used on various devices such as smartphones and personal computers. This ensures users enjoy convenience while maintaining a consistent user experience across different devices.

[0337] Another concrete example is how this system facilitates smooth scheduling for local residents participating in meetings organized by the local government. Residents can enter their available dates and times into the application, and the system will then suggest the most suitable schedule, allowing activities to proceed smoothly.

[0338] Examples of prompts for a generative AI model include: "I want to design a system that efficiently aggregates the schedules of multiple participants and calculates the optimal meeting time. This system also needs real-time notification and reminder sending capabilities. How should the program be structured?"

[0339] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0340] Step 1:

[0341] The user opens the app on their smartphone and enters their available dates. The input data is converted to the appropriate format by the device and sent to the server. This allows the server to receive the user's available dates.

[0342] Step 2:

[0343] The server retrieves the received schedule information and stores it in the database. During this process, the format is standardized to ensure that the entered information is stored correctly, free from duplicates and errors. This process centralizes the management of schedule information in the database.

[0344] Step 3:

[0345] The server retrieves schedule information for all participants from the database and begins analysis using an optimization calculation method. Here, a Python-based algorithm is used to derive the optimal activity time. By comparing multiple candidate dates and times, the most convenient time for all participants is selected.

[0346] Step 4:

[0347] Once the optimal activity time is determined, the server notifies each participant's device of the result. The output is in real time, and users can check the results on their own devices. The notification includes important schedules for the next activity and information on how to prepare for the activity.

[0348] Step 5:

[0349] The user receives a notification, decides whether or not they can participate in the optimal activity time, and sends feedback to the server via their device. Here, the user reviews the details and makes an input to choose whether or not to participate.

[0350] Step 6:

[0351] The server collects participation confirmation information from users and determines the final activity time. Using an aggregation algorithm, it makes adjustments based on participant feedback to determine the time when the most participants can gather.

[0352] Step 7:

[0353] The server will re-notify all participants of the final confirmed activity time. This final notification, accompanied by a reminder function, is automatically sent before the activity date. The system makes it easier for participants to prepare for the activity.

[0354] 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.

[0355] This invention provides a system that streamlines event scheduling and enables more personalized notifications and decision-making by taking user emotions into consideration. The system includes a server as an information processing device, a terminal providing a user interface, and the user themselves. Furthermore, an emotion engine that analyzes user emotions is integrated.

[0356] The server aggregates and analyzes scheduling information and utilizes emotional data obtained by the emotion engine. For example, when a user enters potential meeting dates, the server stores the information in the database and uses the emotion engine to evaluate each user's emotional state. Based on this evaluation, the optimal date and time are selected, and notifications are adjusted accordingly.

[0357] The device allows users to input schedule information and provide emotional feedback through the user interface. When a user enters a schedule or receives a notification, the device collects the user's emotional data. This data is then sent to a server to help optimize notification methods.

[0358] Users can use their devices to input meeting schedules and communicate their feelings and feedback during those meetings. For example, a user's emotions such as stress or anticipation for a specific date and time are recorded and sent to a server, where they can be shared with other users.

[0359] As a concrete example, consider scheduling a PTA meeting. The user enters their available dates on their device and indicates their feelings about those dates using a simple slider or rating. This information is sent to the server. The server analyzes multiple candidate dates and the user's emotional state to determine the optimal meeting date. If there is a lot of positive feedback for a particular meeting date, that date and time will be given high priority and notified; if there is negative feedback, alternative dates can be suggested.

[0360] This format allows for adjustments that take into account the emotional state of the users, which is expected to facilitate smoother communication and improve satisfaction. As a result, it promotes increased overall participation and smoother operation in group meetings such as those of PTAs.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] Users use their devices to enter possible meeting dates. They also use a slider to indicate their feelings about those dates as emotional feedback.

[0364] Step 2:

[0365] The terminal verifies the format of the entered schedule information and sentiment feedback before sending it to the server, ensuring data integrity.

[0366] Step 3:

[0367] The server stores the received schedule information and emotional feedback in a database. The stored emotional data is then incorporated into the optimization algorithm.

[0368] Step 4:

[0369] The server uses an algorithm to analyze candidate date data and sentiment feedback collected from all users to calculate the meeting date that will generate the highest level of participation.

[0370] Step 5:

[0371] The server prepares the calculated optimal date and time as an emotionally sensitive message and notifies the user.

[0372] Step 6:

[0373] The terminal receives notifications from the server and displays them to the user. The user can then make a final decision on whether or not to participate in the event at the notified date and time.

[0374] Step 7:

[0375] The device resends the user's participation status information to the server. The transmitted data also includes re-evaluated sentiment feedback.

[0376] Step 8:

[0377] The server compiles the final attendance confirmation information, re-evaluates participation intentions, and then determines the final meeting date and time.

[0378] Step 9:

[0379] The server notifies all users of the finalized meeting date and time, and automatically updates their calendars.

[0380] Step 10:

[0381] The server schedules to send reminders at the optimal time, using an emotion engine, a few days before the meeting.

[0382] Step 11:

[0383] The device receives a reminder notification and displays it to the user to prompt them to prepare for the meeting.

[0384] (Example 2)

[0385] 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".

[0386] Traditional scheduling management systems fail to consider users' emotional states, leading to decreased user satisfaction during scheduling. Furthermore, they lack effective means of utilizing individual user emotional feedback when selecting the optimal date and time from multiple options. Additionally, notifications are delivered in a generic format, resulting in a lack of personalization for individual users.

[0387] 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.

[0388] In this invention, the server includes means for receiving schedule information from users and storing it in a memory area, means for evaluating each user's emotional state using sentiment analysis, and means for generating personalized notification text using a generative AI model. This enables optimal event adjustment that takes into account the user's emotional state and personalized notifications that are tailored to each individual user.

[0389] An "information processing device" is a device with electronic functions that receive input information from users and perform processing and analysis.

[0390] "Memory space" refers to digital storage used to store received data so that it can be retrieved when needed.

[0391] "Emotional analysis tools" refer to software or algorithms that analyze a user's emotions from data and evaluate their emotional state.

[0392] The "optimal event time" is the most appropriate date and time for an event, determined by considering user sentiment data and participation likelihood.

[0393] A "generative AI model" is a computer model that uses generative artificial intelligence technology to generate output based on specific inputs.

[0394] A "personalized notification message" is a notification message that is customized to reflect the attributes and status of each individual user.

[0395] An "optimization algorithm" is a computational procedure for deriving the best possible result from given options or data.

[0396] This invention is an information processing system for scheduling and notifying events. It primarily involves three parties: a server, a terminal, and a user, and optimizes events while considering the user's emotional state.

[0397] The server functions as a computer and information processing device. It receives scheduled information and sentiment data sent from users via terminals and stores this data in a database. The server also has sentiment analysis capabilities implemented to analyze the sentiment data obtained from users and select the optimal event date and time based on the results. In this process, it utilizes a generative AI model to generate personalized notification messages for users.

[0398] The terminal is a computer that provides a user interface. The user uses it to input schedule information and provides emotional feedback for each proposed date and time. For example, it can use a slider to select emotional states such as "neutral," "anticipatory," or "stressed." The terminal then sends this data to the server.

[0399] Users use this system to input potential event dates and whether they can attend. They also submit sentiment feedback at the same time, and the server analyzes this information to determine the most suitable date and time.

[0400] As a concrete example, consider scheduling PTA meetings. Users input their available dates using a terminal and evaluate their feelings towards each date and time. This information is sent to a server, where sentiment analysis and optimization algorithms select the optimal meeting date. By inputting information such as "I look forward to the meeting on Monday," the system makes appropriate adjustments.

[0401] Examples of prompt statements are as follows:

[0402] "To schedule the PTA meeting, please indicate your likelihood of attending and your feelings regarding the following possible dates. Friday: Highly optimistic, Saturday: Neutral, Sunday: Highly stressed."

[0403] This invention enables efficient schedule management that takes into account the emotions of users, and is expected to improve overall participation and facilitate communication.

[0404] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0405] Step 1:

[0406] The user enters the event date on their device. Specifically, they use a date selection interface to select multiple possible dates. The entered dates are converted to a digital format and temporarily stored on the device.

[0407] Step 2:

[0408] Users rate their emotions for each scheduled date. They use sliders and options displayed on their device to specify emotional states such as "anticipated," "neutral," and "stressed." The emotional ratings are also converted into digital data and saved along with the scheduled information.

[0409] Step 3:

[0410] The device sends the user's entered schedule information and sentiment data to the server. The data is encrypted and transmitted over the network via a secure protocol. The transmitted data is received by the server and stored in a database.

[0411] Step 4:

[0412] The server analyzes the received schedule information and sentiment data. It processes the information retrieved from the database using sentiment analysis tools to quantify each user's emotional tendencies. For example, dates with a high level of expectation are given a higher rating.

[0413] Step 5:

[0414] The server executes an optimization algorithm based on the sentiment analysis results. This algorithm selects the date with the most positive responses based on sentiment evaluation. The algorithm uses sentiment data and candidate date information as input, and the output is the optimal event time.

[0415] Step 6:

[0416] The server uses a generative AI model to create personalized notification messages. It generates notification messages tailored to the selected optimal date and time, with different messages prepared for each user. This process ensures effective information delivery to users.

[0417] Step 7:

[0418] The server sends the generated personalized notification to the device. The device receives the notification and displays it to the user. The user can review the notification on the device and provide feedback or change their schedule as needed.

[0419] This enables optimal event scheduling that takes user emotions into consideration, resulting in highly satisfying schedule management.

[0420] (Application Example 2)

[0421] 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."

[0422] In coordinating events for individuals and communities, optimization is often not performed to take into account participants' feelings and schedules, which can result in decreased motivation to participate. This invention aims to enable event coordination that takes users' feelings into account, thereby improving participant satisfaction and the efficiency of event management.

[0423] 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.

[0424] In this invention, the server includes means for receiving and storing schedule information and sentiment data from users, means for analyzing the stored schedule information and sentiment data to calculate the optimal meeting time, and means for communicating the optimal meeting time to other users. This enables efficient event coordination that takes into account the sentiment of the users.

[0425] An "information processing device" is a computer system that receives data from users and performs processing and analysis.

[0426] "Schedule information" refers to time and date data related to future plans and events entered by the user.

[0427] "Emotional data" refers to data that shows the emotions and feelings that users have towards specific dates or events.

[0428] A "secure data storage location" is a data storage area designed to protect received data from leakage and unauthorized access.

[0429] "Analysis" is an information processing operation that calculates the optimal meeting time for each user based on the received data.

[0430] "Meeting time" refers to the start time or period decided upon for an event or gathering involving multiple users.

[0431] "To communicate" means to use means to transmit information to other users and make them understand it.

[0432] "Emotional analytics" is a technology that analyzes users' emotional data and draws conclusions based on that analysis.

[0433] An "optimization algorithm" is a mathematical method used to derive the most suitable result from among multiple options.

[0434] This application is implemented by the following system: A server receives scheduling information and sentiment data from users via smartphones or other devices to determine the optimal date for a meeting. The collected information is stored in Firebase, a cloud-based secure data storage location.

[0435] The server uses a sentiment engine that performs text sentiment analysis to analyze users' emotional data. The sentiment engine uses Google Cloud's Natural Language API to evaluate the participant's psychological state based on the emotional information extracted from the input text data.

[0436] Subsequently, an optimization algorithm is used to calculate the date that is most convenient for the most users and will elicit the most positive feedback, based on the data stored in Firebase. This calculation includes a predictive model and a feasible optimization plan.

[0437] On the device, a user interface including a user-specified emotion rating slider is built using the Flutter framework, allowing users to intuitively input their emotions when participating in an event. This makes emotional feedback and date selection easier.

[0438] For example, in coordinating a flea market event with citizen participation, users indicate the "dates they might be able to attend" and their "level of expectation" and "level of stress" using sliders. Based on the server's processing of this information, the date determined as the "day with the highest desire to participate" is notified to those who wish to attend.

[0439] A concrete example of a prompt message could be: "Residents, please help us coordinate the dates for this year's flea market. Please select a date you are available to attend and let us know your preference using the slider." This prompt message allows users to easily provide the necessary information, resulting in a more efficient functioning of the entire community.

[0440] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0441] Step 1:

[0442] The device receives the user's selected available dates and sentiment ratings. This input is performed through the user interface, and the device also obtains the user's sentiment data using a sentiment rating slider. The obtained data is sent to the server together as schedule information and sentiment data.

[0443] Step 2:

[0444] The server stores the received schedule and sentiment data in Firebase. This process securely stores the data that will serve as the basis for future analysis and calculations. In the database, each user's information is managed with a unique ID, ensuring efficient access.

[0445] Step 3:

[0446] The server analyzes sentiment data using Google Cloud's Natural Language API. In this step, based on the sentiment information collected from users, the server quantifies and visualizes the user's sentiment for each candidate event date. The analysis results in positive or negative feedback.

[0447] Step 4:

[0448] The server executes an optimization algorithm, combining sentiment ratings and scheduling information to calculate the optimal meeting time. This calculation uses aggregated user data to select the day when participants' happiness levels are maximized.

[0449] Step 5:

[0450] The server notifies eligible users of the calculated optimal meeting time. The notification is sent as a push message to the user's device, allowing them to confirm the determined meeting time. The notification includes a prompt message similar to, "The determined optimal date for the flea market is [Month] [Day]."

[0451] 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.

[0452] 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.

[0453] 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.

[0454] [Third Embodiment]

[0455] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0456] 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.

[0457] 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).

[0458] 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.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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".

[0467] This invention provides a system for streamlining the scheduling of events involving multiple users and for facilitating the smooth sharing of information. This system mainly consists of a server as an information processing device, terminals accessed by users, and the user's own interface.

[0468] The server is responsible for aggregating schedule information sent from each user. Schedule information entered by users via their terminals is stored in a database by the server. Based on this information, the server uses an optimization algorithm to calculate the optimal event time for each user. The calculated optimal date and time are then notified to all users.

[0469] The terminal functions as a means for users to input, confirm, and edit schedule information through an interface. After entering the schedule, the terminal performs the saving and transmission processes, passing the data to the server. It also receives notifications from the server and displays reminders and event change notifications to the user.

[0470] Users can input and modify appointments using their own devices and communicate smoothly with other users. Based on user selections, the final event time is determined, and this information is then notified to all users again.

[0471] As a concrete example, when scheduling a monthly PTA meeting using this system, each member first enters their available dates into a terminal. This information is collected on a server, and a candidate date is calculated through an optimization algorithm. The server notifies all members of the best candidate date, and members select their final attendance status on their terminals. The server compiles this attendance information, determines the final meeting date, and notifies the members. A reminder is automatically sent the day before the meeting, allowing users to prepare efficiently.

[0472] This format allows individual users to schedule activities with minimal burden, enabling the smooth operation of PTA and other organizational activities.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The user uses their device to enter possible dates for meetings they can attend. A scheduling form is provided on the device, and the user fills in the information in a timely manner.

[0476] Step 2:

[0477] The terminal checks the entered schedule information, verifies that there are no errors in the input, and then sends the data to the server. If there are errors, a message prompting the user to correct them will be displayed.

[0478] Step 3:

[0479] The server stores the received schedule information in a database. This database serves to store candidate dates and times for each user.

[0480] Step 4:

[0481] The server aggregates all user-submitted candidate dates stored in the database and applies an AI-based optimization algorithm to calculate the meeting date with the highest overall attendance rate.

[0482] Step 5:

[0483] The server generates a notification message with the calculated optimal date and time and sends it to all users.

[0484] Step 6:

[0485] The terminal displays a notification from the server indicating the optimal date and time for participation. The user reviews the notification and chooses whether or not to participate.

[0486] Step 7:

[0487] Based on the notification, the user specifies on their device whether or not they will participate. Once the selection is complete, the device sends that information back to the server.

[0488] Step 8:

[0489] The server compiles responses from all users indicating whether they can participate or not, and determines the final meeting date and time based on the number of available participants.

[0490] Step 9:

[0491] The server creates a message to notify all users of the final meeting date and time, and then executes the notification.

[0492] Step 10:

[0493] When the device receives notification of the final decision from the server, it displays the details to the user and automatically adds the event to the calendar.

[0494] Step 11:

[0495] The server sets a schedule to send reminders in advance as the meeting date approaches.

[0496] Step 12:

[0497] The device receives a reminder notification and displays a message prompting the user to reconfirm the event.

[0498] (Example 1)

[0499] 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."

[0500] In modern society, coordinating the date and time of events involving many participants is difficult, as it requires selecting the most appropriate date and time to accommodate individual schedules. This is especially true when there are numerous possible dates and participants have diverse availability; manual coordination is time-consuming and laborious. Furthermore, delays in confirming and notifying participants of the chosen date and time can hinder the smooth running of the event. Efficient and effective solutions are needed to address these challenges.

[0501] 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.

[0502] In this invention, the server includes means for receiving schedule information from users and storing the schedule information in a storage area, means for analyzing the schedule information stored in the storage area and determining the optimal event time for each user, and means for notifying other users of the optimal event time. This enables efficient scheduling and smooth event management.

[0503] An "information processing device" is a device that receives, records, and analyzes data entered by a user.

[0504] A "user" is an individual or group that may use the system to input schedule information and potentially participate in an event.

[0505] "Schedule information" refers to data entered by users regarding their available time and participation time during a specific period.

[0506] "Memory area" refers to a part of data storage used to store received data.

[0507] "Analysis" refers to the processing activity of determining the optimal date and time based on the schedule information provided by the user.

[0508] The "optimal event time" is the date and time chosen to maximize efficiency and participation, taking into account the circumstances of all users.

[0509] "Notification" refers to communication activities aimed at conveying decided information to users.

[0510] "Participation status information" refers to information indicating whether a user is able to participate in the proposed event at the suggested time.

[0511] The "final event time" refers to the date and time after all participation confirmation information has been compiled and finalized.

[0512] A "communication domain" refers to the network environment or means of communication used when exchanging information.

[0513] "Optimization" refers to the application of calculations and algorithms to select the most appropriate date and time from the proposed candidate dates.

[0514] This invention is a system for efficiently coordinating the dates and times of events involving multiple users and for smoothly sharing information among users. The system mainly consists of a server acting as an information processing device, terminals accessed by users, and the users themselves.

[0515] The server plays the role of aggregating schedule information sent by users. Specifically, it receives schedule information entered by users via their terminals and stores it in data storage. A general-purpose database system can be used for this storage. For example, RDBMS (relational database management systems) such as MySQL or PostgreSQL can be considered as databases.

[0516] Furthermore, the server performs optimization processing based on the stored information. This process uses the Python library Scikit-learn to select the optimal date and time. This allows the server to select the date and time that is most convenient for multiple users to participate. The determined date and time are automatically notified to all users, and the server aggregates the participation status information sent back by the users. Based on this, the final event date and time are determined. The server also has a function to send reminders to users the day before the event, and can send emails using an SMTP server or utilize push notification services.

[0517] The terminal functions as a means for users to access the system and input, confirm, and edit schedule information. Through the terminal's interface, users can select available days in a calendar format and fill in details in the input form. The entered information is sent from the terminal to the server and used for subsequent processing. The terminal also receives notifications from the server and informs the user via pop-up notifications or screen displays.

[0518] Users can input their schedules using their devices and communicate efficiently with other users. For example, when scheduling a PTA meeting, users input the days they are available into their devices. This information is collected on the server, and the optimal date is calculated and suggested to all users. Users then select whether they will attend or not using their devices, and the final meeting date is determined. An automatic reminder is sent to the user's device the day before the meeting, allowing them to prepare promptly.

[0519] As a concrete example, an example of a prompt message to the generating AI model is, "I would like to schedule a PTA meeting. Please let me know which days you are available next week." This prompt allows the AI ​​to assist the user in entering their schedule, enabling efficient scheduling.

[0520] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0521] Step 1:

[0522] The user accesses the interface through their device to open the schedule entry page. On the calendar-style screen, they select available dates and enter details such as time slots. They enter a prompt message such as "Please tell me which days you are available next week," and this information is collected and sent from their device as structured data in JSON format or similar.

[0523] Step 2:

[0524] The terminal sends the entered schedule information to the server. During this process, the terminal converts the data into a specific format (e.g., JSON format) and transmits it via the communication area. Once the information transmission to the server is complete, a notification indicating the success of the process is displayed on the terminal.

[0525] Step 3:

[0526] The server receives schedule information sent from the terminal and stores it in its storage. Based on this information, the server checks the schedules of all users and stores it in the database. During the saving process, the server checks the accuracy of the data and removes any inconsistent data.

[0527] Step 4:

[0528] The server analyzes the data stored in its memory and begins the optimization process. This analysis uses a generative AI model and optimization algorithms to calculate the optimal event date and time for all users. The algorithm clusters multidimensional data and selects candidate dates that are most likely to be attended. The results of this calculation are stored on the server as internal data.

[0529] Step 5:

[0530] The server generates a notification message with the calculated optimal event date and time and notifies all users. The notification is sent via email or push notification, and a record of the transmission is saved in the log. The server verifies that the notification was successfully delivered to each user.

[0531] Step 6:

[0532] The user receives a notification from the server and checks it on their device. A screen for selecting whether to participate or not appears on the device, and the user selects "Participate" or "Do not participate." Once the selection is confirmed, that information is sent back from the device to the server.

[0533] Step 7:

[0534] The server aggregates the attendance confirmation information submitted by users. This aggregation ultimately determines the event date and time that will ensure the optimal number of participants. The determined date and time are then notified to all users again as a reminder and registered as the final date.

[0535] Step 8:

[0536] The user receives a reminder notification sent from the server and confirms it on the notification screen on their device. By using the prompt message, "I would like to schedule a PTA meeting. Please let me know which days you are available next week," the user can quickly proceed with preparations.

[0537] (Application Example 1)

[0538] 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."

[0539] When coordinating group activities or events involving multiple participants, scheduling can become inefficient. This is especially true for community activities with many participants, where checking everyone's schedules and determining the optimal date is difficult. This challenge can lead to poor communication among participants, resulting in delays or inefficiencies in community activities.

[0540] 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.

[0541] In this invention, the server includes means for an information processing device to receive schedule information from a user and store the schedule information in a storage device, means for analyzing the schedule information stored in the storage device to determine the optimal activity time for each participant, and means for notifying other users of the optimal activity time. This makes it possible to quickly and effectively coordinate the optimal schedule for activities among multiple participants.

[0542] An "information processing device" is a device that has the function of receiving, storing, analyzing, and notifying users of data.

[0543] "User" refers to a person who provides schedule information to an information processing device and receives notification of the result.

[0544] "Schedule information" refers to data that indicates the dates on which a user is available to participate in a specific activity or event.

[0545] A "storage device" is a storage medium used by an information processing device to store scheduled information.

[0546] "Analysis" is the process of evaluating data based on collected schedule information and calculating the optimal activity time.

[0547] An "optimization calculation method" is an algorithm used to derive the optimal result that satisfies multiple conditions.

[0548] "Activity time" refers to the date and time of an activity or event, which is determined considering the participants' schedules.

[0549] "Collective activity coordination" is the process of efficiently combining schedules and plans for activities and events involving multiple participants.

[0550] To realize this system, servers responsible for information processing play a central role. These servers are located on cloud-based platforms such as AWS and Google Cloud, efficiently receiving scheduling information from users and storing it in storage devices. This allows the servers to manage large amounts of data while achieving a secure and scalable configuration.

[0551] The server uses programs implemented in programming languages ​​such as Python and Node.js to analyze the stored schedule information. These programs retrieve data from databases such as MongoDB and MySQL and use optimization calculation methods to determine the optimal activity times for each participant. Through such data calculations, a balanced activity schedule is created for all participants.

[0552] The analysis results are notified to the user's device in real time. The system is developed using React Native and Flutter for cross-platform compatibility, allowing it to be used on various devices such as smartphones and personal computers. This ensures users enjoy convenience while maintaining a consistent user experience across different devices.

[0553] Another concrete example is how this system facilitates smooth scheduling for local residents participating in meetings organized by the local government. Residents can enter their available dates and times into the application, and the system will then suggest the most suitable schedule, allowing activities to proceed smoothly.

[0554] Examples of prompts for a generative AI model include: "I want to design a system that efficiently aggregates the schedules of multiple participants and calculates the optimal meeting time. This system also needs real-time notification and reminder sending capabilities. How should the program be structured?"

[0555] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0556] Step 1:

[0557] The user opens the app on their smartphone and enters their available dates. The input data is converted to the appropriate format by the device and sent to the server. This allows the server to receive the user's available dates.

[0558] Step 2:

[0559] The server retrieves the received schedule information and stores it in the database. During this process, the format is standardized to ensure that the entered information is stored correctly, free from duplicates and errors. This process centralizes the management of schedule information in the database.

[0560] Step 3:

[0561] The server retrieves schedule information for all participants from the database and begins analysis using an optimization calculation method. Here, a Python-based algorithm is used to derive the optimal activity time. By comparing multiple candidate dates and times, the most convenient time for all participants is selected.

[0562] Step 4:

[0563] Once the optimal activity time is determined, the server notifies each participant's device of the result. The output is in real time, and users can check the results on their own devices. The notification includes important schedules for the next activity and information on how to prepare for the activity.

[0564] Step 5:

[0565] The user receives a notification, decides whether or not they can participate in the optimal activity time, and sends feedback to the server via their device. Here, the user reviews the details and makes an input to choose whether or not to participate.

[0566] Step 6:

[0567] The server collects participation confirmation information from users and determines the final activity time. Using an aggregation algorithm, it makes adjustments based on participant feedback to determine the time when the most participants can gather.

[0568] Step 7:

[0569] The server will re-notify all participants of the final confirmed activity time. This final notification, accompanied by a reminder function, is automatically sent before the activity date. The system makes it easier for participants to prepare for the activity.

[0570] 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.

[0571] This invention provides a system that streamlines event scheduling and enables more personalized notifications and decision-making by taking user emotions into consideration. The system includes a server as an information processing device, a terminal providing a user interface, and the user themselves. Furthermore, an emotion engine that analyzes user emotions is integrated.

[0572] The server aggregates and analyzes scheduling information and utilizes emotional data obtained by the emotion engine. For example, when a user enters potential meeting dates, the server stores the information in the database and uses the emotion engine to evaluate each user's emotional state. Based on this evaluation, the optimal date and time are selected, and notifications are adjusted accordingly.

[0573] The device allows users to input schedule information and provide emotional feedback through the user interface. When a user enters a schedule or receives a notification, the device collects the user's emotional data. This data is then sent to a server to help optimize notification methods.

[0574] Users can use their devices to input meeting schedules and communicate their feelings and feedback during those meetings. For example, a user's emotions such as stress or anticipation for a specific date and time are recorded and sent to a server, where they can be shared with other users.

[0575] As a concrete example, consider scheduling a PTA meeting. The user enters their available dates on their device and indicates their feelings about those dates using a simple slider or rating. This information is sent to the server. The server analyzes multiple candidate dates and the user's emotional state to determine the optimal meeting date. If there is a lot of positive feedback for a particular meeting date, that date and time will be given high priority and notified; if there is negative feedback, alternative dates can be suggested.

[0576] This format allows for adjustments that take into account the emotional state of the users, which is expected to facilitate smoother communication and improve satisfaction. As a result, it promotes increased overall participation and smoother operation in group meetings such as those of PTAs.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] Users use their devices to enter possible meeting dates. They also use a slider to indicate their feelings about those dates as emotional feedback.

[0580] Step 2:

[0581] The terminal verifies the format of the entered schedule information and sentiment feedback before sending it to the server, ensuring data integrity.

[0582] Step 3:

[0583] The server stores the received schedule information and emotional feedback in a database. The stored emotional data is then incorporated into the optimization algorithm.

[0584] Step 4:

[0585] The server uses an algorithm to analyze candidate date data and sentiment feedback collected from all users to calculate the meeting date that will generate the highest level of participation.

[0586] Step 5:

[0587] The server prepares the calculated optimal date and time as an emotionally sensitive message and notifies the user.

[0588] Step 6:

[0589] The terminal receives notifications from the server and displays them to the user. The user can then make a final decision on whether or not to participate in the event at the notified date and time.

[0590] Step 7:

[0591] The device resends the user's participation status information to the server. The transmitted data also includes re-evaluated sentiment feedback.

[0592] Step 8:

[0593] The server compiles the final attendance confirmation information, re-evaluates participation intentions, and then determines the final meeting date and time.

[0594] Step 9:

[0595] The server notifies all users of the finalized meeting date and time, and automatically updates their calendars.

[0596] Step 10:

[0597] The server schedules to send reminders at the optimal time, using an emotion engine, a few days before the meeting.

[0598] Step 11:

[0599] The device receives a reminder notification and displays it to the user to prompt them to prepare for the meeting.

[0600] (Example 2)

[0601] 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."

[0602] Traditional scheduling management systems fail to consider users' emotional states, leading to decreased user satisfaction during scheduling. Furthermore, they lack effective means of utilizing individual user emotional feedback when selecting the optimal date and time from multiple options. Additionally, notifications are delivered in a generic format, resulting in a lack of personalization for individual users.

[0603] 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.

[0604] In this invention, the server includes means for receiving schedule information from users and storing it in a memory area, means for evaluating each user's emotional state using sentiment analysis, and means for generating personalized notification text using a generative AI model. This enables optimal event adjustment that takes into account the user's emotional state and personalized notifications that are tailored to each individual user.

[0605] An "information processing device" is a device with electronic functions that receive input information from users and perform processing and analysis.

[0606] "Memory space" refers to digital storage used to store received data so that it can be retrieved when needed.

[0607] "Emotional analysis tools" refer to software or algorithms that analyze a user's emotions from data and evaluate their emotional state.

[0608] The "optimal event time" is the most appropriate date and time for an event, determined by considering user sentiment data and participation likelihood.

[0609] A "generative AI model" is a computer model that uses generative artificial intelligence technology to generate output based on specific inputs.

[0610] A "personalized notification message" is a notification message that is customized to reflect the attributes and status of each individual user.

[0611] An "optimization algorithm" is a computational procedure for deriving the best possible result from given options or data.

[0612] This invention is an information processing system for scheduling and notifying events. It primarily involves three parties: a server, a terminal, and a user, and optimizes events while considering the user's emotional state.

[0613] The server functions as a computer and information processing device. It receives scheduled information and sentiment data sent from users via terminals and stores this data in a database. The server also has sentiment analysis capabilities implemented to analyze the sentiment data obtained from users and select the optimal event date and time based on the results. In this process, it utilizes a generative AI model to generate personalized notification messages for users.

[0614] The terminal is a computer that provides a user interface. The user uses it to input schedule information and provides emotional feedback for each proposed date and time. For example, it can use a slider to select emotional states such as "neutral," "anticipatory," or "stressed." The terminal then sends this data to the server.

[0615] Users use this system to input potential event dates and whether they can attend. They also submit sentiment feedback at the same time, and the server analyzes this information to determine the most suitable date and time.

[0616] As a concrete example, consider scheduling PTA meetings. Users input their available dates using a terminal and evaluate their feelings towards each date and time. This information is sent to a server, where sentiment analysis and optimization algorithms select the optimal meeting date. By inputting information such as "I look forward to the meeting on Monday," the system makes appropriate adjustments.

[0617] Examples of prompt statements are as follows:

[0618] "To schedule the PTA meeting, please indicate your likelihood of attending and your feelings regarding the following possible dates. Friday: Highly optimistic, Saturday: Neutral, Sunday: Highly stressed."

[0619] This invention enables efficient schedule management that takes into account the emotions of users, and is expected to improve overall participation and facilitate communication.

[0620] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0621] Step 1:

[0622] The user enters the event date on their device. Specifically, they use a date selection interface to select multiple possible dates. The entered dates are converted to a digital format and temporarily stored on the device.

[0623] Step 2:

[0624] Users rate their emotions for each scheduled date. They use sliders and options displayed on their device to specify emotional states such as "anticipated," "neutral," and "stressed." The emotional ratings are also converted into digital data and saved along with the scheduled information.

[0625] Step 3:

[0626] The device sends the user's entered schedule information and sentiment data to the server. The data is encrypted and transmitted over the network via a secure protocol. The transmitted data is received by the server and stored in a database.

[0627] Step 4:

[0628] The server analyzes the received schedule information and sentiment data. It processes the information retrieved from the database using sentiment analysis tools to quantify each user's emotional tendencies. For example, dates with a high level of expectation are given a higher rating.

[0629] Step 5:

[0630] The server executes an optimization algorithm based on the sentiment analysis results. This algorithm selects the date with the most positive responses based on sentiment evaluation. The algorithm uses sentiment data and candidate date information as input, and the output is the optimal event time.

[0631] Step 6:

[0632] The server uses a generative AI model to create personalized notification messages. It generates notification messages tailored to the selected optimal date and time, with different messages prepared for each user. This process ensures effective information delivery to users.

[0633] Step 7:

[0634] The server sends the generated personalized notification to the device. The device receives the notification and displays it to the user. The user can review the notification on the device and provide feedback or change their schedule as needed.

[0635] This enables optimal event scheduling that takes user emotions into consideration, resulting in highly satisfying schedule management.

[0636] (Application Example 2)

[0637] 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."

[0638] In coordinating events for individuals and communities, optimization is often not performed to take into account participants' feelings and schedules, which can result in decreased motivation to participate. This invention aims to enable event coordination that takes users' feelings into account, thereby improving participant satisfaction and the efficiency of event management.

[0639] 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.

[0640] In this invention, the server includes means for receiving and storing schedule information and sentiment data from users, means for analyzing the stored schedule information and sentiment data to calculate the optimal meeting time, and means for communicating the optimal meeting time to other users. This enables efficient event coordination that takes into account the sentiment of the users.

[0641] An "information processing device" is a computer system that receives data from users and performs processing and analysis.

[0642] "Schedule information" refers to time and date data related to future plans and events entered by the user.

[0643] "Emotional data" refers to data that shows the emotions and feelings that users have towards specific dates or events.

[0644] A "secure data storage location" is a data storage area designed to protect received data from leakage and unauthorized access.

[0645] "Analysis" is an information processing operation that calculates the optimal meeting time for each user based on the received data.

[0646] "Meeting time" refers to the start time or period decided upon for an event or gathering involving multiple users.

[0647] "To communicate" means to use means to transmit information to other users and make them understand it.

[0648] "Emotional analytics" is a technology that analyzes users' emotional data and draws conclusions based on that analysis.

[0649] An "optimization algorithm" is a mathematical method used to derive the most suitable result from among multiple options.

[0650] This application is implemented by the following system: A server receives scheduling information and sentiment data from users via smartphones or other devices to determine the optimal date for a meeting. The collected information is stored in Firebase, a cloud-based secure data storage location.

[0651] The server uses a sentiment engine that performs text sentiment analysis to analyze users' emotional data. The sentiment engine uses Google Cloud's Natural Language API to evaluate the participant's psychological state based on the emotional information extracted from the input text data.

[0652] Subsequently, an optimization algorithm is used to calculate the date that is most convenient for the most users and will elicit the most positive feedback, based on the data stored in Firebase. This calculation includes a predictive model and a feasible optimization plan.

[0653] On the device, a user interface including a user-specified emotion rating slider is built using the Flutter framework, allowing users to intuitively input their emotions when participating in an event. This makes emotional feedback and date selection easier.

[0654] For example, in coordinating a flea market event with citizen participation, users indicate the "dates they might be able to attend" and their "level of expectation" and "level of stress" using sliders. Based on the server's processing of this information, the date determined as the "day with the highest desire to participate" is notified to those who wish to attend.

[0655] A concrete example of a prompt message could be: "Residents, please help us coordinate the dates for this year's flea market. Please select a date you are available to attend and let us know your preference using the slider." This prompt message allows users to easily provide the necessary information, resulting in a more efficient functioning of the entire community.

[0656] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0657] Step 1:

[0658] The device receives the user's selected available dates and sentiment ratings. This input is performed through the user interface, and the device also obtains the user's sentiment data using a sentiment rating slider. The obtained data is sent to the server together as schedule information and sentiment data.

[0659] Step 2:

[0660] The server stores the received schedule and sentiment data in Firebase. This process securely stores the data that will serve as the basis for future analysis and calculations. In the database, each user's information is managed with a unique ID, ensuring efficient access.

[0661] Step 3:

[0662] The server analyzes sentiment data using Google Cloud's Natural Language API. In this step, based on the sentiment information collected from users, the server quantifies and visualizes the user's sentiment for each candidate event date. The analysis results in positive or negative feedback.

[0663] Step 4:

[0664] The server executes an optimization algorithm, combining sentiment ratings and scheduling information to calculate the optimal meeting time. This calculation uses aggregated user data to select the day when participants' happiness levels are maximized.

[0665] Step 5:

[0666] The server notifies eligible users of the calculated optimal meeting time. The notification is sent as a push message to the user's device, allowing them to confirm the determined meeting time. The notification includes a prompt message similar to, "The determined optimal date for the flea market is [Month] [Day]."

[0667] 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.

[0668] 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.

[0669] 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.

[0670] [Fourth Embodiment]

[0671] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0672] 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.

[0673] 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).

[0674] 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.

[0675] 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.

[0676] 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).

[0677] 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.

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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".

[0684] This invention provides a system for streamlining the scheduling of events involving multiple users and for facilitating the smooth sharing of information. This system mainly consists of a server as an information processing device, terminals accessed by users, and the user's own interface.

[0685] The server is responsible for aggregating schedule information sent from each user. Schedule information entered by users via their terminals is stored in a database by the server. Based on this information, the server uses an optimization algorithm to calculate the optimal event time for each user. The calculated optimal date and time are then notified to all users.

[0686] The terminal functions as a means for users to input, confirm, and edit schedule information through an interface. After entering the schedule, the terminal performs the saving and transmission processes, passing the data to the server. It also receives notifications from the server and displays reminders and event change notifications to the user.

[0687] Users can input and modify appointments using their own devices and communicate smoothly with other users. Based on user selections, the final event time is determined, and this information is then notified to all users again.

[0688] As a concrete example, when scheduling a monthly PTA meeting using this system, each member first enters their available dates into a terminal. This information is collected on a server, and a candidate date is calculated through an optimization algorithm. The server notifies all members of the best candidate date, and members select their final attendance status on their terminals. The server compiles this attendance information, determines the final meeting date, and notifies the members. A reminder is automatically sent the day before the meeting, allowing users to prepare efficiently.

[0689] This format allows individual users to schedule activities with minimal burden, enabling the smooth operation of PTA and other organizational activities.

[0690] The following describes the processing flow.

[0691] Step 1:

[0692] The user uses their device to enter possible dates for meetings they can attend. A scheduling form is provided on the device, and the user fills in the information in a timely manner.

[0693] Step 2:

[0694] The terminal checks the entered schedule information, verifies that there are no errors in the input, and then sends the data to the server. If there are errors, a message prompting the user to correct them will be displayed.

[0695] Step 3:

[0696] The server stores the received schedule information in a database. This database serves to store candidate dates and times for each user.

[0697] Step 4:

[0698] The server aggregates all user-submitted candidate dates stored in the database and applies an AI-based optimization algorithm to calculate the meeting date with the highest overall attendance rate.

[0699] Step 5:

[0700] The server generates a notification message with the calculated optimal date and time and sends it to all users.

[0701] Step 6:

[0702] The terminal displays a notification from the server indicating the optimal date and time for participation. The user reviews the notification and chooses whether or not to participate.

[0703] Step 7:

[0704] Based on the notification, the user specifies on their device whether or not they will participate. Once the selection is complete, the device sends that information back to the server.

[0705] Step 8:

[0706] The server compiles responses from all users indicating whether they can participate or not, and determines the final meeting date and time based on the number of available participants.

[0707] Step 9:

[0708] The server creates a message to notify all users of the final meeting date and time, and then executes the notification.

[0709] Step 10:

[0710] When the device receives notification of the final decision from the server, it displays the details to the user and automatically adds the event to the calendar.

[0711] Step 11:

[0712] The server sets a schedule to send reminders in advance as the meeting date approaches.

[0713] Step 12:

[0714] The device receives a reminder notification and displays a message prompting the user to reconfirm the event.

[0715] (Example 1)

[0716] 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".

[0717] In modern society, coordinating the date and time of events involving many participants is difficult, as it requires selecting the most appropriate date and time to accommodate individual schedules. This is especially true when there are numerous possible dates and participants have diverse availability; manual coordination is time-consuming and laborious. Furthermore, delays in confirming and notifying participants of the chosen date and time can hinder the smooth running of the event. Efficient and effective solutions are needed to address these challenges.

[0718] 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.

[0719] In this invention, the server includes means for receiving schedule information from users and storing the schedule information in a storage area, means for analyzing the schedule information stored in the storage area and determining the optimal event time for each user, and means for notifying other users of the optimal event time. This enables efficient scheduling and smooth event management.

[0720] An "information processing device" is a device that receives, records, and analyzes data entered by a user.

[0721] A "user" is an individual or group that may use the system to input schedule information and potentially participate in an event.

[0722] "Schedule information" refers to data entered by users regarding their available time and participation time during a specific period.

[0723] "Memory area" refers to a part of data storage used to store received data.

[0724] "Analysis" refers to the processing activity of determining the optimal date and time based on the schedule information provided by the user.

[0725] The "optimal event time" is the date and time chosen to maximize efficiency and participation, taking into account the circumstances of all users.

[0726] "Notification" refers to communication activities aimed at conveying decided information to users.

[0727] "Participation status information" refers to information indicating whether a user is able to participate in the proposed event at the suggested time.

[0728] The "final event time" refers to the date and time after all participation confirmation information has been compiled and finalized.

[0729] A "communication domain" refers to the network environment or means of communication used when exchanging information.

[0730] "Optimization" refers to the application of calculations and algorithms to select the most appropriate date and time from the proposed candidate dates.

[0731] This invention is a system for efficiently coordinating the dates and times of events involving multiple users and for smoothly sharing information among users. The system mainly consists of a server acting as an information processing device, terminals accessed by users, and the users themselves.

[0732] The server plays the role of aggregating schedule information sent by users. Specifically, it receives schedule information entered by users via their terminals and stores it in data storage. A general-purpose database system can be used for this storage. For example, RDBMS (relational database management systems) such as MySQL or PostgreSQL can be considered as databases.

[0733] Furthermore, the server performs optimization processing based on the stored information. This process uses the Python library Scikit-learn to select the optimal date and time. This allows the server to select the date and time that is most convenient for multiple users to participate. The determined date and time are automatically notified to all users, and the server aggregates the participation status information sent back by the users. Based on this, the final event date and time are determined. The server also has a function to send reminders to users the day before the event, and can send emails using an SMTP server or utilize push notification services.

[0734] The terminal functions as a means for users to access the system and input, confirm, and edit schedule information. Through the terminal's interface, users can select available days in a calendar format and fill in details in the input form. The entered information is sent from the terminal to the server and used for subsequent processing. The terminal also receives notifications from the server and informs the user via pop-up notifications or screen displays.

[0735] Users can input their schedules using their devices and communicate efficiently with other users. For example, when scheduling a PTA meeting, users input the days they are available into their devices. This information is collected on the server, and the optimal date is calculated and suggested to all users. Users then select whether they will attend or not using their devices, and the final meeting date is determined. An automatic reminder is sent to the user's device the day before the meeting, allowing them to prepare promptly.

[0736] As a concrete example, an example of a prompt message to the generating AI model is, "I would like to schedule a PTA meeting. Please let me know which days you are available next week." This prompt allows the AI ​​to assist the user in entering their schedule, enabling efficient scheduling.

[0737] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0738] Step 1:

[0739] The user accesses the interface through their device to open the schedule entry page. On the calendar-style screen, they select available dates and enter details such as time slots. They enter a prompt message such as "Please tell me which days you are available next week," and this information is collected and sent from their device as structured data in JSON format or similar.

[0740] Step 2:

[0741] The terminal sends the entered schedule information to the server. During this process, the terminal converts the data into a specific format (e.g., JSON format) and transmits it via the communication area. Once the information transmission to the server is complete, a notification indicating the success of the process is displayed on the terminal.

[0742] Step 3:

[0743] The server receives schedule information sent from the terminal and stores it in its storage. Based on this information, the server checks the schedules of all users and stores it in the database. During the saving process, the server checks the accuracy of the data and removes any inconsistent data.

[0744] Step 4:

[0745] The server analyzes the data stored in its memory and begins the optimization process. This analysis uses a generative AI model and optimization algorithms to calculate the optimal event date and time for all users. The algorithm clusters multidimensional data and selects candidate dates that are most likely to be attended. The results of this calculation are stored on the server as internal data.

[0746] Step 5:

[0747] The server generates a notification message with the calculated optimal event date and time and notifies all users. The notification is sent via email or push notification, and a record of the transmission is saved in the log. The server verifies that the notification was successfully delivered to each user.

[0748] Step 6:

[0749] The user receives a notification from the server and checks it on their device. A screen for selecting whether to participate or not appears on the device, and the user selects "Participate" or "Do not participate." Once the selection is confirmed, that information is sent back from the device to the server.

[0750] Step 7:

[0751] The server aggregates the attendance confirmation information submitted by users. This aggregation ultimately determines the event date and time that will ensure the optimal number of participants. The determined date and time are then notified to all users again as a reminder and registered as the final date.

[0752] Step 8:

[0753] The user receives a reminder notification sent from the server and confirms it on the notification screen on their device. By using the prompt message, "I would like to schedule a PTA meeting. Please let me know which days you are available next week," the user can quickly proceed with preparations.

[0754] (Application Example 1)

[0755] 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".

[0756] When coordinating group activities or events involving multiple participants, scheduling can become inefficient. This is especially true for community activities with many participants, where checking everyone's schedules and determining the optimal date is difficult. This challenge can lead to poor communication among participants, resulting in delays or inefficiencies in community activities.

[0757] 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.

[0758] In this invention, the server includes means for an information processing device to receive schedule information from a user and store the schedule information in a storage device, means for analyzing the schedule information stored in the storage device to determine the optimal activity time for each participant, and means for notifying other users of the optimal activity time. This makes it possible to quickly and effectively coordinate the optimal schedule for activities among multiple participants.

[0759] An "information processing device" is a device that has the function of receiving, storing, analyzing, and notifying users of data.

[0760] "User" refers to a person who provides schedule information to an information processing device and receives notification of the result.

[0761] "Schedule information" refers to data that indicates the dates on which a user is available to participate in a specific activity or event.

[0762] A "storage device" is a storage medium used by an information processing device to store scheduled information.

[0763] "Analysis" is the process of evaluating data based on collected schedule information and calculating the optimal activity time.

[0764] An "optimization calculation method" is an algorithm used to derive the optimal result that satisfies multiple conditions.

[0765] "Activity time" refers to the date and time of an activity or event, which is determined considering the participants' schedules.

[0766] "Collective activity coordination" is the process of efficiently combining schedules and plans for activities and events involving multiple participants.

[0767] To realize this system, servers responsible for information processing play a central role. These servers are located on cloud-based platforms such as AWS and Google Cloud, efficiently receiving scheduling information from users and storing it in storage devices. This allows the servers to manage large amounts of data while achieving a secure and scalable configuration.

[0768] The server uses programs implemented in programming languages ​​such as Python and Node.js to analyze the stored schedule information. These programs retrieve data from databases such as MongoDB and MySQL and use optimization calculation methods to determine the optimal activity times for each participant. Through such data calculations, a balanced activity schedule is created for all participants.

[0769] The analysis results are notified to the user's device in real time. The system is developed using React Native and Flutter for cross-platform compatibility, allowing it to be used on various devices such as smartphones and personal computers. This ensures users enjoy convenience while maintaining a consistent user experience across different devices.

[0770] Another concrete example is how this system facilitates smooth scheduling for local residents participating in meetings organized by the local government. Residents can enter their available dates and times into the application, and the system will then suggest the most suitable schedule, allowing activities to proceed smoothly.

[0771] Examples of prompts for a generative AI model include: "I want to design a system that efficiently aggregates the schedules of multiple participants and calculates the optimal meeting time. This system also needs real-time notification and reminder sending capabilities. How should the program be structured?"

[0772] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0773] Step 1:

[0774] The user opens the app on their smartphone and enters their available dates. The input data is converted to the appropriate format by the device and sent to the server. This allows the server to receive the user's available dates.

[0775] Step 2:

[0776] The server retrieves the received schedule information and stores it in the database. During this process, the format is standardized to ensure that the entered information is stored correctly, free from duplicates and errors. This process centralizes the management of schedule information in the database.

[0777] Step 3:

[0778] The server retrieves schedule information for all participants from the database and begins analysis using an optimization calculation method. Here, a Python-based algorithm is used to derive the optimal activity time. By comparing multiple candidate dates and times, the most convenient time for all participants is selected.

[0779] Step 4:

[0780] Once the optimal activity time is determined, the server notifies each participant's device of the result. The output is in real time, and users can check the results on their own devices. The notification includes important schedules for the next activity and information on how to prepare for the activity.

[0781] Step 5:

[0782] The user receives a notification, decides whether or not they can participate in the optimal activity time, and sends feedback to the server via their device. Here, the user reviews the details and makes an input to choose whether or not to participate.

[0783] Step 6:

[0784] The server collects participation confirmation information from users and determines the final activity time. Using an aggregation algorithm, it makes adjustments based on participant feedback to determine the time when the most participants can gather.

[0785] Step 7:

[0786] The server will re-notify all participants of the final confirmed activity time. This final notification, accompanied by a reminder function, is automatically sent before the activity date. The system makes it easier for participants to prepare for the activity.

[0787] 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.

[0788] This invention provides a system that streamlines event scheduling and enables more personalized notifications and decision-making by taking user emotions into consideration. The system includes a server as an information processing device, a terminal providing a user interface, and the user themselves. Furthermore, an emotion engine that analyzes user emotions is integrated.

[0789] The server aggregates and analyzes scheduling information and utilizes emotional data obtained by the emotion engine. For example, when a user enters potential meeting dates, the server stores the information in the database and uses the emotion engine to evaluate each user's emotional state. Based on this evaluation, the optimal date and time are selected, and notifications are adjusted accordingly.

[0790] The device allows users to input schedule information and provide emotional feedback through the user interface. When a user enters a schedule or receives a notification, the device collects the user's emotional data. This data is then sent to a server to help optimize notification methods.

[0791] Users can use their devices to input meeting schedules and communicate their feelings and feedback during those meetings. For example, a user's emotions such as stress or anticipation for a specific date and time are recorded and sent to a server, where they can be shared with other users.

[0792] As a concrete example, consider scheduling a PTA meeting. The user enters their available dates on their device and indicates their feelings about those dates using a simple slider or rating. This information is sent to the server. The server analyzes multiple candidate dates and the user's emotional state to determine the optimal meeting date. If there is a lot of positive feedback for a particular meeting date, that date and time will be given high priority and notified; if there is negative feedback, alternative dates can be suggested.

[0793] This format allows for adjustments that take into account the emotional state of the users, which is expected to facilitate smoother communication and improve satisfaction. As a result, it promotes increased overall participation and smoother operation in group meetings such as those of PTAs.

[0794] The following describes the processing flow.

[0795] Step 1:

[0796] Users use their devices to enter possible meeting dates. They also use a slider to indicate their feelings about those dates as emotional feedback.

[0797] Step 2:

[0798] The terminal verifies the format of the entered schedule information and sentiment feedback before sending it to the server, ensuring data integrity.

[0799] Step 3:

[0800] The server stores the received schedule information and emotional feedback in a database. The stored emotional data is then incorporated into the optimization algorithm.

[0801] Step 4:

[0802] The server uses an algorithm to analyze candidate date data and sentiment feedback collected from all users to calculate the meeting date that will generate the highest level of participation.

[0803] Step 5:

[0804] The server prepares the calculated optimal date and time as an emotionally sensitive message and notifies the user.

[0805] Step 6:

[0806] The terminal receives notifications from the server and displays them to the user. The user can then make a final decision on whether or not to participate in the event at the notified date and time.

[0807] Step 7:

[0808] The device resends the user's participation status information to the server. The transmitted data also includes re-evaluated sentiment feedback.

[0809] Step 8:

[0810] The server compiles the final attendance confirmation information, re-evaluates participation intentions, and then determines the final meeting date and time.

[0811] Step 9:

[0812] The server notifies all users of the finalized meeting date and time, and automatically updates their calendars.

[0813] Step 10:

[0814] The server schedules to send reminders at the optimal time, using an emotion engine, a few days before the meeting.

[0815] Step 11:

[0816] The device receives a reminder notification and displays it to the user to prompt them to prepare for the meeting.

[0817] (Example 2)

[0818] 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".

[0819] Traditional scheduling management systems fail to consider users' emotional states, leading to decreased user satisfaction during scheduling. Furthermore, they lack effective means of utilizing individual user emotional feedback when selecting the optimal date and time from multiple options. Additionally, notifications are delivered in a generic format, resulting in a lack of personalization for individual users.

[0820] 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.

[0821] In this invention, the server includes means for receiving schedule information from users and storing it in a memory area, means for evaluating each user's emotional state using sentiment analysis, and means for generating personalized notification text using a generative AI model. This enables optimal event adjustment that takes into account the user's emotional state and personalized notifications that are tailored to each individual user.

[0822] An "information processing device" is a device with electronic functions that receive input information from users and perform processing and analysis.

[0823] "Memory space" refers to digital storage used to store received data so that it can be retrieved when needed.

[0824] "Emotional analysis tools" refer to software or algorithms that analyze a user's emotions from data and evaluate their emotional state.

[0825] The "optimal event time" is the most appropriate date and time for an event, determined by considering user sentiment data and participation likelihood.

[0826] A "generative AI model" is a computer model that uses generative artificial intelligence technology to generate output based on specific inputs.

[0827] A "personalized notification message" is a notification message that is customized to reflect the attributes and status of each individual user.

[0828] An "optimization algorithm" is a computational procedure for deriving the best possible result from given options or data.

[0829] This invention is an information processing system for scheduling and notifying events. It primarily involves three parties: a server, a terminal, and a user, and optimizes events while considering the user's emotional state.

[0830] The server functions as a computer and information processing device. It receives scheduled information and sentiment data sent from users via terminals and stores this data in a database. The server also has sentiment analysis capabilities implemented to analyze the sentiment data obtained from users and select the optimal event date and time based on the results. In this process, it utilizes a generative AI model to generate personalized notification messages for users.

[0831] The terminal is a computer that provides a user interface. The user uses it to input schedule information and provides emotional feedback for each proposed date and time. For example, it can use a slider to select emotional states such as "neutral," "anticipatory," or "stressed." The terminal then sends this data to the server.

[0832] Users use this system to input potential event dates and whether they can attend. They also submit sentiment feedback at the same time, and the server analyzes this information to determine the most suitable date and time.

[0833] As a concrete example, consider scheduling PTA meetings. Users input their available dates using a terminal and evaluate their feelings towards each date and time. This information is sent to a server, where sentiment analysis and optimization algorithms select the optimal meeting date. By inputting information such as "I look forward to the meeting on Monday," the system makes appropriate adjustments.

[0834] Examples of prompt statements are as follows:

[0835] "To schedule the PTA meeting, please indicate your likelihood of attending and your feelings regarding the following possible dates. Friday: Highly optimistic, Saturday: Neutral, Sunday: Highly stressed."

[0836] This invention enables efficient schedule management that takes into account the emotions of users, and is expected to improve overall participation and facilitate communication.

[0837] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0838] Step 1:

[0839] The user enters the event date on their device. Specifically, they use a date selection interface to select multiple possible dates. The entered dates are converted to a digital format and temporarily stored on the device.

[0840] Step 2:

[0841] Users rate their emotions for each scheduled date. They use sliders and options displayed on their device to specify emotional states such as "anticipated," "neutral," and "stressed." The emotional ratings are also converted into digital data and saved along with the scheduled information.

[0842] Step 3:

[0843] The device sends the user's entered schedule information and sentiment data to the server. The data is encrypted and transmitted over the network via a secure protocol. The transmitted data is received by the server and stored in a database.

[0844] Step 4:

[0845] The server analyzes the received schedule information and sentiment data. It processes the information retrieved from the database using sentiment analysis tools to quantify each user's emotional tendencies. For example, dates with a high level of expectation are given a higher rating.

[0846] Step 5:

[0847] The server executes an optimization algorithm based on the sentiment analysis results. This algorithm selects the date with the most positive responses based on sentiment evaluation. The algorithm uses sentiment data and candidate date information as input, and the output is the optimal event time.

[0848] Step 6:

[0849] The server uses a generative AI model to create personalized notification messages. It generates notification messages tailored to the selected optimal date and time, with different messages prepared for each user. This process ensures effective information delivery to users.

[0850] Step 7:

[0851] The server sends the generated personalized notification to the device. The device receives the notification and displays it to the user. The user can review the notification on the device and provide feedback or change their schedule as needed.

[0852] This enables optimal event scheduling that takes user emotions into consideration, resulting in highly satisfying schedule management.

[0853] (Application Example 2)

[0854] 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".

[0855] In coordinating events for individuals and communities, optimization is often not performed to take into account participants' feelings and schedules, which can result in decreased motivation to participate. This invention aims to enable event coordination that takes users' feelings into account, thereby improving participant satisfaction and the efficiency of event management.

[0856] 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.

[0857] In this invention, the server includes means for receiving and storing schedule information and sentiment data from users, means for analyzing the stored schedule information and sentiment data to calculate the optimal meeting time, and means for communicating the optimal meeting time to other users. This enables efficient event coordination that takes into account the sentiment of the users.

[0858] An "information processing device" is a computer system that receives data from users and performs processing and analysis.

[0859] "Schedule information" refers to time and date data related to future plans and events entered by the user.

[0860] "Emotional data" refers to data that shows the emotions and feelings that users have towards specific dates or events.

[0861] A "secure data storage location" is a data storage area designed to protect received data from leakage and unauthorized access.

[0862] "Analysis" is an information processing operation that calculates the optimal meeting time for each user based on the received data.

[0863] "Meeting time" refers to the start time or period decided upon for an event or gathering involving multiple users.

[0864] "To communicate" means to use means to transmit information to other users and make them understand it.

[0865] "Emotional analytics" is a technology that analyzes users' emotional data and draws conclusions based on that analysis.

[0866] An "optimization algorithm" is a mathematical method used to derive the most suitable result from among multiple options.

[0867] This application is implemented by the following system: A server receives scheduling information and sentiment data from users via smartphones or other devices to determine the optimal date for a meeting. The collected information is stored in Firebase, a cloud-based secure data storage location.

[0868] The server uses a sentiment engine that performs text sentiment analysis to analyze users' emotional data. The sentiment engine uses Google Cloud's Natural Language API to evaluate the participant's psychological state based on the emotional information extracted from the input text data.

[0869] Subsequently, an optimization algorithm is used to calculate the date that is most convenient for the most users and will elicit the most positive feedback, based on the data stored in Firebase. This calculation includes a predictive model and a feasible optimization plan.

[0870] On the device, a user interface including a user-specified emotion rating slider is built using the Flutter framework, allowing users to intuitively input their emotions when participating in an event. This makes emotional feedback and date selection easier.

[0871] For example, in coordinating a flea market event with citizen participation, users indicate the "dates they might be able to attend" and their "level of expectation" and "level of stress" using sliders. Based on the server's processing of this information, the date determined as the "day with the highest desire to participate" is notified to those who wish to attend.

[0872] A concrete example of a prompt message could be: "Residents, please help us coordinate the dates for this year's flea market. Please select a date you are available to attend and let us know your preference using the slider." This prompt message allows users to easily provide the necessary information, resulting in a more efficient functioning of the entire community.

[0873] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0874] Step 1:

[0875] The device receives the user's selected available dates and sentiment ratings. This input is performed through the user interface, and the device also obtains the user's sentiment data using a sentiment rating slider. The obtained data is sent to the server together as schedule information and sentiment data.

[0876] Step 2:

[0877] The server stores the received schedule and sentiment data in Firebase. This process securely stores the data that will serve as the basis for future analysis and calculations. In the database, each user's information is managed with a unique ID, ensuring efficient access.

[0878] Step 3:

[0879] The server analyzes sentiment data using Google Cloud's Natural Language API. In this step, based on the sentiment information collected from users, the server quantifies and visualizes the user's sentiment for each candidate event date. The analysis results in positive or negative feedback.

[0880] Step 4:

[0881] The server executes an optimization algorithm, combining sentiment ratings and scheduling information to calculate the optimal meeting time. This calculation uses aggregated user data to select the day when participants' happiness levels are maximized.

[0882] Step 5:

[0883] The server notifies eligible users of the calculated optimal meeting time. The notification is sent as a push message to the user's device, allowing them to confirm the determined meeting time. The notification includes a prompt message similar to, "The determined optimal date for the flea market is [Month] [Day]."

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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."

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] The following is further disclosed regarding the embodiments described above.

[0906] (Claim 1)

[0907] The information processing device includes means for receiving schedule information from a user and storing the schedule information in a database,

[0908] A means for analyzing the schedule information stored in the aforementioned database and determining the optimal event time for each user,

[0909] The means for notifying other users of the aforementioned optimal event time,

[0910] A means of receiving user responses regarding their participation in an event,

[0911] A means of aggregating the received participation confirmation information and determining the final event time,

[0912] A means for notifying the user of the final event time,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, further comprising means for the information processing device to provide a reminder notification to a user before a determined event time.

[0916] (Claim 3)

[0917] The system according to claim 1, wherein the information processing device includes means for analyzing multiple candidate dates and calculating the optimal event time using an optimization algorithm.

[0918] "Example 1"

[0919] (Claim 1)

[0920] A means for receiving schedule information from a user and storing the schedule information in a memory area,

[0921] A means for analyzing the schedule information stored in the aforementioned memory area and determining the optimal event time for each user,

[0922] A means for notifying other users of the aforementioned optimal event time,

[0923] A means of receiving user responses regarding their participation in events,

[0924] A means of compiling the received information regarding attendance and determining the final event time,

[0925] A means of notifying users of the final event time,

[0926] A means of exchanging schedule information and notifications via the communication domain,

[0927] Means for storing and displaying generated notifications and information,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, further comprising means for providing advance notice to users before the scheduled time of an event.

[0931] (Claim 3)

[0932] The system according to claim 1, comprising means for analyzing multiple candidate dates and calculating the optimal event time using an optimization process.

[0933] "Application Example 1"

[0934] (Claim 1)

[0935] The information processing device includes means for receiving schedule information from a user and storing the schedule information in a storage device,

[0936] A means for analyzing the schedule information stored in the storage device and determining the optimal activity time for each participant,

[0937] A means for notifying other users of the aforementioned optimal activity time,

[0938] A means of receiving user responses regarding their willingness to participate in activities,

[0939] A means of aggregating the received participation confirmation information and determining the final activity time,

[0940] A means to enhance communication in coordinating collective activities involving multiple participants and to improve the efficiency of community activities,

[0941] A means of informing the user of the final activity time,

[0942] A system that includes this.

[0943] (Claim 2)

[0944] The system according to claim 1, further comprising means for the information processing device to provide advance notification to the user based on information stored in the storage device before a determined activity time.

[0945] (Claim 3)

[0946] The system according to claim 1, wherein the information processing device includes means for analyzing a plurality of candidate periods and calculating the optimal activity time using an optimization calculation method.

[0947] "Example 2 of combining an emotion engine"

[0948] (Claim 1)

[0949] The information processing device includes means for receiving schedule information from a user and storing the schedule information in a memory area,

[0950] A means for analyzing the schedule information stored in the memory area and evaluating the emotional state of each user using an emotion analysis means,

[0951] A means to determine the optimal event time for the user and adjust notifications based on the results of an assessment of their emotional state,

[0952] The means for notifying other users of the aforementioned optimal event time,

[0953] A means of receiving user responses regarding their participation in an event,

[0954] A means of aggregating the received participation confirmation information and determining the final event time,

[0955] A means for notifying the user of the final event time,

[0956] A means of generating personalized notification text using a generative AI model,

[0957] A system that includes this.

[0958] (Claim 2)

[0959] The system according to claim 1, further comprising means for providing a reminder notification to the user before the determined event time.

[0960] (Claim 3)

[0961] The system according to claim 1, comprising means for analyzing multiple candidate dates, calculating the optimal event time using an optimization algorithm, and considering sentiment data.

[0962] "Application example 2 when combining with an emotional engine"

[0963] (Claim 1)

[0964] The information processing device includes means for receiving schedule information and sentiment data from a user and storing the schedule information in a secure data storage location.

[0965] A means for analyzing schedule information and sentiment data stored in the aforementioned secure data storage location to calculate the optimal meeting time for each user,

[0966] A means for communicating the aforementioned optimal meeting time to other users,

[0967] A means of receiving user feedback on whether they are willing to participate in the meeting and their emotional assessment,

[0968] A means of compiling the received information regarding participation status and sentiment, and determining the final meeting time,

[0969] A means for communicating the final meeting time to the users,

[0970] A system that includes this.

[0971] (Claim 2)

[0972] The system according to claim 1, further comprising means for an information processing device to provide a user with a reminder notification based on sentiment analytics prior to a determined meeting time.

[0973] (Claim 3)

[0974] The system according to claim 1, comprising an information processing device that analyzes multiple candidate dates and sentiment data and calculates the optimal meeting time using an optimization algorithm. [Explanation of symbols]

[0975] 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. The information processing device includes means for receiving schedule information from a user and storing the schedule information in a storage device, A means for analyzing the schedule information stored in the storage device and determining the optimal activity time for each participant, A means for notifying other users of the aforementioned optimal activity time, A means of receiving user responses regarding their willingness to participate in activities, A means of aggregating the received participation confirmation information and determining the final activity time, A means to enhance communication in coordinating collective activities involving multiple participants and to improve the efficiency of community activities, A means of informing the user of the final activity time, A system that includes this.

2. The system according to claim 1, further comprising means for the information processing device to provide advance notification to the user based on information stored in the storage device before a determined activity time.

3. The system according to claim 1, wherein the information processing device includes means for analyzing a plurality of candidate periods and calculating the optimal activity time using an optimization calculation method.

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