System

Abstract

An object of a system according to an embodiment is to secure equal opportunity in reservation of a meeting room.SOLUTION: A system includes a conference information reception part, an optimum allocation part, a notification part, a real-time update part, and a change / cancellation part. The conference information reception unit receives conference information in advance. The optimum assignment part assigns an optimum conference room and time on the basis of the conference information received by the conference information reception part. The notification unit notifies the conference room and the time allocated by the optimum allocation unit. The real-time updating unit updates the reservation status of the meeting room in real time. The change / cancellation unit accepts a change or cancellation of a reservation.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, conference room reservations were made on a first-come, first-served basis, which meant that equal opportunity was not ensured.

[0005] The system according to the embodiment aims to ensure equal opportunity in reserving conference rooms. [Means for solving the problem]

[0006] The system according to the embodiment includes a conference information receiving unit, an optimal allocation unit, a notification unit, a real-time update unit, and a change / cancellation unit. The conference information receiving unit receives conference information in advance. The optimal allocation unit allocates the optimal conference room and time based on the conference information received by the conference information receiving unit. The notification unit notifies the conference room and time allocated by the optimal allocation unit. The real-time update unit updates the reservation status of the conference room in real time. The change / cancellation unit accepts changes or cancellations to reservations. [Effects of the Invention]

[0007] The system according to the embodiment can ensure equal opportunity in reserving conference rooms. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A conference room reservation system according to an embodiment of the present invention is a system that allows for fair use of conference rooms within a company. This system accepts information such as the content, time, desired room, number of participants, and desired device of a conference in advance for each organizational level, and allocates the optimal conference room and time. This allows each department to use conference rooms fairly, improving the efficiency of conference room usage.

[0029] The conference room reservation system according to the embodiment includes a conference information receiving unit, an optimal allocation unit, a notification unit, a real-time update unit, and a change / cancellation unit. The conference information receiving unit receives conference information in advance. For example, the conference information receiving unit inputs information such as the content, time, desired room, number of participants, and desired device for each division, department, section, and group into the system. The optimal allocation unit allocates the optimal conference room and time based on the conference information received by the conference information receiving unit. For example, the optimal allocation unit allocates the optimal conference room and time taking into consideration the content, number of participants, and desired device for the conference. The notification unit notifies each department of the conference room and time allocated by the optimal allocation unit. For example, the notification unit notifies each department of the reservation details. The real-time update unit updates the reservation status of the conference room in real time. For example, the real-time update unit allows each department to check the current reservation status. The change / cancellation unit accepts changes or cancellations of reservations. For example, the change / cancellation unit provides each department with the ability to change or cancel reservation details. This allows the conference room reservation system to allow each department to use conference rooms fairly, improving the efficiency of conference room usage.

[0030] The conference information receiving unit can use the generation AI to automatically suggest the optimal conference format and required devices based on the content and purpose of the conference. For example, the conference information receiving unit uses the generation AI to analyze the content and purpose of the conference and automatically suggest the optimal conference format (e.g., presentation format, discussion format). For example, in the case of a project progress meeting, it may determine that a discussion format is appropriate. It may also automatically suggest the required devices (e.g., projector, whiteboard, video conferencing system) based on the content of the conference. For example, it may recommend a projector for a conference that includes a presentation. It may also build a system that analyzes the purpose of the conference and suggests the optimal conference format and devices. For example, it may recommend a whiteboard and markers for a brainstorming conference. This makes it possible to suggest the optimal conference format and devices according to the content and purpose of the conference.

[0031] The conference information reception unit analyzes past conference data from each department, predicts frequently used conference rooms and time slots, and recommends advance reservations. For example, the conference information reception unit collects past conference data from each department and analyzes frequently used conference rooms and time slots. For example, if General Affairs Department A tends to hold meetings every Monday from 10:00 to 11:00, that time slot will be reserved preferentially. Furthermore, a system is constructed that predicts each department's meeting patterns based on past conference data and suggests optimal conference rooms and time slots in advance. For example, an appropriate conference room and time slot is automatically suggested for a department that holds many project progress meetings. Furthermore, an algorithm is developed that analyzes each department's conference data and predicts frequently used conference rooms and time slots. For example, if a specific department tends to hold meetings during a specific time slot, that time slot will be reserved preferentially. This allows the optimal conference room and time slot to be reserved in advance based on past data.

[0032] The conference information receiving unit can use voice input or natural language processing to enable users to easily input information. For example, when inputting conference information, the conference information receiving unit provides a voice input function, allowing users to input conference information simply by speaking. For example, information can be input simply by speaking, "Project progress meeting, 10:00-11:00, Conference Room 1, 10 people, Projector required." Furthermore, a system can be constructed that uses natural language processing technology to analyze text input by users and automatically extract conference information. For example, if a user inputs, "I would like to reserve a meeting for next Monday," the system automatically sets the date and time. Furthermore, a system can be provided that combines voice input and natural language processing to enable users to easily input conference information. For example, information input by voice can be converted into text and necessary items can be automatically extracted. This allows users to easily input conference information.

[0033] The conference information receiving unit can build a conference room sharing system between different companies and organizations, promoting the efficient use of available conference rooms. The conference information receiving unit, for example, builds a system for sharing conference rooms between different companies and organizations, improving the efficiency of using available conference rooms. For example, if a conference room at company A is available, company B can use that conference room. The conference room sharing system also allows different companies and organizations to check the availability of conference rooms in real time and make reservations. For example, company B can use a conference room during times when company A has not reserved it. A common reservation platform is also provided to promote the sharing of conference rooms between different companies and organizations. For example, multiple companies can use the same system to reserve conference rooms and share availability information. This allows conference rooms to be shared between different companies and organizations, improving the efficiency of using available conference rooms.

[0034] The optimal allocation unit uses generative AI to consider the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. For example, the optimal allocation unit uses generative AI to build a system that analyzes the content of the meeting and the schedules of the participants and proposes the optimal conference room and time in real time. For example, it proposes the optimal time taking into consideration the schedules of all participants. It also automatically selects the optimal conference room based on the content of the meeting. For example, it proposes a conference room equipped with a projector for a meeting that includes a presentation. It also analyzes the schedules of the participants in real time and proposes the optimal meeting time. For example, it automatically selects a time slot when everyone can participate. This makes it possible to propose the optimal conference room and time in real time based on the content of the meeting and the schedules of the participants.

[0035] The optimal allocation unit can improve overall utilization efficiency by analyzing the usage history of conference rooms and preferentially allocating less frequently used conference rooms. The optimal allocation unit, for example, analyzes the usage history of conference rooms and builds a system that preferentially allocates less frequently used conference rooms. For example, if a specific conference room is not used frequently, it will preferentially suggest that conference room. In addition, an algorithm is developed that improves overall utilization efficiency by preferentially allocating less frequently used conference rooms. For example, it automatically selects less frequently used conference rooms. In addition, a system is introduced that preferentially allocates less frequently used conference rooms based on the usage history of conference rooms. For example, it will suggest conference rooms that are not used during specific time periods. In this way, overall utilization efficiency is improved based on the frequency of conference room usage.

[0036] The optimal allocation unit can also take into account the usage status of other resources when optimally allocating conference rooms. For example, the optimal allocation unit builds a system that takes into account the usage status of other resources, such as projectors and whiteboards, when optimally allocating conference rooms. For example, for a conference room that requires a projector, it will suggest a conference room equipped with a projector. It also analyzes the usage status of other resources in real time and suggests the optimal conference room. For example, for a conference room that requires a whiteboard, it will suggest a conference room equipped with a whiteboard. It also develops an algorithm that takes into account the usage status of other resources when optimally allocating conference rooms. For example, for a conference room that requires a video conferencing system, it will suggest a conference room equipped with a video conferencing system. This makes it possible to take into account the usage status of other resources when optimally allocating conference rooms.

[0037] The optimal allocation unit promotes the sharing of conference rooms between different departments, making effective use of available time. The optimal allocation unit, for example, builds a system for sharing conference rooms between different departments, making effective use of available time. For example, it allows general department B to use a conference room during times when general department A is not using it. In addition, to promote conference room sharing, a system is introduced that shares reservation status between different departments in real time. For example, general department B uses a conference room during times when general department A has not reserved it. In addition, to promote conference room sharing between different departments, a common reservation platform is provided. For example, multiple departments use the same system to reserve conference rooms and share availability status. This promotes conference room sharing between different departments, making effective use of available time.

[0038] The notification unit can use the generation AI to notify additional suggestions and points of caution based on the purpose and content of the meeting when the reservation details are confirmed. For example, the notification unit uses the generation AI to build a system that analyzes the purpose and content of the meeting when the reservation details are confirmed and notifies additional suggestions and points of caution. For example, it notifies if a projector is needed. It also automatically generates and notifies additional suggestions and points of caution based on the purpose and content of the meeting. For example, it suggests that meeting participants share materials in advance. It also uses the generation AI to analyze the purpose and content of the meeting when the reservation details are confirmed and notifies necessary preparations. For example, it notifies the user to check the necessary devices before the meeting. This makes it possible to notify additional suggestions and points of caution based on the purpose and content of the meeting.

[0039] The notification unit can integrate the schedules of each department and automatically detect and notify overlaps and conflicts. The notification unit, for example, builds a system that integrates the schedules of each department and automatically detects overlaps and conflicts. For example, it notifies users when multiple meetings overlap in the same time slot. It also automatically detects schedule overlaps and conflicts and notifies each department. For example, it suggests an alternative conference room if a conference room is already reserved. It also develops an algorithm that analyzes each department's schedule in real time and detects overlaps and conflicts. For example, it notifies users when multiple meetings conflict in the same time slot. This makes it possible to integrate the schedules of each department and automatically detect and notify users of overlaps and conflicts.

[0040] The notification unit can diversify notification methods and send notifications via at least one of email, SMS, and chat apps. For example, the notification unit builds a system that sends confirmation notifications for conference room reservations via multiple channels, such as email, SMS, and chat apps. For example, the details of the conference reservation can be sent simultaneously via email and a chat app. In addition, the notification method can be diversified so that users can receive notifications via their preferred channel. For example, users who request email notifications can be notified by email, and users who request SMS notifications can be notified by SMS. In addition, a system can be developed that integrates multiple notification channels and allows users to receive notifications via the method that is most convenient for them. For example, notifications can be sent in conjunction with a chat app. This makes it possible to diversify notification methods and send notifications via multiple channels.

[0041] The notification unit can also provide information about the conference room's facilities and environment at the same time when a conference room reservation is confirmed. For example, the notification unit will build a system that simultaneously provides information about the conference room's facilities and environment when a conference room reservation is confirmed. For example, it will notify the user whether a projector or whiteboard is available. Information about the conference room's facilities and environment will also be automatically displayed when a reservation is confirmed. For example, it will notify the user of the conference room's size and number of seats. A system will also be developed that provides detailed information about the facilities and environment when a conference room reservation is confirmed. For example, it will notify the user of photos of the conference room and how to use the facilities. This makes it possible to simultaneously provide information about the facilities and environment when a conference room reservation is confirmed.

[0042] The real-time update unit uses generation AI to predict changes in reservation status in real time and automatically suggest available times. The real-time update unit, for example, uses generation AI to build a system that predicts changes in reservation status in real time and automatically suggests available times. For example, if a meeting is canceled, it will immediately suggest available times. In addition, an algorithm will be developed that analyzes changes in reservation status in real time and automatically suggests available times. For example, it will suggest available times if a meeting ends earlier than planned. In addition, a system will be introduced that uses generation AI to predict changes in reservation status and suggest available times in real time. For example, it will suggest available times if the start time of a meeting is delayed. This makes it possible to predict changes in reservation status in real time and automatically suggest available times.

[0043] The real-time update unit can visualize the usage status of conference rooms and provide a dashboard that each department can intuitively understand. The real-time update unit, for example, builds a system that visualizes the usage status of conference rooms and provides a dashboard that each department can intuitively understand. For example, it displays the reservation status of conference rooms in graphs and charts. It also updates the usage status in real time and provides a dashboard that each department can intuitively understand. For example, it displays the availability of conference rooms in color. It also develops a dashboard to visualize the usage status of conference rooms and makes it easy for each department to use. For example, it displays the reservation status of conference rooms in calendar format. This visualizes the usage status of conference rooms and provides a dashboard that each department can intuitively understand.

[0044] The real-time update unit can also update the usage status of other resources in real time and manage them in an integrated manner. The real-time update unit, for example, builds a system that updates the usage status of other resources (for example, projectors and whiteboards) in real time and manages them in an integrated manner. For example, it displays the usage status of projectors in real time. It also updates the usage status of resources in real time and manages them in an integrated manner with the reservation status of conference rooms. For example, it displays the usage status of whiteboards together with the reservation status of conference rooms. It also provides a dashboard that updates the usage status of other resources in real time and manages them in an integrated manner. For example, it makes it possible to check the usage status of projectors and whiteboards at a glance. This allows the usage status of other resources to be updated in real time and managed in an integrated manner.

[0045] The real-time update unit can share reservation status between different departments and promote cooperation to make effective use of available time. The real-time update unit, for example, builds a system that shares reservation status between different departments and promotes cooperation to make effective use of available time. For example, it allows general department B to use a conference room during times when general department A is not using it. It also shares reservation status in real time and promotes cooperation between different departments. For example, it allows general department B to use a conference room during times when general department A has not reserved it. It also provides a platform for sharing reservation status between different departments, making effective use of available time. For example, multiple departments use the same system to reserve conference rooms and share availability status. This allows reservation status to be shared between different departments and promotes cooperation to make effective use of available time.

[0046] The change / cancellation unit can use generation AI to automatically propose the optimal alternative when a change or cancellation occurs. For example, the change / cancellation unit uses generation AI to build a system that automatically proposes the optimal alternative when a reservation is changed or canceled. For example, if a conference room is canceled, it will propose another available conference room. In addition, when a change or cancellation occurs, the generation AI will propose the optimal alternative in real time. For example, if the meeting time is changed, it will propose another available time slot. In addition, a system will be developed using generation AI that automatically generates the optimal alternative and notifies the user when a change or cancellation occurs. For example, if a conference room needs to be changed, it will propose another conference room. This makes it possible to automatically propose the optimal alternative when a change or cancellation occurs.

[0047] The Changes and Cancellations Department analyzes the history of changes and cancellations, identifies departments and time periods where changes frequently occur, and can take measures to address them. For example, the Changes and Cancellations Department builds a system that collects the history of changes and cancellations and analyzes departments and time periods where changes frequently occur. For example, if a specific department frequently cancels meetings, it identifies the cause. Furthermore, based on the history of changes and cancellations, it identifies time periods where changes frequently occur and takes measures to address them. For example, it adjusts schedules so that meetings do not concentrate in specific time periods. It also analyzes the history of changes and cancellations and develops an algorithm to identify departments and time periods where changes frequently occur. For example, if a specific department tends to change meetings at a specific time period, it suggests avoiding that time period. This makes it possible to analyze the history of changes and cancellations, identify departments and time periods where changes frequently occur, and take measures to address them.

[0048] The Changes and Cancellations Department will be able to make adjustments to minimize the impact on other departments when changes or cancellations are made. The Changes and Cancellations Department will build a system that makes adjustments to minimize the impact on other departments when changes or cancellations are made. For example, if a conference room needs to be changed, the adjustment will take into account the reservation status of other departments. In addition, an algorithm will be developed that automatically makes adjustments when changes or cancellations are made to minimize the impact on other departments. For example, if a meeting time is changed, the adjustment will be made to prevent conflicts with meetings in other departments. In addition, a system will be introduced that analyzes the impact on other departments in real time when changes or cancellations are made and makes optimal adjustments. For example, if a conference room needs to be changed, the adjustment will take into account the reservation status of other departments. This will enable adjustments to minimize the impact on other departments when changes or cancellations are made.

[0049] The change / cancellation unit can simultaneously update information about the conference room's equipment and environment when a change or cancellation occurs. The change / cancellation unit will build a system that simultaneously updates information about the conference room's equipment and environment when a change or cancellation occurs. For example, if a change occurs in the conference room, it will notify the system of the equipment information for the new conference room. In addition, it will automatically update information about the conference room's equipment and environment when a change or cancellation occurs. For example, if a meeting that requires a projector is changed to another conference room, it will notify the system of the equipment information for the new conference room. In addition, a system will be developed that updates information about the conference room's equipment and environment in real time when a change or cancellation occurs. For example, if a change occurs in the conference room, it will immediately notify the system of the equipment information for the new conference room. This allows information about the conference room's equipment and environment to be simultaneously updated when a change or cancellation occurs.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The meeting information receiving unit can suggest the optimal meeting format and required devices based on the content and purpose of the meeting. For example, using a generative AI, it can analyze the content and purpose of the meeting and automatically suggest the optimal meeting format (e.g., presentation format, discussion format). For a project progress meeting, it can determine that a discussion format is appropriate. It can also automatically suggest the required devices (e.g., projector, whiteboard, video conferencing system) based on the content of the meeting. For meetings that include presentations, it can recommend a projector. Furthermore, a system can be built that analyzes the purpose of the meeting and suggests the optimal meeting format and devices. For a brainstorming meeting, it can recommend a whiteboard and markers. This makes it possible to suggest the optimal meeting format and devices according to the content and purpose of the meeting.

[0052] The conference information reception unit analyzes past conference data from each department, predicts frequently used conference rooms and time slots, and recommends advance reservations. For example, it collects past conference data from each department and analyzes frequently used conference rooms and time slots. If General Affairs Department A tends to hold meetings every Monday from 10:00 to 11:00, it prioritizes reservations for that time slot. It also predicts each department's meeting patterns based on past conference data and builds a system that suggests the optimal conference room and time slot in advance. It automatically suggests appropriate conference rooms and time slots for departments that hold many project progress meetings. It also develops an algorithm that analyzes each department's conference data and predicts frequently used conference rooms and time slots. If a specific department tends to hold meetings during a specific time slot, it prioritizes reservations for that time slot. This allows the optimal conference room and time slot to be reserved in advance based on past data.

[0053] The conference information receiving unit can use voice input or natural language processing to enable users to easily input information. For example, when entering conference information, a voice input function can be provided, allowing users to enter conference information simply by speaking. Information can be entered by simply speaking, "Project progress meeting, 10:00-11:00, Conference Room 1, 10 people, projector required." Furthermore, a system can be built that uses natural language processing technology to analyze text entered by users and automatically extract conference information. For example, if someone enters, "I'd like to reserve a conference for next Monday," the system will automatically set the date and time. Furthermore, a combination of voice input and natural language processing provides an interface that allows users to easily enter conference information. Information entered by voice is converted into text, and the necessary items are automatically extracted. This allows users to easily enter conference information.

[0054] The conference information reception unit can build a conference room sharing system between different companies and organizations, promoting the efficient use of available conference rooms. For example, a system for sharing conference rooms between different companies and organizations can be built to improve the efficiency of using available conference rooms. If a conference room at Company A is available, Company B can use that conference room. The conference room sharing system also allows different companies and organizations to check the availability of conference rooms in real time and make reservations. Company B can use the conference room during times when Company A has not reserved it. Furthermore, a common reservation platform is provided to promote the sharing of conference rooms between different companies and organizations. Multiple companies use the same system to reserve conference rooms and share availability information. This allows conference rooms to be shared between different companies and organizations, improving the efficiency of using available conference rooms.

[0055] The optimal allocation unit uses generative AI to consider the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. For example, a system can be built using generative AI to analyze the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. The optimal time is proposed taking into account the schedules of all participants. The optimal conference room is also automatically selected based on the content of the meeting. For meetings that include presentations, a conference room equipped with a projector is proposed. Furthermore, the schedules of the participants are analyzed in real time and the optimal meeting time is proposed. A time slot that allows everyone to participate is automatically selected. This makes it possible to propose the optimal conference room and time in real time based on the content of the meeting and the schedules of the participants.

[0056] The optimal allocation unit can improve overall utilization efficiency by analyzing conference room usage history and prioritizing the allocation of less frequently used conference rooms. For example, we will build a system that analyzes conference room usage history and prioritizes the allocation of less frequently used conference rooms. If a specific conference room is not used frequently, we will suggest that conference room as a priority. We will also develop an algorithm that improves overall utilization efficiency by prioritizing the allocation of less frequently used conference rooms. We will automatically select less frequently used conference rooms. Furthermore, we will introduce a system that prioritizes the allocation of less frequently used conference rooms based on the conference room usage history. We will suggest conference rooms that are not used during specific time periods. This will improve overall utilization efficiency based on the frequency of conference room usage.

[0057] The optimal allocation unit can also take into account the usage status of other resources when optimally allocating conference rooms. For example, we will build a system that takes into account the usage status of other resources, such as projectors and whiteboards, when optimally allocating conference rooms. For meetings that require a projector, we will suggest a conference room equipped with a projector. We will also analyze the usage status of other resources in real time and suggest the most suitable conference room. For meetings that require a whiteboard, we will suggest a conference room equipped with a whiteboard. Furthermore, we will develop an algorithm that takes into account the usage status of other resources when optimally allocating conference rooms. For meetings that require a videoconferencing system, we will suggest a conference room equipped with a videoconferencing system. This makes it possible to take into account the usage status of other resources when optimally allocating conference rooms.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The conference information reception unit receives conference information in advance. For example, each division, department, section, and group enters information such as the conference content, time, desired room, number of participants, and desired device into the system. Step 2: The optimal allocation unit allocates the optimal conference room and time based on the conference information received by the conference information receiving unit. For example, the optimal conference room and time are allocated taking into consideration the content of the conference, the number of participants, the desired devices, etc. Step 3: The notification unit notifies the conference room and time allocated by the optimal allocation unit. For example, it notifies each department of the reservation details. Step 4: The real-time update unit updates the reservation status of the conference room in real time, so that each department can check the current reservation status, for example. Step 5: The Change / Cancellation Department accepts changes or cancellations to reservations. For example, it provides a function for each department to change or cancel reservation details.

[0060] (Example 2) A conference room reservation system according to an embodiment of the present invention is a system that allows for fair use of conference rooms within a company. This system accepts information such as the content, time, desired room, number of participants, and desired device of a conference in advance for each organizational level, and allocates the optimal conference room and time. This allows each department to use conference rooms fairly, improving the efficiency of conference room usage.

[0061] The conference room reservation system according to the embodiment includes a conference information receiving unit, an optimal allocation unit, a notification unit, a real-time update unit, and a change / cancellation unit. The conference information receiving unit receives conference information in advance. For example, the conference information receiving unit inputs information such as the content, time, desired room, number of participants, and desired device for each division, department, section, and group into the system. The optimal allocation unit allocates the optimal conference room and time based on the conference information received by the conference information receiving unit. For example, the optimal allocation unit allocates the optimal conference room and time taking into consideration the content, number of participants, and desired device for the conference. The notification unit notifies each department of the conference room and time allocated by the optimal allocation unit. For example, the notification unit notifies each department of the reservation details. The real-time update unit updates the reservation status of the conference room in real time. For example, the real-time update unit allows each department to check the current reservation status. The change / cancellation unit accepts changes or cancellations of reservations. For example, the change / cancellation unit provides each department with the ability to change or cancel reservation details. This allows the conference room reservation system to allow each department to use conference rooms fairly, improving the efficiency of conference room usage.

[0062] The conference information receiving unit can use the generation AI to automatically suggest the optimal conference format and required devices based on the content and purpose of the conference. For example, the conference information receiving unit uses the generation AI to analyze the content and purpose of the conference and automatically suggest the optimal conference format (e.g., presentation format, discussion format). For example, in the case of a project progress meeting, it may determine that a discussion format is appropriate. It may also automatically suggest the required devices (e.g., projector, whiteboard, video conferencing system) based on the content of the conference. For example, it may recommend a projector for a conference that includes a presentation. It may also build a system that analyzes the purpose of the conference and suggests the optimal conference format and devices. For example, it may recommend a whiteboard and markers for a brainstorming conference. This makes it possible to suggest the optimal conference format and devices according to the content and purpose of the conference.

[0063] The conference information reception unit analyzes past conference data from each department, predicts frequently used conference rooms and time slots, and recommends advance reservations. For example, the conference information reception unit collects past conference data from each department and analyzes frequently used conference rooms and time slots. For example, if General Affairs Department A tends to hold meetings every Monday from 10:00 to 11:00, that time slot will be reserved preferentially. Furthermore, a system is constructed that predicts each department's meeting patterns based on past conference data and suggests optimal conference rooms and time slots in advance. For example, an appropriate conference room and time slot is automatically suggested for a department that holds many project progress meetings. Furthermore, an algorithm is developed that analyzes each department's conference data and predicts frequently used conference rooms and time slots. For example, if a specific department tends to hold meetings during a specific time slot, that time slot will be reserved preferentially. This allows the optimal conference room and time slot to be reserved in advance based on past data.

[0064] The conference information receiving unit can use the emotion estimation function to estimate the importance and urgency of a conference and set a priority. The conference information receiving unit, for example, uses the emotion estimation function to analyze the content of a conference and the emotional states of participants to estimate the importance and urgency of a conference. For example, conference rooms are preferentially allocated to conferences with high urgency. In addition, a system is constructed that sets priorities based on emotion estimation data to estimate the importance and urgency of a conference. For example, a high priority is set for an important project conference. In addition, the emotion estimation function is used to analyze the importance and urgency of a conference in real time and dynamically adjust the priority. For example, when a conference with a high urgency occurs, the priority of other conferences is lowered. In this way, priorities can be set according to the importance and urgency of a conference.

[0065] The conference information receiving unit can use voice input or natural language processing to enable users to easily input information. For example, when inputting conference information, the conference information receiving unit provides a voice input function, allowing users to input conference information simply by speaking. For example, information can be input simply by speaking, "Project progress meeting, 10:00-11:00, Conference Room 1, 10 people, Projector required." Furthermore, a system can be constructed that uses natural language processing technology to analyze text input by users and automatically extract conference information. For example, if a user inputs, "I would like to reserve a meeting for next Monday," the system automatically sets the date and time. Furthermore, a system can be provided that combines voice input and natural language processing to enable users to easily input conference information. For example, information input by voice can be converted into text and necessary items can be automatically extracted. This allows users to easily input conference information.

[0066] The conference information receiving unit can build a conference room sharing system between different companies and organizations, promoting the efficient use of available conference rooms. The conference information receiving unit, for example, builds a system for sharing conference rooms between different companies and organizations, improving the efficiency of using available conference rooms. For example, if a conference room at company A is available, company B can use that conference room. The conference room sharing system also allows different companies and organizations to check the availability of conference rooms in real time and make reservations. For example, company B can use a conference room during times when company A has not reserved it. A common reservation platform is also provided to promote the sharing of conference rooms between different companies and organizations. For example, multiple companies can use the same system to reserve conference rooms and share availability information. This allows conference rooms to be shared between different companies and organizations, improving the efficiency of using available conference rooms.

[0067] The conference information receiving unit can use the emotion estimation function to grasp the emotional state of conference participants in advance and provide an optimal conference environment. The conference information receiving unit, for example, uses the emotion estimation function to analyze the emotional state of conference participants in advance and provide an optimal conference environment. For example, if a participant is feeling stressed, a relaxing environment is suggested. Also, a system is constructed that monitors the emotional state of conference participants in real time and adjusts the conference environment as needed. For example, if a participant is tired, a break is provided. Also, based on the emotion estimation data, an optimal conference environment is provided for conference participants. For example, if a participant is nervous, relaxing music is played. In this way, an optimal conference environment can be provided according to the emotional state of the conference participants.

[0068] The optimal allocation unit uses generative AI to consider the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. For example, the optimal allocation unit uses generative AI to build a system that analyzes the content of the meeting and the schedules of the participants and proposes the optimal conference room and time in real time. For example, it proposes the optimal time taking into consideration the schedules of all participants. It also automatically selects the optimal conference room based on the content of the meeting. For example, it proposes a conference room equipped with a projector for a meeting that includes a presentation. It also analyzes the schedules of the participants in real time and proposes the optimal meeting time. For example, it automatically selects a time slot when everyone can participate. This makes it possible to propose the optimal conference room and time in real time based on the content of the meeting and the schedules of the participants.

[0069] The optimal allocation unit can improve overall utilization efficiency by analyzing the usage history of conference rooms and preferentially allocating less frequently used conference rooms. The optimal allocation unit, for example, analyzes the usage history of conference rooms and builds a system that preferentially allocates less frequently used conference rooms. For example, if a specific conference room is not used frequently, it will preferentially suggest that conference room. In addition, an algorithm is developed that improves overall utilization efficiency by preferentially allocating less frequently used conference rooms. For example, it automatically selects less frequently used conference rooms. In addition, a system is introduced that preferentially allocates less frequently used conference rooms based on the usage history of conference rooms. For example, it will suggest conference rooms that are not used during specific time periods. In this way, overall utilization efficiency is improved based on the frequency of conference room usage.

[0070] The optimal allocation unit can use the emotion estimation function to suggest a relaxing environment and time period based on the emotional state of the participants. The optimal allocation unit, for example, uses the emotion estimation function to analyze the emotional state of the participants and build a system that suggests a relaxing environment and time period. For example, if a participant is feeling stressed, it suggests a relaxing time period. It also monitors the participants' emotional state in real time to provide an optimal meeting environment. For example, if a participant is tired, it suggests a relaxing conference room. It also suggests an optimal meeting environment and time period for the participants based on the emotion estimation data. For example, if a participant is tense, it suggests a relaxing time period. In this way, it is possible to suggest a relaxing environment and time period based on the participants' emotional state.

[0071] The optimal allocation unit can also take into account the usage status of other resources when optimally allocating conference rooms. For example, the optimal allocation unit builds a system that takes into account the usage status of other resources, such as projectors and whiteboards, when optimally allocating conference rooms. For example, for a conference room that requires a projector, it will suggest a conference room equipped with a projector. It also analyzes the usage status of other resources in real time and suggests the optimal conference room. For example, for a conference room that requires a whiteboard, it will suggest a conference room equipped with a whiteboard. It also develops an algorithm that takes into account the usage status of other resources when optimally allocating conference rooms. For example, for a conference room that requires a video conferencing system, it will suggest a conference room equipped with a video conferencing system. This makes it possible to take into account the usage status of other resources when optimally allocating conference rooms.

[0072] The optimal allocation unit promotes the sharing of conference rooms between different departments, making effective use of available time. The optimal allocation unit, for example, builds a system for sharing conference rooms between different departments, making effective use of available time. For example, it allows general department B to use a conference room during times when general department A is not using it. In addition, to promote conference room sharing, a system is introduced that shares reservation status between different departments in real time. For example, general department B uses a conference room during times when general department A has not reserved it. In addition, to promote conference room sharing between different departments, a common reservation platform is provided. For example, multiple departments use the same system to reserve conference rooms and share availability status. This promotes conference room sharing between different departments, making effective use of available time.

[0073] The optimal allocation unit uses the emotion estimation function to monitor the emotional state of meeting participants in real time, and can readjust meeting rooms and times as necessary. The optimal allocation unit, for example, uses the emotion estimation function to build a system that monitors the emotional state of meeting participants in real time, and readjusts meeting rooms and times as necessary. For example, if a participant is feeling stressed, it will suggest a meeting room where they can relax. It also analyzes the participants' emotional states in real time to provide an optimal meeting environment. For example, if a participant is tired, it will suggest a time period where they can relax. It also develops a system that dynamically adjusts meeting rooms and times based on emotion estimation data. For example, it will delay the start time of a meeting depending on the participants' emotional state. This makes it possible to readjust meeting rooms and times based on the emotional state of meeting participants.

[0074] The notification unit can use the generation AI to notify additional suggestions and points of caution based on the purpose and content of the meeting when the reservation details are confirmed. For example, the notification unit uses the generation AI to build a system that analyzes the purpose and content of the meeting when the reservation details are confirmed and notifies additional suggestions and points of caution. For example, it notifies if a projector is needed. It also automatically generates and notifies additional suggestions and points of caution based on the purpose and content of the meeting. For example, it suggests that meeting participants share materials in advance. It also uses the generation AI to analyze the purpose and content of the meeting when the reservation details are confirmed and notifies necessary preparations. For example, it notifies the user to check the necessary devices before the meeting. This makes it possible to notify additional suggestions and points of caution based on the purpose and content of the meeting.

[0075] The notification unit can integrate the schedules of each department and automatically detect and notify overlaps and conflicts. The notification unit, for example, builds a system that integrates the schedules of each department and automatically detects overlaps and conflicts. For example, it notifies users when multiple meetings overlap in the same time slot. It also automatically detects schedule overlaps and conflicts and notifies each department. For example, it suggests an alternative conference room if a conference room is already reserved. It also develops an algorithm that analyzes each department's schedule in real time and detects overlaps and conflicts. For example, it notifies users when multiple meetings conflict in the same time slot. This makes it possible to integrate the schedules of each department and automatically detect and notify users of overlaps and conflicts.

[0076] The notification unit can use the emotion estimation function to adjust the timing and content of reminders based on the emotional state of the participants. For example, the notification unit uses the emotion estimation function to build a system that analyzes the emotional state of participants and adjusts the timing and content of reminders. For example, if a participant is feeling stressed, the timing of the reminder is delayed. Also, the emotional state of participants is monitored in real time and the content of the reminder is adjusted. For example, if a participant is tired, the content of the reminder is made brief. Furthermore, a system is developed that dynamically adjusts the timing and content of reminders based on the emotion estimation data. For example, the frequency of reminders is adjusted according to the emotional state of the participants. This makes it possible to adjust the timing and content of reminders based on the emotional state of the participants.

[0077] The notification unit can diversify notification methods and send notifications via at least one of email, SMS, and chat apps. For example, the notification unit builds a system that sends confirmation notifications for conference room reservations via multiple channels, such as email, SMS, and chat apps. For example, the details of the conference reservation can be sent simultaneously via email and a chat app. In addition, the notification method can be diversified so that users can receive notifications via their preferred channel. For example, users who request email notifications can be notified by email, and users who request SMS notifications can be notified by SMS. In addition, a system can be developed that integrates multiple notification channels and allows users to receive notifications via the method that is most convenient for them. For example, notifications can be sent in conjunction with a chat app. This makes it possible to diversify notification methods and send notifications via multiple channels.

[0078] The notification unit can also provide information about the conference room's facilities and environment at the same time when a conference room reservation is confirmed. For example, the notification unit will build a system that simultaneously provides information about the conference room's facilities and environment when a conference room reservation is confirmed. For example, it will notify the user whether a projector or whiteboard is available. Information about the conference room's facilities and environment will also be automatically displayed when a reservation is confirmed. For example, it will notify the user of the conference room's size and number of seats. A system will also be developed that provides detailed information about the facilities and environment when a conference room reservation is confirmed. For example, it will notify the user of photos of the conference room and how to use the facilities. This makes it possible to simultaneously provide information about the facilities and environment when a conference room reservation is confirmed.

[0079] The notification unit can use the emotion estimation function to personalize the notification content based on the emotional state of the participant. The notification unit, for example, uses the emotion estimation function to analyze the emotional state of the participant and build a system that personalizes the notification content. For example, if a participant is feeling stressed, the notification content will be relaxed. The notification unit also monitors the participant's emotional state in real time and dynamically adjusts the notification content. For example, if a participant is tired, a concise notification content will be provided. Furthermore, a system that personalizes the notification content based on the emotion estimation data is developed. For example, the notification content is customized according to the participant's emotional state. This makes it possible to personalize the notification content based on the participant's emotional state.

[0080] The real-time update unit uses generation AI to predict changes in reservation status in real time and automatically suggest available times. The real-time update unit, for example, uses generation AI to build a system that predicts changes in reservation status in real time and automatically suggests available times. For example, if a meeting is canceled, it will immediately suggest available times. In addition, an algorithm will be developed that analyzes changes in reservation status in real time and automatically suggests available times. For example, it will suggest available times if a meeting ends earlier than planned. In addition, a system will be introduced that uses generation AI to predict changes in reservation status and suggest available times in real time. For example, it will suggest available times if the start time of a meeting is delayed. This makes it possible to predict changes in reservation status in real time and automatically suggest available times.

[0081] The real-time update unit can visualize the usage status of conference rooms and provide a dashboard that each department can intuitively understand. The real-time update unit, for example, builds a system that visualizes the usage status of conference rooms and provides a dashboard that each department can intuitively understand. For example, it displays the reservation status of conference rooms in graphs and charts. It also updates the usage status in real time and provides a dashboard that each department can intuitively understand. For example, it displays the availability of conference rooms in color. It also develops a dashboard to visualize the usage status of conference rooms and makes it easy for each department to use. For example, it displays the reservation status of conference rooms in calendar format. This visualizes the usage status of conference rooms and provides a dashboard that each department can intuitively understand.

[0082] The real-time update unit can use the emotion estimation function to adjust the reservation status update frequency and notification method based on the emotional state of the participant. For example, the real-time update unit uses the emotion estimation function to build a system that analyzes the emotional state of the participant and adjusts the reservation status update frequency and notification method. For example, if a participant is feeling stressed, the notification frequency is reduced. The real-time update unit also monitors the participant's emotional state in real time and dynamically adjusts the reservation status update frequency and notification method. For example, if a participant is tired, the notification method is simplified. Furthermore, a system is developed that personalizes the reservation status update frequency and notification method based on the emotion estimation data. For example, the notification content is customized according to the participant's emotional state. This makes it possible to adjust the reservation status update frequency and notification method based on the participant's emotional state.

[0083] The real-time update unit can also update the usage status of other resources in real time and manage them in an integrated manner. The real-time update unit, for example, builds a system that updates the usage status of other resources (for example, projectors and whiteboards) in real time and manages them in an integrated manner. For example, it displays the usage status of projectors in real time. It also updates the usage status of resources in real time and manages them in an integrated manner with the reservation status of conference rooms. For example, it displays the usage status of whiteboards together with the reservation status of conference rooms. It also provides a dashboard that updates the usage status of other resources in real time and manages them in an integrated manner. For example, it makes it possible to check the usage status of projectors and whiteboards at a glance. This allows the usage status of other resources to be updated in real time and managed in an integrated manner.

[0084] The real-time update unit can share reservation status between different departments and promote cooperation to make effective use of available time. The real-time update unit, for example, builds a system that shares reservation status between different departments and promotes cooperation to make effective use of available time. For example, it allows general department B to use a conference room during times when general department A is not using it. It also shares reservation status in real time and promotes cooperation between different departments. For example, it allows general department B to use a conference room during times when general department A has not reserved it. It also provides a platform for sharing reservation status between different departments, making effective use of available time. For example, multiple departments use the same system to reserve conference rooms and share availability status. This allows reservation status to be shared between different departments and promotes cooperation to make effective use of available time.

[0085] The real-time update unit can use the emotion estimation function to personalize the reservation status update content based on the emotional state of the participant. The real-time update unit, for example, uses the emotion estimation function to analyze the emotional state of the participant and build a system that personalizes the reservation status update content. For example, if a participant is feeling stressed, it notifies them of relaxation content. It also monitors the participant's emotional state in real time and dynamically adjusts the reservation status update content. For example, if a participant is tired, it provides a concise notification content. It also develops a system that personalizes the reservation status update content based on the emotion estimation data. For example, it customizes the notification content according to the participant's emotional state. This makes it possible to personalize the reservation status update content based on the participant's emotional state.

[0086] The change / cancellation unit can use generation AI to automatically propose the optimal alternative when a change or cancellation occurs. For example, the change / cancellation unit uses generation AI to build a system that automatically proposes the optimal alternative when a reservation is changed or canceled. For example, if a conference room is canceled, it will propose another available conference room. In addition, when a change or cancellation occurs, the generation AI will propose the optimal alternative in real time. For example, if the meeting time is changed, it will propose another available time slot. In addition, a system will be developed using generation AI that automatically generates the optimal alternative and notifies the user when a change or cancellation occurs. For example, if a conference room needs to be changed, it will propose another conference room. This makes it possible to automatically propose the optimal alternative when a change or cancellation occurs.

[0087] The Changes and Cancellations Department analyzes the history of changes and cancellations, identifies departments and time periods where changes frequently occur, and can take measures to address them. For example, the Changes and Cancellations Department builds a system that collects the history of changes and cancellations and analyzes departments and time periods where changes frequently occur. For example, if a specific department frequently cancels meetings, it identifies the cause. Furthermore, based on the history of changes and cancellations, it identifies time periods where changes frequently occur and takes measures to address them. For example, it adjusts schedules so that meetings do not concentrate in specific time periods. It also analyzes the history of changes and cancellations and develops an algorithm to identify departments and time periods where changes frequently occur. For example, if a specific department tends to change meetings at a specific time period, it suggests avoiding that time period. This makes it possible to analyze the history of changes and cancellations, identify departments and time periods where changes frequently occur, and take measures to address them.

[0088] The change / cancellation unit can use the emotion estimation function to adjust the notification content taking into account the participant's emotional state when making changes or cancellations. For example, the change / cancellation unit uses the emotion estimation function to build a system that analyzes the participant's emotional state when making changes or cancellations and adjusts the notification content. For example, if a participant is feeling stressed, it can notify them of relaxation content. In addition, when making changes or cancellations, it monitors the participant's emotional state in real time and dynamically adjusts the notification content. For example, if a participant is tired, it can provide a concise notification. In addition, we develop a system that personalizes the notification content when making changes or cancellations based on the emotion estimation data. For example, it customizes the notification content according to the participant's emotional state. This makes it possible to adjust the notification content taking into account the participant's emotional state when making changes or cancellations.

[0089] The Changes and Cancellations Department will be able to make adjustments to minimize the impact on other departments when changes or cancellations are made. The Changes and Cancellations Department will build a system that makes adjustments to minimize the impact on other departments when changes or cancellations are made. For example, if a conference room needs to be changed, the adjustment will take into account the reservation status of other departments. In addition, an algorithm will be developed that automatically makes adjustments when changes or cancellations are made to minimize the impact on other departments. For example, if a meeting time is changed, the adjustment will be made to prevent conflicts with meetings in other departments. In addition, a system will be introduced that analyzes the impact on other departments in real time when changes or cancellations are made and makes optimal adjustments. For example, if a conference room needs to be changed, the adjustment will take into account the reservation status of other departments. This will enable adjustments to minimize the impact on other departments when changes or cancellations are made.

[0090] The change / cancellation unit can simultaneously update information about the conference room's equipment and environment when a change or cancellation occurs. The change / cancellation unit will build a system that simultaneously updates information about the conference room's equipment and environment when a change or cancellation occurs. For example, if a change occurs in the conference room, it will notify the system of the equipment information for the new conference room. In addition, it will automatically update information about the conference room's equipment and environment when a change or cancellation occurs. For example, if a meeting that requires a projector is changed to another conference room, it will notify the system of the equipment information for the new conference room. In addition, a system will be developed that updates information about the conference room's equipment and environment in real time when a change or cancellation occurs. For example, if a change occurs in the conference room, it will immediately notify the system of the equipment information for the new conference room. This allows information about the conference room's equipment and environment to be simultaneously updated when a change or cancellation occurs.

[0091] The change / cancellation unit can use the emotion estimation function to propose optimal alternatives based on the participant's emotional state when a change or cancellation is made. For example, the change / cancellation unit uses the emotion estimation function to build a system that analyzes the participant's emotional state when a change or cancellation is made and proposes optimal alternatives. For example, if a participant is feeling stressed, it proposes relaxing alternatives. Furthermore, when a change or cancellation is made, the system monitors the participant's emotional state in real time and dynamically proposes optimal alternatives. For example, if a participant is tired, it provides a concise alternative. Furthermore, a system is developed that personalizes alternatives when a change or cancellation is made based on emotion estimation data. For example, it customizes alternatives according to the participant's emotional state. This makes it possible to propose optimal alternatives based on the participant's emotional state when a change or cancellation is made.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The meeting information receiving unit can suggest the optimal meeting format and required devices based on the content and purpose of the meeting. For example, using a generative AI, it can analyze the content and purpose of the meeting and automatically suggest the optimal meeting format (e.g., presentation format, discussion format). For a project progress meeting, it can determine that a discussion format is appropriate. It can also automatically suggest the required devices (e.g., projector, whiteboard, video conferencing system) based on the content of the meeting. For meetings that include presentations, it can recommend a projector. Furthermore, a system can be built that analyzes the purpose of the meeting and suggests the optimal meeting format and devices. For a brainstorming meeting, it can recommend a whiteboard and markers. This makes it possible to suggest the optimal meeting format and devices according to the content and purpose of the meeting.

[0094] The conference information reception unit analyzes past conference data from each department, predicts frequently used conference rooms and time slots, and recommends advance reservations. For example, it collects past conference data from each department and analyzes frequently used conference rooms and time slots. If General Affairs Department A tends to hold meetings every Monday from 10:00 to 11:00, it prioritizes reservations for that time slot. It also predicts each department's meeting patterns based on past conference data and builds a system that suggests the optimal conference room and time slot in advance. It automatically suggests appropriate conference rooms and time slots for departments that hold many project progress meetings. It also develops an algorithm that analyzes each department's conference data and predicts frequently used conference rooms and time slots. If a specific department tends to hold meetings during a specific time slot, it prioritizes reservations for that time slot. This allows the optimal conference room and time slot to be reserved in advance based on past data.

[0095] The conference information receiving unit can use the emotion estimation function to estimate the importance and urgency of a conference and set a priority. For example, the emotion estimation function is used to analyze the content of the conference and the emotional state of the participants to estimate the importance and urgency of the conference. Conference rooms are preferentially allocated to conferences with high urgency. Furthermore, a system is constructed that sets priorities based on emotion estimation data to estimate the importance and urgency of a conference. A high priority is set for important project conferences. Furthermore, the emotion estimation function is used to analyze the importance and urgency of a conference in real time and dynamically adjust the priority. When a conference with a high urgency occurs, the priority of other conferences is lowered. This makes it possible to set priorities according to the importance and urgency of a conference.

[0096] The conference information receiving unit can use voice input or natural language processing to enable users to easily input information. For example, when entering conference information, a voice input function can be provided, allowing users to enter conference information simply by speaking. Information can be entered by simply speaking, "Project progress meeting, 10:00-11:00, Conference Room 1, 10 people, projector required." Furthermore, a system can be built that uses natural language processing technology to analyze text entered by users and automatically extract conference information. For example, if someone enters, "I'd like to reserve a conference for next Monday," the system will automatically set the date and time. Furthermore, a combination of voice input and natural language processing provides an interface that allows users to easily enter conference information. Information entered by voice is converted into text, and the necessary items are automatically extracted. This allows users to easily enter conference information.

[0097] The conference information reception unit can build a conference room sharing system between different companies and organizations, promoting the efficient use of available conference rooms. For example, a system for sharing conference rooms between different companies and organizations can be built to improve the efficiency of using available conference rooms. If a conference room at Company A is available, Company B can use that conference room. The conference room sharing system also allows different companies and organizations to check the availability of conference rooms in real time and make reservations. Company B can use the conference room during times when Company A has not reserved it. Furthermore, a common reservation platform is provided to promote the sharing of conference rooms between different companies and organizations. Multiple companies use the same system to reserve conference rooms and share availability information. This allows conference rooms to be shared between different companies and organizations, improving the efficiency of using available conference rooms.

[0098] The conference information receiving unit can use the emotion estimation function to grasp the emotional state of conference participants in advance and provide the optimal conference environment. For example, the emotion estimation function can be used to analyze the emotional state of conference participants in advance and provide the optimal conference environment. If a participant is feeling stressed, a relaxing environment can be suggested. Also, a system can be built that monitors the emotional state of conference participants in real time and adjusts the conference environment as needed. If a participant is tired, a break can be provided. Furthermore, based on the emotion estimation data, the optimal conference environment can be provided for conference participants. If a participant is tense, relaxing music can be played. This makes it possible to provide the optimal conference environment according to the emotional state of the conference participants.

[0099] The optimal allocation unit uses generative AI to consider the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. For example, a system can be built using generative AI to analyze the content of the meeting and the schedules of the participants and propose the optimal conference room and time in real time. The optimal time is proposed taking into account the schedules of all participants. The optimal conference room is also automatically selected based on the content of the meeting. For meetings that include presentations, a conference room equipped with a projector is proposed. Furthermore, the schedules of the participants are analyzed in real time and the optimal meeting time is proposed. A time slot that allows everyone to participate is automatically selected. This makes it possible to propose the optimal conference room and time in real time based on the content of the meeting and the schedules of the participants.

[0100] The optimal allocation unit can improve overall utilization efficiency by analyzing conference room usage history and prioritizing the allocation of less frequently used conference rooms. For example, we will build a system that analyzes conference room usage history and prioritizes the allocation of less frequently used conference rooms. If a specific conference room is not used frequently, we will suggest that conference room as a priority. We will also develop an algorithm that improves overall utilization efficiency by prioritizing the allocation of less frequently used conference rooms. We will automatically select less frequently used conference rooms. Furthermore, we will introduce a system that prioritizes the allocation of less frequently used conference rooms based on the conference room usage history. We will suggest conference rooms that are not used during specific time periods. This will improve overall utilization efficiency based on the frequency of conference room usage.

[0101] The optimal allocation unit can use the emotion estimation function to suggest a relaxing environment and time period based on the emotional state of the participants. For example, a system can be constructed that uses the emotion estimation function to analyze the emotional state of participants and suggest a relaxing environment and time period. If a participant is feeling stressed, a relaxing time period can be suggested. In addition, the emotional state of participants can be monitored in real time to provide the optimal meeting environment. If a participant is tired, a relaxing conference room can be suggested. Furthermore, based on the emotion estimation data, a meeting environment and time period that is optimal for the participant can be suggested. If a participant is tense, a relaxing time period can be suggested. In this way, a relaxing environment and time period can be suggested based on the emotional state of the participants.

[0102] The optimal allocation unit can also take into account the usage status of other resources when optimally allocating conference rooms. For example, we will build a system that takes into account the usage status of other resources, such as projectors and whiteboards, when optimally allocating conference rooms. For meetings that require a projector, we will suggest a conference room equipped with a projector. We will also analyze the usage status of other resources in real time and suggest the most suitable conference room. For meetings that require a whiteboard, we will suggest a conference room equipped with a whiteboard. Furthermore, we will develop an algorithm that takes into account the usage status of other resources when optimally allocating conference rooms. For meetings that require a videoconferencing system, we will suggest a conference room equipped with a videoconferencing system. This makes it possible to take into account the usage status of other resources when optimally allocating conference rooms.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The conference information reception unit receives conference information in advance. For example, each division, department, section, and group enters information such as the conference content, time, desired room, number of participants, and desired device into the system. Step 2: The optimal allocation unit allocates the optimal conference room and time based on the conference information received by the conference information receiving unit. For example, the optimal conference room and time are allocated taking into consideration the content of the conference, the number of participants, the desired devices, etc. Step 3: The notification unit notifies the conference room and time allocated by the optimal allocation unit. For example, it notifies each department of the reservation details. Step 4: The real-time update unit updates the reservation status of the conference room in real time, so that each department can check the current reservation status, for example. Step 5: The Change / Cancellation Department accepts changes or cancellations to reservations. For example, it provides a function for each department to change or cancel reservation details.

[0105] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0106] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 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.

[0110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0111] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0112] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0113] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0114] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0115] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0116] 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.

[0117] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0118] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0119] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0120] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0125] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0126] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0127] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0128] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0129] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0130] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0131] 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.

[0132] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0133] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0134] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0135] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0136] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0137] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0140] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0141] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0142] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0143] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0144] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0145] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0146] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0147] 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.

[0148] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0149] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0150] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0151] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0154] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0155] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0156] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0157] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0158] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0159] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0160] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0161] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0162] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0163] 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.

[0164] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0165] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0166] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0167] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0168] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0169] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0170] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0171] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0172] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a conference information receiving unit that receives conference information in advance; an optimal allocation unit that allocates an optimal conference room and time based on the conference information received by the conference information receiving unit; a notification unit that notifies the conference room and time allocated by the optimal allocation unit; A real-time update unit that updates the reservation status of conference rooms in real time; A change / cancellation unit that accepts changes or cancellations to reservations. A system characterized by:

2. The conference information receiving unit Using generative AI, it automatically suggests the optimal meeting format and required devices based on the content and purpose of the meeting.

2. The system of claim 1.

3. The conference information receiving unit Analyze past meeting data from each department to predict frequently used meeting rooms and time slots and recommend advance reservations 2. The system of claim 1.

4. The conference information receiving unit Estimate the importance and urgency of meetings and set priorities 2. The system of claim 1.

5. The conference information receiving unit Allow users to easily enter information using voice input or natural language processing 2. The system of claim 1.

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