system

Abstract

We provide the system. [Solution] A data entry method for receiving date, time, theme, and participant information, A keyword generation means that generates related keywords based on theme information received from a data input means, An image generation means that generates related images using related keywords generated by a keyword generation means, A system including projection means for projecting images generated by image generation means onto walls inside and outside a conference room.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, in order to enhance the effectiveness of meetings and conferences, the impact of the physical environment on participants has been emphasized. However, general meeting rooms often have a fixed design, and it is difficult to provide a flexible environment according to the theme and time zone. Therefore, it is difficult to improve the motivation and concentration of participants, which also affects the quality of meetings. There is a demand for a system that solves this problem and provides an optimal environment according to the theme and time zone of the meeting.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means. First, basic meeting information is obtained by receiving the date, time, theme, and participant information through a data input means. Next, relevant keywords are generated based on the received theme information using a keyword generation means. Furthermore, relevant images are generated using the generated relevant keywords using an image generation means. Finally, the generated images are projected onto the walls inside and outside the meeting room using a projection means, thereby providing an optimal environment according to the meeting's theme and time of day. Through these means, it is possible to enhance participants' motivation and concentration, and improve the quality of the meeting.

[0006] A "data entry method" is an interface for receiving information such as the date, time, theme, and participants of a meeting.

[0007] A "keyword generation means" is a means for generating relevant keywords based on theme information received by a data input means.

[0008] "Image generation means" refers to a model and process for generating a corresponding image using relevant keywords generated by keyword generation means.

[0009] "Projection means" refers to devices and technologies for displaying images generated by image generation means on walls inside and outside a conference room, and includes glass wall displays and projectors.

[0010] "Meeting start time" refers to the pre-set scheduled start time of the meeting, and is the basis for managing the schedule by which the projection device displays images.

[0011] A "slideshow format" is a method of displaying multiple images by switching between them sequentially at regular time intervals. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, a communication I / F (Interface) with a reference numeral is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] System Overview

[0034] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. The following explains, with specific examples, how the server, terminal, and user each operate.

[0035] User input of meeting room reservation information

[0036] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, if a user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data will be sent to the system.

[0037] Keyword generation by the server

[0038] Server: After receiving reservation information, it uses an LLM (Large-Scale Language Model) to generate keywords related to the theme. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0039] Image generation by the server

[0040] Server: After keyword generation, the server uses image generation models such as SD (Stable Diffusion) to generate images based on these keywords. For example, it generates an image of a "beautiful forest landscape" from the keyword "forest," and an image of a "lake and mountain landscape" from the keyword "beautiful landscape."

[0041] Receiving image data via the terminal and preparing for projection.

[0042] Terminal: Receives image data generated from the server and converts it to the required format. Then, it prepares the image data for use with projectors and glass wall displays.

[0043] Projection of an image by projection means

[0044] Terminal: Project images onto a projector or glass wall display in accordance with the meeting start time. For example, project an image of a "beautiful forest landscape" onto the wall at "14:00," and then switch to an image of a "lake and mountain landscape" 15 minutes later.

[0045] User usage

[0046] User: When a meeting begins, images related to the theme are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing a "beautiful forest landscape" can refresh the mind and lead to a more lively discussion.

[0047] result

[0048] This allows the meeting room design to change according to the meeting's theme and time of day, thereby increasing participants' motivation and concentration. It also contributes to improving the quality of the meeting.

[0049] The system of this invention operates seamlessly, from user operation to data processing on the server and image projection on the terminal, enabling efficient management and optimization of the meeting environment.

[0050] The following describes the processing flow.

[0051] Step 1: User enters meeting room reservation information.

[0052] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, the user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0053] Step 2: Server receives and stores reservation information.

[0054] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0055] Step 3: Keyword Generation

[0056] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0057] Step 4: Image generation

[0058] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0059] Step 5: Convert image data format

[0060] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0061] Step 6: Schedule Management

[0062] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0063] Step 7: Projecting the Image

[0064] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0065] Step 8: User Use

[0066] User: Enters the meeting room and sees the displayed images. Users become relaxed or more focused by the topic-related images. As a result, discussion becomes more lively and the quality of the meeting improves.

[0067] This series of steps allows the meeting room design to change according to the theme and time, providing an effective meeting environment.

[0068] (Example 1)

[0069] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0070] Traditional meeting room systems were unable to change the meeting room design in real time based on reservation information, making it difficult to optimize meeting themes and participant motivation. Furthermore, the manual operation required to change the meeting environment design was cumbersome, hindering efficient management. Additionally, the lack of sufficient automation for image generation and projection compromised user convenience.

[0071] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0072] In this invention, the server includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means. This allows users to simply input meeting reservation information, and based on that information, images are generated in real time, format converted, and projected into the meeting room. This automatically provides an optimal environment for the meeting theme and enhances participants' concentration, thereby improving meeting quality and achieving efficient environment management.

[0073] "Data entry means" refers to an interface for users to enter meeting room reservation information, and has the function of accepting information such as date and time, theme, and participant information.

[0074] A "keyword generation means" is a component that has the function of generating relevant keywords based on theme information received from a data input means. Specifically, it generates keywords using a generation AI model.

[0075] An "image generation means" is a component that has the function of generating a corresponding image using an image generation model based on keywords generated by a keyword generation means.

[0076] The "image receiving and format conversion means" is a component that has the function of receiving image data transmitted from a server and converting it into a format suitable for output devices such as projectors and displays.

[0077] A "projection means" is a component that has the function of projecting prepared images onto a projector or display placed in the conference room, and also includes the function of switching images based on set times or events.

[0078] System Overview

[0079] This invention relates to a system that changes the design of a conference room in real time according to the conference room reservation details and the office theme. The system includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means.

[0080] User input of meeting room reservation information

[0081] Users enter meeting room reservation information (date, time, theme, participants, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0082] Keyword generation by the server

[0083] After receiving the reservation information, the server uses a generative AI model (for example, a type of large-scale language model) to generate keywords related to the theme. If the prompt is "Generate keywords related to the theme 'natural environment'", keywords such as "forest", "beautiful scenery", and "fresh air" will be generated.

[0084] Image generation by the server

[0085] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. Specifically, if the keyword is "forest" and the prompt "Generate an image of a beautiful forest landscape" is entered, the image generation model will generate an image file based on that prompt. Images will be generated similarly for other keywords.

[0086] Receiving image data via the terminal and preparing for projection.

[0087] The terminal receives image data sent from the server. After receiving the data, the terminal converts the image data into a format optimized for projectors and glass wall displays. Specifically, the conversion process involves resizing the image file resolution to 1920x1080 and converting it to an appropriate file format (such as JPEG or PNG).

[0088] Projection of an image by projection means

[0089] The device projects images onto a projector or glass wall display in accordance with the meeting start time. For example, at 14:00, it projects an image of a "beautiful forest landscape" onto the wall, and then switches to an image of a "lake and mountain landscape" 15 minutes later. This projection schedule is managed by the device's timer function.

[0090] User usage

[0091] At the start of a meeting, users are shown images related to the theme projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing the displayed "beautiful forest scenery" can be refreshing and lead to a more lively discussion.

[0092] result

[0093] This system allows the meeting room design to dynamically change according to the meeting's theme and time of day, providing an environment that enhances participants' motivation and concentration. This, in turn, improves the quality of meetings and enables more efficient management.

[0094] Examples of prompt statements

[0095] The following are examples of prompts to input into a generative AI model:

[0096] Prompt: "The meeting theme is 'Natural Environment,' please generate related keywords."

[0097] Example output: Forest, beautiful scenery, fresh air

[0098] Prompt: "Generate images of beautiful forest landscapes using the keyword 'forest'."

[0099] Output example: - Image file -

[0100] Prompt: "Generate images of lake and mountain scenery from the keyword 'beautiful scenery'."

[0101] Output example: - Image file -

[0102] This prompt clearly shows the user how the entire system works and how specific results are produced.

[0103] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0104] Step 1:

[0105] Users enter meeting room reservation information using a dedicated web application or terminal. (Input) Date and time, theme, and participant information. (Output) The reservation information is saved in the system's database. For example, a specific action would be for a user to enter details such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" into a web form.

[0106] Step 2:

[0107] The server retrieves reservation information from the database and generates keywords based on theme information. (Input) Reservation information (theme, etc.). (Prompt to the generating AI model: "Generate keywords related to the theme 'Natural Environment'") (Output) Generated keywords (e.g., forest, beautiful scenery, fresh air). For example, the server uses a generating AI model to extract keywords from the theme.

[0108] Step 3:

[0109] The server uses the generated keywords and an image generation model to generate the corresponding image. (Input) Keywords (e.g., forest, beautiful landscape). (Prompt to the image generation model: "Generate an image of a beautiful forest landscape.") (Output) Generated image file (e.g., forest landscape image). For example, this process includes "Generating an image of a beautiful forest landscape based on the keyword 'forest'."

[0110] Step 4:

[0111] The terminal receives image data sent from the server and converts it to the format best suited to the display device. (Input) The generated image file. (Output) The converted image file (e.g., a JPEG file resized to a resolution suitable for a projector). Specifically, the received image is resized to a resolution of 1920x1080, and other image format conversions are performed.

[0112] Step 5:

[0113] The device projects an image onto a projector or glass wall display in time with the start of the meeting. (Input) Converted image file. (Output) Image projected onto the wall or screen. Specifically, projection starts based on the timer setting; for example, it projects a "beautiful forest landscape" at "14:00" and automatically switches to a "lake and mountain landscape" 15 minutes later.

[0114] Step 6:

[0115] The device changes the projected image during a meeting based on user instructions or timer settings. (Input) User instructions or pre-set timer information. (Output) The changed new image is displayed. Specifically, the user can instruct the user to change the image from a smartphone app, or the device will automatically switch to the next image according to a set timer.

[0116] Step 7:

[0117] After a meeting, users provide feedback on the quality of the meeting and the participants' engagement through the system's evaluation function. (Input) Feedback data (e.g., survey responses). (Output) Feedback data stored on the server. For example, users might answer questions such as, "Were the projected images during the meeting helpful for the discussion?" in a post-meeting survey.

[0118] (Application Example 1)

[0119] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0120] Traditional store design and atmosphere changes are often done manually, which is time-consuming and labor-intensive. Furthermore, it's difficult to change the design in real time according to the season or theme, making it difficult to maintain customer interest. This diminishes the store's appeal and hinders customer engagement.

[0121] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0122] In this invention, the server includes data input means, keyword generation means, image generation means, display modification means, and projection means. This makes it possible to change the design and atmosphere of the store interior in real time according to the store's theme or season.

[0123] "Data entry means" refers to the means by which users input the date and time, theme, and user information.

[0124] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0125] "Image generation means" refers to means for generating images based on the generated keywords.

[0126] "Projection means" refers to means for projecting the generated image onto a display device such as a projector or display.

[0127] "Display modification means" refers to means of changing the design or atmosphere inside a store in real time.

[0128] "Date and time" refers to information that specifies a particular year, month, day, and time.

[0129] A "theme" is a specific concept or idea based on the user's intentions and objectives.

[0130] "User information" refers to information about individuals participating in meetings, events, etc.

[0131] "Related keywords" are concepts or words that correspond to the theme.

[0132] "Store interior" refers to the interior space of a physical store.

[0133] "Design" refers to the visual appearance and layout.

[0134] "Atmosphere" refers to the emotions and environment one feels within a space.

[0135] The present invention provides a system for implementing a function that changes the design of a meeting room in real time according to the reservation details and theme of the meeting room. This system operates in a seamless collaboration between the server, terminal, and user.

[0136] First, users enter meeting room reservation information (date and time, theme, user information, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0137] The server generates keywords related to the theme using an LLM (Large-Scale Language Model) based on the received reservation information. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." In this process, it uses generative AI models such as OpenAI® GPT-3®.

[0138] Next, the server generates related images based on the generated keywords using image generation models such as SD (Stable Diffusion). For example, it generates multiple images such as "beautiful forest scenery" from the keyword "forest," and "lake and mountain scenery" from the keyword "beautiful scenery."

[0139] The terminal receives image data transmitted from the server and converts it to an appropriate format. This format conversion is performed so that the image is optimized for projection means such as projectors or glass wall displays.

[0140] Finally, the projection system projects images according to the meeting start time. For example, at 14:00, an image of a beautiful forest landscape is projected onto the wall, and 15 minutes later, it switches to an image of a lake and mountain landscape, promoting user concentration and relaxation.

[0141] For example, if the theme is "Christmas," the server generates keywords such as "Christmas tree," "snowy landscape," and "Santa Claus," and sequentially generates and projects images corresponding to each. In this way, the design changes according to the theme are performed in real time.

[0142] An example of a prompt statement is as follows:

[0143] "Generate keywords based on the following theme: Natural Environment"

[0144] "Please generate related images from the following keywords: forest, beautiful scenery, fresh air"

[0145] In this way, it becomes possible to change the design and atmosphere of not only the meeting rooms but also the interior of the store in real time according to the theme and season. This improves user engagement and allows for the creation of an attractive space.

[0146] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0147] Step 1:

[0148] Users enter meeting room reservation information using a web application or device. Specifically, users enter the date and time, theme, and user information, and send it to the system. For example, the entered data might be "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment." The system then receives this data as reservation information.

[0149] Step 2:

[0150] The server receives reservation information sent by the user. The received data includes the date and time, theme, and user information. Next, the server generates keywords using a Large-Scale Language Model (LLM) based on the theme information. If the input theme information is "natural environment," the generative AI model is used to generate related keywords such as "forest," "beautiful scenery," and "fresh air."

[0151] Step 3:

[0152] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. The keywords generated earlier are used as input data, and the output consists of multiple images corresponding to each keyword. For example, "forest" might generate an image of "beautiful forest scenery," and "beautiful scenery" might generate an image of "lake and mountain scenery."

[0153] Step 4:

[0154] The server sends the generated image data to the terminal. The terminal receives this image data and converts it to the appropriate format. This conversion is performed in a way that is optimal for the image to be projected by a display device (such as a projector or glass wall display). The input is the generated image data, and the output is image data in a format that is optimally displayable by a projector or display.

[0155] Step 5:

[0156] The terminal transmits the received and format-converted image data to the projection means. The projection means projects this image according to the start time of the meeting. For example, at "14:00", an image of a "beautiful forest landscape" is projected onto the wall using a projector, and 15 minutes later, it switches to an image of a "lake and mountain landscape". Format-converted image data is transmitted to the projection means as input, and the image is projected as output at pre-set timings.

[0157] Step 6:

[0158] Users conduct meetings using projected images. Users proceed with the meeting while viewing theme-related images projected onto a projector or glass wall display. This operation is expected to increase participant relaxation and concentration, leading to more active discussion. The input is the image projected onto the projector, and the output is expected to improve the quality of the meeting.

[0159] In this way, the system can automatically change the design according to the theme based on the user's reservation information, optimizing the atmosphere of the meeting room in real time.

[0160] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0161] System Overview

[0162] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. In particular, it is characterized by providing an optimal environment that responds to the user's emotions by combining it with an emotion engine that recognizes the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0163] User input of meeting room reservation information

[0164] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participants, etc.). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0165] Receiving and storing reservation information on the server.

[0166] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0167] Keyword generation

[0168] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0169] Image generation

[0170] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0171] Image data format conversion

[0172] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0173] Schedule management

[0174] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0175] Image projection

[0176] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0177] User emotion recognition by an emotion engine

[0178] Terminal: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it collects user emotion data through the camera and microphone.

[0179] Image changes based on emotions

[0180] Server: The emotion engine recognizes emotional information in real time and selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0181] User usage

[0182] User: When a meeting begins, images related to the topic are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the topic. As a result, discussions become more lively, and the quality of the meeting improves. In addition, emotions are recognized during the meeting, and the images are changed accordingly, providing a more comfortable environment.

[0183] result

[0184] This system allows the meeting room design to change according to the meeting's theme, time of day, and even the user's emotions, thereby increasing participant motivation and concentration. It also contributes to improving the quality of meetings. This system operates seamlessly, from user interaction to server data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0185] The following describes the processing flow.

[0186] Step 1: User enters meeting room reservation information.

[0187] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participant information). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0188] Step 2: Server receives and stores reservation information.

[0189] Server: Receives reservation information submitted by users and stores it in the database. During this process, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0190] Step 3: Keyword Generation

[0191] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0192] Step 4: Image generation

[0193] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0194] Step 5: Convert image data format

[0195] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0196] Step 6: Collecting emotional data using the emotion engine

[0197] Device: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it captures video with a camera and collects audio with a microphone. This data is analyzed in real time to detect the user's emotions.

[0198] Step 7: Emotion-based image selection

[0199] Server: Based on the emotional information recognized by the emotion engine, the server dynamically selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0200] Step 8: Schedule management and image projection

[0201] Terminal: Manages the schedule based on the meeting reservation time and prepares to project relevant images as the reservation start time approaches. Projects images onto the walls inside and outside the meeting room using a projector or glass wall display in line with the meeting start time. For example, project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0202] Step 9: User Use

[0203] User: Enters a meeting room and begins the meeting in an environment where theme-related images are projected onto the walls. The user experiences relaxation or increased concentration effects from the images. Furthermore, if changes in emotions are detected during the meeting, the projected images are changed accordingly, providing a comfortable and adaptive environment.

[0204] This series of steps allows the meeting room design to change according to the theme, time, and even the user's emotions, providing an effective meeting environment.

[0205] (Example 2)

[0206] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0207] Traditional meeting room management systems primarily focus on inputting and managing reservation information, lacking the functionality to dynamically change the meeting room environment. Therefore, it is difficult to provide an optimal environment based on the meeting's theme or the participants' moods. Furthermore, while new methods are needed to improve the quality of meetings, currently, customization of the environment based on user emotions is not realized.

[0208] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0209] In this invention, the server includes data input means, keyword generation means, image generation means, format conversion means, schedule management means, emotion recognition means, real-time update means, and projection means. This makes it possible to dynamically change the design of the meeting room according to the theme of the meeting and the emotions of the participants, thereby providing an optimal environment.

[0210] "Data entry means" refers to the means of inputting meeting room reservation information, such as date, time, theme, and participant information, into the system.

[0211] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0212] "Image generation means" refers to a means of generating images corresponding to a theme using an image generation model based on generated keywords.

[0213] "Format conversion means" refers to means of converting the generated image data into a format suitable for projectors or glass wall displays.

[0214] A "schedule management method" refers to a means of managing the schedule based on the reserved time of a meeting and preparing for the projection of related images.

[0215] "Emotion recognition means" refers to a method of recognizing emotions by analyzing the user's facial expressions and tone of voice during a meeting.

[0216] A "real-time update means" is a means of updating the projected image in real time based on emotional information acquired from an emotion recognition means.

[0217] "Projection means" refers to a means of projecting the generated image onto the walls inside or outside the conference room using a projector or glass wall display.

[0218] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and theme, providing an optimal environment that responds to the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0219] User input of meeting room reservation information

[0220] Users use a dedicated web application or terminal to reserve meeting rooms and enter reservation information such as the date, time, theme, and participants. For example, they might enter "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and press the submit button. This sends the entered data to the server.

[0221] Receiving and storing reservation information on the server.

[0222] The server receives meeting room reservation information sent by the user and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table. Specifically, the server parses the received data, executes SQL queries, and saves the data.

[0223] Keyword generation

[0224] The server reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." Specifically, it generates text prompts for the LLM and retrieves its responses.

[0225] Image generation

[0226] The server uses image generation models such as Stable Diffusion to generate images corresponding to the theme based on the generated keywords. For example, if the keyword is "forest," it will generate an image of a "beautiful forest landscape." The generated image data is temporarily stored in the server's storage.

[0227] Image data format conversion

[0228] The device receives notification of image data generated from the server and downloads the image. The downloaded image data is converted to a format suitable for projectors and glass wall displays. The image is then optimized using image processing libraries such as Unicorn Image Toolkit.

[0229] Schedule management

[0230] The terminal manages the schedule based on the scheduled meeting time. For example, it displays an alert 10 minutes before the scheduled start time and prepares to project any relevant images. Specifically, it uses system timers to handle situations before and after the meeting.

[0231] Image projection

[0232] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, it might project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0233] Emotion recognition by an emotion engine

[0234] During meetings, the device uses an emotion engine to analyze the user's facial expressions and tone of voice to recognize their emotions. Specifically, it collects data in real time through the camera and microphone and inputs it into an emotion analysis model.

[0235] Image changes based on emotions

[0236] The server recognizes emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will project a "calm lake view." Specifically, it generates new image generation prompts based on emotional data acquired periodically.

[0237] Real-time image projection

[0238] The terminal receives new image data sent from the server and projects the images onto the walls inside and outside the conference room in real time. For example, it updates the image the moment a user reacts, providing an optimal environment according to the progress of the meeting.

[0239] Example of a prompt

[0240] For example, the prompt text to be input to the image generation model would be as follows:

[0241] "Please generate images of beautiful forest landscapes based on the theme of the natural environment."

[0242] "Please generate images of lake and mountain scenery using the keyword 'beautiful landscape'."

[0243] This allows for dynamic changes to the meeting room design based on the meeting's theme, time of day, and even the user's emotions, thereby enhancing participant motivation and concentration. The system seamlessly integrates user interaction, server-side data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0244] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0245] System program processing flow

[0246] Step 1: User enters meeting room reservation information.

[0247] Users use a dedicated web application or terminal to reserve meeting rooms, entering reservation information such as date, time, theme, and participants, and then pressing the submit button. Input: Date, time, theme, and participant information. Output: The entered information is sent to the server.

[0248] Step 2: Server receives and stores reservation information.

[0249] The server receives meeting room reservation information submitted by users and stores it in the database. It parses the received data and records it in the reservation information table in the appropriate format. Input: Reservation information submitted by users. Output: Reservation information stored in the database.

[0250] Step 3: Generating keywords from the theme

[0251] The server reads theme information stored in the database and generates related keywords using a Large-Scale Language Model (LLM). It passes the theme information to the LLM to generate a prompt and retrieves its response. Input: Theme information stored in the database. Output: Generated related keywords.

[0252] Step 4: Image generation

[0253] The server uses an image generation model to generate images corresponding to the theme based on the generated keywords. The generated keywords are then used as prompts to retrieve image data from a generative AI model such as Stable Diffusion. Input: Generated keywords. Output: Generated image data.

[0254] Step 5: Convert image data format

[0255] The device receives a notification from the server and downloads the generated image data. Using an image processing library such as Unicorn Image Toolkit, the downloaded image data is converted to a format suitable for projectors or glass wall displays. Input: Generated image data. Output: Image data in the converted format.

[0256] Step 6: Schedule Management

[0257] The terminal manages the schedule based on the meeting reservation time. It sets a system timer, displays alerts before and after the meeting starts, and prepares for the projection of related images. Input: Meeting reservation time and image data. Output: Completion of projection preparation.

[0258] Step 7: Projecting images into the conference room

[0259] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. A system timer projects, for example, a "beautiful forest landscape" image at "14:00" and switches to a "lake and mountain landscape" 15 minutes later. Input: Image data in the converted format. Output: Projected image.

[0260] Step 8: Emotion recognition by the emotion engine

[0261] The device uses an emotion engine to analyze the user's facial expressions and voice tone during meetings to recognize their emotions. Data is collected through the camera and microphone and input into the emotion analysis model. Input: User's facial expression data, voice tone data. Output: Analyzed emotion information.

[0262] Step 9: Change the image according to your emotions.

[0263] The server recognizes the emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will generate a new image generation prompt to change it to a "calm lake view." Input: Analyzed emotional information. Output: New image data.

[0264] Step 10: Real-time image projection

[0265] The terminal receives new image data from the server and projects the images onto the walls inside and outside the conference room in real time. The image is updated the moment the user reacts, providing an optimal environment according to the progress of the meeting. Input: New image data. Output: Updated projected image.

[0266] (Application Example 2)

[0267] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0268] Conventional manufacturing lines lacked environmental adjustments tailored to workers' stress levels and concentration levels, leading to problems such as decreased work efficiency and worker satisfaction. Furthermore, the absence of dynamic environmental optimization methods utilizing emotion recognition prevented real-time countermeasures.

[0269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes data input means, keyword generation means, image generation means, emotion recognition means, environment adjustment means, and projection means. This makes it possible to analyze the facial expressions and tone of voice of workers in real time and provide an optimal work environment that corresponds to their emotions.

[0270] "Data input means" refers to a device or method for receiving data such as date and time, theme, and participant information.

[0271] "Keyword generation means" refers to a device or method that generates relevant keywords based on theme information received from a data input means.

[0272] "Image generation means" refers to a device or method that generates image data based on the generated keywords.

[0273] "Projection means" refers to a device or method for displaying generated image data using a projector, display, or the like.

[0274] "Emotion recognition means" refers to a device or method that analyzes a user's facial expressions and voice data to recognize their emotions in real time.

[0275] "Environmental adjustment means" refers to a device or method that dynamically optimizes the environment, such as music, lighting, and display content, based on emotions recognized by emotion recognition means.

[0276] This invention provides a robotic system that dynamically optimizes the work environment based on the stress levels and concentration levels of workers on a manufacturing line. A specific example of the system is described below.

[0277] System program

[0278] The system consists of data input means, keyword generation means, image generation means, projection means, emotion recognition means, and environment adjustment means. The emotion recognition means has the function of analyzing the facial expressions and voice data of the workers on the production line to recognize the stress level and concentration in real time. Based on this, the environment adjustment means dynamically provides an optimal working environment for the workers.

[0279] Hardware and software

[0280] Hardware:

[0281] Camera (e.g., Logitech C920): Acquires the facial expression data of the workers.

[0282] Microphone (e.g., Blue Yeti): Acquires the voice data of the workers.

[0283] Projector or display: Displays the generated image data.

[0284] Software:

[0285] Emotion engine (e.g., EmotionEngine): Analyzes the facial expressions and voice data of the workers to recognize emotions.

[0286] Environment control system (e.g., EnvironmentControl): Adjusts the environment based on the recognized emotions.

[0287] Image generation model (e.g., Stable Diffusion): Generates images based on keywords.

[0288] Data processing and data calculation

[0289] Data acquisition from camera and microphone:

[0290] The device acquires facial expression data from the camera and audio data from the microphone. This data is analyzed by emotion recognition technology, and stress levels and concentration levels are determined in real time.

[0291] Emotion recognition and environmental adjustment:

[0292] Based on the worker's emotions as determined by the emotion recognition system, the environmental adjustment system optimizes the work environment. For example, if the system determines that the worker is tired, it plays relaxing background music and softens the lighting. Conversely, if the system determines that the worker is focused, it plays background music that helps maintain focus and brightens the lighting.

[0293] Specific example

[0294] Example 1:

[0295] If a worker is deemed to be experiencing stress during work, images of "natural scenery" are projected onto the work area via a projector, providing a relaxing environment.

[0296] Example 2:

[0297] To improve work efficiency, when concentration is needed, the environmental control system plays background music designed for focus, accompanied by an image of a "calm lake landscape."

[0298] Example of a prompt

[0299] Design a system that analyzes the facial expressions and tone of voice of workers on a manufacturing line and adjusts the work environment based on their stress levels and concentration levels. For example, if a worker is determined to be tired, the system should change the background music or lighting to provide a more relaxing environment.

[0300] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0301] Step 1:

[0302] The terminal uses a camera and a microphone to acquire the facial expression data and voice data of the worker. This input data enables subsequent emotion recognition.

[0303] Step 2:

[0304] The terminal inputs the acquired facial expression data and voice data into the emotion recognition means. The emotion recognition means analyzes this data and determines the emotion (stress level and concentration) of the worker. As a result of the emotion recognition, a result is generated.

[0305] Step 3:

[0306] The server receives the emotion data transmitted from the emotion recognition means and triggers the environment adjustment means based on the result. Based on this emotion data, it is determined what kind of environment adjustment is necessary.

[0307] Step 4:

[0308] The server inputs the shift information and theme information received from the data input means into the keyword generation means based on them. The keyword generation means generates keywords related to the theme.

[0309] Step 5:

[0310] The server inputs the generated keywords into the image generation model. This model generates an image based on the keywords. For example, images corresponding to "relax" or "concentrate" are generated.

[0311] Step 6:

[0312] The server transmits the generated image to the terminal. The terminal receives this image data and transmits it to the projection means. The projection means displays the image using a projector or a display.

[0313] Step 7:

[0314] The terminal triggers environmental adjustments based on a schedule. For example, it provides relaxing background music and lighting when a worker is tired, and a focused environment when concentration is needed.

[0315] Step 8:

[0316] Users can experience the effects of environmental adjustments in real time while continuing their work. This provides an environment that improves work efficiency and reduces stress.

[0317] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0318] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0319] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0320] [Second Embodiment]

[0321] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0322] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0323] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0324] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0325] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0326] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0327] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0328] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0329] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0330] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0331] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0332] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0333] System Overview

[0334] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. The following explains, with specific examples, how the server, terminal, and user each operate.

[0335] User input of meeting room reservation information

[0336] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, if a user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data will be sent to the system.

[0337] Keyword generation by the server

[0338] Server: After receiving reservation information, it uses an LLM (Large-Scale Language Model) to generate keywords related to the theme. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0339] Image generation by the server

[0340] Server: After keyword generation, the server uses image generation models such as SD (Stable Diffusion) to generate images based on these keywords. For example, it generates an image of a "beautiful forest landscape" from the keyword "forest," and an image of a "lake and mountain landscape" from the keyword "beautiful landscape."

[0341] Receiving image data via the terminal and preparing for projection.

[0342] Terminal: Receives image data generated from the server and converts it to the required format. Then, it prepares the image data for use with projectors and glass wall displays.

[0343] Projection of an image by projection means

[0344] Terminal: Project images onto a projector or glass wall display in accordance with the meeting start time. For example, project an image of a "beautiful forest landscape" onto the wall at "14:00," and then switch to an image of a "lake and mountain landscape" 15 minutes later.

[0345] User usage

[0346] User: When a meeting begins, images related to the theme are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing a "beautiful forest landscape" can refresh the mind and lead to a more lively discussion.

[0347] result

[0348] This allows the meeting room design to change according to the meeting's theme and time of day, thereby increasing participants' motivation and concentration. It also contributes to improving the quality of the meeting.

[0349] The system of this invention operates seamlessly, from user operation to data processing on the server and image projection on the terminal, enabling efficient management and optimization of the meeting environment.

[0350] The following describes the processing flow.

[0351] Step 1: User enters meeting room reservation information.

[0352] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, the user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0353] Step 2: Server receives and stores reservation information.

[0354] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0355] Step 3: Keyword Generation

[0356] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0357] Step 4: Image generation

[0358] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0359] Step 5: Convert image data format

[0360] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0361] Step 6: Schedule Management

[0362] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0363] Step 7: Projecting the Image

[0364] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0365] Step 8: User Use

[0366] User: Enters the meeting room and sees the displayed images. Users become relaxed or more focused by the topic-related images. As a result, discussion becomes more lively and the quality of the meeting improves.

[0367] This series of steps allows the meeting room design to change according to the theme and time, providing an effective meeting environment.

[0368] (Example 1)

[0369] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0370] Traditional meeting room systems were unable to change the meeting room design in real time based on reservation information, making it difficult to optimize meeting themes and participant motivation. Furthermore, the manual operation required to change the meeting environment design was cumbersome, hindering efficient management. Additionally, the lack of sufficient automation for image generation and projection compromised user convenience.

[0371] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0372] In this invention, the server includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means. This allows users to simply input meeting reservation information, and based on that information, images are generated in real time, format converted, and projected into the meeting room. This automatically provides an optimal environment for the meeting theme and enhances participants' concentration, thereby improving meeting quality and achieving efficient environment management.

[0373] "Data entry means" refers to an interface for users to enter meeting room reservation information, and has the function of accepting information such as date and time, theme, and participant information.

[0374] A "keyword generation means" is a component that has the function of generating relevant keywords based on theme information received from a data input means. Specifically, it generates keywords using a generation AI model.

[0375] An "image generation means" is a component that has the function of generating a corresponding image using an image generation model based on keywords generated by a keyword generation means.

[0376] The "image receiving and format conversion means" is a component that has the function of receiving image data transmitted from a server and converting it into a format suitable for output devices such as projectors and displays.

[0377] A "projection means" is a component that has the function of projecting prepared images onto a projector or display placed in the conference room, and also includes the function of switching images based on set times or events.

[0378] System Overview

[0379] This invention relates to a system that changes the design of a conference room in real time according to the conference room reservation details and the office theme. The system includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means.

[0380] User input of meeting room reservation information

[0381] Users enter meeting room reservation information (date, time, theme, participants, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0382] Keyword generation by the server

[0383] After receiving the reservation information, the server uses a generative AI model (for example, a type of large-scale language model) to generate keywords related to the theme. If the prompt is "Generate keywords related to the theme 'natural environment'", keywords such as "forest", "beautiful scenery", and "fresh air" will be generated.

[0384] Image generation by the server

[0385] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. Specifically, if the keyword is "forest" and the prompt "Generate an image of a beautiful forest landscape" is entered, the image generation model will generate an image file based on that prompt. Images will be generated similarly for other keywords.

[0386] Receiving image data via the terminal and preparing for projection.

[0387] The terminal receives image data sent from the server. After receiving the data, the terminal converts the image data into a format optimized for projectors and glass wall displays. Specifically, the conversion process involves resizing the image file resolution to 1920x1080 and converting it to an appropriate file format (such as JPEG or PNG).

[0388] Projection of an image by projection means

[0389] The device projects images onto a projector or glass wall display in accordance with the meeting start time. For example, at 14:00, it projects an image of a "beautiful forest landscape" onto the wall, and then switches to an image of a "lake and mountain landscape" 15 minutes later. This projection schedule is managed by the device's timer function.

[0390] User usage

[0391] At the start of a meeting, users are shown images related to the theme projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing the displayed "beautiful forest scenery" can be refreshing and lead to a more lively discussion.

[0392] result

[0393] This system allows the meeting room design to dynamically change according to the meeting's theme and time of day, providing an environment that enhances participants' motivation and concentration. This, in turn, improves the quality of meetings and enables more efficient management.

[0394] Examples of prompt statements

[0395] The following are examples of prompts to input into a generative AI model:

[0396] Prompt: "The meeting theme is 'Natural Environment,' please generate related keywords."

[0397] Example output: Forest, beautiful scenery, fresh air

[0398] Prompt: "Generate images of beautiful forest landscapes using the keyword 'forest'."

[0399] Output example: - Image file -

[0400] Prompt: "Generate images of lake and mountain scenery from the keyword 'beautiful scenery'."

[0401] Output example: - Image file -

[0402] This prompt clearly shows the user how the entire system works and how specific results are produced.

[0403] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0404] Step 1:

[0405] Users enter meeting room reservation information using a dedicated web application or terminal. (Input) Date and time, theme, and participant information. (Output) The reservation information is saved in the system's database. For example, a specific action would be for a user to enter details such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" into a web form.

[0406] Step 2:

[0407] The server retrieves reservation information from the database and generates keywords based on theme information. (Input) Reservation information (theme, etc.). (Prompt to the generating AI model: "Generate keywords related to the theme 'Natural Environment'") (Output) Generated keywords (e.g., forest, beautiful scenery, fresh air). For example, the server uses a generating AI model to extract keywords from the theme.

[0408] Step 3:

[0409] The server uses the generated keywords and an image generation model to generate the corresponding image. (Input) Keywords (e.g., forest, beautiful landscape). (Prompt to the image generation model: "Generate an image of a beautiful forest landscape.") (Output) Generated image file (e.g., forest landscape image). For example, this process includes "Generating an image of a beautiful forest landscape based on the keyword 'forest'."

[0410] Step 4:

[0411] The terminal receives image data sent from the server and converts it to the format best suited to the display device. (Input) The generated image file. (Output) The converted image file (e.g., a JPEG file resized to a resolution suitable for a projector). Specifically, the received image is resized to a resolution of 1920x1080, and other image format conversions are performed.

[0412] Step 5:

[0413] The device projects an image onto a projector or glass wall display in time with the start of the meeting. (Input) Converted image file. (Output) Image projected onto the wall or screen. Specifically, projection starts based on the timer setting; for example, it projects a "beautiful forest landscape" at "14:00" and automatically switches to a "lake and mountain landscape" 15 minutes later.

[0414] Step 6:

[0415] The device changes the projected image during a meeting based on user instructions or timer settings. (Input) User instructions or pre-set timer information. (Output) The changed new image is displayed. Specifically, the user can instruct the user to change the image from a smartphone app, or the device will automatically switch to the next image according to a set timer.

[0416] Step 7:

[0417] After a meeting, users provide feedback on the quality of the meeting and the participants' engagement through the system's evaluation function. (Input) Feedback data (e.g., survey responses). (Output) Feedback data stored on the server. For example, users might answer questions such as, "Were the projected images during the meeting helpful for the discussion?" in a post-meeting survey.

[0418] (Application Example 1)

[0419] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0420] Traditional store design and atmosphere changes are often done manually, which is time-consuming and labor-intensive. Furthermore, it's difficult to change the design in real time according to the season or theme, making it difficult to maintain customer interest. This diminishes the store's appeal and hinders customer engagement.

[0421] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0422] In this invention, the server includes data input means, keyword generation means, image generation means, display modification means, and projection means. This makes it possible to change the design and atmosphere of the store interior in real time according to the store's theme or season.

[0423] "Data entry means" refers to the means by which users input the date and time, theme, and user information.

[0424] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0425] "Image generation means" refers to means for generating images based on the generated keywords.

[0426] "Projection means" refers to means for projecting the generated image onto a display device such as a projector or display.

[0427] "Display modification means" refers to means of changing the design or atmosphere inside a store in real time.

[0428] "Date and time" refers to information that specifies a particular year, month, day, and time.

[0429] A "theme" is a specific concept or idea based on the user's intentions and objectives.

[0430] "User information" refers to information about individuals participating in meetings, events, etc.

[0431] "Related keywords" are concepts or words that correspond to the theme.

[0432] "Store interior" refers to the interior space of a physical store.

[0433] "Design" refers to the visual appearance and layout.

[0434] "Atmosphere" refers to the emotions and environment one feels within a space.

[0435] The present invention provides a system for implementing a function that changes the design of a meeting room in real time according to the reservation details and theme of the meeting room. This system operates in a seamless collaboration between the server, terminal, and user.

[0436] First, users enter meeting room reservation information (date and time, theme, user information, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0437] The server generates keywords related to the theme using an LLM (Large-Scale Language Model) based on the received reservation information. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." In this process, it uses a generative AI model such as OpenAI GPT-3.

[0438] Next, the server generates related images based on the generated keywords using image generation models such as SD (Stable Diffusion). For example, it generates multiple images such as "beautiful forest scenery" from the keyword "forest," and "lake and mountain scenery" from the keyword "beautiful scenery."

[0439] The terminal receives image data transmitted from the server and converts it to an appropriate format. This format conversion is performed so that the image is optimized for projection means such as projectors or glass wall displays.

[0440] Finally, the projection system projects images according to the meeting start time. For example, at 14:00, an image of a beautiful forest landscape is projected onto the wall, and 15 minutes later, it switches to an image of a lake and mountain landscape, promoting user concentration and relaxation.

[0441] For example, if the theme is "Christmas," the server generates keywords such as "Christmas tree," "snowy landscape," and "Santa Claus," and sequentially generates and projects images corresponding to each. In this way, the design changes according to the theme are performed in real time.

[0442] An example of a prompt statement is as follows:

[0443] "Generate keywords based on the following theme: Natural Environment"

[0444] "Please generate related images from the following keywords: forest, beautiful scenery, fresh air"

[0445] In this way, it becomes possible to change the design and atmosphere of not only the meeting rooms but also the interior of the store in real time according to the theme and season. This improves user engagement and allows for the creation of an attractive space.

[0446] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0447] Step 1:

[0448] Users enter meeting room reservation information using a web application or device. Specifically, users enter the date and time, theme, and user information, and send it to the system. For example, the entered data might be "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment." The system then receives this data as reservation information.

[0449] Step 2:

[0450] The server receives reservation information sent by the user. The received data includes the date and time, theme, and user information. Next, the server generates keywords using a Large-Scale Language Model (LLM) based on the theme information. If the input theme information is "natural environment," the generative AI model is used to generate related keywords such as "forest," "beautiful scenery," and "fresh air."

[0451] Step 3:

[0452] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. The keywords generated earlier are used as input data, and the output consists of multiple images corresponding to each keyword. For example, "forest" might generate an image of "beautiful forest scenery," and "beautiful scenery" might generate an image of "lake and mountain scenery."

[0453] Step 4:

[0454] The server sends the generated image data to the terminal. The terminal receives this image data and converts it to the appropriate format. This conversion is performed in a way that is optimal for the image to be projected by a display device (such as a projector or glass wall display). The input is the generated image data, and the output is image data in a format that is optimally displayable by a projector or display.

[0455] Step 5:

[0456] The terminal transmits the received and format-converted image data to the projection means. The projection means projects this image according to the start time of the meeting. For example, at "14:00", an image of a "beautiful forest landscape" is projected onto the wall using a projector, and 15 minutes later, it switches to an image of a "lake and mountain landscape". Format-converted image data is transmitted to the projection means as input, and the image is projected as output at pre-set timings.

[0457] Step 6:

[0458] Users conduct meetings using projected images. Users proceed with the meeting while viewing theme-related images projected onto a projector or glass wall display. This operation is expected to increase participant relaxation and concentration, leading to more active discussion. The input is the image projected onto the projector, and the output is expected to improve the quality of the meeting.

[0459] In this way, the system can automatically change the design according to the theme based on the user's reservation information, optimizing the atmosphere of the meeting room in real time.

[0460] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0461] System Overview

[0462] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. In particular, it is characterized by providing an optimal environment that responds to the user's emotions by combining it with an emotion engine that recognizes the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0463] User input of meeting room reservation information

[0464] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participants, etc.). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0465] Receiving and storing reservation information on the server.

[0466] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0467] Keyword generation

[0468] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0469] Image generation

[0470] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0471] Image data format conversion

[0472] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0473] Schedule management

[0474] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0475] Image projection

[0476] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0477] User emotion recognition by an emotion engine

[0478] Terminal: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it collects user emotion data through the camera and microphone.

[0479] Image changes based on emotions

[0480] Server: The emotion engine recognizes emotional information in real time and selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0481] User usage

[0482] User: When a meeting begins, images related to the topic are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the topic. As a result, discussions become more lively, and the quality of the meeting improves. In addition, emotions are recognized during the meeting, and the images are changed accordingly, providing a more comfortable environment.

[0483] result

[0484] This system allows the meeting room design to change according to the meeting's theme, time of day, and even the user's emotions, thereby increasing participant motivation and concentration. It also contributes to improving the quality of meetings. This system operates seamlessly, from user interaction to server data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0485] The following describes the processing flow.

[0486] Step 1: User enters meeting room reservation information.

[0487] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participant information). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0488] Step 2: Server receives and stores reservation information.

[0489] Server: Receives reservation information submitted by users and stores it in the database. During this process, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0490] Step 3: Keyword Generation

[0491] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0492] Step 4: Image generation

[0493] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0494] Step 5: Convert image data format

[0495] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0496] Step 6: Collecting emotional data using the emotion engine

[0497] Device: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it captures video with a camera and collects audio with a microphone. This data is analyzed in real time to detect the user's emotions.

[0498] Step 7: Emotion-based image selection

[0499] Server: Based on the emotional information recognized by the emotion engine, the server dynamically selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0500] Step 8: Schedule management and image projection

[0501] Terminal: Manages the schedule based on the meeting reservation time and prepares to project relevant images as the reservation start time approaches. Projects images onto the walls inside and outside the meeting room using a projector or glass wall display in line with the meeting start time. For example, project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0502] Step 9: User Use

[0503] User: Enters a meeting room and begins the meeting in an environment where theme-related images are projected onto the walls. The user experiences relaxation or increased concentration effects from the images. Furthermore, if changes in emotions are detected during the meeting, the projected images are changed accordingly, providing a comfortable and adaptive environment.

[0504] This series of steps allows the meeting room design to change according to the theme, time, and even the user's emotions, providing an effective meeting environment.

[0505] (Example 2)

[0506] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0507] Traditional meeting room management systems primarily focus on inputting and managing reservation information, lacking the functionality to dynamically change the meeting room environment. Therefore, it is difficult to provide an optimal environment based on the meeting's theme or the participants' moods. Furthermore, while new methods are needed to improve the quality of meetings, currently, customization of the environment based on user emotions is not realized.

[0508] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0509] In this invention, the server includes data input means, keyword generation means, image generation means, format conversion means, schedule management means, emotion recognition means, real-time update means, and projection means. This makes it possible to dynamically change the design of the meeting room according to the theme of the meeting and the emotions of the participants, thereby providing an optimal environment.

[0510] "Data entry means" refers to the means of inputting meeting room reservation information, such as date, time, theme, and participant information, into the system.

[0511] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0512] "Image generation means" refers to a means of generating images corresponding to a theme using an image generation model based on generated keywords.

[0513] "Format conversion means" refers to means of converting the generated image data into a format suitable for projectors or glass wall displays.

[0514] A "schedule management method" refers to a means of managing the schedule based on the reserved time of a meeting and preparing for the projection of related images.

[0515] "Emotion recognition means" refers to a method of recognizing emotions by analyzing the user's facial expressions and tone of voice during a meeting.

[0516] A "real-time update means" is a means of updating the projected image in real time based on emotional information acquired from an emotion recognition means.

[0517] "Projection means" refers to a means of projecting the generated image onto the walls inside or outside the conference room using a projector or glass wall display.

[0518] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and theme, providing an optimal environment that responds to the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0519] User input of meeting room reservation information

[0520] Users use a dedicated web application or terminal to reserve meeting rooms and enter reservation information such as the date, time, theme, and participants. For example, they might enter "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and press the submit button. This sends the entered data to the server.

[0521] Receiving and storing reservation information on the server.

[0522] The server receives meeting room reservation information sent by the user and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table. Specifically, the server parses the received data, executes SQL queries, and saves the data.

[0523] Keyword generation

[0524] The server reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." Specifically, it generates text prompts for the LLM and retrieves its responses.

[0525] Image generation

[0526] The server uses image generation models such as Stable Diffusion to generate images corresponding to the theme based on the generated keywords. For example, if the keyword is "forest," it will generate an image of a "beautiful forest landscape." The generated image data is temporarily stored in the server's storage.

[0527] Image data format conversion

[0528] The device receives notification of image data generated from the server and downloads the image. The downloaded image data is converted to a format suitable for projectors and glass wall displays. The image is then optimized using image processing libraries such as Unicorn Image Toolkit.

[0529] Schedule management

[0530] The terminal manages the schedule based on the scheduled meeting time. For example, it displays an alert 10 minutes before the scheduled start time and prepares to project any relevant images. Specifically, it uses system timers to handle situations before and after the meeting.

[0531] Image projection

[0532] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, it might project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0533] Emotion recognition by an emotion engine

[0534] During meetings, the device uses an emotion engine to analyze the user's facial expressions and tone of voice to recognize their emotions. Specifically, it collects data in real time through the camera and microphone and inputs it into an emotion analysis model.

[0535] Image changes based on emotions

[0536] The server recognizes emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will project a "calm lake view." Specifically, it generates new image generation prompts based on emotional data acquired periodically.

[0537] Real-time image projection

[0538] The terminal receives new image data sent from the server and projects the images onto the walls inside and outside the conference room in real time. For example, it updates the image the moment a user reacts, providing an optimal environment according to the progress of the meeting.

[0539] Example of a prompt

[0540] For example, the prompt text to be input to the image generation model would be as follows:

[0541] "Please generate images of beautiful forest landscapes based on the theme of the natural environment."

[0542] "Please generate images of lake and mountain scenery using the keyword 'beautiful landscape'."

[0543] This allows for dynamic changes to the meeting room design based on the meeting's theme, time of day, and even the user's emotions, thereby enhancing participant motivation and concentration. The system seamlessly integrates user interaction, server-side data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0544] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0545] System program processing flow

[0546] Step 1: User enters meeting room reservation information.

[0547] Users use a dedicated web application or terminal to reserve meeting rooms, entering reservation information such as date, time, theme, and participants, and then pressing the submit button. Input: Date, time, theme, and participant information. Output: The entered information is sent to the server.

[0548] Step 2: Server receives and stores reservation information.

[0549] The server receives meeting room reservation information submitted by users and stores it in the database. It parses the received data and records it in the reservation information table in the appropriate format. Input: Reservation information submitted by users. Output: Reservation information stored in the database.

[0550] Step 3: Generating keywords from the theme

[0551] The server reads theme information stored in the database and generates related keywords using a Large-Scale Language Model (LLM). It passes the theme information to the LLM to generate a prompt and retrieves its response. Input: Theme information stored in the database. Output: Generated related keywords.

[0552] Step 4: Image generation

[0553] The server uses an image generation model to generate images corresponding to the theme based on the generated keywords. The generated keywords are then used as prompts to retrieve image data from a generative AI model such as Stable Diffusion. Input: Generated keywords. Output: Generated image data.

[0554] Step 5: Convert image data format

[0555] The device receives a notification from the server and downloads the generated image data. Using an image processing library such as Unicorn Image Toolkit, the downloaded image data is converted to a format suitable for projectors or glass wall displays. Input: Generated image data. Output: Image data in the converted format.

[0556] Step 6: Schedule Management

[0557] The terminal manages the schedule based on the meeting reservation time. It sets a system timer, displays alerts before and after the meeting starts, and prepares for the projection of related images. Input: Meeting reservation time and image data. Output: Completion of projection preparation.

[0558] Step 7: Projecting images into the conference room

[0559] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. A system timer projects, for example, a "beautiful forest landscape" image at "14:00" and switches to a "lake and mountain landscape" 15 minutes later. Input: Image data in the converted format. Output: Projected image.

[0560] Step 8: Emotion recognition by the emotion engine

[0561] The device uses an emotion engine to analyze the user's facial expressions and voice tone during meetings to recognize their emotions. Data is collected through the camera and microphone and input into the emotion analysis model. Input: User's facial expression data, voice tone data. Output: Analyzed emotion information.

[0562] Step 9: Change the image according to your emotions.

[0563] The server recognizes the emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will generate a new image generation prompt to change it to a "calm lake view." Input: Analyzed emotional information. Output: New image data.

[0564] Step 10: Real-time image projection

[0565] The terminal receives new image data from the server and projects the images onto the walls inside and outside the conference room in real time. The image is updated the moment the user reacts, providing an optimal environment according to the progress of the meeting. Input: New image data. Output: Updated projected image.

[0566] (Application Example 2)

[0567] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0568] Conventional manufacturing lines lacked environmental adjustments tailored to workers' stress levels and concentration levels, leading to problems such as decreased work efficiency and worker satisfaction. Furthermore, the absence of dynamic environmental optimization methods utilizing emotion recognition prevented real-time countermeasures.

[0569] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes data input means, keyword generation means, image generation means, emotion recognition means, environment adjustment means, and projection means. This makes it possible to analyze the facial expressions and tone of voice of workers in real time and provide an optimal work environment that corresponds to their emotions.

[0570] "Data input means" refers to a device or method for receiving data such as date and time, theme, and participant information.

[0571] "Keyword generation means" refers to a device or method that generates relevant keywords based on theme information received from a data input means.

[0572] "Image generation means" refers to a device or method that generates image data based on the generated keywords.

[0573] "Projection means" refers to a device or method for displaying generated image data using a projector, display, or the like.

[0574] "Emotion recognition means" refers to a device or method that analyzes a user's facial expressions and voice data to recognize their emotions in real time.

[0575] "Environmental adjustment means" refers to a device or method that dynamically optimizes the environment, such as music, lighting, and display content, based on emotions recognized by emotion recognition means.

[0576] This invention provides a robotic system that dynamically optimizes the work environment based on the stress levels and concentration levels of workers on a manufacturing line. A specific example of the system is described below.

[0577] System program

[0578] The system consists of data input means, keyword generation means, image generation means, projection means, emotion recognition means, and environment adjustment means. The emotion recognition means has the function of analyzing the facial expressions and voice data of workers on the manufacturing line to recognize stress levels and concentration levels in real time. Based on this, the environment adjustment means dynamically provides the optimal working environment for the workers.

[0579] Hardware and software

[0580] Hardware:

[0581] Camera (e.g., Logitech C920): Acquires facial expression data of workers.

[0582] Microphone (e.g., Blue Yeti): Captures the worker's voice data.

[0583] Projector or display: Displays the generated image data.

[0584] software:

[0585] Emotion Engine (e.g., EmotionEngine): Analyzes workers' facial expressions and voice data to recognize emotions.

[0586] Environmental control systems (e.g., EnvironmentControl): Adjust the environment based on recognized emotions.

[0587] Image generation model (e.g., Stable Diffusion): Generates images based on keywords.

[0588] Data processing and data calculation

[0589] Data acquisition from camera and microphone:

[0590] The device acquires facial expression data from the camera and audio data from the microphone. This data is analyzed by emotion recognition technology, and stress levels and concentration levels are determined in real time.

[0591] Emotion recognition and environmental adjustment:

[0592] Based on the worker's emotions as determined by the emotion recognition system, the environmental adjustment system optimizes the work environment. For example, if the system determines that the worker is tired, it plays relaxing background music and softens the lighting. Conversely, if the system determines that the worker is focused, it plays background music that helps maintain focus and brightens the lighting.

[0593] Specific example

[0594] Example 1:

[0595] If a worker is deemed to be experiencing stress during work, images of "natural scenery" are projected onto the work area via a projector, providing a relaxing environment.

[0596] Example 2:

[0597] To improve work efficiency, when concentration is needed, the environmental control system plays background music designed for focus, accompanied by an image of a "calm lake landscape."

[0598] Example of a prompt

[0599] Design a system that analyzes the facial expressions and tone of voice of workers on a manufacturing line and adjusts the work environment based on their stress levels and concentration levels. For example, if a worker is determined to be tired, the system should change the background music or lighting to provide a more relaxing environment.

[0600] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0601] Step 1:

[0602] The device uses a camera and microphone to acquire facial and voice data from workers. This input data enables subsequent emotion recognition.

[0603] Step 2:

[0604] The terminal inputs the acquired facial expression data and voice data into the emotion recognition device. The emotion recognition device analyzes this data and determines the worker's emotions (stress level and concentration level). The emotion recognition result is then generated.

[0605] Step 3:

[0606] The server receives emotion data transmitted from the emotion recognition device and triggers the environment adjustment device based on the results. This emotion data determines what kind of environment adjustment is needed.

[0607] Step 4:

[0608] The server inputs shift information and theme information received from the data input means into the keyword generation means. The keyword generation means generates keywords related to the theme.

[0609] Step 5:

[0610] The server inputs the generated keywords into an image generation model. This model generates images based on the keywords. For example, it might generate images corresponding to "relax" or "concentrate."

[0611] Step 6:

[0612] The server sends the generated image to the terminal. The terminal receives this image data and sends it to the projection means. The projection means displays the image using a projector or display.

[0613] Step 7:

[0614] The terminal triggers environmental adjustments based on a schedule. For example, it provides relaxing background music and lighting when a worker is tired, and a focused environment when concentration is needed.

[0615] Step 8:

[0616] Users can experience the effects of environmental adjustments in real time while continuing their work. This provides an environment that improves work efficiency and reduces stress.

[0617] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0618] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0619] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0620] [Third Embodiment]

[0621] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0622] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0623] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0624] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0625] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0626] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0627] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0628] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0629] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0630] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0631] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0632] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0633] System Overview

[0634] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. The following explains, with specific examples, how the server, terminal, and user each operate.

[0635] User input of meeting room reservation information

[0636] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, if a user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data will be sent to the system.

[0637] Keyword generation by the server

[0638] Server: After receiving reservation information, it uses an LLM (Large-Scale Language Model) to generate keywords related to the theme. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0639] Image generation by the server

[0640] Server: After keyword generation, the server uses image generation models such as SD (Stable Diffusion) to generate images based on these keywords. For example, it generates an image of a "beautiful forest landscape" from the keyword "forest," and an image of a "lake and mountain landscape" from the keyword "beautiful landscape."

[0641] Receiving image data via the terminal and preparing for projection.

[0642] Terminal: Receives image data generated from the server and converts it to the required format. Then, it prepares the image data for use with projectors and glass wall displays.

[0643] Projection of an image by projection means

[0644] Terminal: Project images onto a projector or glass wall display in accordance with the meeting start time. For example, project an image of a "beautiful forest landscape" onto the wall at "14:00," and then switch to an image of a "lake and mountain landscape" 15 minutes later.

[0645] User usage

[0646] User: When a meeting begins, images related to the theme are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing a "beautiful forest landscape" can refresh the mind and lead to a more lively discussion.

[0647] result

[0648] This allows the meeting room design to change according to the meeting's theme and time of day, thereby increasing participants' motivation and concentration. It also contributes to improving the quality of the meeting.

[0649] The system of this invention operates seamlessly, from user operation to data processing on the server and image projection on the terminal, enabling efficient management and optimization of the meeting environment.

[0650] The following describes the processing flow.

[0651] Step 1: User enters meeting room reservation information.

[0652] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, the user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0653] Step 2: Server receives and stores reservation information.

[0654] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0655] Step 3: Keyword Generation

[0656] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0657] Step 4: Image generation

[0658] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0659] Step 5: Convert image data format

[0660] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0661] Step 6: Schedule Management

[0662] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0663] Step 7: Projecting the Image

[0664] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0665] Step 8: User Use

[0666] User: Enters the meeting room and sees the displayed images. Users become relaxed or more focused by the topic-related images. As a result, discussion becomes more lively and the quality of the meeting improves.

[0667] This series of steps allows the meeting room design to change according to the theme and time, providing an effective meeting environment.

[0668] (Example 1)

[0669] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0670] Traditional meeting room systems were unable to change the meeting room design in real time based on reservation information, making it difficult to optimize meeting themes and participant motivation. Furthermore, the manual operation required to change the meeting environment design was cumbersome, hindering efficient management. Additionally, the lack of sufficient automation for image generation and projection compromised user convenience.

[0671] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0672] In this invention, the server includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means. This allows users to simply input meeting reservation information, and based on that information, images are generated in real time, format converted, and projected into the meeting room. This automatically provides an optimal environment for the meeting theme and enhances participants' concentration, thereby improving meeting quality and achieving efficient environment management.

[0673] "Data entry means" refers to an interface for users to enter meeting room reservation information, and has the function of accepting information such as date and time, theme, and participant information.

[0674] A "keyword generation means" is a component that has the function of generating relevant keywords based on theme information received from a data input means. Specifically, it generates keywords using a generation AI model.

[0675] An "image generation means" is a component that has the function of generating a corresponding image using an image generation model based on keywords generated by a keyword generation means.

[0676] The "image receiving and format conversion means" is a component that has the function of receiving image data transmitted from a server and converting it into a format suitable for output devices such as projectors and displays.

[0677] A "projection means" is a component that has the function of projecting prepared images onto a projector or display placed in the conference room, and also includes the function of switching images based on set times or events.

[0678] System Overview

[0679] This invention relates to a system that changes the design of a conference room in real time according to the conference room reservation details and the office theme. The system includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means.

[0680] User input of meeting room reservation information

[0681] Users enter meeting room reservation information (date, time, theme, participants, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0682] Keyword generation by the server

[0683] After receiving the reservation information, the server uses a generative AI model (for example, a type of large-scale language model) to generate keywords related to the theme. If the prompt is "Generate keywords related to the theme 'natural environment'", keywords such as "forest", "beautiful scenery", and "fresh air" will be generated.

[0684] Image generation by the server

[0685] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. Specifically, if the keyword is "forest" and the prompt "Generate an image of a beautiful forest landscape" is entered, the image generation model will generate an image file based on that prompt. Images will be generated similarly for other keywords.

[0686] Receiving image data via the terminal and preparing for projection.

[0687] The terminal receives image data sent from the server. After receiving the data, the terminal converts the image data into a format optimized for projectors and glass wall displays. Specifically, the conversion process involves resizing the image file resolution to 1920x1080 and converting it to an appropriate file format (such as JPEG or PNG).

[0688] Projection of an image by projection means

[0689] The device projects images onto a projector or glass wall display in accordance with the meeting start time. For example, at 14:00, it projects an image of a "beautiful forest landscape" onto the wall, and then switches to an image of a "lake and mountain landscape" 15 minutes later. This projection schedule is managed by the device's timer function.

[0690] User usage

[0691] At the start of a meeting, users are shown images related to the theme projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing the displayed "beautiful forest scenery" can be refreshing and lead to a more lively discussion.

[0692] result

[0693] This system allows the meeting room design to dynamically change according to the meeting's theme and time of day, providing an environment that enhances participants' motivation and concentration. This, in turn, improves the quality of meetings and enables more efficient management.

[0694] Examples of prompt statements

[0695] The following are examples of prompts to input into a generative AI model:

[0696] Prompt: "The meeting theme is 'Natural Environment,' please generate related keywords."

[0697] Example output: Forest, beautiful scenery, fresh air

[0698] Prompt: "Generate images of beautiful forest landscapes using the keyword 'forest'."

[0699] Output example: - Image file -

[0700] Prompt: "Generate images of lake and mountain scenery from the keyword 'beautiful scenery'."

[0701] Output example: - Image file -

[0702] This prompt clearly shows the user how the entire system works and how specific results are produced.

[0703] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0704] Step 1:

[0705] Users enter meeting room reservation information using a dedicated web application or terminal. (Input) Date and time, theme, and participant information. (Output) The reservation information is saved in the system's database. For example, a specific action would be for a user to enter details such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" into a web form.

[0706] Step 2:

[0707] The server retrieves reservation information from the database and generates keywords based on theme information. (Input) Reservation information (theme, etc.). (Prompt to the generating AI model: "Generate keywords related to the theme 'Natural Environment'") (Output) Generated keywords (e.g., forest, beautiful scenery, fresh air). For example, the server uses a generating AI model to extract keywords from the theme.

[0708] Step 3:

[0709] The server uses the generated keywords and an image generation model to generate the corresponding image. (Input) Keywords (e.g., forest, beautiful landscape). (Prompt to the image generation model: "Generate an image of a beautiful forest landscape.") (Output) Generated image file (e.g., forest landscape image). For example, this process includes "Generating an image of a beautiful forest landscape based on the keyword 'forest'."

[0710] Step 4:

[0711] The terminal receives image data sent from the server and converts it to the format best suited to the display device. (Input) The generated image file. (Output) The converted image file (e.g., a JPEG file resized to a resolution suitable for a projector). Specifically, the received image is resized to a resolution of 1920x1080, and other image format conversions are performed.

[0712] Step 5:

[0713] The device projects an image onto a projector or glass wall display in time with the start of the meeting. (Input) Converted image file. (Output) Image projected onto the wall or screen. Specifically, projection starts based on the timer setting; for example, it projects a "beautiful forest landscape" at "14:00" and automatically switches to a "lake and mountain landscape" 15 minutes later.

[0714] Step 6:

[0715] The device changes the projected image during a meeting based on user instructions or timer settings. (Input) User instructions or pre-set timer information. (Output) The changed new image is displayed. Specifically, the user can instruct the user to change the image from a smartphone app, or the device will automatically switch to the next image according to a set timer.

[0716] Step 7:

[0717] After a meeting, users provide feedback on the quality of the meeting and the participants' engagement through the system's evaluation function. (Input) Feedback data (e.g., survey responses). (Output) Feedback data stored on the server. For example, users might answer questions such as, "Were the projected images during the meeting helpful for the discussion?" in a post-meeting survey.

[0718] (Application Example 1)

[0719] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0720] Traditional store design and atmosphere changes are often done manually, which is time-consuming and labor-intensive. Furthermore, it's difficult to change the design in real time according to the season or theme, making it difficult to maintain customer interest. This diminishes the store's appeal and hinders customer engagement.

[0721] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0722] In this invention, the server includes data input means, keyword generation means, image generation means, display modification means, and projection means. This makes it possible to change the design and atmosphere of the store interior in real time according to the store's theme or season.

[0723] "Data entry means" refers to the means by which users input the date and time, theme, and user information.

[0724] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0725] "Image generation means" refers to means for generating images based on the generated keywords.

[0726] "Projection means" refers to means for projecting the generated image onto a display device such as a projector or display.

[0727] "Display modification means" refers to means of changing the design or atmosphere inside a store in real time.

[0728] "Date and time" refers to information that specifies a particular year, month, day, and time.

[0729] A "theme" is a specific concept or idea based on the user's intentions and objectives.

[0730] "User information" refers to information about individuals participating in meetings, events, etc.

[0731] "Related keywords" are concepts or words that correspond to the theme.

[0732] "Store interior" refers to the interior space of a physical store.

[0733] "Design" refers to the visual appearance and layout.

[0734] "Atmosphere" refers to the emotions and environment one feels within a space.

[0735] The present invention provides a system for implementing a function that changes the design of a meeting room in real time according to the reservation details and theme of the meeting room. This system operates in a seamless collaboration between the server, terminal, and user.

[0736] First, users enter meeting room reservation information (date and time, theme, user information, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0737] The server generates keywords related to the theme using an LLM (Large-Scale Language Model) based on the received reservation information. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." In this process, it uses a generative AI model such as OpenAI GPT-3.

[0738] Next, the server generates related images based on the generated keywords using image generation models such as SD (Stable Diffusion). For example, it generates multiple images such as "beautiful forest scenery" from the keyword "forest," and "lake and mountain scenery" from the keyword "beautiful scenery."

[0739] The terminal receives image data transmitted from the server and converts it to an appropriate format. This format conversion is performed so that the image is optimized for projection means such as projectors or glass wall displays.

[0740] Finally, the projection system projects images according to the meeting start time. For example, at 14:00, an image of a beautiful forest landscape is projected onto the wall, and 15 minutes later, it switches to an image of a lake and mountain landscape, promoting user concentration and relaxation.

[0741] For example, if the theme is "Christmas," the server generates keywords such as "Christmas tree," "snowy landscape," and "Santa Claus," and sequentially generates and projects images corresponding to each. In this way, the design changes according to the theme are performed in real time.

[0742] An example of a prompt statement is as follows:

[0743] "Generate keywords based on the following theme: Natural Environment"

[0744] "Please generate related images from the following keywords: forest, beautiful scenery, fresh air"

[0745] In this way, it becomes possible to change the design and atmosphere of not only the meeting rooms but also the interior of the store in real time according to the theme and season. This improves user engagement and allows for the creation of an attractive space.

[0746] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0747] Step 1:

[0748] Users enter meeting room reservation information using a web application or device. Specifically, users enter the date and time, theme, and user information, and send it to the system. For example, the entered data might be "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment." The system then receives this data as reservation information.

[0749] Step 2:

[0750] The server receives reservation information sent by the user. The received data includes the date and time, theme, and user information. Next, the server generates keywords using a Large-Scale Language Model (LLM) based on the theme information. If the input theme information is "natural environment," the generative AI model is used to generate related keywords such as "forest," "beautiful scenery," and "fresh air."

[0751] Step 3:

[0752] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. The keywords generated earlier are used as input data, and the output consists of multiple images corresponding to each keyword. For example, "forest" might generate an image of "beautiful forest scenery," and "beautiful scenery" might generate an image of "lake and mountain scenery."

[0753] Step 4:

[0754] The server sends the generated image data to the terminal. The terminal receives this image data and converts it to the appropriate format. This conversion is performed in a way that is optimal for the image to be projected by a display device (such as a projector or glass wall display). The input is the generated image data, and the output is image data in a format that is optimally displayable by a projector or display.

[0755] Step 5:

[0756] The terminal transmits the received and format-converted image data to the projection means. The projection means projects this image according to the start time of the meeting. For example, at "14:00", an image of a "beautiful forest landscape" is projected onto the wall using a projector, and 15 minutes later, it switches to an image of a "lake and mountain landscape". Format-converted image data is transmitted to the projection means as input, and the image is projected as output at pre-set timings.

[0757] Step 6:

[0758] Users conduct meetings using projected images. Users proceed with the meeting while viewing theme-related images projected onto a projector or glass wall display. This operation is expected to increase participant relaxation and concentration, leading to more active discussion. The input is the image projected onto the projector, and the output is expected to improve the quality of the meeting.

[0759] In this way, the system can automatically change the design according to the theme based on the user's reservation information, optimizing the atmosphere of the meeting room in real time.

[0760] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0761] System Overview

[0762] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. In particular, it is characterized by providing an optimal environment that responds to the user's emotions by combining it with an emotion engine that recognizes the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0763] User input of meeting room reservation information

[0764] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participants, etc.). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0765] Receiving and storing reservation information on the server.

[0766] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0767] Keyword generation

[0768] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0769] Image generation

[0770] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0771] Image data format conversion

[0772] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0773] Schedule management

[0774] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0775] Image projection

[0776] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0777] User emotion recognition by an emotion engine

[0778] Terminal: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it collects user emotion data through the camera and microphone.

[0779] Image changes based on emotions

[0780] Server: The emotion engine recognizes emotional information in real time and selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0781] User usage

[0782] User: When a meeting begins, images related to the topic are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the topic. As a result, discussions become more lively, and the quality of the meeting improves. In addition, emotions are recognized during the meeting, and the images are changed accordingly, providing a more comfortable environment.

[0783] result

[0784] This system allows the meeting room design to change according to the meeting's theme, time of day, and even the user's emotions, thereby increasing participant motivation and concentration. It also contributes to improving the quality of meetings. This system operates seamlessly, from user interaction to server data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0785] The following describes the processing flow.

[0786] Step 1: User enters meeting room reservation information.

[0787] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participant information). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0788] Step 2: Server receives and stores reservation information.

[0789] Server: Receives reservation information submitted by users and stores it in the database. During this process, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0790] Step 3: Keyword Generation

[0791] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0792] Step 4: Image generation

[0793] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0794] Step 5: Convert image data format

[0795] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0796] Step 6: Collecting emotional data using the emotion engine

[0797] Device: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it captures video with a camera and collects audio with a microphone. This data is analyzed in real time to detect the user's emotions.

[0798] Step 7: Emotion-based image selection

[0799] Server: Based on the emotional information recognized by the emotion engine, the server dynamically selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[0800] Step 8: Schedule management and image projection

[0801] Terminal: Manages the schedule based on the meeting reservation time and prepares to project relevant images as the reservation start time approaches. Projects images onto the walls inside and outside the meeting room using a projector or glass wall display in line with the meeting start time. For example, project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0802] Step 9: User Use

[0803] User: Enters a meeting room and begins the meeting in an environment where theme-related images are projected onto the walls. The user experiences relaxation or increased concentration effects from the images. Furthermore, if changes in emotions are detected during the meeting, the projected images are changed accordingly, providing a comfortable and adaptive environment.

[0804] This series of steps allows the meeting room design to change according to the theme, time, and even the user's emotions, providing an effective meeting environment.

[0805] (Example 2)

[0806] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0807] Traditional meeting room management systems primarily focus on inputting and managing reservation information, lacking the functionality to dynamically change the meeting room environment. Therefore, it is difficult to provide an optimal environment based on the meeting's theme or the participants' moods. Furthermore, while new methods are needed to improve the quality of meetings, currently, customization of the environment based on user emotions is not realized.

[0808] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0809] In this invention, the server includes data input means, keyword generation means, image generation means, format conversion means, schedule management means, emotion recognition means, real-time update means, and projection means. This makes it possible to dynamically change the design of the meeting room according to the theme of the meeting and the emotions of the participants, thereby providing an optimal environment.

[0810] "Data entry means" refers to the means of inputting meeting room reservation information, such as date, time, theme, and participant information, into the system.

[0811] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[0812] "Image generation means" refers to a means of generating images corresponding to a theme using an image generation model based on generated keywords.

[0813] "Format conversion means" refers to means of converting the generated image data into a format suitable for projectors or glass wall displays.

[0814] A "schedule management method" refers to a means of managing the schedule based on the reserved time of a meeting and preparing for the projection of related images.

[0815] "Emotion recognition means" refers to a method of recognizing emotions by analyzing the user's facial expressions and tone of voice during a meeting.

[0816] A "real-time update means" is a means of updating the projected image in real time based on emotional information acquired from an emotion recognition means.

[0817] "Projection means" refers to a means of projecting the generated image onto the walls inside or outside the conference room using a projector or glass wall display.

[0818] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and theme, providing an optimal environment that responds to the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[0819] User input of meeting room reservation information

[0820] Users use a dedicated web application or terminal to reserve meeting rooms and enter reservation information such as the date, time, theme, and participants. For example, they might enter "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and press the submit button. This sends the entered data to the server.

[0821] Receiving and storing reservation information on the server.

[0822] The server receives meeting room reservation information sent by the user and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table. Specifically, the server parses the received data, executes SQL queries, and saves the data.

[0823] Keyword generation

[0824] The server reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." Specifically, it generates text prompts for the LLM and retrieves its responses.

[0825] Image generation

[0826] The server uses image generation models such as Stable Diffusion to generate images corresponding to the theme based on the generated keywords. For example, if the keyword is "forest," it will generate an image of a "beautiful forest landscape." The generated image data is temporarily stored in the server's storage.

[0827] Image data format conversion

[0828] The device receives notification of image data generated from the server and downloads the image. The downloaded image data is converted to a format suitable for projectors and glass wall displays. The image is then optimized using image processing libraries such as Unicorn Image Toolkit.

[0829] Schedule management

[0830] The terminal manages the schedule based on the scheduled meeting time. For example, it displays an alert 10 minutes before the scheduled start time and prepares to project any relevant images. Specifically, it uses system timers to handle situations before and after the meeting.

[0831] Image projection

[0832] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, it might project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[0833] Emotion recognition by an emotion engine

[0834] During meetings, the device uses an emotion engine to analyze the user's facial expressions and tone of voice to recognize their emotions. Specifically, it collects data in real time through the camera and microphone and inputs it into an emotion analysis model.

[0835] Image changes based on emotions

[0836] The server recognizes emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will project a "calm lake view." Specifically, it generates new image generation prompts based on emotional data acquired periodically.

[0837] Real-time image projection

[0838] The terminal receives new image data sent from the server and projects the images onto the walls inside and outside the conference room in real time. For example, it updates the image the moment a user reacts, providing an optimal environment according to the progress of the meeting.

[0839] Example of a prompt

[0840] For example, the prompt text to be input to the image generation model would be as follows:

[0841] "Please generate images of beautiful forest landscapes based on the theme of the natural environment."

[0842] "Please generate images of lake and mountain scenery using the keyword 'beautiful landscape'."

[0843] This allows for dynamic changes to the meeting room design based on the meeting's theme, time of day, and even the user's emotions, thereby enhancing participant motivation and concentration. The system seamlessly integrates user interaction, server-side data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[0844] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0845] System program processing flow

[0846] Step 1: User enters meeting room reservation information.

[0847] Users use a dedicated web application or terminal to reserve meeting rooms, entering reservation information such as date, time, theme, and participants, and then pressing the submit button. Input: Date, time, theme, and participant information. Output: The entered information is sent to the server.

[0848] Step 2: Server receives and stores reservation information.

[0849] The server receives meeting room reservation information submitted by users and stores it in the database. It parses the received data and records it in the reservation information table in the appropriate format. Input: Reservation information submitted by users. Output: Reservation information stored in the database.

[0850] Step 3: Generating keywords from the theme

[0851] The server reads theme information stored in the database and generates related keywords using a Large-Scale Language Model (LLM). It passes the theme information to the LLM to generate a prompt and retrieves its response. Input: Theme information stored in the database. Output: Generated related keywords.

[0852] Step 4: Image generation

[0853] The server uses an image generation model to generate images corresponding to the theme based on the generated keywords. The generated keywords are then used as prompts to retrieve image data from a generative AI model such as Stable Diffusion. Input: Generated keywords. Output: Generated image data.

[0854] Step 5: Convert image data format

[0855] The device receives a notification from the server and downloads the generated image data. Using an image processing library such as Unicorn Image Toolkit, the downloaded image data is converted to a format suitable for projectors or glass wall displays. Input: Generated image data. Output: Image data in the converted format.

[0856] Step 6: Schedule Management

[0857] The terminal manages the schedule based on the meeting reservation time. It sets a system timer, displays alerts before and after the meeting starts, and prepares for the projection of related images. Input: Meeting reservation time and image data. Output: Completion of projection preparation.

[0858] Step 7: Projecting images into the conference room

[0859] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. A system timer projects, for example, a "beautiful forest landscape" image at "14:00" and switches to a "lake and mountain landscape" 15 minutes later. Input: Image data in the converted format. Output: Projected image.

[0860] Step 8: Emotion recognition by the emotion engine

[0861] The device uses an emotion engine to analyze the user's facial expressions and voice tone during meetings to recognize their emotions. Data is collected through the camera and microphone and input into the emotion analysis model. Input: User's facial expression data, voice tone data. Output: Analyzed emotion information.

[0862] Step 9: Change the image according to your emotions.

[0863] The server recognizes the emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will generate a new image generation prompt to change it to a "calm lake view." Input: Analyzed emotional information. Output: New image data.

[0864] Step 10: Real-time image projection

[0865] The terminal receives new image data from the server and projects the images onto the walls inside and outside the conference room in real time. The image is updated the moment the user reacts, providing an optimal environment according to the progress of the meeting. Input: New image data. Output: Updated projected image.

[0866] (Application Example 2)

[0867] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0868] Conventional manufacturing lines lacked environmental adjustments tailored to workers' stress levels and concentration levels, leading to problems such as decreased work efficiency and worker satisfaction. Furthermore, the absence of dynamic environmental optimization methods utilizing emotion recognition prevented real-time countermeasures.

[0869] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes data input means, keyword generation means, image generation means, emotion recognition means, environment adjustment means, and projection means. This makes it possible to analyze the facial expressions and tone of voice of workers in real time and provide an optimal work environment that corresponds to their emotions.

[0870] "Data input means" refers to a device or method for receiving data such as date and time, theme, and participant information.

[0871] "Keyword generation means" refers to a device or method that generates relevant keywords based on theme information received from a data input means.

[0872] "Image generation means" refers to a device or method that generates image data based on the generated keywords.

[0873] "Projection means" refers to a device or method for displaying generated image data using a projector, display, or the like.

[0874] "Emotion recognition means" refers to a device or method that analyzes a user's facial expressions and voice data to recognize their emotions in real time.

[0875] "Environmental adjustment means" refers to a device or method that dynamically optimizes the environment, such as music, lighting, and display content, based on emotions recognized by emotion recognition means.

[0876] This invention provides a robotic system that dynamically optimizes the work environment based on the stress levels and concentration levels of workers on a manufacturing line. A specific example of the system is described below.

[0877] System program

[0878] The system consists of data input means, keyword generation means, image generation means, projection means, emotion recognition means, and environment adjustment means. The emotion recognition means has the function of analyzing the facial expressions and voice data of workers on the manufacturing line to recognize stress levels and concentration levels in real time. Based on this, the environment adjustment means dynamically provides the optimal working environment for the workers.

[0879] Hardware and software

[0880] Hardware:

[0881] Camera (e.g., Logitech C920): Acquires facial expression data of workers.

[0882] Microphone (e.g., Blue Yeti): Captures the worker's voice data.

[0883] Projector or display: Displays the generated image data.

[0884] software:

[0885] Emotion Engine (e.g., EmotionEngine): Analyzes workers' facial expressions and voice data to recognize emotions.

[0886] Environmental control systems (e.g., EnvironmentControl): Adjust the environment based on recognized emotions.

[0887] Image generation model (e.g., Stable Diffusion): Generates images based on keywords.

[0888] Data processing and data calculation

[0889] Data acquisition from camera and microphone:

[0890] The device acquires facial expression data from the camera and audio data from the microphone. This data is analyzed by emotion recognition technology, and stress levels and concentration levels are determined in real time.

[0891] Emotion recognition and environmental adjustment:

[0892] Based on the worker's emotions as determined by the emotion recognition system, the environmental adjustment system optimizes the work environment. For example, if the system determines that the worker is tired, it plays relaxing background music and softens the lighting. Conversely, if the system determines that the worker is focused, it plays background music that helps maintain focus and brightens the lighting.

[0893] Specific example

[0894] Example 1:

[0895] If a worker is deemed to be experiencing stress during work, images of "natural scenery" are projected onto the work area via a projector, providing a relaxing environment.

[0896] Example 2:

[0897] To improve work efficiency, when concentration is needed, the environmental control system plays background music designed for focus, accompanied by an image of a "calm lake landscape."

[0898] Example of a prompt

[0899] Design a system that analyzes the facial expressions and tone of voice of workers on a manufacturing line and adjusts the work environment based on their stress levels and concentration levels. For example, if a worker is determined to be tired, the system should change the background music or lighting to provide a more relaxing environment.

[0900] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0901] Step 1:

[0902] The device uses a camera and microphone to acquire facial and voice data from workers. This input data enables subsequent emotion recognition.

[0903] Step 2:

[0904] The terminal inputs the acquired facial expression data and voice data into the emotion recognition device. The emotion recognition device analyzes this data and determines the worker's emotions (stress level and concentration level). The emotion recognition result is then generated.

[0905] Step 3:

[0906] The server receives emotion data transmitted from the emotion recognition device and triggers the environment adjustment device based on the results. This emotion data determines what kind of environment adjustment is needed.

[0907] Step 4:

[0908] The server inputs shift information and theme information received from the data input means into the keyword generation means. The keyword generation means generates keywords related to the theme.

[0909] Step 5:

[0910] The server inputs the generated keywords into an image generation model. This model generates images based on the keywords. For example, it might generate images corresponding to "relax" or "concentrate."

[0911] Step 6:

[0912] The server sends the generated image to the terminal. The terminal receives this image data and sends it to the projection means. The projection means displays the image using a projector or display.

[0913] Step 7:

[0914] The terminal triggers environmental adjustments based on a schedule. For example, it provides relaxing background music and lighting when a worker is tired, and a focused environment when concentration is needed.

[0915] Step 8:

[0916] Users can experience the effects of environmental adjustments in real time while continuing their work. This provides an environment that improves work efficiency and reduces stress.

[0917] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0918] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0919] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0920] [Fourth Embodiment]

[0921] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0922] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0923] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0924] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0925] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0926] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0927] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0928] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0929] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0930] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0931] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0932] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0933] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0934] System Overview

[0935] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. The following explains, with specific examples, how the server, terminal, and user each operate.

[0936] User input of meeting room reservation information

[0937] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, if a user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data will be sent to the system.

[0938] Keyword generation by the server

[0939] Server: After receiving reservation information, it uses an LLM (Large-Scale Language Model) to generate keywords related to the theme. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0940] Image generation by the server

[0941] Server: After keyword generation, the server uses image generation models such as SD (Stable Diffusion) to generate images based on these keywords. For example, it generates an image of a "beautiful forest landscape" from the keyword "forest," and an image of a "lake and mountain landscape" from the keyword "beautiful landscape."

[0942] Receiving image data via the terminal and preparing for projection.

[0943] Terminal: Receives image data generated from the server and converts it to the required format. Then, it prepares the image data for use with projectors and glass wall displays.

[0944] Projection of an image by projection means

[0945] Terminal: Project images onto a projector or glass wall display in accordance with the meeting start time. For example, project an image of a "beautiful forest landscape" onto the wall at "14:00," and then switch to an image of a "lake and mountain landscape" 15 minutes later.

[0946] User usage

[0947] User: When a meeting begins, images related to the theme are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing a "beautiful forest landscape" can refresh the mind and lead to a more lively discussion.

[0948] result

[0949] This allows the meeting room design to change according to the meeting's theme and time of day, thereby increasing participants' motivation and concentration. It also contributes to improving the quality of the meeting.

[0950] The system of this invention operates seamlessly, from user operation to data processing on the server and image projection on the terminal, enabling efficient management and optimization of the meeting environment.

[0951] The following describes the processing flow.

[0952] Step 1: User enters meeting room reservation information.

[0953] User: Use a dedicated web application or terminal to enter meeting room reservation information (date, time, theme, participants, etc.). For example, the user enters "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[0954] Step 2: Server receives and stores reservation information.

[0955] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[0956] Step 3: Keyword Generation

[0957] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[0958] Step 4: Image generation

[0959] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[0960] Step 5: Convert image data format

[0961] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[0962] Step 6: Schedule Management

[0963] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[0964] Step 7: Projecting the Image

[0965] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[0966] Step 8: User Use

[0967] User: Enters the meeting room and sees the displayed images. Users become relaxed or more focused by the topic-related images. As a result, discussion becomes more lively and the quality of the meeting improves.

[0968] This series of steps allows the meeting room design to change according to the theme and time, providing an effective meeting environment.

[0969] (Example 1)

[0970] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0971] Traditional meeting room systems were unable to change the meeting room design in real time based on reservation information, making it difficult to optimize meeting themes and participant motivation. Furthermore, the manual operation required to change the meeting environment design was cumbersome, hindering efficient management. Additionally, the lack of sufficient automation for image generation and projection compromised user convenience.

[0972] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0973] In this invention, the server includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means. This allows users to simply input meeting reservation information, and based on that information, images are generated in real time, format converted, and projected into the meeting room. This automatically provides an optimal environment for the meeting theme and enhances participants' concentration, thereby improving meeting quality and achieving efficient environment management.

[0974] "Data entry means" refers to an interface for users to enter meeting room reservation information, and has the function of accepting information such as date and time, theme, and participant information.

[0975] A "keyword generation means" is a component that has the function of generating relevant keywords based on theme information received from a data input means. Specifically, it generates keywords using a generation AI model.

[0976] An "image generation means" is a component that has the function of generating a corresponding image using an image generation model based on keywords generated by a keyword generation means.

[0977] The "image receiving and format conversion means" is a component that has the function of receiving image data transmitted from a server and converting it into a format suitable for output devices such as projectors and displays.

[0978] A "projection means" is a component that has the function of projecting prepared images onto a projector or display placed in the conference room, and also includes the function of switching images based on set times or events.

[0979] System Overview

[0980] This invention relates to a system that changes the design of a conference room in real time according to the conference room reservation details and the office theme. The system includes data input means, keyword generation means, image generation means, image reception and format conversion means, and projection means.

[0981] User input of meeting room reservation information

[0982] Users enter meeting room reservation information (date, time, theme, participants, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[0983] Keyword generation by the server

[0984] After receiving the reservation information, the server uses a generative AI model (for example, a type of large-scale language model) to generate keywords related to the theme. If the prompt is "Generate keywords related to the theme 'natural environment'", keywords such as "forest", "beautiful scenery", and "fresh air" will be generated.

[0985] Image generation by the server

[0986] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. Specifically, if the keyword is "forest" and the prompt "Generate an image of a beautiful forest landscape" is entered, the image generation model will generate an image file based on that prompt. Images will be generated similarly for other keywords.

[0987] Receiving image data via the terminal and preparing for projection.

[0988] The terminal receives image data sent from the server. After receiving the data, the terminal converts the image data into a format optimized for projectors and glass wall displays. Specifically, the conversion process involves resizing the image file resolution to 1920x1080 and converting it to an appropriate file format (such as JPEG or PNG).

[0989] Projection of an image by projection means

[0990] The device projects images onto a projector or glass wall display in accordance with the meeting start time. For example, at 14:00, it projects an image of a "beautiful forest landscape" onto the wall, and then switches to an image of a "lake and mountain landscape" 15 minutes later. This projection schedule is managed by the device's timer function.

[0991] User usage

[0992] At the start of a meeting, users are shown images related to the theme projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the theme. For example, entering a meeting room designed with a natural environment theme and seeing the displayed "beautiful forest scenery" can be refreshing and lead to a more lively discussion.

[0993] result

[0994] This system allows the meeting room design to dynamically change according to the meeting's theme and time of day, providing an environment that enhances participants' motivation and concentration. This, in turn, improves the quality of meetings and enables more efficient management.

[0995] Examples of prompt statements

[0996] The following are examples of prompts to input into a generative AI model:

[0997] Prompt: "The meeting theme is 'Natural Environment,' please generate related keywords."

[0998] Example output: Forest, beautiful scenery, fresh air

[0999] Prompt: "Generate images of beautiful forest landscapes using the keyword 'forest'."

[1000] Output example: - Image file -

[1001] Prompt: "Generate images of lake and mountain scenery from the keyword 'beautiful scenery'."

[1002] Output example: - Image file -

[1003] This prompt clearly shows the user how the entire system works and how specific results are produced.

[1004] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1005] Step 1:

[1006] Users enter meeting room reservation information using a dedicated web application or terminal. (Input) Date and time, theme, and participant information. (Output) The reservation information is saved in the system's database. For example, a specific action would be for a user to enter details such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" into a web form.

[1007] Step 2:

[1008] The server retrieves reservation information from the database and generates keywords based on theme information. (Input) Reservation information (theme, etc.). (Prompt to the generating AI model: "Generate keywords related to the theme 'Natural Environment'") (Output) Generated keywords (e.g., forest, beautiful scenery, fresh air). For example, the server uses a generating AI model to extract keywords from the theme.

[1009] Step 3:

[1010] The server uses the generated keywords and an image generation model to generate the corresponding image. (Input) Keywords (e.g., forest, beautiful landscape). (Prompt to the image generation model: "Generate an image of a beautiful forest landscape.") (Output) Generated image file (e.g., forest landscape image). For example, this process includes "Generating an image of a beautiful forest landscape based on the keyword 'forest'."

[1011] Step 4:

[1012] The terminal receives image data sent from the server and converts it to the format best suited to the display device. (Input) The generated image file. (Output) The converted image file (e.g., a JPEG file resized to a resolution suitable for a projector). Specifically, the received image is resized to a resolution of 1920x1080, and other image format conversions are performed.

[1013] Step 5:

[1014] The device projects an image onto a projector or glass wall display in time with the start of the meeting. (Input) Converted image file. (Output) Image projected onto the wall or screen. Specifically, projection starts based on the timer setting; for example, it projects a "beautiful forest landscape" at "14:00" and automatically switches to a "lake and mountain landscape" 15 minutes later.

[1015] Step 6:

[1016] The device changes the projected image during a meeting based on user instructions or timer settings. (Input) User instructions or pre-set timer information. (Output) The changed new image is displayed. Specifically, the user can instruct the user to change the image from a smartphone app, or the device will automatically switch to the next image according to a set timer.

[1017] Step 7:

[1018] After a meeting, users provide feedback on the quality of the meeting and the participants' engagement through the system's evaluation function. (Input) Feedback data (e.g., survey responses). (Output) Feedback data stored on the server. For example, users might answer questions such as, "Were the projected images during the meeting helpful for the discussion?" in a post-meeting survey.

[1019] (Application Example 1)

[1020] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1021] Traditional store design and atmosphere changes are often done manually, which is time-consuming and labor-intensive. Furthermore, it's difficult to change the design in real time according to the season or theme, making it difficult to maintain customer interest. This diminishes the store's appeal and hinders customer engagement.

[1022] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1023] In this invention, the server includes data input means, keyword generation means, image generation means, display modification means, and projection means. This makes it possible to change the design and atmosphere of the store interior in real time according to the store's theme or season.

[1024] "Data entry means" refers to the means by which users input the date and time, theme, and user information.

[1025] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[1026] "Image generation means" refers to means for generating images based on the generated keywords.

[1027] "Projection means" refers to means for projecting the generated image onto a display device such as a projector or display.

[1028] "Display modification means" refers to means of changing the design or atmosphere inside a store in real time.

[1029] "Date and time" refers to information that specifies a particular year, month, day, and time.

[1030] A "theme" is a specific concept or idea based on the user's intentions and objectives.

[1031] "User information" refers to information about individuals participating in meetings, events, etc.

[1032] "Related keywords" are concepts or words that correspond to the theme.

[1033] "Store interior" refers to the interior space of a physical store.

[1034] "Design" refers to the visual appearance and layout.

[1035] "Atmosphere" refers to the emotions and environment one feels within a space.

[1036] The present invention provides a system for implementing a function that changes the design of a meeting room in real time according to the reservation details and theme of the meeting room. This system operates in a seamless collaboration between the server, terminal, and user.

[1037] First, users enter meeting room reservation information (date and time, theme, user information, etc.) using a dedicated web application or terminal for meeting room reservations. For example, if a user enters information such as "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment," this data is sent to the system.

[1038] The server generates keywords related to the theme using an LLM (Large-Scale Language Model) based on the received reservation information. For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." In this process, it uses a generative AI model such as OpenAI GPT-3.

[1039] Next, the server generates related images based on the generated keywords using image generation models such as SD (Stable Diffusion). For example, it generates multiple images such as "beautiful forest scenery" from the keyword "forest," and "lake and mountain scenery" from the keyword "beautiful scenery."

[1040] The terminal receives image data transmitted from the server and converts it to an appropriate format. This format conversion is performed so that the image is optimized for projection means such as projectors or glass wall displays.

[1041] Finally, the projection system projects images according to the meeting start time. For example, at 14:00, an image of a beautiful forest landscape is projected onto the wall, and 15 minutes later, it switches to an image of a lake and mountain landscape, promoting user concentration and relaxation.

[1042] For example, if the theme is "Christmas," the server generates keywords such as "Christmas tree," "snowy landscape," and "Santa Claus," and sequentially generates and projects images corresponding to each. In this way, the design changes according to the theme are performed in real time.

[1043] An example of a prompt statement is as follows:

[1044] "Generate keywords based on the following theme: Natural Environment"

[1045] "Please generate related images from the following keywords: forest, beautiful scenery, fresh air"

[1046] In this way, it becomes possible to change the design and atmosphere of not only the meeting rooms but also the interior of the store in real time according to the theme and season. This improves user engagement and allows for the creation of an attractive space.

[1047] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1048] Step 1:

[1049] Users enter meeting room reservation information using a web application or device. Specifically, users enter the date and time, theme, and user information, and send it to the system. For example, the entered data might be "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment." The system then receives this data as reservation information.

[1050] Step 2:

[1051] The server receives reservation information sent by the user. The received data includes the date and time, theme, and user information. Next, the server generates keywords using a Large-Scale Language Model (LLM) based on the theme information. If the input theme information is "natural environment," the generative AI model is used to generate related keywords such as "forest," "beautiful scenery," and "fresh air."

[1052] Step 3:

[1053] The server generates images using an image generation model (e.g., Stable Diffusion) based on the generated keywords. The keywords generated earlier are used as input data, and the output consists of multiple images corresponding to each keyword. For example, "forest" might generate an image of "beautiful forest scenery," and "beautiful scenery" might generate an image of "lake and mountain scenery."

[1054] Step 4:

[1055] The server sends the generated image data to the terminal. The terminal receives this image data and converts it to the appropriate format. This conversion is performed in a way that is optimal for the image to be projected by a display device (such as a projector or glass wall display). The input is the generated image data, and the output is image data in a format that is optimally displayable by a projector or display.

[1056] Step 5:

[1057] The terminal transmits the received and format-converted image data to the projection means. The projection means projects this image according to the start time of the meeting. For example, at "14:00", an image of a "beautiful forest landscape" is projected onto the wall using a projector, and 15 minutes later, it switches to an image of a "lake and mountain landscape". Format-converted image data is transmitted to the projection means as input, and the image is projected as output at pre-set timings.

[1058] Step 6:

[1059] Users conduct meetings using projected images. Users proceed with the meeting while viewing theme-related images projected onto a projector or glass wall display. This operation is expected to increase participant relaxation and concentration, leading to more active discussion. The input is the image projected onto the projector, and the output is expected to improve the quality of the meeting.

[1060] In this way, the system can automatically change the design according to the theme based on the user's reservation information, optimizing the atmosphere of the meeting room in real time.

[1061] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1062] System Overview

[1063] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and the theme of the office. In particular, it is characterized by providing an optimal environment that responds to the user's emotions by combining it with an emotion engine that recognizes the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[1064] User input of meeting room reservation information

[1065] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participants, etc.). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[1066] Receiving and storing reservation information on the server.

[1067] Server: Receives reservation information sent by users and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[1068] Keyword generation

[1069] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[1070] Image generation

[1071] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[1072] Image data format conversion

[1073] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[1074] Schedule management

[1075] Terminal: Manages the schedule based on the meeting reservation time. As the reservation start time approaches, prepares the projection of relevant images.

[1076] Image projection

[1077] Terminal: Images generated using a projector or glass wall display are projected onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, an image of a "beautiful forest landscape" is projected at "14:00," and then switched to a "lake and mountain landscape" 15 minutes later.

[1078] User emotion recognition by an emotion engine

[1079] Terminal: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it collects user emotion data through the camera and microphone.

[1080] Image changes based on emotions

[1081] Server: The emotion engine recognizes emotional information in real time and selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[1082] User usage

[1083] User: When a meeting begins, images related to the topic are projected onto the walls inside and outside the meeting room. This design change helps users relax and focus on the topic. As a result, discussions become more lively, and the quality of the meeting improves. In addition, emotions are recognized during the meeting, and the images are changed accordingly, providing a more comfortable environment.

[1084] result

[1085] This system allows the meeting room design to change according to the meeting's theme, time of day, and even the user's emotions, thereby increasing participant motivation and concentration. It also contributes to improving the quality of meetings. This system operates seamlessly, from user interaction to server data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[1086] The following describes the processing flow.

[1087] Step 1: User enters meeting room reservation information.

[1088] User: Use a dedicated web application or terminal to reserve a meeting room and enter the reservation information (date, time, theme, participant information). For example, the user enters the information "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and presses the submit button.

[1089] Step 2: Server receives and stores reservation information.

[1090] Server: Receives reservation information submitted by users and stores it in the database. During this process, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table.

[1091] Step 3: Keyword Generation

[1092] Server: Reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air."

[1093] Step 4: Image generation

[1094] Server: Based on the generated keywords, it uses image generation models such as Stable Diffusion to generate images corresponding to the theme. For example, it generates images of "beautiful forest scenery" from "forest" and images of "lake and mountain scenery" from "beautiful scenery". The generated image data is temporarily stored.

[1095] Step 5: Convert image data format

[1096] Terminal: Receives notifications from the server and downloads the generated image data. Converts the downloaded image data to a format suitable for projectors and glass wall displays.

[1097] Step 6: Collecting emotional data using the emotion engine

[1098] Device: During a meeting, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, it captures video with a camera and collects audio with a microphone. This data is analyzed in real time to detect the user's emotions.

[1099] Step 7: Emotion-based image selection

[1100] Server: Based on the emotional information recognized by the emotion engine, the server dynamically selects the image to project. For example, if the user is relaxed, it maintains a "natural landscape" image, and if they are stressed, it changes to a "calm lake view."

[1101] Step 8: Schedule management and image projection

[1102] Terminal: Manages the schedule based on the meeting reservation time and prepares to project relevant images as the reservation start time approaches. Projects images onto the walls inside and outside the meeting room using a projector or glass wall display in line with the meeting start time. For example, project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[1103] Step 9: User Use

[1104] User: Enters a meeting room and begins the meeting in an environment where theme-related images are projected onto the walls. The user experiences relaxation or increased concentration effects from the images. Furthermore, if changes in emotions are detected during the meeting, the projected images are changed accordingly, providing a comfortable and adaptive environment.

[1105] This series of steps allows the meeting room design to change according to the theme, time, and even the user's emotions, providing an effective meeting environment.

[1106] (Example 2)

[1107] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1108] Traditional meeting room management systems primarily focus on inputting and managing reservation information, lacking the functionality to dynamically change the meeting room environment. Therefore, it is difficult to provide an optimal environment based on the meeting's theme or the participants' moods. Furthermore, while new methods are needed to improve the quality of meetings, currently, customization of the environment based on user emotions is not realized.

[1109] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1110] In this invention, the server includes data input means, keyword generation means, image generation means, format conversion means, schedule management means, emotion recognition means, real-time update means, and projection means. This makes it possible to dynamically change the design of the meeting room according to the theme of the meeting and the emotions of the participants, thereby providing an optimal environment.

[1111] "Data entry means" refers to the means of inputting meeting room reservation information, such as date, time, theme, and participant information, into the system.

[1112] A "keyword generation means" is a means for generating relevant keywords based on theme information received from a data input means.

[1113] "Image generation means" refers to a means of generating images corresponding to a theme using an image generation model based on generated keywords.

[1114] "Format conversion means" refers to means of converting the generated image data into a format suitable for projectors or glass wall displays.

[1115] A "schedule management method" refers to a means of managing the schedule based on the reserved time of a meeting and preparing for the projection of related images.

[1116] "Emotion recognition means" refers to a method of recognizing emotions by analyzing the user's facial expressions and tone of voice during a meeting.

[1117] A "real-time update means" is a means of updating the projected image in real time based on emotional information acquired from an emotion recognition means.

[1118] "Projection means" refers to a means of projecting the generated image onto the walls inside or outside the conference room using a projector or glass wall display.

[1119] This invention relates to a system that changes the design of a meeting room in real time according to the reservation details and theme, providing an optimal environment that responds to the user's emotions. The following explains how the server, terminal, and user each operate with specific examples.

[1120] User input of meeting room reservation information

[1121] Users use a dedicated web application or terminal to reserve meeting rooms and enter reservation information such as the date, time, theme, and participants. For example, they might enter "October 15, 2023, 14:00 - 16:00, Theme: Natural Environment" and press the submit button. This sends the entered data to the server.

[1122] Receiving and storing reservation information on the server.

[1123] The server receives meeting room reservation information sent by the user and stores it in the database. At this time, the date, time, theme, and participant information are appropriately formatted and recorded in the reservation information table. Specifically, the server parses the received data, executes SQL queries, and saves the data.

[1124] Keyword generation

[1125] The server reads theme information stored in the database and generates keywords related to the theme using a Large-Scale Language Model (LLM). For example, based on the theme "natural environment," it generates keywords such as "forest," "beautiful scenery," and "fresh air." Specifically, it generates text prompts for the LLM and retrieves its responses.

[1126] Image generation

[1127] The server uses image generation models such as Stable Diffusion to generate images corresponding to the theme based on the generated keywords. For example, if the keyword is "forest," it will generate an image of a "beautiful forest landscape." The generated image data is temporarily stored in the server's storage.

[1128] Image data format conversion

[1129] The device receives notification of image data generated from the server and downloads the image. The downloaded image data is converted to a format suitable for projectors and glass wall displays. The image is then optimized using image processing libraries such as Unicorn Image Toolkit.

[1130] Schedule management

[1131] The terminal manages the schedule based on the scheduled meeting time. For example, it displays an alert 10 minutes before the scheduled start time and prepares to project any relevant images. Specifically, it uses system timers to handle situations before and after the meeting.

[1132] Image projection

[1133] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. For example, it might project an image of a "beautiful forest landscape" at "14:00" and switch to a "lake and mountain landscape" 15 minutes later.

[1134] Emotion recognition by an emotion engine

[1135] During meetings, the device uses an emotion engine to analyze the user's facial expressions and tone of voice to recognize their emotions. Specifically, it collects data in real time through the camera and microphone and inputs it into an emotion analysis model.

[1136] Image changes based on emotions

[1137] The server recognizes emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will project a "calm lake view." Specifically, it generates new image generation prompts based on emotional data acquired periodically.

[1138] Real-time image projection

[1139] The terminal receives new image data sent from the server and projects the images onto the walls inside and outside the conference room in real time. For example, it updates the image the moment a user reacts, providing an optimal environment according to the progress of the meeting.

[1140] Example of a prompt

[1141] For example, the prompt text to be input to the image generation model would be as follows:

[1142] "Please generate images of beautiful forest landscapes based on the theme of the natural environment."

[1143] "Please generate images of lake and mountain scenery using the keyword 'beautiful landscape'."

[1144] This allows for dynamic changes to the meeting room design based on the meeting's theme, time of day, and even the user's emotions, thereby enhancing participant motivation and concentration. The system seamlessly integrates user interaction, server-side data processing, image projection on terminals, and emotion recognition, enabling efficient management and optimization of the meeting environment.

[1145] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1146] System program processing flow

[1147] Step 1: User enters meeting room reservation information.

[1148] Users use a dedicated web application or terminal to reserve meeting rooms, entering reservation information such as date, time, theme, and participants, and then pressing the submit button. Input: Date, time, theme, and participant information. Output: The entered information is sent to the server.

[1149] Step 2: Server receives and stores reservation information.

[1150] The server receives meeting room reservation information submitted by users and stores it in the database. It parses the received data and records it in the reservation information table in the appropriate format. Input: Reservation information submitted by users. Output: Reservation information stored in the database.

[1151] Step 3: Generating keywords from the theme

[1152] The server reads theme information stored in the database and generates related keywords using a Large-Scale Language Model (LLM). It passes the theme information to the LLM to generate a prompt and retrieves its response. Input: Theme information stored in the database. Output: Generated related keywords.

[1153] Step 4: Image generation

[1154] The server uses an image generation model to generate images corresponding to the theme based on the generated keywords. The generated keywords are then used as prompts to retrieve image data from a generative AI model such as Stable Diffusion. Input: Generated keywords. Output: Generated image data.

[1155] Step 5: Convert image data format

[1156] The device receives a notification from the server and downloads the generated image data. Using an image processing library such as Unicorn Image Toolkit, the downloaded image data is converted to a format suitable for projectors or glass wall displays. Input: Generated image data. Output: Image data in the converted format.

[1157] Step 6: Schedule Management

[1158] The terminal manages the schedule based on the meeting reservation time. It sets a system timer, displays alerts before and after the meeting starts, and prepares for the projection of related images. Input: Meeting reservation time and image data. Output: Completion of projection preparation.

[1159] Step 7: Projecting images into the conference room

[1160] The terminal projects images generated using a projector or glass wall display onto the walls inside and outside the meeting room, timed to coincide with the start of the meeting. A system timer projects, for example, a "beautiful forest landscape" image at "14:00" and switches to a "lake and mountain landscape" 15 minutes later. Input: Image data in the converted format. Output: Projected image.

[1161] Step 8: Emotion recognition by the emotion engine

[1162] The device uses an emotion engine to analyze the user's facial expressions and voice tone during meetings to recognize their emotions. Data is collected through the camera and microphone and input into the emotion analysis model. Input: User's facial expression data, voice tone data. Output: Analyzed emotion information.

[1163] Step 9: Change the image according to your emotions.

[1164] The server recognizes the emotional information sent from the emotion engine in real time and decides to change the projected image. For example, if the user is feeling stressed, it will generate a new image generation prompt to change it to a "calm lake view." Input: Analyzed emotional information. Output: New image data.

[1165] Step 10: Real-time image projection

[1166] The terminal receives new image data from the server and projects the images onto the walls inside and outside the conference room in real time. The image is updated the moment the user reacts, providing an optimal environment according to the progress of the meeting. Input: New image data. Output: Updated projected image.

[1167] (Application Example 2)

[1168] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1169] Conventional manufacturing lines lacked environmental adjustments tailored to workers' stress levels and concentration levels, leading to problems such as decreased work efficiency and worker satisfaction. Furthermore, the absence of dynamic environmental optimization methods utilizing emotion recognition prevented real-time countermeasures.

[1170] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes data input means, keyword generation means, image generation means, emotion recognition means, environment adjustment means, and projection means. This makes it possible to analyze the facial expressions and tone of voice of workers in real time and provide an optimal work environment that corresponds to their emotions.

[1171] "Data input means" refers to a device or method for receiving data such as date and time, theme, and participant information.

[1172] "Keyword generation means" refers to a device or method that generates relevant keywords based on theme information received from a data input means.

[1173] "Image generation means" refers to a device or method that generates image data based on the generated keywords.

[1174] "Projection means" refers to a device or method for displaying generated image data using a projector, display, or the like.

[1175] "Emotion recognition means" refers to a device or method that analyzes a user's facial expressions and voice data to recognize their emotions in real time.

[1176] "Environmental adjustment means" refers to a device or method that dynamically optimizes the environment, such as music, lighting, and display content, based on emotions recognized by emotion recognition means.

[1177] This invention provides a robotic system that dynamically optimizes the work environment based on the stress levels and concentration levels of workers on a manufacturing line. A specific example of the system is described below.

[1178] System program

[1179] The system consists of data input means, keyword generation means, image generation means, projection means, emotion recognition means, and environment adjustment means. The emotion recognition means has the function of analyzing the facial expressions and voice data of workers on the manufacturing line to recognize stress levels and concentration levels in real time. Based on this, the environment adjustment means dynamically provides the optimal working environment for the workers.

[1180] Hardware and software

[1181] Hardware:

[1182] Camera (e.g., Logitech C920): Acquires facial expression data of workers.

[1183] Microphone (e.g., Blue Yeti): Captures the worker's voice data.

[1184] Projector or display: Displays the generated image data.

[1185] software:

[1186] Emotion Engine (e.g., EmotionEngine): Analyzes workers' facial expressions and voice data to recognize emotions.

[1187] Environmental control systems (e.g., EnvironmentControl): Adjust the environment based on recognized emotions.

[1188] Image generation model (e.g., Stable Diffusion): Generates images based on keywords.

[1189] Data processing and data calculation

[1190] Data acquisition from camera and microphone:

[1191] The device acquires facial expression data from the camera and audio data from the microphone. This data is analyzed by emotion recognition technology, and stress levels and concentration levels are determined in real time.

[1192] Emotion recognition and environmental adjustment:

[1193] Based on the worker's emotions as determined by the emotion recognition system, the environmental adjustment system optimizes the work environment. For example, if the system determines that the worker is tired, it plays relaxing background music and softens the lighting. Conversely, if the system determines that the worker is focused, it plays background music that helps maintain focus and brightens the lighting.

[1194] Specific example

[1195] Example 1:

[1196] If a worker is deemed to be experiencing stress during work, images of "natural scenery" are projected onto the work area via a projector, providing a relaxing environment.

[1197] Example 2:

[1198] To improve work efficiency, when concentration is needed, the environmental control system plays background music designed for focus, accompanied by an image of a "calm lake landscape."

[1199] Example of a prompt

[1200] Design a system that analyzes the facial expressions and tone of voice of workers on a manufacturing line and adjusts the work environment based on their stress levels and concentration levels. For example, if a worker is determined to be tired, the system should change the background music or lighting to provide a more relaxing environment.

[1201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1202] Step 1:

[1203] The device uses a camera and microphone to acquire facial and voice data from workers. This input data enables subsequent emotion recognition.

[1204] Step 2:

[1205] The terminal inputs the acquired facial expression data and voice data into the emotion recognition device. The emotion recognition device analyzes this data and determines the worker's emotions (stress level and concentration level). The emotion recognition result is then generated.

[1206] Step 3:

[1207] The server receives emotion data transmitted from the emotion recognition device and triggers the environment adjustment device based on the results. This emotion data determines what kind of environment adjustment is needed.

[1208] Step 4:

[1209] The server inputs shift information and theme information received from the data input means into the keyword generation means. The keyword generation means generates keywords related to the theme.

[1210] Step 5:

[1211] The server inputs the generated keywords into an image generation model. This model generates images based on the keywords. For example, it might generate images corresponding to "relax" or "concentrate."

[1212] Step 6:

[1213] The server sends the generated image to the terminal. The terminal receives this image data and sends it to the projection means. The projection means displays the image using a projector or display.

[1214] Step 7:

[1215] The terminal triggers environmental adjustments based on a schedule. For example, it provides relaxing background music and lighting when a worker is tired, and a focused environment when concentration is needed.

[1216] Step 8:

[1217] Users can experience the effects of environmental adjustments in real time while continuing their work. This provides an environment that improves work efficiency and reduces stress.

[1218] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1219] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1220] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1221] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1222] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1223] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1224] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1225] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1226] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1227] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1228] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1229] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1230] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1231] 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.

[1232] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1233] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1234] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1235] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1236] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1237] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1238] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1239] The following is further disclosed regarding the embodiments described above.

[1240] (Claim 1)

[1241] Data input means,

[1242] Keyword generation method,

[1243] Image generation means,

[1244] A system including projection means.

[1245] (Claim 2)

[1246] The system according to claim 1, wherein the data input means is a means for receiving date and time, theme and participant information.

[1247] (Claim 3)

[1248] The system according to claim 1, wherein the keyword generation means is a means for generating related keywords based on theme information received from the data input means.

[1249] (Claim 4)

[1250] The system according to claim 1, wherein the image generation means is a means for generating related images using related keywords generated by the keyword generation means.

[1251] (Claim 5)

[1252] The system according to claim 1, wherein the projection means is a means for projecting an image generated by the image generation means onto the walls inside or outside the conference room.

[1253] (Claim 6)

[1254] The system according to claim 5, wherein the projection means includes a scheduling means for projecting images according to the start time of a meeting.

[1255] (Claim 7)

[1256] The system according to claim 5, wherein the projection means includes means for displaying a plurality of images in a slideshow format at regular time intervals.

[1257] "Example 1"

[1258] (Claim 1)

[1259] Data input means,

[1260] Keyword generation method,

[1261] Image generation means,

[1262] Image receiving and format conversion means,

[1263] A system including projection means.

[1264] (Claim 2)

[1265] The system according to claim 1, wherein the data input means is a means for receiving date and time, theme and participant information.

[1266] (Claim 3)

[1267] The system according to claim 1, wherein the keyword generation means is a means for generating related keywords based on theme information received from the data input means.

[1268] "Application Example 1"

[1269] (Claim 1)

[1270] Data input means,

[1271] Keyword generation method,

[1272] Image generation means,

[1273] Projection means and

[1274] A system including means for changing the display.

[1275] (Claim 2)

[1276] The system according to claim 1, wherein the data input means is a means for receiving date and time, theme, and user information.

[1277] (Claim 3)

[1278] The system according to claim 1, wherein the keyword generation means is a means for generating related keywords based on theme information received from the data input means.

[1279] (Claim 4)

[1280] The system according to claim 1, wherein the display changing means is a means for changing the design or atmosphere inside the store in real time.

[1281] "Example 2 of combining an emotion engine"

[1282] (Claim 1)

[1283] Data input means,

[1284] Keyword generation method,

[1285] Image generation means,

[1286] A format conversion means,

[1287] Schedule management methods,

[1288] Means of recognizing emotions,

[1289] Real-time update method,

[1290] A system including projection means.

[1291] (Claim 2)

[1292] The system according to claim 1, wherein the data input means is a means for receiving date and time, theme and participant information.

[1293] (Claim 3)

[1294] The system according to claim 1, wherein the keyword generation means is a means for generating related keywords based on theme information received from the data input means.

[1295] "Application example 2 when combining with an emotional engine"

[1296] (Claim 1)

[1297] Data input means,

[1298] Keyword generation method,

[1299] Image generation means,

[1300] Projection means and

[1301] Means of recognizing emotions,

[1302] A system including means for adjusting the environment.

[1303] (Claim 2)

[1304] The data entry method is a means of receiving date, time, theme, and participant information.

[1305] The system according to claim 1, wherein the emotion recognition means is a means for recognizing an emotion by analyzing the user's facial expressions and voice data.

[1306] (Claim 3)

[1307] The keyword generation means generates relevant keywords based on theme information received from the data input means.

[1308] The system according to claim 1, wherein the environmental adjustment means is a means for dynamically optimizing the environment, such as music, lighting, and display content, based on emotions recognized by the emotion recognition means. [Explanation of Symbols]

[1309] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data entry method for receiving date, time, theme, and participant information, A keyword generation means that generates related keywords based on theme information received from a data input means, An image generation means that generates related images using related keywords generated by a keyword generation means, A system including projection means for projecting images generated by image generation means onto walls inside and outside a conference room.

2. The system according to claim 1, wherein the projection means includes a scheduling means for projecting images according to the start time of a meeting.

3. The system according to claim 1, wherein the projection means includes means for displaying a plurality of images in a slideshow format at regular time intervals.

Images