system

Abstract

Provide a system. [Solution] a means for inputting stereometric data of the human body; A means for inputting floor plans, furniture layout information, light source positions, and hobby information; A means for calculating the optimal ergonomic furniture list and its layout based on the input data; means for presenting the calculation results to a user and providing an interface that allows the user to visually confirm the results; The system includes a means for receiving feedback from the user and recalculating the furniture list and placement.

Description

[Technical Field]

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

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

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

[0004] In modern society, many people sit for long periods of time while working, increasing the risk of health problems due to poor posture and inappropriate furniture arrangement. In particular, in occupations where desk work is the norm, prolonged sitting posture can easily lead to back pain, stiff shoulders, and eye strain. Furthermore, if the furniture and layout do not suit the user's body shape or preferences, it can be difficult to create a comfortable work environment. There is a need for a system that can solve these problems and provide the optimal work environment for each individual user. [Means for solving the problem]

[0005] To address these challenges, the present invention provides a system that includes a means for inputting three-dimensional human body measurement data and a means for inputting floor plans, furniture layout information, light source positions, and hobby information. It also includes a means for calculating an optimal furniture list and its layout based on ergonomics based on the input data, and a means for presenting the calculation results to the user and providing an interface that allows the user to visually confirm them. It also includes a means for receiving feedback from the user and recalculating the furniture list and layout. The system also includes a means for determining the optimal chair height and angle based on the three-dimensional human body measurement data, and a means for simulating the brightness in the room based on the light source position and determining the optimal furniture layout. This makes it possible to provide an optimal work environment that takes user health into consideration.

[0006] "Three-dimensional measurement data of the human body" refers to data obtained by measuring the dimensions and shape of various parts of the human body, such as height, weight, shoulder width, and waist width, in three dimensions.

[0007] A "floor plan" is a drawing showing the relative positions, dimensions, shapes, and related elements of each room or space within a building.

[0008] "Furniture arrangement information" is information that indicates details such as the type, position, and orientation of furniture arranged in a room.

[0009] "Light source position" is information indicating the location of the source of natural light or artificial light in a room.

[0010] "Hobby information" is information about a user's personal preferences or special requests (for example, preferred furniture style or color coordination).

[0011] Ergonomics is an academic field that designs comfortable and efficient work environments and products based on human characteristics and behavior.

[0012] The "furniture list" is a list of the most suitable furniture items suggested to the user.

[0013] "Interface" refers to the means by which a user interacts with a system, particularly a screen display that can be visually confirmed and operated.

[0014] "Feedback" refers to opinions and improvements that users provide to the proposed furniture arrangement.

[0015] "Recalculation" refers to the process of recalculating and revising the optimal furniture list and layout based on user feedback.

[0016] "Chair height and angle" refers to the seat height and back angle of a chair that are most suitable for the user's body.

[0017] "Simulation" is a method of modeling and reproducing real-world situations and environments, and in this case refers to virtually reproducing and analyzing the effects of light sources and furniture placement.

[0018] The "work environment" includes the location where the user works and the surrounding environmental conditions, particularly the furniture arrangement and lighting settings. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The system of the present invention proposes optimal furniture and its layout taking into consideration the user's health. Below, the program processing of this system will be explained in natural language and in detail with concrete examples.

[0041] Program Overview

[0042] 1. Data collection steps

[0043] First, the user inputs the three-dimensional measurement data of his or her own body, specifically, detailed dimensional data such as height, weight, shoulder width, and waist width.

[0044] The user then uploads the floor plan to the application and enters details such as the room shape, dimensions, window locations, light source locations, and door locations.

[0045] The user also inputs their tastes and preferences (eg, particular furniture styles, color preferences, special feature requests, etc.).

[0046] The terminal validates all entered data in real time, prompts the user for any missing information, and once all data is collected, sends it to the server.

[0047] 2. Data analysis steps

[0048] The server then uses the received data to generate a 3D model of the human body, which is constructed based on the user's posture and body shape.

[0049] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow.

[0050] The server simulates the effects of natural and artificial light in the room based on the light source position, and then considers the placement of furniture to achieve the appropriate brightness balance.

[0051] The server considers the user's tastes and preferences, lists suitable furniture candidates, and calculates the optimal dimensions, shape, and placement of the furniture based on the stereoscopic measurement data and ergonomics of the human body.

[0052] 3. Furniture and layout proposal steps

[0053] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal.

[0054] The terminal provides users with an interface that allows them to visually check furniture and layout plans, and through 3D views and simulation screens, users can intuitively understand the proposals.

[0055] The user uses the provided visual interface to review the proposed furniture and layout and, if desired, provide feedback on the proposal.

[0056] 4. User Feedback Step

[0057] The user provides feedback and suggestions for improvements to the proposed furniture arrangement (for example, moving the chair a little further to the left).

[0058] The terminal records the feedback from the user and sends it to the server.

[0059] The server analyzes the user feedback and re-runs the algorithms to modify the furniture list and layout plan as needed.

[0060] The server regenerates the revised plan and sends it to the terminal.

[0061] The terminal presents the newly revised plan to the user and again accepts feedback.

[0062] Specific examples

[0063] Case study: System usage example of a freelancer who works long hours at a desk at home

[0064] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0065] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0066] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0067] 4. The terminal sends all the information entered to the server.

[0068] 5. The server generates a 3D model of the human body based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0069] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0070] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0071] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0072] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0073] By repeating this process, users can create the optimal working environment for themselves. This system is characterized by its maximum consideration of health and provides an environment that allows users to work comfortably even during long hours of desk work.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user after having previously acquired it using a measuring device, or it can be automatically acquired using a dedicated 3D scanning device. After completing the input, the data is sent to the server.

[0077] Step 2:

[0078] The user uploads a floor plan to the application, which includes detailed information such as room dimensions, shape, window and light source positions, and door positions. After uploading, the user can review this information using the application interface and make any necessary corrections. Once the corrections are complete, the data is sent to the server.

[0079] Step 3:

[0080] Users input their preferences and special requests, such as a particular furniture style (e.g., modern or minimalist), preferred color coordination, and special feature requirements (e.g., a desk with standing capabilities or an ergonomic chair). Once completed, all data is sent to the server.

[0081] Step 4:

[0082] The device verifies all data entered by the user in real time, checking that all required fields have been entered, and notifying the user if any information is missing, prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[0083] Step 5:

[0084] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[0085] Step 6:

[0086] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0087] Step 7:

[0088] The server analyzes the user's input preferences and special requests and generates a list of suitable furniture options, generated using ergonomic algorithms that take into account the dimensions, shape, and placement of the furniture that best suits the user.

[0089] Step 8:

[0090] The server generates an optimal furniture list and layout plan based on the analysis results, and the generated list and plan are sent to the terminal in data format.

[0091] Step 9:

[0092] The terminal provides an interface that allows users to visually check the proposed contents. Users can intuitively understand and check the proposed furniture arrangement using 3D views and simulation screens.

[0093] Step 10:

[0094] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0095] Step 11:

[0096] The terminal records the feedback from the user and sends it to the server.

[0097] Step 12:

[0098] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[0099] Step 13:

[0100] The server regenerates a revised plan and sends it to the terminal, which then presents the revised plan to the user, who then confirms it again. If further feedback is required, the cycle repeats.

[0101] Example 1

[0102] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0103] In recent years, with the increase in telecommuting and remote work, the importance of a comfortable working environment at home has increased. However, when it comes to furniture placement and selection, it is difficult to receive suggestions that are optimized for each individual's body shape and preferences. Inappropriate furniture placement and selection can be harmful to health, so a system to solve this problem is needed.

[0104] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0105] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for generating a three-dimensional model of the human body based on the input data, means for analyzing the floor plan data to determine areas where furniture can be placed and efficient traffic lines, means for simulating the effects of natural light and artificial light in the room based on the light source positions, means for calculating an optimal furniture list and layout based on the three-dimensional measurement data of the human body and ergonomics, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and means for receiving feedback from the user and recalculating the furniture list and layout. This makes it possible to suggest optimal furniture selection and layout that takes the user's health into consideration in real time, thereby realizing a comfortable working environment.

[0106] "Human body three-dimensional measurement data" refers to individual dimensional data such as height, weight, shoulder width, and waist width, and is basic information for generating a three-dimensional model.

[0107] A "floor plan" is a layout diagram of an entire room that includes information such as the shape, dimensions, window, light source position, and door position of the room.

[0108] "Light source position" is position information that indicates where natural light or artificial light in a room is emitted from.

[0109] "Hobby information" is information that indicates a user's personal preferences, such as a particular furniture style, color preferences, or special function requirements.

[0110] A "three-dimensional model" is a three-dimensional model generated by computer software based on inputted dimensional data of the human body.

[0111] "Traffic lines" refer to the routes people take within a room, and are information used in layout planning to enable efficient movement.

[0112] "Simulation" refers to reproducing the situation and effects on a computer based on real-world conditions such as the position of a light source.

[0113] The "optimal furniture list" is a list of furniture selected based on the user's dimensional data, floor plan, hobby information, and ergonomics.

[0114] An "interface" refers to the screens and operating methods that allow a user to interact with a system, providing information in a visually identifiable format.

[0115] "Feedback" refers to input information such as opinions and improvements provided by the user regarding the proposed furniture arrangement plan.

[0116] The system of the present invention is a system that proposes optimal furniture and its layout taking into consideration the health of the user. An embodiment of this system will be specifically described below.

[0117] Program Overview

[0118] Data Collection Steps

[0119] First, a user launches the application and inputs their own anthropometric data, including detailed measurements such as height, weight, shoulder width, and hip width. Next, the user uploads a floor plan to the application and inputs detailed information such as the room's shape, dimensions, window position, light source position, and door position. Additionally, the user inputs their personal tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.).

[0120] The terminal validates all of this input data in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server. Specifically, the data is sent using an HTTP POST request.

[0121] Data analysis steps

[0122] The server generates a 3D model of the human body based on the received data. This model is constructed based on the user's posture and body shape. Specifically, it uses 3D modeling software (e.g., Blender or Maya).

[0123] The server then analyzes the floor plan data to determine areas where furniture can be placed and efficient traffic flow. Image analysis software is used to analyze the floor plan images.

[0124] The server also simulates the effects of natural and artificial light in the room based on the light source position. It uses a light and shadow calculation algorithm to simulate the brightness of each area of ​​the room. Based on this information, the server takes into account the user's tastes and preferences and lists suitable furniture candidates. Furthermore, it calculates the optimal furniture dimensions, shape, and placement based on the stereoscopic measurement data of the human body and ergonomics.

[0125] Furniture and layout proposal steps

[0126] The server generates an optimal furniture list and layout plan based on the analysis results and sends this to the device in a data format, typically JSON.

[0127] The terminal provides users with an interface that allows them to visually check the furniture and layout plans. Specifically, it displays a 3D viewer and a simulation screen, allowing users to intuitively check the proposals.

[0128] Users can use it to review the proposed furniture and layout and provide feedback if needed, such as entering specific requests like "I'd like the chair to be moved a little further to the left."

[0129] User Feedback Steps

[0130] The device records the feedback from the user and sends it to the server, again using an HTTP POST request to send the feedback data.

[0131] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. Once the recalculation is complete, a new layout plan is regenerated and sent to the device.

[0132] The device presents the newly revised plan to the user and again accepts feedback. By repeating this process, it is possible to provide the user with an optimal working environment.

[0133] Specific examples

[0134] Case study: System usage example of a freelancer who works long hours at a desk at home

[0135] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0136] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0137] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0138] 4. The terminal sends all the information entered to the server.

[0139] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0140] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0141] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0142] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0143] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0144] By repeating this process, the user can create the optimal working environment for themselves.

[0145] Example prompt statement

[0146] "I work at a desk for long periods of time at home, so I'd like a system that suggests optimal furniture layouts that take my health into consideration. I'm 170cm tall, weigh 65kg, and prefer modern-style furniture. I've entered my floor plan and detailed information, so please provide me with the optimal furniture list and layout plan."

[0147] This system is characterized by its maximum consideration of health and provides a comfortable environment even during long hours of desk work.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] The user starts the application and inputs their own 3D body measurement data. The input includes detailed dimensional data such as height, weight, shoulder width, and hip width. Specifically, the user enters this information into the application's data input form, and the data is acquired as 3D body measurement data.

[0151] Step 2:

[0152] Users upload floor plans to the application and enter details such as room shape, dimensions, window locations, light source locations, and door locations. The input includes floor plan files in JPEG and PDF formats, which then imports the floor plan data into the system.

[0153] Step 3:

[0154] Users input their tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.). The input includes preference information such as "modern style" and "blue and white color scheme." This taste information is then incorporated into the system.

[0155] Step 4:

[0156] The device validates all entered data in real time and prompts the user to enter any missing information. Specifically, the device checks each field on the input form and displays a pop-up message to the user, such as "Weight is missing." Once all the data is collected, the device sends it to the server. An HTTP POST request is used for transmission.

[0157] Step 5:

[0158] The server generates a 3D model of the human body based on the received data. The input data is the stereoscopic measurement data of the human body, and the output is a 3D model. Specifically, a human body model is generated based on the input dimensional data using 3D modeling software (e.g., Blender or Maya).

[0159] Step 6:

[0160] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. The input data is floor plan data, and the output is information on the areas where furniture can be placed and traffic flow. Specifically, the floor plan is analyzed using image analysis software, and furniture placement space and aisle width are calculated.

[0161] Step 7:

[0162] The server simulates the effects of natural and artificial light in a room based on the light source position. The input data is light source position information, and the output is brightness information for each area. Specifically, it uses a light and shadow calculation algorithm to calculate the brightness of the room based on the window and lighting positions.

[0163] Step 8:

[0164] The server considers the user's tastes and preferences and lists suitable furniture candidates. The input data is hobby information and ergonomic data, and the output is a list of optimal furniture. Specifically, it searches the database for modern-style furniture and generates a list of furniture that matches the user's tastes and room dimensions.

[0165] Step 9:

[0166] The server calculates the optimal furniture dimensions, shape, and layout based on the stereoscopic measurement data of the human body and ergonomics. The input data is a human body model and an ergonomics algorithm, and the output is an optimal furniture layout plan. Specifically, it calculates, for example, chair heights and desk positions and creates a layout plan.

[0167] Step 10:

[0168] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal. The input data is the optimal furniture placement plan, and the output is a furniture list and layout plan in data format. JSON format is generally used.

[0169] Step 11:

[0170] The terminal provides the user with an interface that allows them to visually check the furniture and layout plan. The input data is the furniture list and layout plan sent from the server, and the output is a 3D viewer or simulation screen. This allows the user to intuitively check the proposal.

[0171] Step 12:

[0172] The user uses the provided visual interface to review the proposed furniture and layout and provide feedback as needed. The input data are the user's opinions and suggestions for improvement, and the output is feedback information. For example, the user can input a specific request such as "I'd like to move the chair a little further to the left."

[0173] Step 13:

[0174] The terminal records the feedback from the user and sends it to the server. The input data is the feedback information, and the output is an HTTP POST request to the server.

[0175] Step 14:

[0176] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. The input data is the feedback information, and the output is the modified furniture placement plan.

[0177] Step 15:

[0178] The server regenerates the modified plan and sends it to the terminal. The input data is the modified furniture layout plan, and the output is the data format sent to the terminal.

[0179] Step 16:

[0180] The device then presents the newly revised plan to the user and again accepts feedback. The input data is the revised furniture layout plan, and the output is an updated 3D view or simulation screen. By repeating this process, the user is provided with an optimal working environment.

[0181] (Application example 1)

[0182] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0183] Currently, food delivery stores lack concrete measures to create an efficient working environment, and furniture layout and traffic flow are not optimized with consideration for staff health. This can result in a decline in work efficiency and an increased risk to staff health. Furthermore, there is no system in place to incorporate feedback and make continuous improvements, making it difficult to optimize the working environment.

[0184] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0185] In this invention, the server includes a means for inputting three-dimensional measurement data of the human body, a means for inputting floor plans, work environment information, light source positions, and work flow information, a means for calculating an optimal work environment list and its layout based on ergonomics based on the input data, a means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and a means for receiving feedback from the user and recalculating the work environment list and layout. This makes it possible to provide an efficient and healthy work environment in food delivery stores. Furthermore, by continuously reflecting feedback, the work environment can be continuously optimized.

[0186] "Human body three-dimensional measurement data" refers to detailed dimensional data such as the user's height, shoulder width, and weight, and refers to three-dimensional information about the user's body shape and posture.

[0187] A floor plan is a drawing that shows the shape, dimensions, window and door locations of a room or store.

[0188] "Work environment information" refers to detailed data regarding the layout of equipment within the work area, the location of the warehouse, and the work content.

[0189] "Light source position" refers to information about the location of a light source, such as natural light or artificial light.

[0190] "Work flow information" refers to information regarding efficient routes for people and things to move within a work area.

[0191] "Ergonomics" refers to the scientific knowledge and methods for designing work environments and products that take into account the physical and psychological characteristics of people.

[0192] The "work environment list" refers to a list of optimal furniture and equipment that takes into consideration work efficiency and health.

[0193] A "visually verifiable interface" refers to a user interface that provides a 3D view or simulation screen so that users can intuitively understand the calculation results.

[0194] "User feedback" refers to information that users input regarding their opinions and suggestions for improvement regarding the layout plan and furniture list provided.

[0195] "Recalculation" refers to recalculating the optimal work environment list and its layout based on feedback from the user.

[0196] To put this invention into practice, it is first necessary to build a system for inputting three-dimensional measurement data of the human body, work environment information, light source position, and work flow information. Below, we will explain the program processing of this system and provide a detailed explanation of the hardware and software used.

[0197] Users use their smartphones or PCs to input their three-dimensional body measurement data. This data includes detailed measurements such as height, shoulder width, and weight. They also upload floor plans to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter details about work flow and the work environment. Once this data is entered, the device verifies it in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server.

[0198] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information. This is done using programming languages ​​such as Python and APIs such as Flask.

[0199] The server sends the calculated results to the device, which then provides a visual interface for the user. The user can intuitively understand the proposed furniture and layout using a 3D view or simulation screen. This interface also makes it easier for the user to provide feedback on the proposed content.

[0200] Feedback from the user is recorded by the device and sent back to the server. The server analyzes the user's feedback and recalculates the work environment list and layout plan as necessary. The server then sends the revised plan back to the device, where the user can review the newly revised plan. By repeating this process, the optimal work environment can be provided to the user.

[0201] Specific examples

[0202] For example, when a food delivery store manager uses this system, they first input three-dimensional measurement data such as the height and shoulder width of their cooking and delivery staff. Next, they upload a floor plan of the store and input the layout of the kitchen and warehouse, as well as the position of the light source. They then provide information on work flow and details of the required work environment.

[0203] The server calculates a healthy and efficient work environment based on each staff member's body data and store layout information. For example, it optimizes counter height, shelf placement, and traffic flow, and makes suggestions on a visual interface. Managers can provide feedback on these suggestions and request recalculations to create the ideal work environment.

[0204] Example prompt sentence:

[0205] "This system proposes optimal furniture layouts that take user health into consideration. The system proposes optimal work environments based on the user's 3D body measurement data, store floor plans, and equipment layout. For example, the system considers an arrangement that would be comfortable for a staff member with a height of 170 cm and shoulder width of 45 cm, and includes the shape of the room, the position of the light source, and the location of the warehouse as input data."

[0206] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0207] Step 1:

[0208] Users use their smartphones or PCs to input their own three-dimensional body measurement data. Specifically, detailed dimensional data such as height, shoulder width, and weight are entered. They also upload a floor plan to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter information about work flow and the work environment. Once all the information has been entered, it is sent to the server.

[0209] Input: 3D body measurement data, floor plan, detailed information (windows, doors, light source positions, etc.), work flow information, work environment information

[0210] Output: All input data sent to the server

[0211] Step 2:

[0212] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information.

[0213] Input: All input data sent to the server

[0214] Output: 3D model of the human body, analysis results (area where furniture can be placed, traffic flow, lighting simulation)

[0215] Step 3:

[0216] The server sends the calculated results to the terminal, which then provides a visual interface for the user, allowing them to intuitively understand and check the proposed furniture and layout using a 3D view or simulation screen.

[0217] Input: Analysis results (3D model of the human body, area where furniture can be placed, traffic flow, lighting simulation)

[0218] Output: Visual interface presented to the user (3D view, simulation screen)

[0219] Step 4:

[0220] The user can check the proposed content through a visual interface and provide necessary feedback, such as requests for changes to furniture positions or work flow. This feedback is sent to the server via the terminal.

[0221] Input: User feedback (changing furniture position, correcting traffic flow, etc.)

[0222] Output: Feedback sent to the server

[0223] Step 5:

[0224] The server analyzes the user's feedback, recalculates the work environment list and layout plan as necessary, and then sends the revised plan back to the terminal, where the user can view the newly revised plan.

[0225] Input: Feedback sent to the server

[0226] Output: Recalculated workspace list and layout plan

[0227] Step 6:

[0228] The device presents the recalculated plan to the user and prompts them to confirm the newly revised plan. This process is repeated until the user is satisfied, providing an optimal working environment.

[0229] Input: Recalculated workspace list and layout plan

[0230] Output: Optimal work environment plan presented to the user (for final confirmation)

[0231] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0232] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics based on 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. This system also recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. Below, the program processing of this system is explained in natural language and in detail with concrete examples.

[0233] Program Overview

[0234] 1. Data collection steps

[0235] First, the user inputs their own 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user using a measuring device in advance, or automatically acquired using a dedicated 3D scanning device.

[0236] The user then uploads a floor plan to the application, which includes details such as room shape, dimensions, window and light source locations, and door locations. After uploading, the user can review this information using the application's interface and make any necessary corrections.

[0237] The user also inputs their preferences and special requests (e.g., specific furniture styles, color coordination, special function requests), and once input is complete, this data is sent to the server.

[0238] 2. Data analysis steps

[0239] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[0240] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0241] The server then generates an optimal furniture list and layout plan based on the analysis results, using ergonomic algorithms to consider the dimensions, shapes, and placement of furniture that best suit the user.

[0242] 3. Emotion Engine Steps

[0243] The server recognizes the user's emotional state using an emotion engine. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer emotions in real time. This emotion data is reflected in the analysis results, and a furniture list and arrangement optimal for the user's current emotional state are created.

[0244] The server learns the user's past emotional data and makes furniture suggestions taking into account their long-term emotional trends, thereby providing a comfortable environment for the user to live in for a long time.

[0245] 4. Furniture and layout proposal steps

[0246] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends this in data format to the terminal.

[0247] The terminal provides users with an interface that allows them to visually check the furniture and layout plan. Users can intuitively understand and check the proposal using 3D views, simulation screens, etc.

[0248] 5. User Feedback Steps

[0249] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0250] The terminal records the feedback from the user and sends it to the server.

[0251] The server analyzes the user's feedback and performs recalculations to modify the furniture list and layout plan as needed.

[0252] Specific examples

[0253] Case study: System usage example of a freelancer who works long hours at a desk at home

[0254] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0255] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0256] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0257] 4. The terminal sends all the information entered to the server.

[0258] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0259] 6. The server uses an emotion engine to recognize the user's emotional state and makes suggestions that best fit the current emotional state.

[0260] 7. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0261] 8. The user reviews the proposed furniture and layout and provides feedback, for example, suggesting that the chair be moved slightly to the left.

[0262] 9. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0263] 10. The server sends the revised plan to the device, which presents it to the user again. The cycle repeats if the user checks again and provides feedback.

[0264] This system takes maximum consideration of the user's health and, by combining it with an emotion engine, can provide an optimal working environment that also takes into account the user's emotional state, thus creating an environment where users can work comfortably even during long hours of desk work.

[0265] The processing flow will be explained below.

[0266] Step 1:

[0267] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, hip width, etc.). This data can be manually input by the user using a measuring device or automatically acquired using a dedicated 3D scanning device.

[0268] Step 2:

[0269] Users upload floor plans to the application, which include details such as room dimensions, shape, window and light source locations, and door locations. After uploading, users can review this information and make any necessary corrections using the application's interface.

[0270] Step 3:

[0271] Users input their preferences and special requests (e.g., specific furniture styles and colors, special feature requests, etc.) Once input is complete, all data is sent to the server.

[0272] Step 4:

[0273] The terminal validates all data entered by the user in real time, checking that all required fields have been entered, notifying the user if any information is missing and prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[0274] Step 5:

[0275] The server then generates a 3D model of the user's body based on the received data, using an algorithm that analyzes the dimensions of each part of the body in three dimensions and creates an accurate model based on the user's posture and body shape.

[0276] Step 6:

[0277] The server analyzes furniture placement areas and user movement lines based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user movement lines. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0278] Step 7:

[0279] The server takes into account the user's tastes and special requests and generates a list of suitable furniture options, taking into account the ergonomic dimensions, shapes, and placement of the furniture.

[0280] Step 8:

[0281] The server uses an emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer their current emotional state. This information is reflected in furniture and layout suggestions.

[0282] Step 9:

[0283] The server learns past emotional data and makes furniture suggestions taking into account the user's long-term emotional trends, thereby providing a comfortable environment for the user over the long term.

[0284] Step 10:

[0285] The server generates an optimal furniture list and layout plan based on the analysis results and the emotion engine results, and the generated list and plan are sent to the terminal in data format.

[0286] Step 11:

[0287] The terminal provides an interface that allows users to visually check the furniture and layout plan, and users can intuitively understand and check the proposal using 3D views and simulation screens.

[0288] Step 12:

[0289] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0290] Step 13:

[0291] The terminal records the feedback from the user and sends it to the server.

[0292] Step 14:

[0293] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[0294] Step 15:

[0295] The server regenerates the revised plan and sends it to the device, which presents the new revised plan to the user for confirmation again. If further feedback is required, the cycle repeats.

[0296] This system provides an optimal working environment that takes into account the user's health and emotional state, making it possible to work comfortably even during long hours of desk work.

[0297] Example 2

[0298] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0299] Conventional furniture layout systems could provide optimal furniture layouts based on the user's body data and room layout information, but because they did not take the user's emotional state into account, it was difficult to fully guarantee long-term comfort and user satisfaction. Furthermore, when recalculating based on feedback, optimization was not possible in combination with past emotional data, making it difficult to provide the optimal environment the user desired.

[0300] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for recognizing the user's emotional state and analyzing the emotional data, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data and emotional data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, and means for learning from the feedback and past emotional data and improving the proposal. This makes it possible to provide an optimal furniture layout and its proposal taking into account the user's emotional state.

[0301] "Human body 3D measurement data" refers to data indicating the user's physical dimensions such as height, weight, shoulder width, and waist width, and is data obtained using a dedicated 3D scanning device or manual input.

[0302] A "floor plan" is a drawing that shows the shape, dimensions, window positions, light source positions, door positions, etc. of a room, and is data that a user uploads to the application.

[0303] "Furniture arrangement information" is data that indicates information such as the type, position, dimensions, and shape of furniture arranged in a room.

[0304] "Light source position" is data that indicates the specific position of a light source (window, lighting fixture, etc.) in a room.

[0305] "Hobby information" is data that indicates the user's furniture preferences, style, color coordination, special requests, and the like.

[0306] "Emotional state" is data indicating the emotional state of the user that is estimated by analyzing the user's facial expression, tone of voice, body movements, and the like.

[0307] "Emotion data" is data that expresses emotional states using numerical values ​​and categories, and is data that is analyzed and collected by the emotion engine.

[0308] The "ergonomically optimal furniture list" is a list showing the type, dimensions, and shape of furniture that is considered optimal from an ergonomic perspective based on the user's body data, room floor plan, furniture placement information, light source position, and hobby information.

[0309] A "visual interface" refers to an interface that allows users to visually check the furniture layout plan through a 3D view or simulation screen.

[0310] "Feedback" refers to information that a user inputs into the application about their opinions and requests regarding the proposed furniture and layout, and sends it to the server.

[0311] The present invention is a system that calculates an optimal furniture list and its layout based on the user's ergonomics based on the user's 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. Furthermore, the system recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. The detailed implementation method of this system is described below.

[0312] Data collection

[0313] First, a user launches the application and inputs their anthropometric data (e.g., height 170 cm, weight 65 kg, shoulder width 45 cm). This data can be entered manually or automatically obtained using a dedicated 3D scanning device. Next, the user uploads a floor plan of the room to the application. The floor plan includes details such as the room's shape, dimensions, window locations, light source locations, and door locations. In addition, the user can input their preferences and special requests (e.g., specific furniture style and color coordination).

[0314] Data analysis

[0315] The server generates a three-dimensional model of the user's body based on the received stereoscopic body measurement data. This process uses 3D modeling software (e.g., Blender) to analyze the dimensions of each part of the body in three dimensions and create an accurate model. The server then analyzes the floor plan data to calculate furniture placement areas and traffic flow. It also simulates natural and artificial light based on the light source position. For example, it uses emotion analysis tools such as "Affectiva" and "Microsoft® Azure® Emotion API."

[0316] Emotion analysis

[0317] The server uses an emotion engine to recognize the user's emotional state. This allows it to analyze the user's facial expressions, tone of voice, and physical movements to infer emotions in real time. This emotional data is reflected in the analysis results, creating a furniture list and placement that is optimal for the user's current emotional state. The server also learns from past emotional data and makes furniture suggestions that take long-term emotional trends into account.

[0318] Furniture and layout suggestions

[0319] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends it to the device. The device then provides an interface that allows users to visually check the furniture and layout plan. For example, users can use game engines such as Unity or Unreal Engine to understand the proposals through 3D views and simulation screens.

[0320] User Feedback

[0321] Finally, the user reviews the proposed furniture and layout and provides feedback. For example, they might enter a specific suggestion such as, "I'd like to move the chair a little to the left." The device records the feedback and sends it to the server. The server analyzes the feedback, recalculates as necessary, and generates a new furniture list and layout plan. This cycle is repeated until the user is satisfied.

[0322] Specific examples

[0323] This shows how a freelancer working from home uses this system.

[0324] 1. The user starts the application and enters data such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0325] 2. The user uploads a floor plan and inputs the shape of the room, the position of the light source, the location of the door, etc.

[0326] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0327] 4. The server analyzes the data and generates a 3D human body model.

[0328] 5. The server uses an emotion engine to analyze the user's emotional state.

[0329] 6. The server generates an optimal furniture list and layout plan and sends it to the terminal.

[0330] 7. The device presents the furniture and layout plan to the user in a 3D view.

[0331] 8. The user reviews the proposal and provides feedback.

[0332] 9. The server recalculates based on the feedback and creates a new plan.

[0333] This system allows users to create a comfortable working environment.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1:

[0336] The user launches the application and inputs their body stereoscopic measurement data. For example, height 170 cm, weight 65 kg, shoulder width 45 cm, etc., can be entered manually or automatically using a stereoscopic scanning device. This operation inputs the user's physical dimensions into the application. The input includes the body stereoscopic measurement data. The output is the input data sent to the server.

[0337] Step 2:

[0338] The user uploads a floor plan to the application. The floor plan includes detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. After uploading, the user can review this information and modify it as necessary. For example, the user can fine-tune the room dimensions or light source positions using the application interface. The input includes the floor plan. The output is the modified floor plan data sent to the server.

[0339] Step 3:

[0340] Users input their preferences and special requests (e.g., preferences for a particular furniture style or color) into the application, which then collects the user's preference data. The input includes the preferences and special requests. The output is sent to the server.

[0341] Step 4:

[0342] The server generates a 3D human body model of the user based on the received 3D human body measurement data, floor plan data, and hobby information. In this process, 3D modeling software (e.g., Blender) is used to analyze the data in three dimensions and create a 3D human body model. The inputs include the 3D human body measurement data, floor plan data, and hobby information. The output is the generated 3D human body model and the analysis results.

[0343] Step 5:

[0344] The server analyzes floor plan data and calculates furniture placement areas and traffic flow. At this stage, it determines where furniture can be placed and what the optimal traffic flow is. It also simulates natural and artificial light based on the light source position, simulating the brightness of the entire room. The input includes floor plan data and light source position data. The output is the placement area analysis results and light simulation results.

[0345] Step 6:

[0346] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements in real time to generate emotional data. Here, emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API" are used. The input includes real-time user information (facial expressions, tone of voice, and body movements). The output is the analyzed emotional data.

[0347] Step 7:

[0348] The server generates an optimal ergonomic furniture list and layout plan based on the input data and emotion data. This process uses an algorithm to calculate the optimal furniture dimensions, shape, and layout. Inputs include a 3D human body model, floor plan analysis results, and emotion data. The output is an optimal furniture list and layout plan.

[0349] Step 8:

[0350] The server sends the generated furniture list and layout plan to the terminal. The terminal provides an interface that the user can visually check, and displays the proposed content in a 3D view or simulation screen. For example, a game engine (e.g., Unity or Unreal Engine) is used to display a simulation of the furniture layout in real time. The input includes the furniture list and layout plan sent from the server. The output is the interface that is visually presented to the user.

[0351] Step 9:

[0352] The user reviews the proposed furniture and layout and provides feedback. Specifically, the user inputs their feedback, such as rearranging the furniture or adjusting the layout, into the application. The input includes the user's feedback. The output is sent to the server.

[0353] Step 10:

[0354] The server analyzes the received feedback and recalculates the furniture list and layout plan as needed, taking into account past emotional data to update the proposals. The inputs include the user's feedback and past emotional data. The output is a revised furniture list and layout plan.

[0355] Step 11:

[0356] The server sends the revised plan to the terminal and presents it again to the user. The terminal updates the interface for further user review. The input includes the revised plan. The output is an updated visual interface.

[0357] By repeating the above processing steps, an optimal furniture arrangement that satisfies the user is provided.

[0358] (Application example 2)

[0359] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0360] Conventional furniture layout suggestion systems do not take into account the user's detailed 3D body measurement data or emotional state, making it difficult to select and arrange optimal furniture. Furthermore, they lacked an interface for visually confirming the proposed content, making it difficult for users to intuitively understand the content. Furthermore, there was no means in place to provide optimal furniture suggestions to users on the spot in physical stores or commercial facilities. There was a need to solve these issues and improve user comfort and ease of use.

[0361] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0362] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, means for recognizing the user's emotional state and using an emotion engine to make optimal furniture suggestions, means for visualizing the consideration results through a three-dimensional view or simulation screen, and means for making optimal furniture suggestions to the user in a store or commercial facility where there is a physical presence. This enables optimal furniture suggestions that reflect the user's detailed human body data and emotional state, and not only can suggestions be made through an intuitively easy-to-understand visual interface, but also enables instantly customized furniture suggestions in physical stores and commercial facilities.

[0363] "Three-dimensional measurement data of the human body" refers to data obtained in three dimensions that indicates specific human body dimensions such as the user's height, weight, shoulder width, and waist width.

[0364] A "floor plan" is a drawing that includes detailed information such as the shape and dimensions of a room, the location of windows, the location of light sources, and the location of doors.

[0365] "Furniture arrangement information" is data relating to where in a room each piece of furniture is arranged.

[0366] "Light source position" is information indicating the position of a source of natural light or artificial light in a room.

[0367] "Hobby information" is data about the user's preferences, such as preferred furniture styles, color coordination, and special functional requirements.

[0368] "Ergonomics" is the study of creating comfortable and efficient designs that take into account human physical characteristics and movements.

[0369] A "furniture list" is a list of the most suitable furniture suggested to the user.

[0370] The "emotion engine" is a system that analyzes and infers the user's emotional state from facial expressions, tone of voice, physical movements, etc.

[0371] "Interface" refers to the screen and input devices that users use to operate the system.

[0372] "Feedback" refers to the act of communicating to the system the user's opinions and requests for corrections regarding the proposed content.

[0373] A "3D view" is a display format that visualizes proposed furniture placement and room layout in three dimensions.

[0374] A "simulation screen" is a display means for virtually reproducing how a proposed furniture arrangement will function.

[0375] A "physical commercial facility" refers to a store or facility that actually exists as a building and that customers can visit.

[0376] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics and presents it to the user. This system operates based on three-dimensional human body measurement data, floor plans, furniture layout information, light source position, and hobby information. It also uses an emotion engine to recognize the user's emotional state and make suggestions based on that emotional state. This system provides furniture suggestions optimized for the user's characteristics and emotions in brick-and-mortar stores and commercial facilities.

[0377] The following hardware and software are used to process the data. First, a body scanning device (BodyScanner) is required to collect stereoscopic measurement data of the human body. Dedicated software (LayoutAnalyzer) is used to analyze floor plans and furniture layout information. An emotion recognition engine (EmotionRecognitionEngine) is used to recognize emotional states. A furniture recommendation engine (FurnitureRecommender) is required to recommend furniture, and this incorporates ergonomic algorithms. Finally, software (VisualizationInterface) is used to provide a 3D view display and simulation screen as an interface to visually display suggestions to the user.

[0378] The server operates by coordinating the various software modules described above. Specifically, the server collects and analyzes three-dimensional measurement data of the human body and calculates the optimal furniture list and its placement based on the floor plan and furniture layout information. It also uses an emotion engine to recognize the user's emotional state and suggests furniture that best suits that emotional state. The calculation results are then sent to the device, which then visually presents the suggestions to the user through a 3D view or simulation screen.

[0379] Consider the following scenario: In a physical store, a user uses a body scanning device to collect stereoscopic measurement data of their body. Then, they upload a floor plan and enter their hobbies and special requests. All of this data is sent to a server, which calculates the optimal furniture list and its placement. An emotion engine analyzes the user's emotional state and generates optimal furniture suggestions. The calculation results are sent to the device, which visually presents the suggestions to the user through a 3D view or simulation screen.

[0380] For example, you can make suggestions using prompts like the following:

[0381] "Please suggest a furniture list and layout to optimize the interior of a living room and bedroom. The user's anthropometric data are height 170cm, weight 65kg, and shoulder width 45cm. The floor plan is as follows:

[0382] Living room: Light source is located in the center of the ceiling, window is on the south side, door is on the north side

[0383] Bedroom: Light source is on the west side of the ceiling, window is on the east side, door is on the south side

[0384] The user's preferred furniture style is modern, their preferred color is blue and white, and their emotional state is relaxed.

[0385] Based on this information, please design an algorithm that will suggest the optimal furniture list and its placement."

[0386] In this way, the present invention can provide optimal furniture suggestions that take into account the user's physical characteristics and emotional state, improving the user experience in physical stores and commercial facilities.

[0387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0388] Step 1:

[0389] A user uses a body scanning device to collect stereoscopic data of their body. The device acquires dimensional data such as height, weight, shoulder width, and hip width, and sends it to a cloud server. The input is the user's body data, and the output is analyzable stereoscopic data.

[0390] Step 2:

[0391] Users upload floor plans to the application. They also input information about furniture layout, light source positions, and door and window locations. This data is sent to a cloud server via the device. The input is the floor plan and related information, and the output is spatial information data for analysis.

[0392] Step 3:

[0393] The server analyzes the transmitted stereoscopic body measurement data and floor plan data. It uses ergonomic algorithms to calculate the optimal furniture dimensions, shape, and placement. The input is the body and floor plan data, and the output is the optimal furniture list and placement plan.

[0394] Step 4:

[0395] The server uses an emotion recognition engine to analyze the user's emotional state. It uses a camera and microphone to detect facial expressions, tone of voice, and body movements to determine emotions. The input is real-time user facial and voice data, and the output is analyzed emotional state data.

[0396] Step 5:

[0397] Based on the results of the emotion engine, the server recalculates optimal furniture suggestions, adjusting the suggestions to suit the user's current emotional state. The input is emotional state data, and the output is an optimal furniture list and its placement that takes emotions into account.

[0398] Step 6:

[0399] The server sends the calculation results to the terminal, which visually displays the proposal to the user through a 3D view or simulation screen. The input is the calculated furniture list and placement data, and the output is the proposal displayed on the visual interface.

[0400] Step 7:

[0401] The user checks the visually displayed furniture arrangement proposal and inputs their feedback into the device, providing specific suggestions for revisions, such as the desired furniture position or height. The input is the user's feedback, and the output is the revision proposal data.

[0402] Step 8:

[0403] The device sends the user's feedback to the server, which then recalculates the optimal furniture list and layout based on the feedback and generates a revised plan. The input is the user's feedback, and the output is the revised layout plan.

[0404] Step 9:

[0405] The server sends the revised furniture list and layout plan to the terminal, which then displays it again to the user. This cycle is repeated until the user is satisfied. The input is the revised data, and the output is the final proposal to be confirmed.

[0406] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0407] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0408] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0409] [Second embodiment]

[0410] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0411] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0412] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0413] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0414] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0415] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0416] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0417] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0418] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0419] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0420] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0421] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0422] The system of the present invention proposes optimal furniture and its layout taking into consideration the user's health. Below, the program processing of this system will be explained in natural language and in detail with concrete examples.

[0423] Program Overview

[0424] 1. Data collection steps

[0425] First, the user inputs the three-dimensional measurement data of his or her own body, specifically, detailed dimensional data such as height, weight, shoulder width, and waist width.

[0426] The user then uploads the floor plan to the application and enters details such as the room shape, dimensions, window locations, light source locations, and door locations.

[0427] The user also inputs their tastes and preferences (eg, particular furniture styles, color preferences, special feature requests, etc.).

[0428] The terminal validates all entered data in real time, prompts the user for any missing information, and once all data is collected, sends it to the server.

[0429] 2. Data analysis steps

[0430] The server then uses the received data to generate a 3D model of the human body, which is constructed based on the user's posture and body shape.

[0431] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow.

[0432] The server simulates the effects of natural and artificial light in the room based on the light source position, and then considers the placement of furniture to achieve the appropriate brightness balance.

[0433] The server considers the user's tastes and preferences, lists suitable furniture candidates, and calculates the optimal dimensions, shape, and placement of the furniture based on the stereoscopic measurement data and ergonomics of the human body.

[0434] 3. Furniture and layout proposal steps

[0435] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal.

[0436] The terminal provides users with an interface that allows them to visually check furniture and layout plans, and through 3D views and simulation screens, users can intuitively understand the proposals.

[0437] The user uses the provided visual interface to review the proposed furniture and layout and, if desired, provide feedback on the proposal.

[0438] 4. User Feedback Step

[0439] The user provides feedback and suggestions for improvements to the proposed furniture arrangement (for example, moving the chair a little further to the left).

[0440] The terminal records the feedback from the user and sends it to the server.

[0441] The server analyzes the user feedback and re-runs the algorithms to modify the furniture list and layout plan as needed.

[0442] The server regenerates the revised plan and sends it to the terminal.

[0443] The terminal presents the newly revised plan to the user and again accepts feedback.

[0444] Specific examples

[0445] Case study: System usage example of a freelancer who works long hours at a desk at home

[0446] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0447] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0448] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0449] 4. The terminal sends all the information entered to the server.

[0450] 5. The server generates a 3D model of the human body based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0451] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0452] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0453] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0454] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0455] By repeating this process, users can create the optimal working environment for themselves. This system is characterized by its maximum consideration of health and provides an environment that allows users to work comfortably even during long hours of desk work.

[0456] The processing flow will be explained below.

[0457] Step 1:

[0458] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user after having previously acquired it using a measuring device, or it can be automatically acquired using a dedicated 3D scanning device. After completing the input, the data is sent to the server.

[0459] Step 2:

[0460] The user uploads a floor plan to the application, which includes detailed information such as room dimensions, shape, window and light source positions, and door positions. After uploading, the user can review this information using the application interface and make any necessary corrections. Once the corrections are complete, the data is sent to the server.

[0461] Step 3:

[0462] Users input their preferences and special requests, such as a particular furniture style (e.g., modern or minimalist), preferred color coordination, and special feature requirements (e.g., a desk with standing capabilities or an ergonomic chair). Once completed, all data is sent to the server.

[0463] Step 4:

[0464] The device verifies all data entered by the user in real time, checking that all required fields have been entered, and notifying the user if any information is missing, prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[0465] Step 5:

[0466] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[0467] Step 6:

[0468] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0469] Step 7:

[0470] The server analyzes the user's input preferences and special requests and generates a list of suitable furniture options, generated using ergonomic algorithms that take into account the dimensions, shape, and placement of the furniture that best suits the user.

[0471] Step 8:

[0472] The server generates an optimal furniture list and layout plan based on the analysis results, and the generated list and plan are sent to the terminal in data format.

[0473] Step 9:

[0474] The terminal provides an interface that allows users to visually check the proposed contents. Users can intuitively understand and check the proposed furniture arrangement using 3D views and simulation screens.

[0475] Step 10:

[0476] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0477] Step 11:

[0478] The terminal records the feedback from the user and sends it to the server.

[0479] Step 12:

[0480] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[0481] Step 13:

[0482] The server regenerates a revised plan and sends it to the terminal, which then presents the revised plan to the user, who then confirms it again. If further feedback is required, the cycle repeats.

[0483] Example 1

[0484] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0485] In recent years, with the increase in telecommuting and remote work, the importance of a comfortable working environment at home has increased. However, when it comes to furniture placement and selection, it is difficult to receive suggestions that are optimized for each individual's body shape and preferences. Inappropriate furniture placement and selection can be harmful to health, so a system to solve this problem is needed.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0487] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for generating a three-dimensional model of the human body based on the input data, means for analyzing the floor plan data to determine areas where furniture can be placed and efficient traffic lines, means for simulating the effects of natural light and artificial light in the room based on the light source positions, means for calculating an optimal furniture list and layout based on the three-dimensional measurement data of the human body and ergonomics, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and means for receiving feedback from the user and recalculating the furniture list and layout. This makes it possible to suggest optimal furniture selection and layout that takes the user's health into consideration in real time, thereby realizing a comfortable working environment.

[0488] "Human body three-dimensional measurement data" refers to individual dimensional data such as height, weight, shoulder width, and waist width, and is basic information for generating a three-dimensional model.

[0489] A "floor plan" is a layout diagram of an entire room that includes information such as the shape, dimensions, window, light source position, and door position of the room.

[0490] "Light source position" is position information that indicates where natural light or artificial light in a room is emitted from.

[0491] "Hobby information" is information that indicates a user's personal preferences, such as a particular furniture style, color preferences, or special function requirements.

[0492] A "three-dimensional model" is a three-dimensional model generated by computer software based on inputted dimensional data of the human body.

[0493] "Traffic lines" refer to the routes people take within a room, and are information used in layout planning to enable efficient movement.

[0494] "Simulation" refers to reproducing the situation and effects on a computer based on real-world conditions such as the position of a light source.

[0495] The "optimal furniture list" is a list of furniture selected based on the user's dimensional data, floor plan, hobby information, and ergonomics.

[0496] An "interface" refers to the screens and operating methods that allow a user to interact with a system, providing information in a visually identifiable format.

[0497] "Feedback" refers to input information such as opinions and improvements provided by the user regarding the proposed furniture arrangement plan.

[0498] The system of the present invention is a system that proposes optimal furniture and its layout taking into consideration the health of the user. An embodiment of this system will be specifically described below.

[0499] Program Overview

[0500] Data Collection Steps

[0501] First, a user launches the application and inputs their own anthropometric data, including detailed measurements such as height, weight, shoulder width, and hip width. Next, the user uploads a floor plan to the application and inputs detailed information such as the room's shape, dimensions, window position, light source position, and door position. Additionally, the user inputs their personal tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.).

[0502] The terminal validates all of this input data in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server. Specifically, the data is sent using an HTTP POST request.

[0503] Data analysis steps

[0504] The server generates a 3D model of the human body based on the received data. This model is constructed based on the user's posture and body shape. Specifically, it uses 3D modeling software (e.g., Blender or Maya).

[0505] The server then analyzes the floor plan data to determine areas where furniture can be placed and efficient traffic flow. Image analysis software is used to analyze the floor plan images.

[0506] The server also simulates the effects of natural and artificial light in the room based on the light source position. It uses a light and shadow calculation algorithm to simulate the brightness of each area of ​​the room. Based on this information, the server takes into account the user's tastes and preferences and lists suitable furniture candidates. Furthermore, it calculates the optimal furniture dimensions, shape, and placement based on the stereoscopic measurement data of the human body and ergonomics.

[0507] Furniture and layout proposal steps

[0508] The server generates an optimal furniture list and layout plan based on the analysis results and sends this to the device in a data format, typically JSON.

[0509] The terminal provides users with an interface that allows them to visually check the furniture and layout plans. Specifically, it displays a 3D viewer and a simulation screen, allowing users to intuitively check the proposals.

[0510] Users can use it to review the proposed furniture and layout and provide feedback if needed, such as entering specific requests like "I'd like the chair to be moved a little further to the left."

[0511] User Feedback Steps

[0512] The device records the feedback from the user and sends it to the server, again using an HTTP POST request to send the feedback data.

[0513] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. Once the recalculation is complete, a new layout plan is regenerated and sent to the device.

[0514] The device presents the newly revised plan to the user and again accepts feedback. By repeating this process, it is possible to provide the user with an optimal working environment.

[0515] Specific examples

[0516] Case study: System usage example of a freelancer who works long hours at a desk at home

[0517] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0518] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0519] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0520] 4. The terminal sends all the information entered to the server.

[0521] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0522] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0523] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0524] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0525] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0526] By repeating this process, the user can create the optimal working environment for themselves.

[0527] Example prompt statement

[0528] "I work at a desk for long periods of time at home, so I'd like a system that suggests optimal furniture layouts that take my health into consideration. I'm 170cm tall, weigh 65kg, and prefer modern-style furniture. I've entered my floor plan and detailed information, so please provide me with the optimal furniture list and layout plan."

[0529] This system is characterized by its maximum consideration of health and provides a comfortable environment even during long hours of desk work.

[0530] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0531] Step 1:

[0532] The user starts the application and inputs their own 3D body measurement data. The input includes detailed dimensional data such as height, weight, shoulder width, and hip width. Specifically, the user enters this information into the application's data input form, and the data is acquired as 3D body measurement data.

[0533] Step 2:

[0534] Users upload floor plans to the application and enter details such as room shape, dimensions, window locations, light source locations, and door locations. The input includes floor plan files in JPEG and PDF formats, which then imports the floor plan data into the system.

[0535] Step 3:

[0536] Users input their tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.). The input includes preference information such as "modern style" and "blue and white color scheme." This taste information is then incorporated into the system.

[0537] Step 4:

[0538] The device validates all entered data in real time and prompts the user to enter any missing information. Specifically, the device checks each field on the input form and displays a pop-up message to the user, such as "Weight is missing." Once all the data is collected, the device sends it to the server. An HTTP POST request is used for transmission.

[0539] Step 5:

[0540] The server generates a 3D model of the human body based on the received data. The input data is the stereoscopic measurement data of the human body, and the output is a 3D model. Specifically, a human body model is generated based on the input dimensional data using 3D modeling software (e.g., Blender or Maya).

[0541] Step 6:

[0542] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. The input data is floor plan data, and the output is information on the areas where furniture can be placed and traffic flow. Specifically, the floor plan is analyzed using image analysis software, and furniture placement space and aisle width are calculated.

[0543] Step 7:

[0544] The server simulates the effects of natural and artificial light in a room based on the light source position. The input data is light source position information, and the output is brightness information for each area. Specifically, it uses a light and shadow calculation algorithm to calculate the brightness of the room based on the window and lighting positions.

[0545] Step 8:

[0546] The server considers the user's tastes and preferences and lists suitable furniture candidates. The input data is hobby information and ergonomic data, and the output is a list of optimal furniture. Specifically, it searches the database for modern-style furniture and generates a list of furniture that matches the user's tastes and room dimensions.

[0547] Step 9:

[0548] The server calculates the optimal furniture dimensions, shape, and layout based on the stereoscopic measurement data of the human body and ergonomics. The input data is a human body model and an ergonomics algorithm, and the output is an optimal furniture layout plan. Specifically, it calculates, for example, chair heights and desk positions and creates a layout plan.

[0549] Step 10:

[0550] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal. The input data is the optimal furniture placement plan, and the output is a furniture list and layout plan in data format. JSON format is generally used.

[0551] Step 11:

[0552] The terminal provides the user with an interface that allows them to visually check the furniture and layout plan. The input data is the furniture list and layout plan sent from the server, and the output is a 3D viewer or simulation screen. This allows the user to intuitively check the proposal.

[0553] Step 12:

[0554] The user uses the provided visual interface to review the proposed furniture and layout and provide feedback as needed. The input data are the user's opinions and suggestions for improvement, and the output is feedback information. For example, the user can input a specific request such as "I'd like to move the chair a little further to the left."

[0555] Step 13:

[0556] The terminal records the feedback from the user and sends it to the server. The input data is the feedback information, and the output is an HTTP POST request to the server.

[0557] Step 14:

[0558] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. The input data is the feedback information, and the output is the modified furniture placement plan.

[0559] Step 15:

[0560] The server regenerates the modified plan and sends it to the terminal. The input data is the modified furniture layout plan, and the output is the data format sent to the terminal.

[0561] Step 16:

[0562] The device then presents the newly revised plan to the user and again accepts feedback. The input data is the revised furniture layout plan, and the output is an updated 3D view or simulation screen. By repeating this process, the user is provided with an optimal working environment.

[0563] (Application example 1)

[0564] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0565] Currently, food delivery stores lack concrete measures to create an efficient working environment, and furniture layout and traffic flow are not optimized with consideration for staff health. This can result in a decline in work efficiency and an increased risk to staff health. Furthermore, there is no system in place to incorporate feedback and make continuous improvements, making it difficult to optimize the working environment.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0567] In this invention, the server includes a means for inputting three-dimensional measurement data of the human body, a means for inputting floor plans, work environment information, light source positions, and work flow information, a means for calculating an optimal work environment list and its layout based on ergonomics based on the input data, a means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and a means for receiving feedback from the user and recalculating the work environment list and layout. This makes it possible to provide an efficient and healthy work environment in food delivery stores. Furthermore, by continuously reflecting feedback, the work environment can be continuously optimized.

[0568] "Human body three-dimensional measurement data" refers to detailed dimensional data such as the user's height, shoulder width, and weight, and refers to three-dimensional information about the user's body shape and posture.

[0569] A floor plan is a drawing that shows the shape, dimensions, window and door locations of a room or store.

[0570] "Work environment information" refers to detailed data regarding the layout of equipment within the work area, the location of the warehouse, and the work content.

[0571] "Light source position" refers to information about the location of a light source, such as natural light or artificial light.

[0572] "Work flow information" refers to information regarding efficient routes for people and things to move within a work area.

[0573] "Ergonomics" refers to the scientific knowledge and methods for designing work environments and products that take into account the physical and psychological characteristics of people.

[0574] The "work environment list" refers to a list of optimal furniture and equipment that takes into consideration work efficiency and health.

[0575] A "visually verifiable interface" refers to a user interface that provides a 3D view or simulation screen so that users can intuitively understand the calculation results.

[0576] "User feedback" refers to information that users input regarding their opinions and suggestions for improvement regarding the layout plan and furniture list provided.

[0577] "Recalculation" refers to recalculating the optimal work environment list and its layout based on feedback from the user.

[0578] To put this invention into practice, it is first necessary to build a system for inputting three-dimensional measurement data of the human body, work environment information, light source position, and work flow information. Below, we will explain the program processing of this system and provide a detailed explanation of the hardware and software used.

[0579] Users use their smartphones or PCs to input their three-dimensional body measurement data. This data includes detailed measurements such as height, shoulder width, and weight. They also upload floor plans to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter details about work flow and the work environment. Once this data is entered, the device verifies it in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server.

[0580] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information. This is done using programming languages ​​such as Python and APIs such as Flask.

[0581] The server sends the calculated results to the device, which then provides a visual interface for the user. The user can intuitively understand the proposed furniture and layout using a 3D view or simulation screen. This interface also makes it easier for the user to provide feedback on the proposed content.

[0582] Feedback from the user is recorded by the device and sent back to the server. The server analyzes the user's feedback and recalculates the work environment list and layout plan as necessary. The server then sends the revised plan back to the device, where the user can review the newly revised plan. By repeating this process, the optimal work environment can be provided to the user.

[0583] Specific examples

[0584] For example, when a food delivery store manager uses this system, they first input three-dimensional measurement data such as the height and shoulder width of their cooking and delivery staff. Next, they upload a floor plan of the store and input the layout of the kitchen and warehouse, as well as the position of the light source. They then provide information on work flow and details of the required work environment.

[0585] The server calculates a healthy and efficient work environment based on each staff member's body data and store layout information. For example, it optimizes counter height, shelf placement, and traffic flow, and makes suggestions on a visual interface. Managers can provide feedback on these suggestions and request recalculations to create the ideal work environment.

[0586] Example prompt sentence:

[0587] "This system proposes optimal furniture layouts that take user health into consideration. The system proposes optimal work environments based on the user's 3D body measurement data, store floor plans, and equipment layout. For example, the system considers an arrangement that would be comfortable for a staff member with a height of 170 cm and shoulder width of 45 cm, and includes the shape of the room, the position of the light source, and the location of the warehouse as input data."

[0588] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0589] Step 1:

[0590] Users use their smartphones or PCs to input their own three-dimensional body measurement data. Specifically, detailed dimensional data such as height, shoulder width, and weight are entered. They also upload a floor plan to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter information about work flow and the work environment. Once all the information has been entered, it is sent to the server.

[0591] Input: 3D body measurement data, floor plan, detailed information (windows, doors, light source positions, etc.), work flow information, work environment information

[0592] Output: All input data sent to the server

[0593] Step 2:

[0594] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information.

[0595] Input: All input data sent to the server

[0596] Output: 3D model of the human body, analysis results (area where furniture can be placed, traffic flow, lighting simulation)

[0597] Step 3:

[0598] The server sends the calculated results to the terminal, which then provides a visual interface for the user, allowing them to intuitively understand and check the proposed furniture and layout using a 3D view or simulation screen.

[0599] Input: Analysis results (3D model of the human body, area where furniture can be placed, traffic flow, lighting simulation)

[0600] Output: Visual interface presented to the user (3D view, simulation screen)

[0601] Step 4:

[0602] The user can check the proposed content through a visual interface and provide necessary feedback, such as requests for changes to furniture positions or work flow. This feedback is sent to the server via the terminal.

[0603] Input: User feedback (changing furniture position, correcting traffic flow, etc.)

[0604] Output: Feedback sent to the server

[0605] Step 5:

[0606] The server analyzes the user's feedback, recalculates the work environment list and layout plan as necessary, and then sends the revised plan back to the terminal, where the user can view the newly revised plan.

[0607] Input: Feedback sent to the server

[0608] Output: Recalculated workspace list and layout plan

[0609] Step 6:

[0610] The device presents the recalculated plan to the user and prompts them to confirm the newly revised plan. This process is repeated until the user is satisfied, providing an optimal working environment.

[0611] Input: Recalculated workspace list and layout plan

[0612] Output: Optimal work environment plan presented to the user (for final confirmation)

[0613] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0614] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics based on 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. This system also recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. Below, the program processing of this system is explained in natural language and in detail with concrete examples.

[0615] Program Overview

[0616] 1. Data collection steps

[0617] First, the user inputs their own 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user using a measuring device in advance, or automatically acquired using a dedicated 3D scanning device.

[0618] The user then uploads a floor plan to the application, which includes details such as room shape, dimensions, window and light source locations, and door locations. After uploading, the user can review this information using the application's interface and make any necessary corrections.

[0619] The user also inputs their preferences and special requests (e.g., specific furniture styles, color coordination, special function requests), and once input is complete, this data is sent to the server.

[0620] 2. Data analysis steps

[0621] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[0622] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0623] The server then generates an optimal furniture list and layout plan based on the analysis results, using ergonomic algorithms to consider the dimensions, shapes, and placement of furniture that best suit the user.

[0624] 3. Emotion Engine Steps

[0625] The server recognizes the user's emotional state using an emotion engine. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer emotions in real time. This emotion data is reflected in the analysis results, and a furniture list and arrangement optimal for the user's current emotional state are created.

[0626] The server learns the user's past emotional data and makes furniture suggestions taking into account their long-term emotional trends, thereby providing a comfortable environment for the user to live in for a long time.

[0627] 4. Furniture and layout proposal steps

[0628] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends this in data format to the terminal.

[0629] The terminal provides users with an interface that allows them to visually check the furniture and layout plan. Users can intuitively understand and check the proposal using 3D views, simulation screens, etc.

[0630] 5. User Feedback Steps

[0631] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0632] The terminal records the feedback from the user and sends it to the server.

[0633] The server analyzes the user's feedback and performs recalculations to modify the furniture list and layout plan as needed.

[0634] Specific examples

[0635] Case study: System usage example of a freelancer who works long hours at a desk at home

[0636] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0637] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0638] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0639] 4. The terminal sends all the information entered to the server.

[0640] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0641] 6. The server uses an emotion engine to recognize the user's emotional state and makes suggestions that best fit the current emotional state.

[0642] 7. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0643] 8. The user reviews the proposed furniture and layout and provides feedback, for example, suggesting that the chair be moved slightly to the left.

[0644] 9. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0645] 10. The server sends the revised plan to the device, which presents it to the user again. The cycle repeats if the user checks again and provides feedback.

[0646] This system takes maximum consideration of the user's health and, by combining it with an emotion engine, can provide an optimal working environment that also takes into account the user's emotional state, thus creating an environment where users can work comfortably even during long hours of desk work.

[0647] The processing flow will be explained below.

[0648] Step 1:

[0649] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, hip width, etc.). This data can be manually input by the user using a measuring device or automatically acquired using a dedicated 3D scanning device.

[0650] Step 2:

[0651] Users upload floor plans to the application, which include details such as room dimensions, shape, window and light source locations, and door locations. After uploading, users can review this information and make any necessary corrections using the application's interface.

[0652] Step 3:

[0653] Users input their preferences and special requests (e.g., specific furniture styles and colors, special feature requests, etc.) Once input is complete, all data is sent to the server.

[0654] Step 4:

[0655] The terminal validates all data entered by the user in real time, checking that all required fields have been entered, notifying the user if any information is missing and prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[0656] Step 5:

[0657] The server then generates a 3D model of the user's body based on the received data, using an algorithm that analyzes the dimensions of each part of the body in three dimensions and creates an accurate model based on the user's posture and body shape.

[0658] Step 6:

[0659] The server analyzes furniture placement areas and user movement lines based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user movement lines. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0660] Step 7:

[0661] The server takes into account the user's tastes and special requests and generates a list of suitable furniture options, taking into account the ergonomic dimensions, shapes, and placement of the furniture.

[0662] Step 8:

[0663] The server uses an emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer their current emotional state. This information is reflected in furniture and layout suggestions.

[0664] Step 9:

[0665] The server learns past emotional data and makes furniture suggestions taking into account the user's long-term emotional trends, thereby providing a comfortable environment for the user over the long term.

[0666] Step 10:

[0667] The server generates an optimal furniture list and layout plan based on the analysis results and the emotion engine results, and the generated list and plan are sent to the terminal in data format.

[0668] Step 11:

[0669] The terminal provides an interface that allows users to visually check the furniture and layout plan, and users can intuitively understand and check the proposal using 3D views and simulation screens.

[0670] Step 12:

[0671] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0672] Step 13:

[0673] The terminal records the feedback from the user and sends it to the server.

[0674] Step 14:

[0675] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[0676] Step 15:

[0677] The server regenerates the revised plan and sends it to the device, which presents the new revised plan to the user for confirmation again. If further feedback is required, the cycle repeats.

[0678] This system provides an optimal working environment that takes into account the user's health and emotional state, making it possible to work comfortably even during long hours of desk work.

[0679] Example 2

[0680] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0681] Conventional furniture layout systems could provide optimal furniture layouts based on the user's body data and room layout information, but because they did not take the user's emotional state into account, it was difficult to fully guarantee long-term comfort and user satisfaction. Furthermore, when recalculating based on feedback, optimization was not possible in combination with past emotional data, making it difficult to provide the optimal environment the user desired.

[0682] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for recognizing the user's emotional state and analyzing the emotional data, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data and emotional data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, and means for learning from the feedback and past emotional data and improving the proposal. This makes it possible to provide an optimal furniture layout and its proposal taking into account the user's emotional state.

[0683] "Human body 3D measurement data" refers to data indicating the user's physical dimensions such as height, weight, shoulder width, and waist width, and is data obtained using a dedicated 3D scanning device or manual input.

[0684] A "floor plan" is a drawing that shows the shape, dimensions, window positions, light source positions, door positions, etc. of a room, and is data that a user uploads to the application.

[0685] "Furniture arrangement information" is data that indicates information such as the type, position, dimensions, and shape of furniture arranged in a room.

[0686] "Light source position" is data that indicates the specific position of a light source (window, lighting fixture, etc.) in a room.

[0687] "Hobby information" is data that indicates the user's furniture preferences, style, color coordination, special requests, and the like.

[0688] "Emotional state" is data indicating the emotional state of the user that is estimated by analyzing the user's facial expression, tone of voice, body movements, and the like.

[0689] "Emotion data" is data that expresses emotional states using numerical values ​​and categories, and is data that is analyzed and collected by the emotion engine.

[0690] The "ergonomically optimal furniture list" is a list showing the type, dimensions, and shape of furniture that is considered optimal from an ergonomic perspective based on the user's body data, room floor plan, furniture placement information, light source position, and hobby information.

[0691] A "visual interface" refers to an interface that allows users to visually check the furniture layout plan through a 3D view or simulation screen.

[0692] "Feedback" refers to information that a user inputs into the application about their opinions and requests regarding the proposed furniture and layout, and sends it to the server.

[0693] The present invention is a system that calculates an optimal furniture list and its layout based on the user's ergonomics based on the user's 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. Furthermore, the system recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. The detailed implementation method of this system is described below.

[0694] Data collection

[0695] First, a user launches the application and inputs their anthropometric data (e.g., height 170 cm, weight 65 kg, shoulder width 45 cm). This data can be entered manually or automatically obtained using a dedicated 3D scanning device. Next, the user uploads a floor plan of the room to the application. The floor plan includes details such as the room's shape, dimensions, window locations, light source locations, and door locations. In addition, the user can input their preferences and special requests (e.g., specific furniture style and color coordination).

[0696] Data analysis

[0697] The server generates a three-dimensional model of the user's body based on the received stereoscopic body measurement data. This process uses 3D modeling software (e.g., Blender) to analyze the dimensions of each part of the body in three dimensions and create an accurate model. The server then analyzes the floor plan data to calculate furniture placement areas and traffic flow. It also simulates natural and artificial light based on the light source position. For example, it uses emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API."

[0698] Emotion analysis

[0699] The server uses an emotion engine to recognize the user's emotional state. This allows it to analyze the user's facial expressions, tone of voice, and physical movements to infer emotions in real time. This emotional data is reflected in the analysis results, creating a furniture list and placement that is optimal for the user's current emotional state. The server also learns from past emotional data and makes furniture suggestions that take long-term emotional trends into account.

[0700] Furniture and layout suggestions

[0701] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends it to the device. The device then provides an interface that allows users to visually check the furniture and layout plan. For example, users can use game engines such as Unity or Unreal Engine to understand the proposals through 3D views and simulation screens.

[0702] User Feedback

[0703] Finally, the user reviews the proposed furniture and layout and provides feedback. For example, they might enter a specific suggestion such as, "I'd like to move the chair a little to the left." The device records the feedback and sends it to the server. The server analyzes the feedback, recalculates as necessary, and generates a new furniture list and layout plan. This cycle is repeated until the user is satisfied.

[0704] Specific examples

[0705] This shows how a freelancer working from home uses this system.

[0706] 1. The user starts the application and enters data such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0707] 2. The user uploads a floor plan and inputs the shape of the room, the position of the light source, the location of the door, etc.

[0708] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0709] 4. The server analyzes the data and generates a 3D human body model.

[0710] 5. The server uses an emotion engine to analyze the user's emotional state.

[0711] 6. The server generates an optimal furniture list and layout plan and sends it to the terminal.

[0712] 7. The device presents the furniture and layout plan to the user in a 3D view.

[0713] 8. The user reviews the proposal and provides feedback.

[0714] 9. The server recalculates based on the feedback and creates a new plan.

[0715] This system allows users to create a comfortable working environment.

[0716] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0717] Step 1:

[0718] The user launches the application and inputs their body stereoscopic measurement data. For example, height 170 cm, weight 65 kg, shoulder width 45 cm, etc., can be entered manually or automatically using a stereoscopic scanning device. This operation inputs the user's physical dimensions into the application. The input includes the body stereoscopic measurement data. The output is the input data sent to the server.

[0719] Step 2:

[0720] The user uploads a floor plan to the application. The floor plan includes detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. After uploading, the user can review this information and modify it as necessary. For example, the user can fine-tune the room dimensions or light source positions using the application interface. The input includes the floor plan. The output is the modified floor plan data sent to the server.

[0721] Step 3:

[0722] Users input their preferences and special requests (e.g., preferences for a particular furniture style or color) into the application, which then collects the user's preference data. The input includes the preferences and special requests. The output is sent to the server.

[0723] Step 4:

[0724] The server generates a 3D human body model of the user based on the received 3D human body measurement data, floor plan data, and hobby information. In this process, 3D modeling software (e.g., Blender) is used to analyze the data in three dimensions and create a 3D human body model. The inputs include the 3D human body measurement data, floor plan data, and hobby information. The output is the generated 3D human body model and the analysis results.

[0725] Step 5:

[0726] The server analyzes floor plan data and calculates furniture placement areas and traffic flow. At this stage, it determines where furniture can be placed and what the optimal traffic flow is. It also simulates natural and artificial light based on the light source position, simulating the brightness of the entire room. The input includes floor plan data and light source position data. The output is the placement area analysis results and light simulation results.

[0727] Step 6:

[0728] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements in real time to generate emotional data. Here, emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API" are used. The input includes real-time user information (facial expressions, tone of voice, and body movements). The output is the analyzed emotional data.

[0729] Step 7:

[0730] The server generates an optimal ergonomic furniture list and layout plan based on the input data and emotion data. This process uses an algorithm to calculate the optimal furniture dimensions, shape, and layout. Inputs include a 3D human body model, floor plan analysis results, and emotion data. The output is an optimal furniture list and layout plan.

[0731] Step 8:

[0732] The server sends the generated furniture list and layout plan to the terminal. The terminal provides an interface that the user can visually check, and displays the proposed content in a 3D view or simulation screen. For example, a game engine (e.g., Unity or Unreal Engine) is used to display a simulation of the furniture layout in real time. The input includes the furniture list and layout plan sent from the server. The output is the interface that is visually presented to the user.

[0733] Step 9:

[0734] The user reviews the proposed furniture and layout and provides feedback. Specifically, the user inputs their feedback, such as rearranging the furniture or adjusting the layout, into the application. The input includes the user's feedback. The output is sent to the server.

[0735] Step 10:

[0736] The server analyzes the received feedback and recalculates the furniture list and layout plan as needed, taking into account past emotional data to update the proposals. The inputs include the user's feedback and past emotional data. The output is a revised furniture list and layout plan.

[0737] Step 11:

[0738] The server sends the revised plan to the terminal and presents it again to the user. The terminal updates the interface for further user review. The input includes the revised plan. The output is an updated visual interface.

[0739] By repeating the above processing steps, an optimal furniture arrangement that satisfies the user is provided.

[0740] (Application example 2)

[0741] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0742] Conventional furniture layout suggestion systems do not take into account the user's detailed 3D body measurement data or emotional state, making it difficult to select and arrange optimal furniture. Furthermore, they lacked an interface for visually confirming the proposed content, making it difficult for users to intuitively understand the content. Furthermore, there was no means in place to provide optimal furniture suggestions to users on the spot in physical stores or commercial facilities. There was a need to solve these issues and improve user comfort and ease of use.

[0743] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0744] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, means for recognizing the user's emotional state and using an emotion engine to make optimal furniture suggestions, means for visualizing the consideration results through a three-dimensional view or simulation screen, and means for making optimal furniture suggestions to the user in a store or commercial facility where there is a physical presence. This enables optimal furniture suggestions that reflect the user's detailed human body data and emotional state, and not only can suggestions be made through an intuitively easy-to-understand visual interface, but also enables instantly customized furniture suggestions in physical stores and commercial facilities.

[0745] "Three-dimensional measurement data of the human body" refers to data obtained in three dimensions that indicates specific human body dimensions such as the user's height, weight, shoulder width, and waist width.

[0746] A "floor plan" is a drawing that includes detailed information such as the shape and dimensions of a room, the location of windows, the location of light sources, and the location of doors.

[0747] "Furniture arrangement information" is data relating to where in a room each piece of furniture is arranged.

[0748] "Light source position" is information indicating the position of a source of natural light or artificial light in a room.

[0749] "Hobby information" is data about the user's preferences, such as preferred furniture styles, color coordination, and special functional requirements.

[0750] "Ergonomics" is the study of creating comfortable and efficient designs that take into account human physical characteristics and movements.

[0751] A "furniture list" is a list of the most suitable furniture suggested to the user.

[0752] The "emotion engine" is a system that analyzes and infers the user's emotional state from facial expressions, tone of voice, physical movements, etc.

[0753] "Interface" refers to the screen and input devices that users use to operate the system.

[0754] "Feedback" refers to the act of communicating to the system the user's opinions and requests for corrections regarding the proposed content.

[0755] A "3D view" is a display format that visualizes proposed furniture placement and room layout in three dimensions.

[0756] A "simulation screen" is a display means for virtually reproducing how a proposed furniture arrangement will function.

[0757] A "physical commercial facility" refers to a store or facility that actually exists as a building and that customers can visit.

[0758] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics and presents it to the user. This system operates based on three-dimensional human body measurement data, floor plans, furniture layout information, light source position, and hobby information. It also uses an emotion engine to recognize the user's emotional state and make suggestions based on that emotional state. This system provides furniture suggestions optimized for the user's characteristics and emotions in brick-and-mortar stores and commercial facilities.

[0759] The following hardware and software are used to process the data. First, a body scanning device (BodyScanner) is required to collect stereoscopic measurement data of the human body. Dedicated software (LayoutAnalyzer) is used to analyze floor plans and furniture layout information. An emotion recognition engine (EmotionRecognitionEngine) is used to recognize emotional states. A furniture recommendation engine (FurnitureRecommender) is required to recommend furniture, and this incorporates ergonomic algorithms. Finally, software (VisualizationInterface) is used to provide a 3D view display and simulation screen as an interface to visually display suggestions to the user.

[0760] The server operates by coordinating the various software modules described above. Specifically, the server collects and analyzes three-dimensional measurement data of the human body and calculates the optimal furniture list and its placement based on the floor plan and furniture layout information. It also uses an emotion engine to recognize the user's emotional state and suggests furniture that best suits that emotional state. The calculation results are then sent to the device, which then visually presents the suggestions to the user through a 3D view or simulation screen.

[0761] Consider the following scenario: In a physical store, a user uses a body scanning device to collect stereoscopic measurement data of their body. Then, they upload a floor plan and enter their hobbies and special requests. All of this data is sent to a server, which calculates the optimal furniture list and its placement. An emotion engine analyzes the user's emotional state and generates optimal furniture suggestions. The calculation results are sent to the device, which visually presents the suggestions to the user through a 3D view or simulation screen.

[0762] For example, you can make suggestions using prompts like the following:

[0763] "Please suggest a furniture list and layout to optimize the interior of a living room and bedroom. The user's anthropometric data are height 170cm, weight 65kg, and shoulder width 45cm. The floor plan is as follows:

[0764] Living room: Light source is located in the center of the ceiling, window is on the south side, door is on the north side

[0765] Bedroom: Light source is on the west side of the ceiling, window is on the east side, door is on the south side

[0766] The user's preferred furniture style is modern, their preferred color is blue and white, and their emotional state is relaxed.

[0767] Based on this information, please design an algorithm that will suggest the optimal furniture list and its placement."

[0768] In this way, the present invention can provide optimal furniture suggestions that take into account the user's physical characteristics and emotional state, improving the user experience in physical stores and commercial facilities.

[0769] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0770] Step 1:

[0771] A user uses a body scanning device to collect stereoscopic data of their body. The device acquires dimensional data such as height, weight, shoulder width, and hip width, and sends it to a cloud server. The input is the user's body data, and the output is analyzable stereoscopic data.

[0772] Step 2:

[0773] Users upload floor plans to the application. They also input information about furniture layout, light source positions, and door and window locations. This data is sent to a cloud server via the device. The input is the floor plan and related information, and the output is spatial information data for analysis.

[0774] Step 3:

[0775] The server analyzes the transmitted stereoscopic body measurement data and floor plan data. It uses ergonomic algorithms to calculate the optimal furniture dimensions, shape, and placement. The input is the body and floor plan data, and the output is the optimal furniture list and placement plan.

[0776] Step 4:

[0777] The server uses an emotion recognition engine to analyze the user's emotional state. It uses a camera and microphone to detect facial expressions, tone of voice, and body movements to determine emotions. The input is real-time user facial and voice data, and the output is analyzed emotional state data.

[0778] Step 5:

[0779] Based on the results of the emotion engine, the server recalculates optimal furniture suggestions, adjusting the suggestions to suit the user's current emotional state. The input is emotional state data, and the output is an optimal furniture list and its placement that takes emotions into account.

[0780] Step 6:

[0781] The server sends the calculation results to the terminal, which visually displays the proposal to the user through a 3D view or simulation screen. The input is the calculated furniture list and placement data, and the output is the proposal displayed on the visual interface.

[0782] Step 7:

[0783] The user checks the visually displayed furniture arrangement proposal and inputs their feedback into the device, providing specific suggestions for revisions, such as the desired furniture position or height. The input is the user's feedback, and the output is the revision proposal data.

[0784] Step 8:

[0785] The device sends the user's feedback to the server, which then recalculates the optimal furniture list and layout based on the feedback and generates a revised plan. The input is the user's feedback, and the output is the revised layout plan.

[0786] Step 9:

[0787] The server sends the revised furniture list and layout plan to the terminal, which then displays it again to the user. This cycle is repeated until the user is satisfied. The input is the revised data, and the output is the final proposal to be confirmed.

[0788] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0789] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0790] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0791] [Third embodiment]

[0792] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0793] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0794] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0795] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0796] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0797] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0798] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0799] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0800] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0801] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0802] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0803] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0804] The system of the present invention proposes optimal furniture and its layout taking into consideration the user's health. Below, the program processing of this system will be explained in natural language and in detail with concrete examples.

[0805] Program Overview

[0806] 1. Data collection steps

[0807] First, the user inputs the three-dimensional measurement data of his or her own body, specifically, detailed dimensional data such as height, weight, shoulder width, and waist width.

[0808] The user then uploads the floor plan to the application and enters details such as the room shape, dimensions, window locations, light source locations, and door locations.

[0809] The user also inputs their tastes and preferences (eg, particular furniture styles, color preferences, special feature requests, etc.).

[0810] The terminal validates all entered data in real time, prompts the user for any missing information, and once all data is collected, sends it to the server.

[0811] 2. Data analysis steps

[0812] The server then uses the received data to generate a 3D model of the human body, which is constructed based on the user's posture and body shape.

[0813] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow.

[0814] The server simulates the effects of natural and artificial light in the room based on the light source position, and then considers the placement of furniture to achieve the appropriate brightness balance.

[0815] The server considers the user's tastes and preferences, lists suitable furniture candidates, and calculates the optimal dimensions, shape, and placement of the furniture based on the stereoscopic measurement data and ergonomics of the human body.

[0816] 3. Furniture and layout proposal steps

[0817] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal.

[0818] The terminal provides users with an interface that allows them to visually check furniture and layout plans, and through 3D views and simulation screens, users can intuitively understand the proposals.

[0819] The user uses the provided visual interface to review the proposed furniture and layout and, if desired, provide feedback on the proposal.

[0820] 4. User Feedback Step

[0821] The user provides feedback and suggestions for improvements to the proposed furniture arrangement (for example, moving the chair a little further to the left).

[0822] The terminal records the feedback from the user and sends it to the server.

[0823] The server analyzes the user feedback and re-runs the algorithms to modify the furniture list and layout plan as needed.

[0824] The server regenerates the revised plan and sends it to the terminal.

[0825] The terminal presents the newly revised plan to the user and again accepts feedback.

[0826] Specific examples

[0827] Case study: System usage example of a freelancer who works long hours at a desk at home

[0828] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0829] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0830] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0831] 4. The terminal sends all the information entered to the server.

[0832] 5. The server generates a 3D model of the human body based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0833] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0834] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0835] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0836] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0837] By repeating this process, users can create the optimal working environment for themselves. This system is characterized by its maximum consideration of health and provides an environment that allows users to work comfortably even during long hours of desk work.

[0838] The processing flow will be explained below.

[0839] Step 1:

[0840] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user after having previously acquired it using a measuring device, or it can be automatically acquired using a dedicated 3D scanning device. After completing the input, the data is sent to the server.

[0841] Step 2:

[0842] The user uploads a floor plan to the application, which includes detailed information such as room dimensions, shape, window and light source positions, and door positions. After uploading, the user can review this information using the application interface and make any necessary corrections. Once the corrections are complete, the data is sent to the server.

[0843] Step 3:

[0844] Users input their preferences and special requests, such as a particular furniture style (e.g., modern or minimalist), preferred color coordination, and special feature requirements (e.g., a desk with standing capabilities or an ergonomic chair). Once completed, all data is sent to the server.

[0845] Step 4:

[0846] The device verifies all data entered by the user in real time, checking that all required fields have been entered, and notifying the user if any information is missing, prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[0847] Step 5:

[0848] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[0849] Step 6:

[0850] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[0851] Step 7:

[0852] The server analyzes the user's input preferences and special requests and generates a list of suitable furniture options, generated using ergonomic algorithms that take into account the dimensions, shape, and placement of the furniture that best suits the user.

[0853] Step 8:

[0854] The server generates an optimal furniture list and layout plan based on the analysis results, and the generated list and plan are sent to the terminal in data format.

[0855] Step 9:

[0856] The terminal provides an interface that allows users to visually check the proposed contents. Users can intuitively understand and check the proposed furniture arrangement using 3D views and simulation screens.

[0857] Step 10:

[0858] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[0859] Step 11:

[0860] The terminal records the feedback from the user and sends it to the server.

[0861] Step 12:

[0862] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[0863] Step 13:

[0864] The server regenerates a revised plan and sends it to the terminal, which then presents the revised plan to the user, who then confirms it again. If further feedback is required, the cycle repeats.

[0865] Example 1

[0866] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0867] In recent years, with the increase in telecommuting and remote work, the importance of a comfortable working environment at home has increased. However, when it comes to furniture placement and selection, it is difficult to receive suggestions that are optimized for each individual's body shape and preferences. Inappropriate furniture placement and selection can be harmful to health, so a system to solve this problem is needed.

[0868] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0869] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for generating a three-dimensional model of the human body based on the input data, means for analyzing the floor plan data to determine areas where furniture can be placed and efficient traffic lines, means for simulating the effects of natural light and artificial light in the room based on the light source positions, means for calculating an optimal furniture list and layout based on the three-dimensional measurement data of the human body and ergonomics, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and means for receiving feedback from the user and recalculating the furniture list and layout. This makes it possible to suggest optimal furniture selection and layout that takes the user's health into consideration in real time, thereby realizing a comfortable working environment.

[0870] "Human body three-dimensional measurement data" refers to individual dimensional data such as height, weight, shoulder width, and waist width, and is basic information for generating a three-dimensional model.

[0871] A "floor plan" is a layout diagram of an entire room that includes information such as the shape, dimensions, window, light source position, and door position of the room.

[0872] "Light source position" is position information that indicates where natural light or artificial light in a room is emitted from.

[0873] "Hobby information" is information that indicates a user's personal preferences, such as a particular furniture style, color preferences, or special function requirements.

[0874] A "three-dimensional model" is a three-dimensional model generated by computer software based on inputted dimensional data of the human body.

[0875] "Traffic lines" refer to the routes people take within a room, and are information used in layout planning to enable efficient movement.

[0876] "Simulation" refers to reproducing the situation and effects on a computer based on real-world conditions such as the position of a light source.

[0877] The "optimal furniture list" is a list of furniture selected based on the user's dimensional data, floor plan, hobby information, and ergonomics.

[0878] An "interface" refers to the screens and operating methods that allow a user to interact with a system, providing information in a visually identifiable format.

[0879] "Feedback" refers to input information such as opinions and improvements provided by the user regarding the proposed furniture arrangement plan.

[0880] The system of the present invention is a system that proposes optimal furniture and its layout taking into consideration the health of the user. An embodiment of this system will be specifically described below.

[0881] Program Overview

[0882] Data Collection Steps

[0883] First, a user launches the application and inputs their own anthropometric data, including detailed measurements such as height, weight, shoulder width, and hip width. Next, the user uploads a floor plan to the application and inputs detailed information such as the room's shape, dimensions, window position, light source position, and door position. Additionally, the user inputs their personal tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.).

[0884] The terminal validates all of this input data in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server. Specifically, the data is sent using an HTTP POST request.

[0885] Data analysis steps

[0886] The server generates a 3D model of the human body based on the received data. This model is constructed based on the user's posture and body shape. Specifically, it uses 3D modeling software (e.g., Blender or Maya).

[0887] The server then analyzes the floor plan data to determine areas where furniture can be placed and efficient traffic flow. Image analysis software is used to analyze the floor plan images.

[0888] The server also simulates the effects of natural and artificial light in the room based on the light source position. It uses a light and shadow calculation algorithm to simulate the brightness of each area of ​​the room. Based on this information, the server takes into account the user's tastes and preferences and lists suitable furniture candidates. Furthermore, it calculates the optimal furniture dimensions, shape, and placement based on the stereoscopic measurement data of the human body and ergonomics.

[0889] Furniture and layout proposal steps

[0890] The server generates an optimal furniture list and layout plan based on the analysis results and sends this to the device in a data format, typically JSON.

[0891] The terminal provides users with an interface that allows them to visually check the furniture and layout plans. Specifically, it displays a 3D viewer and a simulation screen, allowing users to intuitively check the proposals.

[0892] Users can use it to review the proposed furniture and layout and provide feedback if needed, such as entering specific requests like "I'd like the chair to be moved a little further to the left."

[0893] User Feedback Steps

[0894] The device records the feedback from the user and sends it to the server, again using an HTTP POST request to send the feedback data.

[0895] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. Once the recalculation is complete, a new layout plan is regenerated and sent to the device.

[0896] The device presents the newly revised plan to the user and again accepts feedback. By repeating this process, it is possible to provide the user with an optimal working environment.

[0897] Specific examples

[0898] Case study: System usage example of a freelancer who works long hours at a desk at home

[0899] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[0900] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[0901] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[0902] 4. The terminal sends all the information entered to the server.

[0903] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[0904] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[0905] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[0906] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[0907] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[0908] By repeating this process, the user can create the optimal working environment for themselves.

[0909] Example prompt statement

[0910] "I work at a desk for long periods of time at home, so I'd like a system that suggests optimal furniture layouts that take my health into consideration. I'm 170cm tall, weigh 65kg, and prefer modern-style furniture. I've entered my floor plan and detailed information, so please provide me with the optimal furniture list and layout plan."

[0911] This system is characterized by its maximum consideration of health and provides a comfortable environment even during long hours of desk work.

[0912] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0913] Step 1:

[0914] The user starts the application and inputs their own 3D body measurement data. The input includes detailed dimensional data such as height, weight, shoulder width, and hip width. Specifically, the user enters this information into the application's data input form, and the data is acquired as 3D body measurement data.

[0915] Step 2:

[0916] Users upload floor plans to the application and enter details such as room shape, dimensions, window locations, light source locations, and door locations. The input includes floor plan files in JPEG and PDF formats, which then imports the floor plan data into the system.

[0917] Step 3:

[0918] Users input their tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.). The input includes preference information such as "modern style" and "blue and white color scheme." This taste information is then incorporated into the system.

[0919] Step 4:

[0920] The device validates all entered data in real time and prompts the user to enter any missing information. Specifically, the device checks each field on the input form and displays a pop-up message to the user, such as "Weight is missing." Once all the data is collected, the device sends it to the server. An HTTP POST request is used for transmission.

[0921] Step 5:

[0922] The server generates a 3D model of the human body based on the received data. The input data is the stereoscopic measurement data of the human body, and the output is a 3D model. Specifically, a human body model is generated based on the input dimensional data using 3D modeling software (e.g., Blender or Maya).

[0923] Step 6:

[0924] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. The input data is floor plan data, and the output is information on the areas where furniture can be placed and traffic flow. Specifically, the floor plan is analyzed using image analysis software, and furniture placement space and aisle width are calculated.

[0925] Step 7:

[0926] The server simulates the effects of natural and artificial light in a room based on the light source position. The input data is light source position information, and the output is brightness information for each area. Specifically, it uses a light and shadow calculation algorithm to calculate the brightness of the room based on the window and lighting positions.

[0927] Step 8:

[0928] The server considers the user's tastes and preferences and lists suitable furniture candidates. The input data is hobby information and ergonomic data, and the output is a list of optimal furniture. Specifically, it searches the database for modern-style furniture and generates a list of furniture that matches the user's tastes and room dimensions.

[0929] Step 9:

[0930] The server calculates the optimal furniture dimensions, shape, and layout based on the stereoscopic measurement data of the human body and ergonomics. The input data is a human body model and an ergonomics algorithm, and the output is an optimal furniture layout plan. Specifically, it calculates, for example, chair heights and desk positions and creates a layout plan.

[0931] Step 10:

[0932] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal. The input data is the optimal furniture placement plan, and the output is a furniture list and layout plan in data format. JSON format is generally used.

[0933] Step 11:

[0934] The terminal provides the user with an interface that allows them to visually check the furniture and layout plan. The input data is the furniture list and layout plan sent from the server, and the output is a 3D viewer or simulation screen. This allows the user to intuitively check the proposal.

[0935] Step 12:

[0936] The user uses the provided visual interface to review the proposed furniture and layout and provide feedback as needed. The input data are the user's opinions and suggestions for improvement, and the output is feedback information. For example, the user can input a specific request such as "I'd like to move the chair a little further to the left."

[0937] Step 13:

[0938] The terminal records the feedback from the user and sends it to the server. The input data is the feedback information, and the output is an HTTP POST request to the server.

[0939] Step 14:

[0940] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. The input data is the feedback information, and the output is the modified furniture placement plan.

[0941] Step 15:

[0942] The server regenerates the modified plan and sends it to the terminal. The input data is the modified furniture layout plan, and the output is the data format sent to the terminal.

[0943] Step 16:

[0944] The device then presents the newly revised plan to the user and again accepts feedback. The input data is the revised furniture layout plan, and the output is an updated 3D view or simulation screen. By repeating this process, the user is provided with an optimal working environment.

[0945] (Application example 1)

[0946] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0947] Currently, food delivery stores lack concrete measures to create an efficient working environment, and furniture layout and traffic flow are not optimized with consideration for staff health. This can result in a decline in work efficiency and an increased risk to staff health. Furthermore, there is no system in place to incorporate feedback and make continuous improvements, making it difficult to optimize the working environment.

[0948] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0949] In this invention, the server includes a means for inputting three-dimensional measurement data of the human body, a means for inputting floor plans, work environment information, light source positions, and work flow information, a means for calculating an optimal work environment list and its layout based on ergonomics based on the input data, a means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and a means for receiving feedback from the user and recalculating the work environment list and layout. This makes it possible to provide an efficient and healthy work environment in food delivery stores. Furthermore, by continuously reflecting feedback, the work environment can be continuously optimized.

[0950] "Human body three-dimensional measurement data" refers to detailed dimensional data such as the user's height, shoulder width, and weight, and refers to three-dimensional information about the user's body shape and posture.

[0951] A floor plan is a drawing that shows the shape, dimensions, window and door locations of a room or store.

[0952] "Work environment information" refers to detailed data regarding the layout of equipment within the work area, the location of the warehouse, and the work content.

[0953] "Light source position" refers to information about the location of a light source, such as natural light or artificial light.

[0954] "Work flow information" refers to information regarding efficient routes for people and things to move within a work area.

[0955] "Ergonomics" refers to the scientific knowledge and methods for designing work environments and products that take into account the physical and psychological characteristics of people.

[0956] The "work environment list" refers to a list of optimal furniture and equipment that takes into consideration work efficiency and health.

[0957] A "visually verifiable interface" refers to a user interface that provides a 3D view or simulation screen so that users can intuitively understand the calculation results.

[0958] "User feedback" refers to information that users input regarding their opinions and suggestions for improvement regarding the layout plan and furniture list provided.

[0959] "Recalculation" refers to recalculating the optimal work environment list and its layout based on feedback from the user.

[0960] To put this invention into practice, it is first necessary to build a system for inputting three-dimensional measurement data of the human body, work environment information, light source position, and work flow information. Below, we will explain the program processing of this system and provide a detailed explanation of the hardware and software used.

[0961] Users use their smartphones or PCs to input their three-dimensional body measurement data. This data includes detailed measurements such as height, shoulder width, and weight. They also upload floor plans to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter details about work flow and the work environment. Once this data is entered, the device verifies it in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server.

[0962] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information. This is done using programming languages ​​such as Python and APIs such as Flask.

[0963] The server sends the calculated results to the device, which then provides a visual interface for the user. The user can intuitively understand the proposed furniture and layout using a 3D view or simulation screen. This interface also makes it easier for the user to provide feedback on the proposed content.

[0964] Feedback from the user is recorded by the device and sent back to the server. The server analyzes the user's feedback and recalculates the work environment list and layout plan as necessary. The server then sends the revised plan back to the device, where the user can review the newly revised plan. By repeating this process, the optimal work environment can be provided to the user.

[0965] Specific examples

[0966] For example, when a food delivery store manager uses this system, they first input three-dimensional measurement data such as the height and shoulder width of their cooking and delivery staff. Next, they upload a floor plan of the store and input the layout of the kitchen and warehouse, as well as the position of the light source. They then provide information on work flow and details of the required work environment.

[0967] The server calculates a healthy and efficient work environment based on each staff member's body data and store layout information. For example, it optimizes counter height, shelf placement, and traffic flow, and makes suggestions on a visual interface. Managers can provide feedback on these suggestions and request recalculations to create the ideal work environment.

[0968] Example prompt sentence:

[0969] "This system proposes optimal furniture layouts that take user health into consideration. The system proposes optimal work environments based on the user's 3D body measurement data, store floor plans, and equipment layout. For example, the system considers an arrangement that would be comfortable for a staff member with a height of 170 cm and shoulder width of 45 cm, and includes the shape of the room, the position of the light source, and the location of the warehouse as input data."

[0970] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0971] Step 1:

[0972] Users use their smartphones or PCs to input their own three-dimensional body measurement data. Specifically, detailed dimensional data such as height, shoulder width, and weight are entered. They also upload a floor plan to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter information about work flow and the work environment. Once all the information has been entered, it is sent to the server.

[0973] Input: 3D body measurement data, floor plan, detailed information (windows, doors, light source positions, etc.), work flow information, work environment information

[0974] Output: All input data sent to the server

[0975] Step 2:

[0976] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information.

[0977] Input: All input data sent to the server

[0978] Output: 3D model of the human body, analysis results (area where furniture can be placed, traffic flow, lighting simulation)

[0979] Step 3:

[0980] The server sends the calculated results to the terminal, which then provides a visual interface for the user, allowing them to intuitively understand and check the proposed furniture and layout using a 3D view or simulation screen.

[0981] Input: Analysis results (3D model of the human body, area where furniture can be placed, traffic flow, lighting simulation)

[0982] Output: Visual interface presented to the user (3D view, simulation screen)

[0983] Step 4:

[0984] The user can check the proposed content through a visual interface and provide necessary feedback, such as requests for changes to furniture positions or work flow. This feedback is sent to the server via the terminal.

[0985] Input: User feedback (changing furniture position, correcting traffic flow, etc.)

[0986] Output: Feedback sent to the server

[0987] Step 5:

[0988] The server analyzes the user's feedback, recalculates the work environment list and layout plan as necessary, and then sends the revised plan back to the terminal, where the user can view the newly revised plan.

[0989] Input: Feedback sent to the server

[0990] Output: Recalculated workspace list and layout plan

[0991] Step 6:

[0992] The device presents the recalculated plan to the user and prompts them to confirm the newly revised plan. This process is repeated until the user is satisfied, providing an optimal working environment.

[0993] Input: Recalculated workspace list and layout plan

[0994] Output: Optimal work environment plan presented to the user (for final confirmation)

[0995] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0996] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics based on 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. This system also recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. Below, the program processing of this system is explained in natural language and in detail with concrete examples.

[0997] Program Overview

[0998] 1. Data collection steps

[0999] First, the user inputs their own 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user using a measuring device in advance, or automatically acquired using a dedicated 3D scanning device.

[1000] The user then uploads a floor plan to the application, which includes details such as room shape, dimensions, window and light source locations, and door locations. After uploading, the user can review this information using the application's interface and make any necessary corrections.

[1001] The user also inputs their preferences and special requests (e.g., specific furniture styles, color coordination, special function requests), and once input is complete, this data is sent to the server.

[1002] 2. Data analysis steps

[1003] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[1004] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[1005] The server then generates an optimal furniture list and layout plan based on the analysis results, using ergonomic algorithms to consider the dimensions, shapes, and placement of furniture that best suit the user.

[1006] 3. Emotion Engine Steps

[1007] The server recognizes the user's emotional state using an emotion engine. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer emotions in real time. This emotion data is reflected in the analysis results, and a furniture list and arrangement optimal for the user's current emotional state are created.

[1008] The server learns the user's past emotional data and makes furniture suggestions taking into account their long-term emotional trends, thereby providing a comfortable environment for the user to live in for a long time.

[1009] 4. Furniture and layout proposal steps

[1010] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends this in data format to the terminal.

[1011] The terminal provides users with an interface that allows them to visually check the furniture and layout plan. Users can intuitively understand and check the proposal using 3D views, simulation screens, etc.

[1012] 5. User Feedback Steps

[1013] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[1014] The terminal records the feedback from the user and sends it to the server.

[1015] The server analyzes the user's feedback and performs recalculations to modify the furniture list and layout plan as needed.

[1016] Specific examples

[1017] Case study: System usage example of a freelancer who works long hours at a desk at home

[1018] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1019] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[1020] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1021] 4. The terminal sends all the information entered to the server.

[1022] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[1023] 6. The server uses an emotion engine to recognize the user's emotional state and makes suggestions that best fit the current emotional state.

[1024] 7. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[1025] 8. The user reviews the proposed furniture and layout and provides feedback, for example, suggesting that the chair be moved slightly to the left.

[1026] 9. The device sends feedback to the server, which recalculates and generates a revised proposal.

[1027] 10. The server sends the revised plan to the device, which presents it to the user again. The cycle repeats if the user checks again and provides feedback.

[1028] This system takes maximum consideration of the user's health and, by combining it with an emotion engine, can provide an optimal working environment that also takes into account the user's emotional state, thus creating an environment where users can work comfortably even during long hours of desk work.

[1029] The processing flow will be explained below.

[1030] Step 1:

[1031] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, hip width, etc.). This data can be manually input by the user using a measuring device or automatically acquired using a dedicated 3D scanning device.

[1032] Step 2:

[1033] Users upload floor plans to the application, which include details such as room dimensions, shape, window and light source locations, and door locations. After uploading, users can review this information and make any necessary corrections using the application's interface.

[1034] Step 3:

[1035] Users input their preferences and special requests (e.g., specific furniture styles and colors, special feature requests, etc.) Once input is complete, all data is sent to the server.

[1036] Step 4:

[1037] The terminal validates all data entered by the user in real time, checking that all required fields have been entered, notifying the user if any information is missing and prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[1038] Step 5:

[1039] The server then generates a 3D model of the user's body based on the received data, using an algorithm that analyzes the dimensions of each part of the body in three dimensions and creates an accurate model based on the user's posture and body shape.

[1040] Step 6:

[1041] The server analyzes furniture placement areas and user movement lines based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user movement lines. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[1042] Step 7:

[1043] The server takes into account the user's tastes and special requests and generates a list of suitable furniture options, taking into account the ergonomic dimensions, shapes, and placement of the furniture.

[1044] Step 8:

[1045] The server uses an emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer their current emotional state. This information is reflected in furniture and layout suggestions.

[1046] Step 9:

[1047] The server learns past emotional data and makes furniture suggestions taking into account the user's long-term emotional trends, thereby providing a comfortable environment for the user over the long term.

[1048] Step 10:

[1049] The server generates an optimal furniture list and layout plan based on the analysis results and the emotion engine results, and the generated list and plan are sent to the terminal in data format.

[1050] Step 11:

[1051] The terminal provides an interface that allows users to visually check the furniture and layout plan, and users can intuitively understand and check the proposal using 3D views and simulation screens.

[1052] Step 12:

[1053] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[1054] Step 13:

[1055] The terminal records the feedback from the user and sends it to the server.

[1056] Step 14:

[1057] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[1058] Step 15:

[1059] The server regenerates the revised plan and sends it to the device, which presents the new revised plan to the user for confirmation again. If further feedback is required, the cycle repeats.

[1060] This system provides an optimal working environment that takes into account the user's health and emotional state, making it possible to work comfortably even during long hours of desk work.

[1061] Example 2

[1062] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1063] Conventional furniture layout systems could provide optimal furniture layouts based on the user's body data and room layout information, but because they did not take the user's emotional state into account, it was difficult to fully guarantee long-term comfort and user satisfaction. Furthermore, when recalculating based on feedback, optimization was not possible in combination with past emotional data, making it difficult to provide the optimal environment the user desired.

[1064] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for recognizing the user's emotional state and analyzing the emotional data, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data and emotional data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, and means for learning from the feedback and past emotional data and improving the proposal. This makes it possible to provide an optimal furniture layout and its proposal taking into account the user's emotional state.

[1065] "Human body 3D measurement data" refers to data indicating the user's physical dimensions such as height, weight, shoulder width, and waist width, and is data obtained using a dedicated 3D scanning device or manual input.

[1066] A "floor plan" is a drawing that shows the shape, dimensions, window positions, light source positions, door positions, etc. of a room, and is data that a user uploads to the application.

[1067] "Furniture arrangement information" is data that indicates information such as the type, position, dimensions, and shape of furniture arranged in a room.

[1068] "Light source position" is data that indicates the specific position of a light source (window, lighting fixture, etc.) in a room.

[1069] "Hobby information" is data that indicates the user's furniture preferences, style, color coordination, special requests, and the like.

[1070] "Emotional state" is data indicating the emotional state of the user that is estimated by analyzing the user's facial expression, tone of voice, body movements, and the like.

[1071] "Emotion data" is data that expresses emotional states using numerical values ​​and categories, and is data that is analyzed and collected by the emotion engine.

[1072] The "ergonomically optimal furniture list" is a list showing the type, dimensions, and shape of furniture that is considered optimal from an ergonomic perspective based on the user's body data, room floor plan, furniture placement information, light source position, and hobby information.

[1073] A "visual interface" refers to an interface that allows users to visually check the furniture layout plan through a 3D view or simulation screen.

[1074] "Feedback" refers to information that a user inputs into the application about their opinions and requests regarding the proposed furniture and layout, and sends it to the server.

[1075] The present invention is a system that calculates an optimal furniture list and its layout based on the user's ergonomics based on the user's 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. Furthermore, the system recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. The detailed implementation method of this system is described below.

[1076] Data collection

[1077] First, a user launches the application and inputs their anthropometric data (e.g., height 170 cm, weight 65 kg, shoulder width 45 cm). This data can be entered manually or automatically obtained using a dedicated 3D scanning device. Next, the user uploads a floor plan of the room to the application. The floor plan includes details such as the room's shape, dimensions, window locations, light source locations, and door locations. In addition, the user can input their preferences and special requests (e.g., specific furniture style and color coordination).

[1078] Data analysis

[1079] The server generates a three-dimensional model of the user's body based on the received stereoscopic body measurement data. This process uses 3D modeling software (e.g., Blender) to analyze the dimensions of each part of the body in three dimensions and create an accurate model. The server then analyzes the floor plan data to calculate furniture placement areas and traffic flow. It also simulates natural and artificial light based on the light source position. For example, it uses emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API."

[1080] Emotion analysis

[1081] The server uses an emotion engine to recognize the user's emotional state. This allows it to analyze the user's facial expressions, tone of voice, and physical movements to infer emotions in real time. This emotional data is reflected in the analysis results, creating a furniture list and placement that is optimal for the user's current emotional state. The server also learns from past emotional data and makes furniture suggestions that take long-term emotional trends into account.

[1082] Furniture and layout suggestions

[1083] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends it to the device. The device then provides an interface that allows users to visually check the furniture and layout plan. For example, users can use game engines such as Unity or Unreal Engine to understand the proposals through 3D views and simulation screens.

[1084] User Feedback

[1085] Finally, the user reviews the proposed furniture and layout and provides feedback. For example, they might enter a specific suggestion such as, "I'd like to move the chair a little to the left." The device records the feedback and sends it to the server. The server analyzes the feedback, recalculates as necessary, and generates a new furniture list and layout plan. This cycle is repeated until the user is satisfied.

[1086] Specific examples

[1087] This shows how a freelancer working from home uses this system.

[1088] 1. The user starts the application and enters data such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1089] 2. The user uploads a floor plan and inputs the shape of the room, the position of the light source, the location of the door, etc.

[1090] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1091] 4. The server analyzes the data and generates a 3D human body model.

[1092] 5. The server uses an emotion engine to analyze the user's emotional state.

[1093] 6. The server generates an optimal furniture list and layout plan and sends it to the terminal.

[1094] 7. The device presents the furniture and layout plan to the user in a 3D view.

[1095] 8. The user reviews the proposal and provides feedback.

[1096] 9. The server recalculates based on the feedback and creates a new plan.

[1097] This system allows users to create a comfortable working environment.

[1098] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1099] Step 1:

[1100] The user launches the application and inputs their body stereoscopic measurement data. For example, height 170 cm, weight 65 kg, shoulder width 45 cm, etc., can be entered manually or automatically using a stereoscopic scanning device. This operation inputs the user's physical dimensions into the application. The input includes the body stereoscopic measurement data. The output is the input data sent to the server.

[1101] Step 2:

[1102] The user uploads a floor plan to the application. The floor plan includes detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. After uploading, the user can review this information and modify it as necessary. For example, the user can fine-tune the room dimensions or light source positions using the application interface. The input includes the floor plan. The output is the modified floor plan data sent to the server.

[1103] Step 3:

[1104] Users input their preferences and special requests (e.g., preferences for a particular furniture style or color) into the application, which then collects the user's preference data. The input includes the preferences and special requests. The output is sent to the server.

[1105] Step 4:

[1106] The server generates a 3D human body model of the user based on the received 3D human body measurement data, floor plan data, and hobby information. In this process, 3D modeling software (e.g., Blender) is used to analyze the data in three dimensions and create a 3D human body model. The inputs include the 3D human body measurement data, floor plan data, and hobby information. The output is the generated 3D human body model and the analysis results.

[1107] Step 5:

[1108] The server analyzes floor plan data and calculates furniture placement areas and traffic flow. At this stage, it determines where furniture can be placed and what the optimal traffic flow is. It also simulates natural and artificial light based on the light source position, simulating the brightness of the entire room. The input includes floor plan data and light source position data. The output is the placement area analysis results and light simulation results.

[1109] Step 6:

[1110] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements in real time to generate emotional data. Here, emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API" are used. The input includes real-time user information (facial expressions, tone of voice, and body movements). The output is the analyzed emotional data.

[1111] Step 7:

[1112] The server generates an optimal ergonomic furniture list and layout plan based on the input data and emotion data. This process uses an algorithm to calculate the optimal furniture dimensions, shape, and layout. Inputs include a 3D human body model, floor plan analysis results, and emotion data. The output is an optimal furniture list and layout plan.

[1113] Step 8:

[1114] The server sends the generated furniture list and layout plan to the terminal. The terminal provides an interface that the user can visually check, and displays the proposed content in a 3D view or simulation screen. For example, a game engine (e.g., Unity or Unreal Engine) is used to display a simulation of the furniture layout in real time. The input includes the furniture list and layout plan sent from the server. The output is the interface that is visually presented to the user.

[1115] Step 9:

[1116] The user reviews the proposed furniture and layout and provides feedback. Specifically, the user inputs their feedback, such as rearranging the furniture or adjusting the layout, into the application. The input includes the user's feedback. The output is sent to the server.

[1117] Step 10:

[1118] The server analyzes the received feedback and recalculates the furniture list and layout plan as needed, taking into account past emotional data to update the proposals. The inputs include the user's feedback and past emotional data. The output is a revised furniture list and layout plan.

[1119] Step 11:

[1120] The server sends the revised plan to the terminal and presents it again to the user. The terminal updates the interface for further user review. The input includes the revised plan. The output is an updated visual interface.

[1121] By repeating the above processing steps, an optimal furniture arrangement that satisfies the user is provided.

[1122] (Application example 2)

[1123] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1124] Conventional furniture layout suggestion systems do not take into account the user's detailed 3D body measurement data or emotional state, making it difficult to select and arrange optimal furniture. Furthermore, they lacked an interface for visually confirming the proposed content, making it difficult for users to intuitively understand the content. Furthermore, there was no means in place to provide optimal furniture suggestions to users on the spot in physical stores or commercial facilities. There was a need to solve these issues and improve user comfort and ease of use.

[1125] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1126] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, means for recognizing the user's emotional state and using an emotion engine to make optimal furniture suggestions, means for visualizing the consideration results through a three-dimensional view or simulation screen, and means for making optimal furniture suggestions to the user in a store or commercial facility where there is a physical presence. This enables optimal furniture suggestions that reflect the user's detailed human body data and emotional state, and not only can suggestions be made through an intuitively easy-to-understand visual interface, but also enables instantly customized furniture suggestions in physical stores and commercial facilities.

[1127] "Three-dimensional measurement data of the human body" refers to data obtained in three dimensions that indicates specific human body dimensions such as the user's height, weight, shoulder width, and waist width.

[1128] A "floor plan" is a drawing that includes detailed information such as the shape and dimensions of a room, the location of windows, the location of light sources, and the location of doors.

[1129] "Furniture arrangement information" is data relating to where in a room each piece of furniture is arranged.

[1130] "Light source position" is information indicating the position of a source of natural light or artificial light in a room.

[1131] "Hobby information" is data about the user's preferences, such as preferred furniture styles, color coordination, and special functional requirements.

[1132] "Ergonomics" is the study of creating comfortable and efficient designs that take into account human physical characteristics and movements.

[1133] A "furniture list" is a list of the most suitable furniture suggested to the user.

[1134] The "emotion engine" is a system that analyzes and infers the user's emotional state from facial expressions, tone of voice, physical movements, etc.

[1135] "Interface" refers to the screen and input devices that users use to operate the system.

[1136] "Feedback" refers to the act of communicating to the system the user's opinions and requests for corrections regarding the proposed content.

[1137] A "3D view" is a display format that visualizes proposed furniture placement and room layout in three dimensions.

[1138] A "simulation screen" is a display means for virtually reproducing how a proposed furniture arrangement will function.

[1139] A "physical commercial facility" refers to a store or facility that actually exists as a building and that customers can visit.

[1140] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics and presents it to the user. This system operates based on three-dimensional human body measurement data, floor plans, furniture layout information, light source position, and hobby information. It also uses an emotion engine to recognize the user's emotional state and make suggestions based on that emotional state. This system provides furniture suggestions optimized for the user's characteristics and emotions in brick-and-mortar stores and commercial facilities.

[1141] The following hardware and software are used to process the data. First, a body scanning device (BodyScanner) is required to collect stereoscopic measurement data of the human body. Dedicated software (LayoutAnalyzer) is used to analyze floor plans and furniture layout information. An emotion recognition engine (EmotionRecognitionEngine) is used to recognize emotional states. A furniture recommendation engine (FurnitureRecommender) is required to recommend furniture, and this incorporates ergonomic algorithms. Finally, software (VisualizationInterface) is used to provide a 3D view display and simulation screen as an interface to visually display suggestions to the user.

[1142] The server operates by coordinating the various software modules described above. Specifically, the server collects and analyzes three-dimensional measurement data of the human body and calculates the optimal furniture list and its placement based on the floor plan and furniture layout information. It also uses an emotion engine to recognize the user's emotional state and suggests furniture that best suits that emotional state. The calculation results are then sent to the device, which then visually presents the suggestions to the user through a 3D view or simulation screen.

[1143] Consider the following scenario: In a physical store, a user uses a body scanning device to collect stereoscopic measurement data of their body. Then, they upload a floor plan and enter their hobbies and special requests. All of this data is sent to a server, which calculates the optimal furniture list and its placement. An emotion engine analyzes the user's emotional state and generates optimal furniture suggestions. The calculation results are sent to the device, which visually presents the suggestions to the user through a 3D view or simulation screen.

[1144] For example, you can make suggestions using prompts like the following:

[1145] "Please suggest a furniture list and layout to optimize the interior of a living room and bedroom. The user's anthropometric data are height 170cm, weight 65kg, and shoulder width 45cm. The floor plan is as follows:

[1146] Living room: Light source is located in the center of the ceiling, window is on the south side, door is on the north side

[1147] Bedroom: Light source is on the west side of the ceiling, window is on the east side, door is on the south side

[1148] The user's preferred furniture style is modern, their preferred color is blue and white, and their emotional state is relaxed.

[1149] Based on this information, please design an algorithm that will suggest the optimal furniture list and its placement."

[1150] In this way, the present invention can provide optimal furniture suggestions that take into account the user's physical characteristics and emotional state, improving the user experience in physical stores and commercial facilities.

[1151] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1152] Step 1:

[1153] A user uses a body scanning device to collect stereoscopic data of their body. The device acquires dimensional data such as height, weight, shoulder width, and hip width, and sends it to a cloud server. The input is the user's body data, and the output is analyzable stereoscopic data.

[1154] Step 2:

[1155] Users upload floor plans to the application. They also input information about furniture layout, light source positions, and door and window locations. This data is sent to a cloud server via the device. The input is the floor plan and related information, and the output is spatial information data for analysis.

[1156] Step 3:

[1157] The server analyzes the transmitted stereoscopic body measurement data and floor plan data. It uses ergonomic algorithms to calculate the optimal furniture dimensions, shape, and placement. The input is the body and floor plan data, and the output is the optimal furniture list and placement plan.

[1158] Step 4:

[1159] The server uses an emotion recognition engine to analyze the user's emotional state. It uses a camera and microphone to detect facial expressions, tone of voice, and body movements to determine emotions. The input is real-time user facial and voice data, and the output is analyzed emotional state data.

[1160] Step 5:

[1161] Based on the results of the emotion engine, the server recalculates optimal furniture suggestions, adjusting the suggestions to suit the user's current emotional state. The input is emotional state data, and the output is an optimal furniture list and its placement that takes emotions into account.

[1162] Step 6:

[1163] The server sends the calculation results to the terminal, which visually displays the proposal to the user through a 3D view or simulation screen. The input is the calculated furniture list and placement data, and the output is the proposal displayed on the visual interface.

[1164] Step 7:

[1165] The user checks the visually displayed furniture arrangement proposal and inputs their feedback into the device, providing specific suggestions for revisions, such as the desired furniture position or height. The input is the user's feedback, and the output is the revision proposal data.

[1166] Step 8:

[1167] The device sends the user's feedback to the server, which then recalculates the optimal furniture list and layout based on the feedback and generates a revised plan. The input is the user's feedback, and the output is the revised layout plan.

[1168] Step 9:

[1169] The server sends the revised furniture list and layout plan to the terminal, which then displays it again to the user. This cycle is repeated until the user is satisfied. The input is the revised data, and the output is the final proposal to be confirmed.

[1170] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1171] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1172] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1173] [Fourth embodiment]

[1174] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1175] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1176] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1177] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1178] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1179] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1180] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1181] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1182] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1183] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1184] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1185] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1186] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1187] The system of the present invention proposes optimal furniture and its layout taking into consideration the user's health. Below, the program processing of this system will be explained in natural language and in detail with concrete examples.

[1188] Program Overview

[1189] 1. Data collection steps

[1190] First, the user inputs the three-dimensional measurement data of his or her own body, specifically, detailed dimensional data such as height, weight, shoulder width, and waist width.

[1191] The user then uploads the floor plan to the application and enters details such as the room shape, dimensions, window locations, light source locations, and door locations.

[1192] The user also inputs their tastes and preferences (eg, particular furniture styles, color preferences, special feature requests, etc.).

[1193] The terminal validates all entered data in real time, prompts the user for any missing information, and once all data is collected, sends it to the server.

[1194] 2. Data analysis steps

[1195] The server then uses the received data to generate a 3D model of the human body, which is constructed based on the user's posture and body shape.

[1196] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow.

[1197] The server simulates the effects of natural and artificial light in the room based on the light source position, and then considers the placement of furniture to achieve the appropriate brightness balance.

[1198] The server considers the user's tastes and preferences, lists suitable furniture candidates, and calculates the optimal dimensions, shape, and placement of the furniture based on the stereoscopic measurement data and ergonomics of the human body.

[1199] 3. Furniture and layout proposal steps

[1200] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal.

[1201] The terminal provides users with an interface that allows them to visually check furniture and layout plans, and through 3D views and simulation screens, users can intuitively understand the proposals.

[1202] The user uses the provided visual interface to review the proposed furniture and layout and, if desired, provide feedback on the proposal.

[1203] 4. User Feedback Step

[1204] The user provides feedback and suggestions for improvements to the proposed furniture arrangement (for example, moving the chair a little further to the left).

[1205] The terminal records the feedback from the user and sends it to the server.

[1206] The server analyzes the user feedback and re-runs the algorithms to modify the furniture list and layout plan as needed.

[1207] The server regenerates the revised plan and sends it to the terminal.

[1208] The terminal presents the newly revised plan to the user and again accepts feedback.

[1209] Specific examples

[1210] Case study: System usage example of a freelancer who works long hours at a desk at home

[1211] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1212] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[1213] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1214] 4. The terminal sends all the information entered to the server.

[1215] 5. The server generates a 3D model of the human body based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[1216] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[1217] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[1218] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[1219] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[1220] By repeating this process, users can create the optimal working environment for themselves. This system is characterized by its maximum consideration of health and provides an environment that allows users to work comfortably even during long hours of desk work.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user after having previously acquired it using a measuring device, or it can be automatically acquired using a dedicated 3D scanning device. After completing the input, the data is sent to the server.

[1224] Step 2:

[1225] The user uploads a floor plan to the application, which includes detailed information such as room dimensions, shape, window and light source positions, and door positions. After uploading, the user can review this information using the application interface and make any necessary corrections. Once the corrections are complete, the data is sent to the server.

[1226] Step 3:

[1227] Users input their preferences and special requests, such as a particular furniture style (e.g., modern or minimalist), preferred color coordination, and special feature requirements (e.g., a desk with standing capabilities or an ergonomic chair). Once completed, all data is sent to the server.

[1228] Step 4:

[1229] The device verifies all data entered by the user in real time, checking that all required fields have been entered, and notifying the user if any information is missing, prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[1230] Step 5:

[1231] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[1232] Step 6:

[1233] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[1234] Step 7:

[1235] The server analyzes the user's input preferences and special requests and generates a list of suitable furniture options, generated using ergonomic algorithms that take into account the dimensions, shape, and placement of the furniture that best suits the user.

[1236] Step 8:

[1237] The server generates an optimal furniture list and layout plan based on the analysis results, and the generated list and plan are sent to the terminal in data format.

[1238] Step 9:

[1239] The terminal provides an interface that allows users to visually check the proposed contents. Users can intuitively understand and check the proposed furniture arrangement using 3D views and simulation screens.

[1240] Step 10:

[1241] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[1242] Step 11:

[1243] The terminal records the feedback from the user and sends it to the server.

[1244] Step 12:

[1245] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[1246] Step 13:

[1247] The server regenerates a revised plan and sends it to the terminal, which then presents the revised plan to the user, who then confirms it again. If further feedback is required, the cycle repeats.

[1248] Example 1

[1249] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1250] In recent years, with the increase in telecommuting and remote work, the importance of a comfortable working environment at home has increased. However, when it comes to furniture placement and selection, it is difficult to receive suggestions that are optimized for each individual's body shape and preferences. Inappropriate furniture placement and selection can be harmful to health, so a system to solve this problem is needed.

[1251] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1252] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for generating a three-dimensional model of the human body based on the input data, means for analyzing the floor plan data to determine areas where furniture can be placed and efficient traffic lines, means for simulating the effects of natural light and artificial light in the room based on the light source positions, means for calculating an optimal furniture list and layout based on the three-dimensional measurement data of the human body and ergonomics, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and means for receiving feedback from the user and recalculating the furniture list and layout. This makes it possible to suggest optimal furniture selection and layout that takes the user's health into consideration in real time, thereby realizing a comfortable working environment.

[1253] "Human body three-dimensional measurement data" refers to individual dimensional data such as height, weight, shoulder width, and waist width, and is basic information for generating a three-dimensional model.

[1254] A "floor plan" is a layout diagram of an entire room that includes information such as the shape, dimensions, window, light source position, and door position of the room.

[1255] "Light source position" is position information that indicates where natural light or artificial light in a room is emitted from.

[1256] "Hobby information" is information that indicates a user's personal preferences, such as a particular furniture style, color preferences, or special function requirements.

[1257] A "three-dimensional model" is a three-dimensional model generated by computer software based on inputted dimensional data of the human body.

[1258] "Traffic lines" refer to the routes people take within a room, and are information used in layout planning to enable efficient movement.

[1259] "Simulation" refers to reproducing the situation and effects on a computer based on real-world conditions such as the position of a light source.

[1260] The "optimal furniture list" is a list of furniture selected based on the user's dimensional data, floor plan, hobby information, and ergonomics.

[1261] An "interface" refers to the screens and operating methods that allow a user to interact with a system, providing information in a visually identifiable format.

[1262] "Feedback" refers to input information such as opinions and improvements provided by the user regarding the proposed furniture arrangement plan.

[1263] The system of the present invention is a system that proposes optimal furniture and its layout taking into consideration the health of the user. An embodiment of this system will be specifically described below.

[1264] Program Overview

[1265] Data Collection Steps

[1266] First, a user launches the application and inputs their own anthropometric data, including detailed measurements such as height, weight, shoulder width, and hip width. Next, the user uploads a floor plan to the application and inputs detailed information such as the room's shape, dimensions, window position, light source position, and door position. Additionally, the user inputs their personal tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.).

[1267] The terminal validates all of this input data in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server. Specifically, the data is sent using an HTTP POST request.

[1268] Data analysis steps

[1269] The server generates a 3D model of the human body based on the received data. This model is constructed based on the user's posture and body shape. Specifically, it uses 3D modeling software (e.g., Blender or Maya).

[1270] The server then analyzes the floor plan data to determine areas where furniture can be placed and efficient traffic flow. Image analysis software is used to analyze the floor plan images.

[1271] The server also simulates the effects of natural and artificial light in the room based on the light source position. It uses a light and shadow calculation algorithm to simulate the brightness of each area of ​​the room. Based on this information, the server takes into account the user's tastes and preferences and lists suitable furniture candidates. Furthermore, it calculates the optimal furniture dimensions, shape, and placement based on the stereoscopic measurement data of the human body and ergonomics.

[1272] Furniture and layout proposal steps

[1273] The server generates an optimal furniture list and layout plan based on the analysis results and sends this to the device in a data format, typically JSON.

[1274] The terminal provides users with an interface that allows them to visually check the furniture and layout plans. Specifically, it displays a 3D viewer and a simulation screen, allowing users to intuitively check the proposals.

[1275] Users can use it to review the proposed furniture and layout and provide feedback if needed, such as entering specific requests like "I'd like the chair to be moved a little further to the left."

[1276] User Feedback Steps

[1277] The device records the feedback from the user and sends it to the server, again using an HTTP POST request to send the feedback data.

[1278] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. Once the recalculation is complete, a new layout plan is regenerated and sent to the device.

[1279] The device presents the newly revised plan to the user and again accepts feedback. By repeating this process, it is possible to provide the user with an optimal working environment.

[1280] Specific examples

[1281] Case study: System usage example of a freelancer who works long hours at a desk at home

[1282] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1283] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[1284] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1285] 4. The terminal sends all the information entered to the server.

[1286] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[1287] 6. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[1288] 7. The user reviews the proposed furniture and layout and provides feedback that they would like to move the chair slightly to the left.

[1289] 8. The device sends feedback to the server, which recalculates and generates a revised proposal.

[1290] 9. The server sends the revised plan to the terminal, which presents the newly revised plan to the user.

[1291] By repeating this process, the user can create the optimal working environment for themselves.

[1292] Example prompt statement

[1293] "I work at a desk for long periods of time at home, so I'd like a system that suggests optimal furniture layouts that take my health into consideration. I'm 170cm tall, weigh 65kg, and prefer modern-style furniture. I've entered my floor plan and detailed information, so please provide me with the optimal furniture list and layout plan."

[1294] This system is characterized by its maximum consideration of health and provides a comfortable environment even during long hours of desk work.

[1295] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1296] Step 1:

[1297] The user starts the application and inputs their own 3D body measurement data. The input includes detailed dimensional data such as height, weight, shoulder width, and hip width. Specifically, the user enters this information into the application's data input form, and the data is acquired as 3D body measurement data.

[1298] Step 2:

[1299] Users upload floor plans to the application and enter details such as room shape, dimensions, window locations, light source locations, and door locations. The input includes floor plan files in JPEG and PDF formats, which then imports the floor plan data into the system.

[1300] Step 3:

[1301] Users input their tastes and preferences (e.g., specific furniture styles, color preferences, special function requests, etc.). The input includes preference information such as "modern style" and "blue and white color scheme." This taste information is then incorporated into the system.

[1302] Step 4:

[1303] The device validates all entered data in real time and prompts the user to enter any missing information. Specifically, the device checks each field on the input form and displays a pop-up message to the user, such as "Weight is missing." Once all the data is collected, the device sends it to the server. An HTTP POST request is used for transmission.

[1304] Step 5:

[1305] The server generates a 3D model of the human body based on the received data. The input data is the stereoscopic measurement data of the human body, and the output is a 3D model. Specifically, a human body model is generated based on the input dimensional data using 3D modeling software (e.g., Blender or Maya).

[1306] Step 6:

[1307] The server analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. The input data is floor plan data, and the output is information on the areas where furniture can be placed and traffic flow. Specifically, the floor plan is analyzed using image analysis software, and furniture placement space and aisle width are calculated.

[1308] Step 7:

[1309] The server simulates the effects of natural and artificial light in a room based on the light source position. The input data is light source position information, and the output is brightness information for each area. Specifically, it uses a light and shadow calculation algorithm to calculate the brightness of the room based on the window and lighting positions.

[1310] Step 8:

[1311] The server considers the user's tastes and preferences and lists suitable furniture candidates. The input data is hobby information and ergonomic data, and the output is a list of optimal furniture. Specifically, it searches the database for modern-style furniture and generates a list of furniture that matches the user's tastes and room dimensions.

[1312] Step 9:

[1313] The server calculates the optimal furniture dimensions, shape, and layout based on the stereoscopic measurement data of the human body and ergonomics. The input data is a human body model and an ergonomics algorithm, and the output is an optimal furniture layout plan. Specifically, it calculates, for example, chair heights and desk positions and creates a layout plan.

[1314] Step 10:

[1315] The server generates an optimal furniture list and layout plan based on the analysis results and sends this in data format to the terminal. The input data is the optimal furniture placement plan, and the output is a furniture list and layout plan in data format. JSON format is generally used.

[1316] Step 11:

[1317] The terminal provides the user with an interface that allows them to visually check the furniture and layout plan. The input data is the furniture list and layout plan sent from the server, and the output is a 3D viewer or simulation screen. This allows the user to intuitively check the proposal.

[1318] Step 12:

[1319] The user uses the provided visual interface to review the proposed furniture and layout and provide feedback as needed. The input data are the user's opinions and suggestions for improvement, and the output is feedback information. For example, the user can input a specific request such as "I'd like to move the chair a little further to the left."

[1320] Step 13:

[1321] The terminal records the feedback from the user and sends it to the server. The input data is the feedback information, and the output is an HTTP POST request to the server.

[1322] Step 14:

[1323] The server analyzes the received feedback and re-runs the algorithm to modify the furniture list and layout plan as needed. The input data is the feedback information, and the output is the modified furniture placement plan.

[1324] Step 15:

[1325] The server regenerates the modified plan and sends it to the terminal. The input data is the modified furniture layout plan, and the output is the data format sent to the terminal.

[1326] Step 16:

[1327] The device then presents the newly revised plan to the user and again accepts feedback. The input data is the revised furniture layout plan, and the output is an updated 3D view or simulation screen. By repeating this process, the user is provided with an optimal working environment.

[1328] (Application example 1)

[1329] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1330] Currently, food delivery stores lack concrete measures to create an efficient working environment, and furniture layout and traffic flow are not optimized with consideration for staff health. This can result in a decline in work efficiency and an increased risk to staff health. Furthermore, there is no system in place to incorporate feedback and make continuous improvements, making it difficult to optimize the working environment.

[1331] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1332] In this invention, the server includes a means for inputting three-dimensional measurement data of the human body, a means for inputting floor plans, work environment information, light source positions, and work flow information, a means for calculating an optimal work environment list and its layout based on ergonomics based on the input data, a means for presenting the calculation results to the user and providing an interface that the user can visually confirm, and a means for receiving feedback from the user and recalculating the work environment list and layout. This makes it possible to provide an efficient and healthy work environment in food delivery stores. Furthermore, by continuously reflecting feedback, the work environment can be continuously optimized.

[1333] "Human body three-dimensional measurement data" refers to detailed dimensional data such as the user's height, shoulder width, and weight, and refers to three-dimensional information about the user's body shape and posture.

[1334] A floor plan is a drawing that shows the shape, dimensions, window and door locations of a room or store.

[1335] "Work environment information" refers to detailed data regarding the layout of equipment within the work area, the location of the warehouse, and the work content.

[1336] "Light source position" refers to information about the location of a light source, such as natural light or artificial light.

[1337] "Work flow information" refers to information regarding efficient routes for people and things to move within a work area.

[1338] "Ergonomics" refers to the scientific knowledge and methods for designing work environments and products that take into account the physical and psychological characteristics of people.

[1339] The "work environment list" refers to a list of optimal furniture and equipment that takes into consideration work efficiency and health.

[1340] A "visually verifiable interface" refers to a user interface that provides a 3D view or simulation screen so that users can intuitively understand the calculation results.

[1341] "User feedback" refers to information that users input regarding their opinions and suggestions for improvement regarding the layout plan and furniture list provided.

[1342] "Recalculation" refers to recalculating the optimal work environment list and its layout based on feedback from the user.

[1343] To put this invention into practice, it is first necessary to build a system for inputting three-dimensional measurement data of the human body, work environment information, light source position, and work flow information. Below, we will explain the program processing of this system and provide a detailed explanation of the hardware and software used.

[1344] Users use their smartphones or PCs to input their three-dimensional body measurement data. This data includes detailed measurements such as height, shoulder width, and weight. They also upload floor plans to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter details about work flow and the work environment. Once this data is entered, the device verifies it in real time and prompts the user to enter any missing information. Once all the data is collected, it is sent to the server.

[1345] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information. This is done using programming languages ​​such as Python and APIs such as Flask.

[1346] The server sends the calculated results to the device, which then provides a visual interface for the user. The user can intuitively understand the proposed furniture and layout using a 3D view or simulation screen. This interface also makes it easier for the user to provide feedback on the proposed content.

[1347] Feedback from the user is recorded by the device and sent back to the server. The server analyzes the user's feedback and recalculates the work environment list and layout plan as necessary. The server then sends the revised plan back to the device, where the user can review the newly revised plan. By repeating this process, the optimal work environment can be provided to the user.

[1348] Specific examples

[1349] For example, when a food delivery store manager uses this system, they first input three-dimensional measurement data such as the height and shoulder width of their cooking and delivery staff. Next, they upload a floor plan of the store and input the layout of the kitchen and warehouse, as well as the position of the light source. They then provide information on work flow and details of the required work environment.

[1350] The server calculates a healthy and efficient work environment based on each staff member's body data and store layout information. For example, it optimizes counter height, shelf placement, and traffic flow, and makes suggestions on a visual interface. Managers can provide feedback on these suggestions and request recalculations to create the ideal work environment.

[1351] Example prompt sentence:

[1352] "This system proposes optimal furniture layouts that take user health into consideration. The system proposes optimal work environments based on the user's 3D body measurement data, store floor plans, and equipment layout. For example, the system considers an arrangement that would be comfortable for a staff member with a height of 170 cm and shoulder width of 45 cm, and includes the shape of the room, the position of the light source, and the location of the warehouse as input data."

[1353] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1354] Step 1:

[1355] Users use their smartphones or PCs to input their own three-dimensional body measurement data. Specifically, detailed dimensional data such as height, shoulder width, and weight are entered. They also upload a floor plan to the application and enter detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. They also enter information about work flow and the work environment. Once all the information has been entered, it is sent to the server.

[1356] Input: 3D body measurement data, floor plan, detailed information (windows, doors, light source positions, etc.), work flow information, work environment information

[1357] Output: All input data sent to the server

[1358] Step 2:

[1359] The server generates a three-dimensional model of the user's body based on the received data. This model is constructed based on the user's posture and body shape. It also analyzes floor plan data to determine areas where furniture can be placed and efficient traffic flow. It also simulates the brightness of the work area based on the light source position and calculates the optimal work environment list and its layout, taking into account the user's work environment information.

[1360] Input: All input data sent to the server

[1361] Output: 3D model of the human body, analysis results (area where furniture can be placed, traffic flow, lighting simulation)

[1362] Step 3:

[1363] The server sends the calculated results to the terminal, which then provides a visual interface for the user, allowing them to intuitively understand and check the proposed furniture and layout using a 3D view or simulation screen.

[1364] Input: Analysis results (3D model of the human body, area where furniture can be placed, traffic flow, lighting simulation)

[1365] Output: Visual interface presented to the user (3D view, simulation screen)

[1366] Step 4:

[1367] The user can check the proposed content through a visual interface and provide necessary feedback, such as requests for changes to furniture positions or work flow. This feedback is sent to the server via the terminal.

[1368] Input: User feedback (changing furniture position, correcting traffic flow, etc.)

[1369] Output: Feedback sent to the server

[1370] Step 5:

[1371] The server analyzes the user's feedback, recalculates the work environment list and layout plan as necessary, and then sends the revised plan back to the terminal, where the user can view the newly revised plan.

[1372] Input: Feedback sent to the server

[1373] Output: Recalculated workspace list and layout plan

[1374] Step 6:

[1375] The device presents the recalculated plan to the user and prompts them to confirm the newly revised plan. This process is repeated until the user is satisfied, providing an optimal working environment.

[1376] Input: Recalculated workspace list and layout plan

[1377] Output: Optimal work environment plan presented to the user (for final confirmation)

[1378] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1379] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics based on 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. This system also recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. Below, the program processing of this system is explained in natural language and in detail with concrete examples.

[1380] Program Overview

[1381] 1. Data collection steps

[1382] First, the user inputs their own 3D body measurement data (height, weight, shoulder width, waist width, etc.). This data can be manually input by the user using a measuring device in advance, or automatically acquired using a dedicated 3D scanning device.

[1383] The user then uploads a floor plan to the application, which includes details such as room shape, dimensions, window and light source locations, and door locations. After uploading, the user can review this information using the application's interface and make any necessary corrections.

[1384] The user also inputs their preferences and special requests (e.g., specific furniture styles, color coordination, special function requests), and once input is complete, this data is sent to the server.

[1385] 2. Data analysis steps

[1386] The server then generates a 3D model of the user's body based on the received data. This model is then used in subsequent analysis steps, using algorithms that analyze the dimensions of each part of the body in 3D and create an accurate model based on the user's posture and shape.

[1387] The server analyzes furniture placement areas and traffic flow based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user traffic flow. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[1388] The server then generates an optimal furniture list and layout plan based on the analysis results, using ergonomic algorithms to consider the dimensions, shapes, and placement of furniture that best suit the user.

[1389] 3. Emotion Engine Steps

[1390] The server recognizes the user's emotional state using an emotion engine. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer emotions in real time. This emotion data is reflected in the analysis results, and a furniture list and arrangement optimal for the user's current emotional state are created.

[1391] The server learns the user's past emotional data and makes furniture suggestions taking into account their long-term emotional trends, thereby providing a comfortable environment for the user to live in for a long time.

[1392] 4. Furniture and layout proposal steps

[1393] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends this in data format to the terminal.

[1394] The terminal provides users with an interface that allows them to visually check the furniture and layout plan. Users can intuitively understand and check the proposal using 3D views, simulation screens, etc.

[1395] 5. User Feedback Steps

[1396] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[1397] The terminal records the feedback from the user and sends it to the server.

[1398] The server analyzes the user's feedback and performs recalculations to modify the furniture list and layout plan as needed.

[1399] Specific examples

[1400] Case study: System usage example of a freelancer who works long hours at a desk at home

[1401] 1. The user starts the application and inputs their own body measurement data, such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1402] 2. The user uploads a floor plan and enters details such as the shape of the room, the location of the light source, and the location of the door.

[1403] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1404] 4. The terminal sends all the information entered to the server.

[1405] 5. The server generates a three-dimensional human body model based on the received data and uses ergonomic algorithms to calculate the optimal furniture list and layout plan.

[1406] 6. The server uses an emotion engine to recognize the user's emotional state and makes suggestions that best fit the current emotional state.

[1407] 7. The server sends the calculation results to the terminal, which provides the user with a visual interface.

[1408] 8. The user reviews the proposed furniture and layout and provides feedback, for example, suggesting that the chair be moved slightly to the left.

[1409] 9. The device sends feedback to the server, which recalculates and generates a revised proposal.

[1410] 10. The server sends the revised plan to the device, which presents it to the user again. The cycle repeats if the user checks again and provides feedback.

[1411] This system takes maximum consideration of the user's health and, by combining it with an emotion engine, can provide an optimal working environment that also takes into account the user's emotional state, thus creating an environment where users can work comfortably even during long hours of desk work.

[1412] The processing flow will be explained below.

[1413] Step 1:

[1414] The user starts the application and inputs their 3D body measurement data (height, weight, shoulder width, hip width, etc.). This data can be manually input by the user using a measuring device or automatically acquired using a dedicated 3D scanning device.

[1415] Step 2:

[1416] Users upload floor plans to the application, which include details such as room dimensions, shape, window and light source locations, and door locations. After uploading, users can review this information and make any necessary corrections using the application's interface.

[1417] Step 3:

[1418] Users input their preferences and special requests (e.g., specific furniture styles and colors, special feature requests, etc.) Once input is complete, all data is sent to the server.

[1419] Step 4:

[1420] The terminal validates all data entered by the user in real time, checking that all required fields have been entered, notifying the user if any information is missing and prompting them to enter it. Once it determines that all data is complete, it automatically sends this data to the server.

[1421] Step 5:

[1422] The server then generates a 3D model of the user's body based on the received data, using an algorithm that analyzes the dimensions of each part of the body in three dimensions and creates an accurate model based on the user's posture and body shape.

[1423] Step 6:

[1424] The server analyzes furniture placement areas and user movement lines based on floor plan data. Taking into account the dimensions and shape of the floor plan, it calculates areas where furniture can be placed and user movement lines. It also reflects the position of the light source and simulates how natural and artificial light affect the entire room.

[1425] Step 7:

[1426] The server takes into account the user's tastes and special requests and generates a list of suitable furniture options, taking into account the ergonomic dimensions, shapes, and placement of the furniture.

[1427] Step 8:

[1428] The server uses an emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements to infer their current emotional state. This information is reflected in furniture and layout suggestions.

[1429] Step 9:

[1430] The server learns past emotional data and makes furniture suggestions taking into account the user's long-term emotional trends, thereby providing a comfortable environment for the user over the long term.

[1431] Step 10:

[1432] The server generates an optimal furniture list and layout plan based on the analysis results and the emotion engine results, and the generated list and plan are sent to the terminal in data format.

[1433] Step 11:

[1434] The terminal provides an interface that allows users to visually check the furniture and layout plan, and users can intuitively understand and check the proposal using 3D views and simulation screens.

[1435] Step 12:

[1436] Users can review the proposed furniture and layout and provide feedback, such as moving a particular chair slightly to the left or adjusting the desk height.

[1437] Step 13:

[1438] The terminal records the feedback from the user and sends it to the server.

[1439] Step 14:

[1440] The server analyzes the user's feedback and performs recalculation to modify the furniture list and layout plan as needed. This process is repeated until the optimal proposal is completed based on the user's needs.

[1441] Step 15:

[1442] The server regenerates the revised plan and sends it to the device, which presents the new revised plan to the user for confirmation again. If further feedback is required, the cycle repeats.

[1443] This system provides an optimal working environment that takes into account the user's health and emotional state, making it possible to work comfortably even during long hours of desk work.

[1444] Example 2

[1445] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1446] Conventional furniture layout systems could provide optimal furniture layouts based on the user's body data and room layout information, but because they did not take the user's emotional state into account, it was difficult to fully guarantee long-term comfort and user satisfaction. Furthermore, when recalculating based on feedback, optimization was not possible in combination with past emotional data, making it difficult to provide the optimal environment the user desired.

[1447] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for recognizing the user's emotional state and analyzing the emotional data, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data and emotional data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, and means for learning from the feedback and past emotional data and improving the proposal. This makes it possible to provide an optimal furniture layout and its proposal taking into account the user's emotional state.

[1448] "Human body 3D measurement data" refers to data indicating the user's physical dimensions such as height, weight, shoulder width, and waist width, and is data obtained using a dedicated 3D scanning device or manual input.

[1449] A "floor plan" is a drawing that shows the shape, dimensions, window positions, light source positions, door positions, etc. of a room, and is data that a user uploads to the application.

[1450] "Furniture arrangement information" is data that indicates information such as the type, position, dimensions, and shape of furniture arranged in a room.

[1451] "Light source position" is data that indicates the specific position of a light source (window, lighting fixture, etc.) in a room.

[1452] "Hobby information" is data that indicates the user's furniture preferences, style, color coordination, special requests, and the like.

[1453] "Emotional state" is data indicating the emotional state of the user that is estimated by analyzing the user's facial expression, tone of voice, body movements, and the like.

[1454] "Emotion data" is data that expresses emotional states using numerical values ​​and categories, and is data that is analyzed and collected by the emotion engine.

[1455] The "ergonomically optimal furniture list" is a list showing the type, dimensions, and shape of furniture that is considered optimal from an ergonomic perspective based on the user's body data, room floor plan, furniture placement information, light source position, and hobby information.

[1456] A "visual interface" refers to an interface that allows users to visually check the furniture layout plan through a 3D view or simulation screen.

[1457] "Feedback" refers to information that a user inputs into the application about their opinions and requests regarding the proposed furniture and layout, and sends it to the server.

[1458] The present invention is a system that calculates an optimal furniture list and its layout based on the user's ergonomics based on the user's 3D body measurement data, floor plan, furniture layout information, light source position, and hobby information, and presents it to the user. Furthermore, the system recognizes the user's emotional state and uses an emotion engine to suggest optimal furniture. The detailed implementation method of this system is described below.

[1459] Data collection

[1460] First, a user launches the application and inputs their anthropometric data (e.g., height 170 cm, weight 65 kg, shoulder width 45 cm). This data can be entered manually or automatically obtained using a dedicated 3D scanning device. Next, the user uploads a floor plan of the room to the application. The floor plan includes details such as the room's shape, dimensions, window locations, light source locations, and door locations. In addition, the user can input their preferences and special requests (e.g., specific furniture style and color coordination).

[1461] Data analysis

[1462] The server generates a three-dimensional model of the user's body based on the received stereoscopic body measurement data. This process uses 3D modeling software (e.g., Blender) to analyze the dimensions of each part of the body in three dimensions and create an accurate model. The server then analyzes the floor plan data to calculate furniture placement areas and traffic flow. It also simulates natural and artificial light based on the light source position. For example, it uses emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API."

[1463] Emotion analysis

[1464] The server uses an emotion engine to recognize the user's emotional state. This allows it to analyze the user's facial expressions, tone of voice, and physical movements to infer emotions in real time. This emotional data is reflected in the analysis results, creating a furniture list and placement that is optimal for the user's current emotional state. The server also learns from past emotional data and makes furniture suggestions that take long-term emotional trends into account.

[1465] Furniture and layout suggestions

[1466] The server generates an optimal furniture list and layout plan based on the results of the analysis and emotion engine, and sends it to the device. The device then provides an interface that allows users to visually check the furniture and layout plan. For example, users can use game engines such as Unity or Unreal Engine to understand the proposals through 3D views and simulation screens.

[1467] User Feedback

[1468] Finally, the user reviews the proposed furniture and layout and provides feedback. For example, they might enter a specific suggestion such as, "I'd like to move the chair a little to the left." The device records the feedback and sends it to the server. The server analyzes the feedback, recalculates as necessary, and generates a new furniture list and layout plan. This cycle is repeated until the user is satisfied.

[1469] Specific examples

[1470] This shows how a freelancer working from home uses this system.

[1471] 1. The user starts the application and enters data such as height 170 cm, weight 65 kg, and shoulder width 45 cm.

[1472] 2. The user uploads a floor plan and inputs the shape of the room, the position of the light source, the location of the door, etc.

[1473] 3. The user inputs their preferred furniture style (e.g., modern style) and color preferences (e.g., blue and white color scheme).

[1474] 4. The server analyzes the data and generates a 3D human body model.

[1475] 5. The server uses an emotion engine to analyze the user's emotional state.

[1476] 6. The server generates an optimal furniture list and layout plan and sends it to the terminal.

[1477] 7. The device presents the furniture and layout plan to the user in a 3D view.

[1478] 8. The user reviews the proposal and provides feedback.

[1479] 9. The server recalculates based on the feedback and creates a new plan.

[1480] This system allows users to create a comfortable working environment.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1:

[1483] The user launches the application and inputs their body stereoscopic measurement data. For example, height 170 cm, weight 65 kg, shoulder width 45 cm, etc., can be entered manually or automatically using a stereoscopic scanning device. This operation inputs the user's physical dimensions into the application. The input includes the body stereoscopic measurement data. The output is the input data sent to the server.

[1484] Step 2:

[1485] The user uploads a floor plan to the application. The floor plan includes detailed information such as the room shape, dimensions, window positions, light source positions, and door positions. After uploading, the user can review this information and modify it as necessary. For example, the user can fine-tune the room dimensions or light source positions using the application interface. The input includes the floor plan. The output is the modified floor plan data sent to the server.

[1486] Step 3:

[1487] Users input their preferences and special requests (e.g., preferences for a particular furniture style or color) into the application, which then collects the user's preference data. The input includes the preferences and special requests. The output is sent to the server.

[1488] Step 4:

[1489] The server generates a 3D human body model of the user based on the received 3D human body measurement data, floor plan data, and hobby information. In this process, 3D modeling software (e.g., Blender) is used to analyze the data in three dimensions and create a 3D human body model. The inputs include the 3D human body measurement data, floor plan data, and hobby information. The output is the generated 3D human body model and the analysis results.

[1490] Step 5:

[1491] The server analyzes floor plan data and calculates furniture placement areas and traffic flow. At this stage, it determines where furniture can be placed and what the optimal traffic flow is. It also simulates natural and artificial light based on the light source position, simulating the brightness of the entire room. The input includes floor plan data and light source position data. The output is the placement area analysis results and light simulation results.

[1492] Step 6:

[1493] The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's facial expressions, tone of voice, and body movements in real time to generate emotional data. Here, emotion analysis tools such as "Affectiva" and "Microsoft Azure Emotion API" are used. The input includes real-time user information (facial expressions, tone of voice, and body movements). The output is the analyzed emotional data.

[1494] Step 7:

[1495] The server generates an optimal ergonomic furniture list and layout plan based on the input data and emotion data. This process uses an algorithm to calculate the optimal furniture dimensions, shape, and layout. Inputs include a 3D human body model, floor plan analysis results, and emotion data. The output is an optimal furniture list and layout plan.

[1496] Step 8:

[1497] The server sends the generated furniture list and layout plan to the terminal. The terminal provides an interface that the user can visually check, and displays the proposed content in a 3D view or simulation screen. For example, a game engine (e.g., Unity or Unreal Engine) is used to display a simulation of the furniture layout in real time. The input includes the furniture list and layout plan sent from the server. The output is the interface that is visually presented to the user.

[1498] Step 9:

[1499] The user reviews the proposed furniture and layout and provides feedback. Specifically, the user inputs their feedback, such as rearranging the furniture or adjusting the layout, into the application. The input includes the user's feedback. The output is sent to the server.

[1500] Step 10:

[1501] The server analyzes the received feedback and recalculates the furniture list and layout plan as needed, taking into account past emotional data to update the proposals. The inputs include the user's feedback and past emotional data. The output is a revised furniture list and layout plan.

[1502] Step 11:

[1503] The server sends the revised plan to the terminal and presents it again to the user. The terminal updates the interface for further user review. The input includes the revised plan. The output is an updated visual interface.

[1504] By repeating the above processing steps, an optimal furniture arrangement that satisfies the user is provided.

[1505] (Application example 2)

[1506] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1507] Conventional furniture layout suggestion systems do not take into account the user's detailed 3D body measurement data or emotional state, making it difficult to select and arrange optimal furniture. Furthermore, they lacked an interface for visually confirming the proposed content, making it difficult for users to intuitively understand the content. Furthermore, there was no means in place to provide optimal furniture suggestions to users on the spot in physical stores or commercial facilities. There was a need to solve these issues and improve user comfort and ease of use.

[1508] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1509] In this invention, the server includes means for inputting three-dimensional measurement data of the human body, means for inputting floor plans, furniture layout information, light source positions, and hobby information, means for calculating an optimal furniture list and its layout based on ergonomics based on the input data, means for presenting the calculation results to the user and providing an interface that the user can visually confirm, means for receiving feedback from the user and recalculating the furniture list and layout, means for recognizing the user's emotional state and using an emotion engine to make optimal furniture suggestions, means for visualizing the consideration results through a three-dimensional view or simulation screen, and means for making optimal furniture suggestions to the user in a store or commercial facility where there is a physical presence. This enables optimal furniture suggestions that reflect the user's detailed human body data and emotional state, and not only can suggestions be made through an intuitively easy-to-understand visual interface, but also enables instantly customized furniture suggestions in physical stores and commercial facilities.

[1510] "Three-dimensional measurement data of the human body" refers to data obtained in three dimensions that indicates specific human body dimensions such as the user's height, weight, shoulder width, and waist width.

[1511] A "floor plan" is a drawing that includes detailed information such as the shape and dimensions of a room, the location of windows, the location of light sources, and the location of doors.

[1512] "Furniture arrangement information" is data relating to where in a room each piece of furniture is arranged.

[1513] "Light source position" is information indicating the position of a source of natural light or artificial light in a room.

[1514] "Hobby information" is data about the user's preferences, such as preferred furniture styles, color coordination, and special functional requirements.

[1515] "Ergonomics" is the study of creating comfortable and efficient designs that take into account human physical characteristics and movements.

[1516] A "furniture list" is a list of the most suitable furniture suggested to the user.

[1517] The "emotion engine" is a system that analyzes and infers the user's emotional state from facial expressions, tone of voice, physical movements, etc.

[1518] "Interface" refers to the screen and input devices that users use to operate the system.

[1519] "Feedback" refers to the act of communicating to the system the user's opinions and requests for corrections regarding the proposed content.

[1520] A "3D view" is a display format that visualizes proposed furniture placement and room layout in three dimensions.

[1521] A "simulation screen" is a display means for virtually reproducing how a proposed furniture arrangement will function.

[1522] A "physical commercial facility" refers to a store or facility that actually exists as a building and that customers can visit.

[1523] This invention is a system that calculates an optimal furniture list and its layout based on ergonomics and presents it to the user. This system operates based on three-dimensional human body measurement data, floor plans, furniture layout information, light source position, and hobby information. It also uses an emotion engine to recognize the user's emotional state and make suggestions based on that emotional state. This system provides furniture suggestions optimized for the user's characteristics and emotions in brick-and-mortar stores and commercial facilities.

[1524] The following hardware and software are used to process the data. First, a body scanning device (BodyScanner) is required to collect stereoscopic measurement data of the human body. Dedicated software (LayoutAnalyzer) is used to analyze floor plans and furniture layout information. An emotion recognition engine (EmotionRecognitionEngine) is used to recognize emotional states. A furniture recommendation engine (FurnitureRecommender) is required to recommend furniture, and this incorporates ergonomic algorithms. Finally, software (VisualizationInterface) is used to provide a 3D view display and simulation screen as an interface to visually display suggestions to the user.

[1525] The server operates by coordinating the various software modules described above. Specifically, the server collects and analyzes three-dimensional measurement data of the human body and calculates the optimal furniture list and its placement based on the floor plan and furniture layout information. It also uses an emotion engine to recognize the user's emotional state and suggests furniture that best suits that emotional state. The calculation results are then sent to the device, which then visually presents the suggestions to the user through a 3D view or simulation screen.

[1526] Consider the following scenario: In a physical store, a user uses a body scanning device to collect stereoscopic measurement data of their body. Then, they upload a floor plan and enter their hobbies and special requests. All of this data is sent to a server, which calculates the optimal furniture list and its placement. An emotion engine analyzes the user's emotional state and generates optimal furniture suggestions. The calculation results are sent to the device, which visually presents the suggestions to the user through a 3D view or simulation screen.

[1527] For example, you can make suggestions using prompts like the following:

[1528] "Please suggest a furniture list and layout to optimize the interior of a living room and bedroom. The user's anthropometric data are height 170cm, weight 65kg, and shoulder width 45cm. The floor plan is as follows:

[1529] Living room: Light source is located in the center of the ceiling, window is on the south side, door is on the north side

[1530] Bedroom: Light source is on the west side of the ceiling, window is on the east side, door is on the south side

[1531] The user's preferred furniture style is modern, their preferred color is blue and white, and their emotional state is relaxed.

[1532] Based on this information, please design an algorithm that will suggest the optimal furniture list and its placement."

[1533] In this way, the present invention can provide optimal furniture suggestions that take into account the user's physical characteristics and emotional state, improving the user experience in physical stores and commercial facilities.

[1534] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1535] Step 1:

[1536] A user uses a body scanning device to collect stereoscopic data of their body. The device acquires dimensional data such as height, weight, shoulder width, and hip width, and sends it to a cloud server. The input is the user's body data, and the output is analyzable stereoscopic data.

[1537] Step 2:

[1538] Users upload floor plans to the application. They also input information about furniture layout, light source positions, and door and window locations. This data is sent to a cloud server via the device. The input is the floor plan and related information, and the output is spatial information data for analysis.

[1539] Step 3:

[1540] The server analyzes the transmitted stereoscopic body measurement data and floor plan data. It uses ergonomic algorithms to calculate the optimal furniture dimensions, shape, and placement. The input is the body and floor plan data, and the output is the optimal furniture list and placement plan.

[1541] Step 4:

[1542] The server uses an emotion recognition engine to analyze the user's emotional state. It uses a camera and microphone to detect facial expressions, tone of voice, and body movements to determine emotions. The input is real-time user facial and voice data, and the output is analyzed emotional state data.

[1543] Step 5:

[1544] Based on the results of the emotion engine, the server recalculates optimal furniture suggestions, adjusting the suggestions to suit the user's current emotional state. The input is emotional state data, and the output is an optimal furniture list and its placement that takes emotions into account.

[1545] Step 6:

[1546] The server sends the calculation results to the terminal, which visually displays the proposal to the user through a 3D view or simulation screen. The input is the calculated furniture list and placement data, and the output is the proposal displayed on the visual interface.

[1547] Step 7:

[1548] The user checks the visually displayed furniture arrangement proposal and inputs their feedback into the device, providing specific suggestions for revisions, such as the desired furniture position or height. The input is the user's feedback, and the output is the revision proposal data.

[1549] Step 8:

[1550] The device sends the user's feedback to the server, which then recalculates the optimal furniture list and layout based on the feedback and generates a revised plan. The input is the us...

Claims

1. a means for inputting stereometric data of the human body; A means for inputting floor plans, furniture layout information, light source positions, and hobby information; A means for calculating the optimal ergonomic furniture list and its layout based on the input data; means for presenting the calculation results to a user and providing an interface that allows the user to visually confirm the results; The system includes a means for receiving feedback from the user and recalculating the furniture list and placement.

2. 2. The system according to claim 1, further comprising means for determining the optimum chair height and angle based on the stereoscopic measurement data of the human body.

3. 2. The system according to claim 1, further comprising means for simulating the brightness in a room based on the position of a light source and determining the optimum furniture arrangement.

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