System

Abstract

A system is provided.SOLUTION: A system for optimizing home furnishings placement for the physical and cognitive functions of an elderly person, comprising: means for inputting information about the user's physical limitations and cognitive state; means for inputting existing furnishings information and making new furnishings suggestions; means comprising a generative AI for calculating optimal furnishings placement considering ergonomics and behavioral patterns; and means for visually displaying the placement results of the generative AI to the user and making adjustments.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Due to physical limitations and declining cognitive function, elderly people are prone to accidents while moving around their homes and engaging in daily activities. Therefore, there is a need to optimize furniture arrangements to reduce accidents within the home and enable elderly people to live their daily lives safely and comfortably. However, it is difficult to effortlessly achieve safe furniture arrangements based on the physical and cognitive conditions of each elderly person. Therefore, the objective of this invention is to provide a system that uses AI to propose optimal furniture arrangements that are easy for elderly people to use, thereby providing a safe and comfortable living environment. [Means for solving the problem]

[0005] To this end, the present invention provides a system having the following characteristics:

[0006] First, the system includes a means for inputting information about the user's physical limitations and cognitive status. This allows for an accurate understanding of the elderly person's physical abilities and needs. Second, the system includes a means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data. This allows for detailed information about the living space to be obtained. Furthermore, the system includes a means for inputting existing furniture information and proposing new furniture. This allows for the optimal furniture arrangement for the elderly person's living environment to be considered. Third, the system includes a means including a generation AI that calculates the optimal furniture arrangement taking into account ergonomics and behavioral patterns. This generation AI quickly proposes furniture arrangements that are suited to the elderly person's daily movements. Finally, the system includes a means for visually displaying the arrangement results generated by the generation AI to the user and for adjustment. This allows the user to confirm and adjust the proposed arrangement and confirm the optimal arrangement. Furthermore, the system includes an additional means for storing the calculation results generated by the generation AI on a server and using them for future readjustments, enabling continuous optimization and the provision of a stable living environment.

[0007] This makes it possible for the system to provide users with a safe and comfortable living environment.

[0008] "User" refers to an individual who uses the system, particularly the elderly.

[0009] "Physical limitations" refers to conditions including restrictions on the user's physical functions, such as impaired vision or hearing, or weakened legs and hips.

[0010] "Cognitive state" is a term that describes the current state of a user's memory, judgment, and cognitive abilities.

[0011] "Room dimensions" refers to the measurements of the length, width, and height of the scanned room.

[0012] "Positions of doors and windows" refers to specific position information where doors and windows are located within a room.

[0013] "Power supply location" refers to the specific location information of power sockets and electrical wiring within a room.

[0014] "Digital data" refers to data that records information such as room dimensions, the location of doors and windows, and the location of power sources in digital format.

[0015] "Existing furniture" refers to furniture that the user currently owns.

[0016] "New Furniture" means new furniture proposed to supplement or replace existing furniture.

[0017] "Ergonomics" refers to the layout and design of furniture that takes into consideration the user's ergonomics, that is, their physical abilities and movements.

[0018] "Behavioral patterns" refer to the habits and tendencies of the actions and travel routes that a user takes in their daily life.

[0019] "Generative AI" refers to artificial intelligence that automatically calculates and suggests optimal furniture layouts based on the user's physical limitations, cognitive state, room dimensions, etc.

[0020] "Visually displaying" refers to visually showing the calculated furniture arrangement to the user on the screen.

[0021] "Making adjustments" refers to the user making changes or tweaks to the proposed furniture arrangement.

[0022] "Optimal furniture arrangement" refers to the arrangement of furniture that takes into consideration ergonomics and behavioral patterns, allowing elderly people to live most safely and comfortably.

[0023] "Server" refers to a computer system for collecting, storing, and processing data located on a cloud or local network. [Brief explanation of the drawings]

[0024] [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

[0025] 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.

[0026] First, the terms used in the following description will be explained.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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."

[0032] [First embodiment]

[0033] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0034] 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.

[0035] 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).

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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."

[0045] The system for implementing the present invention is implemented in a form that includes multiple means for optimizing furniture arrangement in a home according to the user's physical limitations and cognitive status. This system uses generative AI to provide a safe and comfortable living environment for the elderly.

[0046] Program processing explanation

[0047] 1. Create a user profile

[0048] The user launches a dedicated application on the device. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server, which stores this information in a database for later processing.

[0049] 2. Collecting spatial information

[0050] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[0051] 3. Furniture selection assistance

[0052] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[0053] 4. Placement suggestions using generative AI

[0054] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[0055] 5. Viewing and adjusting results

[0056] The device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal as needed. If the user feels it is optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database for future adjustments and as reference information for other users.

[0057] Specific examples

[0058] 1. Create a user profile

[0059] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0060] 2. Collecting spatial information

[0061] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0062] 3. Furniture selection assistance

[0063] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0064] 4. Placement suggestions using generative AI

[0065] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0066] 5. Viewing and adjusting results

[0067] The device visually displays the AI's proposed placement to the user and performs a virtual simulation. After the user makes some fine adjustments and presses the "Confirm" button, the placement information is sent to the server and stored in a database.

[0068] This system will enable elderly people to have a safe and comfortable living environment in their own homes.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[0072] Step 2:

[0073] Users answer questions on the device and enter information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[0074] Step 3:

[0075] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[0076] Step 4:

[0077] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[0078] Step 5:

[0079] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[0080] Step 6:

[0081] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[0082] Step 7:

[0083] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[0084] Step 8:

[0085] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[0086] Step 9:

[0087] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[0088] Step 10:

[0089] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[0090] Step 11:

[0091] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[0092] Step 12:

[0093] When the user is satisfied with the arrangement, he / she presses the "confirm" button on the device, and the device sends the final arrangement information to the server as feedback.

[0094] Step 13:

[0095] The server stores the determined placement information in a database and makes it available for future readjustments or as reference for other users, thereby improving the safety and comfort of users in their homes.

[0096] Example 1

[0097] 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."

[0098] Optimizing furniture arrangement in the home to accommodate the physical and cognitive functions of elderly people is important for providing a safe and comfortable living environment. However, traditional manual furniture arrangement methods have the drawback of being difficult to consider the specific needs and limitations of elderly people, making the process of achieving optimal furniture arrangement cumbersome and time-consuming. Furthermore, future changes or readjustments require manually collecting new information and reconsidering the arrangement, which is inefficient.

[0099] 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.

[0100] In this invention, the server includes a means for inputting information about the user's physical limitations and cognitive state, a means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data, and a means for inputting existing furniture information and proposing new furniture. This allows the generative AI to propose optimal furniture layouts that take ergonomics and behavioral patterns into consideration. The resulting layouts generated by the generative AI are visually displayed to the user, providing a virtual simulation, allowing the user to make fine adjustments and finalize the layout. This information can then be fed back to the server for further adjustments or as reference information.

[0101] A "user profile" is data that includes information about a user's physical limitations and cognitive state.

[0102] "Generative AI" is an artificial intelligence system that calculates and suggests optimal furniture layouts taking into account ergonomics and behavioral patterns.

[0103] "Ergonomics" is the science of optimizing the layout of work environments and tools to improve human efficiency and comfort.

[0104] A "virtual simulation" is a digital simulation that allows users to visually review and fine-tune the proposed furniture arrangement.

[0105] "Feedback" is the process by which the user sends the final placement information to the server.

[0106] The "database" is a system that stores user profile information, spatial information, furniture information, etc., and can be used for future readjustments or as reference information.

[0107] The "server" is a central processing unit that manages user profile information, spatial information, and furniture information, and exchanges data with the generating AI.

[0108] A "terminal" is a device that allows a user to input information using a dedicated application and exchange data with a server.

[0109] "Scanning" is the act of converting information such as room dimensions, the location of doors and windows, and the location of power sources into digital data using a camera function.

[0110] The term "means" refers to individual elements or devices that perform a particular function for carrying out the invention.

[0111] The present invention provides a system that utilizes generative AI to optimize the furniture arrangement in a home based on the user's physical limitations and cognitive status, providing a safe and comfortable living environment for the elderly.

[0112] First, the user installs and launches a dedicated application on a device such as a smartphone or tablet. The device then displays questions about the user's physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences. The user answers the questions on the screen and enters this information into the device. The device then sends the collected user profile information to a server, which stores the information in a database.

[0113] Next, the process moves to the spatial information collection phase. The user scans their room using a device such as a smartphone or tablet. Specifically, the camera function is used to scan the room's dimensions, the location of doors and windows, and the location of power sources, and this is converted into digital data. The device then analyzes the scanned image in real time and records it as digital data. The acquired spatial information data is immediately sent to a server and saved.

[0114] When selecting furniture, the server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for their confirmation. The user can enter details of the displayed furniture and receive suggestions for new furniture if necessary. This information is sent to the server in real time and stored in a database.

[0115] In the next step, the server provides all collected information—user profile, spatial information, and furniture information—as input data to a generative AI model. The generative AI calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns. The server outputs the optimal layout proposal calculated by the generative AI in data format and sends it to the device.

[0116] Finally, the device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal if necessary. If the user feels it is finally optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database, allowing it to be used for future adjustments or as reference information for other users.

[0117] Specific examples

[0118] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0119] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0120] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0121] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0122] Finally, the device visually displays the AI's proposed layout to the user and performs a virtual simulation. After making fine adjustments, the user presses the "Confirm" button, and the layout information is sent to the server and stored in a database. By using this system, users can achieve a safe and comfortable living environment in their own homes.

[0123] Prompt Sentence Examples

[0124] "Ask your generative AI to suggest optimal furniture arrangements for a 70-year-old with visual limitations to live safely in their home."

[0125] "Explain how to calculate the optimal furniture placement for a living room, including the placement of a sofa, TV stand, and dining table."

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Specific processing steps of the program

[0128] Step 1:

[0129] The user launches the dedicated application on a device such as a smartphone or tablet. The device then displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. Specifically, the user enters their answers into checkboxes and text boxes on the screen and presses the send button. The input data is profile information including the user's physical limitations and lifestyle habits, and the output data is a data packet that organizes this information.

[0130] Step 2:

[0131] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a database. Specifically, the terminal encodes the user input data and sends it over the network to the server. The server decodes the received data and stores it in a structured format in the database. The input of this step is the user profile information, and the output is the user profile stored in the database.

[0132] Step 3:

[0133] The user scans a room using a device such as a smartphone or tablet. The device uses its camera to scan the room's dimensions, the locations of doors and windows, and power outlets, and converts the data into digital data. Specifically, the user operates the camera while walking around the room, capturing images of the room in real time. The input data is the camera image, and the output data is digital data including the room's dimensions and structural information.

[0134] Step 4:

[0135] The device sends the scanned spatial information data to a server. The server receives this information and stores it in a database. Specifically, the device analyzes the captured video data, identifies the room dimensions and the locations of doors, windows, and power sources, and converts it into a dataset. This dataset is then sent to the server, which receives it and stores it in the database. The input to this step is the spatial information of the room, and the output is the spatial information stored in the database.

[0136] Step 5:

[0137] The server generates a list of existing furniture based on the user profile information and spatial information. The terminal displays this generated furniture list to the user. Specifically, the server compares the user profile and spatial information in the database and generates a list of appropriate furniture. The generated list is sent to the terminal, which displays it to the user. The input of this step is the user profile and spatial information, and the output is a list of furniture.

[0138] Step 6:

[0139] The user enters details of existing furniture and suggests new furniture if necessary. The device sends the information entered by the user to the server. Specifically, the user checks the displayed list of existing furniture and uses tabs and text boxes to enter detailed information and information about new furniture. The device then sends this information to the server. The input to this step is the furniture information entered by the user, and the output is the furniture information stored in the database.

[0140] Step 7:

[0141] The server provides the collected user profile, spatial information, and furniture information to the generation AI. The generation AI considers ergonomics and the user's behavioral patterns to calculate the optimal furniture layout. Specifically, the server inputs all relevant information into the generation AI model, and the generation AI starts calculations. This calculation generates data on the optimal furniture layout. The inputs for this step are the user profile, spatial information, and furniture information, and the output is a dataset containing the optimal furniture layout.

[0142] Step 8:

[0143] The server sends the optimal layout proposal calculated by the generative AI to the device. The device visually displays the proposed furniture layout to the user, providing a virtual simulation. Specifically, the server sends the layout data from the generative AI to the device, which then visually displays it to the user. The user can view and manipulate the layout on the screen. The input of this step is a dataset containing the optimal furniture layout, and the output is a visual layout proposal displayed to the user.

[0144] Step 9:

[0145] The user checks the displayed suggestions and makes fine adjustments as necessary. The device then sends the finalized layout information to the server. Specifically, the user adjusts the furniture layout on the screen by tapping and dragging, and finally presses the "Confirm" button. The device then sends this final layout information to the server. The input to this step is the user's layout adjustment information, and the output is the finalized layout information sent to the server.

[0146] Step 10:

[0147] The server stores the final placement information in a database and uses it for future readjustments and as reference information for other users. Specifically, the server stores the received final placement information in a database and links it with related data as needed. The input of this step is the final placement information, and the output is the placement information stored in the database.

[0148] (Application example 1)

[0149] 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."

[0150] It is necessary to provide a safe and comfortable living environment for the elderly by optimizing the furniture arrangement in their homes to accommodate their physical and cognitive functions. In addition, it is necessary to efficiently support users in physical stores in selecting and arranging the optimal furniture based on their physical limitations and preferences.

[0151] 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.

[0152] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the dimensions of the room, the positions of doors and windows, and the positions of power sources and converting them into digital data; means for inputting information about existing furniture and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results calculated by the generation AI to the user and allowing the user to make adjustments; and means for displaying a list of existing furniture from a furniture store and viewing and selecting furniture details to support the user's interior selection in a physical store, thereby enabling elderly people and users with physical limitations to enjoy a safe and comfortable living environment both inside and outside their homes.

[0153] "Information about the user's physical limitations and cognitive status" refers to information about the user's visual and hearing abilities, physical function status, cognitive function status, and daily living needs and preferences.

[0154] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a method of using a device such as a smartphone or tablet to measure the physical structure of a room through its camera function and convert this into digital data.

[0155] "Means for inputting existing furniture information and making suggestions for new furniture" refers to a method for recording information about furniture that a user currently owns and making suggestions for additional or new furniture based on that information.

[0156] "Generative AI" refers to a system that uses artificial intelligence technology to calculate optimal furniture layouts, taking into account ergonomics and user behavior patterns.

[0157] "Means for visually displaying the placement results of the generative AI to the user and allowing them to make adjustments" refers to an interface that graphically displays the optimal furniture placement calculated by the generative AI to the user, allowing the user to visually check the placement and make fine adjustments.

[0158] "A means for displaying a list of existing furniture in a furniture store and viewing and selecting furniture details to assist users in selecting interior items in a physical store" refers to a method in a furniture shop that allows users to view a list of furniture available in the store and select furniture while checking detailed information.

[0159] A system for implementing the present invention provides various functions to enable elderly people and users with physical limitations to have a safe and comfortable living environment both inside and outside their homes. This system includes an information input means adapted to the user's physical limitations and cognitive state, a means for scanning room dimensions and the locations of doors, windows, and power sources, a means for inputting existing furniture information and proposing new furniture, a means for calculating the optimal furniture layout using a generative AI, a means for visually displaying the layout results generated by the generative AI so that the user can make adjustments, and a means for supporting interior design selection in a physical store.

[0160] Creating a User Profile

[0161] The device (smartphone or tablet) provides an interface through which users can input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences through a dedicated application, which is then sent to a server and stored in a database.

[0162] Collection of spatial information

[0163] Users can use the device's camera to scan the dimensions of their rooms, the locations of doors and windows, and power outlets, and convert this information into digital data. The acquired spatial information is then immediately sent to a server and stored. This processing is done using the camera module and the open-source library "OpenCV."

[0164] Assistance with furniture selection

[0165] The server uses the user profile information and spatial information to generate a list of existing furniture and sends it to the device. The user can then check the existing furniture on the device and receive suggestions for new furniture if necessary.

[0166] Placement suggestions by generative AI

[0167] The server uses a generative AI to calculate the optimal furniture layout based on the collected user profile information, spatial information, and furniture information. The generative AI takes ergonomics and user behavior patterns into account to generate the optimal furniture layout plan. This generative AI uses deep learning libraries such as "PyTorch" or "TensorFlow."

[0168] Viewing and adjusting results

[0169] The device visually displays the placement results generated by the AI, allowing the user to check them through a virtual simulation. After the user makes fine adjustments as needed and confirms the final placement, the information is fed back to the server and stored in a database.

[0170] Support for choosing interior decor in a physical store

[0171] When users visit a physical store, they can check the furniture store's existing furniture list through the application on their device, browse detailed information, select the furniture they like, and incorporate it directly into their layout plan.

[0172] As a concrete example, by inputting the following prompt sentence into the generative AI model, optimal furniture layout suggestions suitable for the user can be obtained.

[0173] Example prompt sentence:

[0174] User profile: Age: 70, Vision limitations: Yes, Mobility: Weak legs, Interior preferences: Kitchen and living room

[0175] Space information: Room dimensions: width 5.0m, height 5.0m, door location: x1.0m, y0.5m, window location: x4.0m, y0.5m, power location: x2.0m, y1.0m

[0176] Furniture list: sofa, TV stand, dining table

[0177] This allows seniors to get furniture arrangement plans that suit their needs and limitations.

[0178] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0179] Step 1:

[0180] The user installs and launches a dedicated application on their device (smartphone or tablet).

[0181] Input: Information such as the user's physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences.

[0182] How it works: The application collects this information through the user interface and formats it as digital data.

[0183] Output: User profile data is generated and sent to the server.

[0184] Step 2:

[0185] The device helps users scan their home to determine the dimensions of rooms, the location of doors and windows, and the location of power outlets.

[0186] Input: Room video data collected using the device's camera function.

[0187] How it works: It uses OpenCV to analyze camera footage and converts the room dimensions, the location of doors and windows, and the location of power sources into digital data.

[0188] Output: Spatial information data is generated and sent to the server.

[0189] Step 3:

[0190] The server receives the user profile data and spatial information data and stores them in a database.

[0191] Input: User profile data and spatial information data.

[0192] What it does: Efficiently stores incoming data and saves it in a database to serve as an input dataset for generative AI.

[0193] Output: User profile data and spatial information data stored in a database.

[0194] Step 4:

[0195] The server provides the user with a list of existing furniture based on the generated data.

[0196] Input: User profile data and spatial information data in the database.

[0197] Operation: Generates a list of existing furniture and sends the list to the user's device.

[0198] Output: A list of existing furniture displayed on the device.

[0199] Step 5:

[0200] Users can review their existing furniture list and receive suggestions for new furniture.

[0201] Input: Existing furniture list and user furniture selection information.

[0202] How it works: The user sees the furniture list on their device and uses the interface to add / modify new furniture.

[0203] Output: The updated furniture list is sent to the server.

[0204] Step 6:

[0205] The server provides the collected data to a generative AI model to calculate the optimal furniture layout.

[0206] Input: User profile data, spatial information data, updated furniture list.

[0207] How it works: Data is fed into a generative AI model (PyTorch or TensorFlow) to calculate optimal furniture layouts, taking into account ergonomics and behavioral patterns.

[0208] Output: The optimal furniture layout plan is generated and stored on the server.

[0209] Step 7:

[0210] The server transmits the generated placement plan to the user's terminal and displays it visually.

[0211] Input: Furniture layout ideas generated by a generative AI model.

[0212] What it does: Loads furniture layout ideas and sends them to the user's device.

[0213] Output: Furniture layout proposals visually displayed on the device.

[0214] Step 8:

[0215] Users can check the layout plan through a virtual simulation and make adjustments as necessary.

[0216] Input: Furniture layout suggestions displayed on the device.

[0217] How it works: The user uses the virtual simulation to view furniture placement, make adjustments as needed, and finalize the layout.

[0218] Output: The final placement proposal is fine-tuned and fed back to the server.

[0219] Step 9:

[0220] The server stores the final placement plan in a database for future reference and readjustment.

[0221] Input: Final, fine-tuned layout proposal.

[0222] How it works: Saves the final placement plan to a database for future refinements and as a reference for other users.

[0223] Output: Final placement proposal stored in database.

[0224] These processing steps allow the user to plan an efficient and optimal furniture arrangement.

[0225] 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.

[0226] The system for implementing the present invention is implemented as a combination of a means for optimizing furniture arrangement in the home according to the user's physical limitations and cognitive state, and an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions accordingly. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[0227] Program processing explanation

[0228] 1. Create a user profile

[0229] The user launches a dedicated application on the device. The device then displays a questionnaire about the user's physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server. The server stores this information in a database for later processing.

[0230] 2. Collecting spatial information

[0231] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[0232] 3. Furniture selection assistance

[0233] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[0234] 4. Placement suggestions using generative AI

[0235] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[0236] 5. Emotion Recognition by Emotion Engine

[0237] When a user receives furniture layout suggestions, the device recognizes the user's emotions in real time using the device's camera and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions.

[0238] 6. Adjusting and displaying the proposed results

[0239] The emotion engine sends the emotional data it recognizes to the server and stores it. The server then uses this emotional data to adjust the placement proposals made by the generation AI. For example, if the user is dissatisfied, the generation AI will review and recalculate the placement proposals. The server then sends the adjusted results to the device, which then visually displays them to the user.

[0240] 7. Finalize and save

[0241] If the user is satisfied with the proposed placement and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The device then sends the confirmed placement information to the server as feedback. The server stores this final placement information in a database and uses it for future readjustments and as reference information for other users.

[0242] Specific examples

[0243] 1. Create a user profile

[0244] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0245] 2. Collecting spatial information

[0246] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, which stores it.

[0247] 3. Furniture selection assistance

[0248] The server generates existing furniture information based on the user profile and spatial information. The terminal prompts the user to input existing furniture information such as "sofa," "TV stand," and "dining table," and will also suggest new furniture if necessary. The input information is sent to the server and saved in a database.

[0249] 4. Placement suggestions using generative AI

[0250] The server provides the collected information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0251] 5. Emotion Recognition by Emotion Engine

[0252] When a user receives a placement suggestion, the device analyzes the user's emotions in real time through the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the suggestion.

[0253] 6. Adjusting and displaying the proposed results

[0254] The emotion data recognized by the emotion engine is sent to the server, which then provides feedback to the generation AI, recalculating and adjusting it as needed. The adjusted results are then sent back to the device and displayed visually to the user.

[0255] 7. Finalize and save

[0256] When the user is satisfied with the adjustment results and finalizes the placement, they press the "Confirm" button on their device to send the placement information to the server. The server then stores the final placement information in a database, which can be used for future readjustments or as reference information for other users.

[0257] This system will enable elderly people to have a safe and comfortable living environment that also takes into consideration their emotional satisfaction.

[0258] The processing flow will be explained below.

[0259] Step 1:

[0260] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[0261] Step 2:

[0262] Users answer questions on the device and input information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[0263] Step 3:

[0264] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[0265] Step 4:

[0266] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[0267] Step 5:

[0268] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[0269] Step 6:

[0270] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[0271] Step 7:

[0272] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[0273] Step 8:

[0274] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[0275] Step 9:

[0276] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[0277] Step 10:

[0278] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[0279] Step 11:

[0280] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[0281] Step 12:

[0282] While the user is reviewing the placement proposal, the device's camera and microphone are used to collect the user's emotions in real time. The emotion engine analyzes the user's emotional data and determines how the user feels about the proposal.

[0283] Step 13:

[0284] The emotion engine sends the recognized emotion data to the server, which then adjusts the placement proposals of the generation AI based on this data. If the user is dissatisfied, the generation AI will review the proposals and recalculate.

[0285] Step 14:

[0286] The server sends the adjusted placement results to the terminal, which visually displays them to the user, allowing them to confirm the improved suggestions.

[0287] Step 15:

[0288] If the user is satisfied with the adjusted proposal, he / she presses the confirm button on the device to confirm the final arrangement, and the device sends the confirmed arrangement information to the server as feedback.

[0289] Step 16:

[0290] The server stores the final placement information in a database for future readjustments and as reference for other users.

[0291] In this way, the system of the present invention provides a safe and comfortable living environment while also taking into account the user's emotional state.

[0292] Example 2

[0293] 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."

[0294] Elderly people often have difficulty arranging furniture in their daily lives due to physical limitations and cognitive conditions. Furthermore, declining visual, auditory, and motor functions make it difficult to ensure a safe and comfortable living space. Furthermore, existing systems do not consider the user's emotions when proposing furniture arrangements, which may result in low user satisfaction. Therefore, a new system is needed that can propose appropriate furniture arrangements for elderly people and also consider their emotional satisfaction.

[0295] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power source locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for recognizing the user's emotional data regarding the proposed furniture layout in real time; means including an emotion engine for adjusting the layout proposal based on the emotional data; and means for visually displaying the layout results calculated by the generation AI and emotion engine to the user and allowing the user to make adjustments. This allows the elderly to not only receive the optimal furniture layout based on their physical limitations and cognitive state, but also to enjoy a safe and comfortable living environment that takes emotional satisfaction into consideration.

[0296] "Information about the user's physical limitations and cognitive status" refers to data about the user's physical limitations and cognitive capabilities.

[0297] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to technology that uses a scanning device such as a camera to measure the location and dimensions of each element in a room and converts that information into a digital format.

[0298] "Means for inputting existing furniture information and proposing new furniture" refers to technology that allows users to input information about furniture they already own and then suggests the most suitable new furniture based on that information.

[0299] "Generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to artificial intelligence technology that calculates effective and efficient furniture layout within a living space based on ergonomics and user behavioral patterns.

[0300] "Means for recognizing the user's emotional data regarding the proposed furniture layout in real time" refers to technology that uses sensors such as cameras and microphones to analyze in real time how the user feels about the presented furniture layout.

[0301] "Emotion engine for adjusting furniture placement suggestions based on emotional data" refers to technology that analyzes a user's emotional data and optimizes furniture placement suggestions based on the results.

[0302] "Means for visually displaying the placement results of the generative AI and emotion engine to the user and allowing adjustments" refers to technology that displays the furniture placement calculated by the generative AI and emotion engine to the user in a graphical format and allows the user to change the placement as needed.

[0303] "Means of storing the calculation results of the generative AI and emotion engine on a server and using them for future readjustments" refers to technology that stores the placement results calculated by the generative AI and emotion engine on a server, and reuses that data at a later date to make appropriate adjustments.

[0304] "Proposals to provide users with a safe and comfortable living environment" refers to technology that suggests furniture arrangements and living environment improvements necessary for users to live safely and comfortably.

[0305] A system for implementing this invention combines a means for optimizing furniture arrangement in a home according to a user's physical limitations and cognitive state with an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[0306] First, the user launches a dedicated application that can be used at home on a device such as a smartphone. This application displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences, and the user answers the questions. The response data is sent from the device to a server and stored in a database.

[0307] Next, the user scans a room in their home using a device such as a smartphone or tablet. The camera function captures the dimensions of the room, the location of doors and windows, the location of power outlets, and other information, and records this data digitally. The scanned data is also sent to a server and stored.

[0308] The server generates a list of existing furniture based on the user profile information and spatial information. This list is displayed on the terminal, and the user inputs details of each piece of furniture. New furniture items are also suggested as needed. The information entered by the user is sent to the server in real time and stored in a database.

[0309] The server then provides the collected user profile, spatial information, and furniture information as input data to the generation AI, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the device via the server in a data format such as JSON.

[0310] When receiving furniture layout suggestions, the device recognizes the user's emotions in real time using camera functions and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions. The recognized emotional data is sent to the server and stored.

[0311] The server adjusts the placement proposals made by the generation AI based on the emotional data. For example, if the user is dissatisfied, the generation AI will review the placement proposal and recalculate. The adjusted results are then sent back to the device by the server, where the user can visually confirm them.

[0312] If the user is satisfied with the placement proposal and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The confirmation information sent from the device is sent to the server as feedback and saved in the database as the final placement information. This information can be used for future readjustments or as reference information for other users.

[0313] Specific examples

[0314] Users launch a dedicated application on their smartphone and enter information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0315] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the room and the location of doors, windows, and power outlets, which is then sent from the device to a server where it is stored.

[0316] The server then generates a list of existing furniture based on the user profile and spatial information. The list includes items such as a sofa, TV stand, and dining table, and the user inputs details of these items. New furniture is also suggested as needed, and the information is also saved on the server.

[0317] The server provides the collected information to the AI ​​generator, which calculates the optimal layout taking into account ergonomics and behavioral patterns. For example, it suggests "placing the TV in a location that is easy to watch" or "placing the TV in a location with few obstacles when walking." The calculation results are sent to the device via the server and can be confirmed by the user.

[0318] While the user is reviewing the placement proposal, the device uses a camera and microphone to analyze the user's emotions in real time, which are then analyzed by the emotion engine. For example, if the user looks at the placement with a smile, it is judged to be "satisfied." The emotion data is sent to the server and stored.

[0319] The server provides feedback to the AI ​​based on the emotion data, and performs recalculation and adjustments. The adjusted placement is then sent back to the device and visually displayed to the user.

[0320] When the user is satisfied with the final arrangement and presses the confirm button, the arrangement information is sent to the server and stored in a database.

[0321] Prompt Sentence Examples

[0322] "Please suggest the optimal furniture arrangement that meets the following requirements so that the elderly can live safely and comfortably."

[0323] User profile: Limited vision, weak legs, frequent kitchen users

[0324] Spatial information: dimensions of living room, kitchen, bedrooms, and locations of doors, windows, and power outlets

[0325] Furniture information: sofa, TV stand, dining table

[0326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0327] Step 1:

[0328] The user launches a dedicated application on the device and enters information about their physical limitations and cognitive status.

[0329] Specific operations: The user launches a dedicated smartphone app and answers questions on a screen about things like "visual limitations," "hearing limitations," and "daily life needs."

[0330] Input: Information about physical limitations and cognitive status (e.g., limited vision, weak legs)

[0331] Output: User profile information is sent to the server and stored in the database.

[0332] Step 2:

[0333] The user uses the device to scan the room's dimensions, the location of doors and windows, and the location of power sources.

[0334] How it works: A user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the location of doors, windows, and power outlets.

[0335] Input: Room spatial information from camera images

[0336] Output: Sent as digital data to a server and stored in a database.

[0337] Step 3:

[0338] The server generates a list of existing furniture based on the user profile information and the spatial information.

[0339] Specific operation: The server generates a list of existing furniture such as "sofa," "TV stand," and "dining table" based on the user profile and room information.

[0340] Input: User profile information, spatial information

[0341] Output: Generate a list of existing furniture and send it to the device.

[0342] Step 4:

[0343] The device displays a list of existing furniture to the user, provides detailed information, and suggests new furniture.

[0344] Specific operation: The device displays the generated furniture list to the user, and the user enters details for each piece of furniture. New furniture pieces are also suggested as needed.

[0345] Input: Existing furniture list

[0346] Output: The furniture details entered by the user are sent to the server and stored in the database.

[0347] Step 5:

[0348] The server provides the collected information to the generation AI, which calculates the optimal furniture layout.

[0349] Specific operation: The server inputs the user profile, spatial information, and furniture information into the generative AI model, which then calculates the optimal furniture layout.

[0350] Input: User profile information, space information, furniture information

[0351] Output: The generated AI sends the optimal placement proposal data to the device.

[0352] Step 6:

[0353] The device uses a camera and microphone to recognize the user's emotions in real time.

[0354] Specific operation: While the user is viewing the placement suggestions, the device uses the camera and microphone to analyze the user's emotions.

[0355] Input: User's facial expressions and voice

[0356] Output: Emotion data is sent to the server and analyzed by the emotion engine.

[0357] Step 7:

[0358] The server adjusts placement suggestions made by the generative AI based on the emotional data.

[0359] Specific operation: The server feeds emotion data back to the generation AI, which then recalculates and adjusts the placement proposal.

[0360] Input: Emotion data

[0361] Output: The adjusted placement proposal data is sent to the terminal.

[0362] Step 8:

[0363] The terminal visually displays the adjusted placement proposal to the user and asks for reconfirmation.

[0364] Specific behavior: The device displays the adjusted furniture layout to the user, who then confirms it.

[0365] Input: Adjusted placement proposal

[0366] Output: User enters feedback for review and final adjustment.

[0367] Step 9:

[0368] The user confirms the final arrangement and presses the "confirm" button on the terminal.

[0369] Specific operation: The user confirms the final adjusted placement and presses the "Confirm" button on the device.

[0370] Input: User confirmation

[0371] Output: The final placement information is sent to the server and stored in the database.

[0372] In this way, a system is realized that proposes optimal furniture arrangements according to the physical limitations and cognitive state of the elderly, and provides a safe and comfortable living environment that also takes into account the user's emotional satisfaction.

[0373] (Application example 2)

[0374] 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."

[0375] To provide a safe and comfortable living environment that accommodates the physical and cognitive functions of elderly people, it is necessary to optimize furniture arrangement within the home. However, conventional methods for furniture arrangement do not fully consider the physical limitations, cognitive state, and emotions of elderly people, making it difficult to increase user satisfaction. Furthermore, there is a problem in that feedback on the proposed furniture arrangement is not provided in real time, making it difficult to make appropriate adjustments.

[0376] 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.

[0377] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results generated by the generation AI to the user and allowing the user to make adjustments; means for recognizing the user's emotions in real time using an emotion engine and adjusting the proposal results; and means for performing a final confirmation of the proposal results and saving the confirmed layout information on the server. This makes it possible to propose and adjust a safe and comfortable furniture layout that comprehensively takes into consideration the user's physical limitations, cognitive state, and emotions.

[0378] The "means for inputting information about the user's physical limitations and cognitive status" is an interface that collects information about the user's physical and cognitive functions and inputs it as digital data.

[0379] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a technology that uses a smartphone or tablet camera to scan the dimensions and structure of a room and converts it into digital data.

[0380] The "means for inputting existing furniture information and proposing new furniture" is an interface that allows the user to input information about furniture they already own and then suggests new furniture based on that information.

[0381] "Means including a generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to a system that incorporates a generative AI that calculates optimal furniture layout taking into account ergonomics and user behavioral patterns.

[0382] "Means for visually displaying the placement results of the generative AI to the user and allowing adjustments" refers to an interface that visually displays the furniture placement results calculated by the generative AI to the user and allows adjustments to be made based on the user's opinions and feedback.

[0383] "Means for recognizing user emotions in real time using an emotion engine and adjusting the proposed results" is a system that uses sensors such as cameras and microphones to recognize user emotions in real time and adjusts furniture placement proposals based on that emotional data.

[0384] The "means for making a final confirmation of the proposed furniture arrangement and storing the confirmed arrangement information on the server" is a means for the user to make a final confirmation of the proposed furniture arrangement and store the confirmed information on the server.

[0385] This invention uses a server, terminals, generative AI models, and emotion engines to optimize furniture placement according to the user's physical limitations and cognitive state, providing a comfortable and safe living environment.

[0386] Hardware and software used

[0387] Device: Smartphone or tablet

[0388] Server: Amazon Web Services (AWS), MySQL

[0389] Generative AI model: OpenAI GPT-4

[0390] Emotion engine: IBM Watson Tone Analyzer

[0391] Image analysis: ARKit (iOS) / ARCore (Android), OpenCV

[0392] Program processing explanation

[0393] 1. Create a user profile

[0394] The server allows users to launch a dedicated application on their device and input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences, which is then sent to the server in JSON format and stored in a database.

[0395] 2. Collecting spatial information

[0396] The device uses its camera to scan the dimensions of the room, the location of doors and windows, and the location of power sources, and converts this data into digital data, which is also sent to a server and stored.

[0397] 3. Furniture selection assistance

[0398] The server generates existing furniture information based on the user profile information and spatial information. This information is displayed on the terminal, and the user can add or modify it. This data is also saved on the server in real time.

[0399] 4. Placement suggestions using generative AI

[0400] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model. The generative AI model calculates the optimal furniture layout based on this information and returns the results to the server. The results are then visually displayed on the device.

[0401] 5. Emotion Recognition by Emotion Engine

[0402] The device uses a camera and microphone to recognize the user's emotions in real time when the user is checking the placement proposal. The emotion engine analyzes this data and transmits the user's emotion data to the server.

[0403] 6. Adjusting and displaying the proposed results

[0404] The server adjusts the placement proposals made by the generative AI based on the emotional data recognized by the emotion engine. The recalculated optimal placement proposal is sent back to the device and visually displayed to the user.

[0405] 7. Finalize and save

[0406] If the user is satisfied with the proposed placement and confirms it, they press the "Confirm" button on their device. The confirmed placement information is saved on the server and can be used for future readjustments or as reference information for other users.

[0407] Specific examples

[0408] A 70-year-old user launches a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device sends the entered information to a server and stores it in a database. The user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, where it is stored. The server generates existing furniture information based on the user profile and spatial information. The device then prompts the user to enter existing furniture information such as a sofa, TV stand, and dining table, and suggests new furniture if necessary. The input information is sent to the server and stored in a database. The server then provides the collected information to a generation AI, which calculates the optimal furniture layout. The generation AI generates layout proposals that take ergonomics and behavioral patterns into account and sends the data to the device via the server. When the user receives the layout proposals, the device analyzes the user's emotions in real time using the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the proposals. The emotion data recognized by the emotion engine is sent to the server, which provides feedback to the generation AI and performs recalculations and adjustments as appropriate. The adjusted results are sent back to the device and visually displayed to the user. When the user is satisfied with the adjustment results and has finalized the placement, they press the "Confirm" button on the device, which sends the placement information to the server. The server saves the final placement information in a database and uses it for future readjustments and as reference information for other users.

[0409] Prompt Sentence Examples

[0410] User: 75-year-old female, weak legs, normal vision. Scan data of the room is as follows.

[0411] Living room: 4m wide, 5m deep, 2.5m high, window located in the center, power outlet on the left wall.

[0412] Current furniture: sofa, TV stand, low table.

[0413] Suggestion: I have weak legs, so I would like low furniture. Please suggest adding a height-adjustable bed and a chair with soft cushions.

[0414] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0415] Step 1:

[0416] The user starts up the device and opens the dedicated application. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The information entered by the user is sent to the server in JSON format, which is then stored in a database.

[0417] Input: Information about the user's physical limitations, cognitive state, and preferences

[0418] Data processing: Convert input information into JSON format

[0419] Output: User profile data sent to the server

[0420] Step 2:

[0421] The user uses the camera function of their smartphone to scan the dimensions of the room, the location of doors and windows, and the location of power sources. The device analyzes the captured image data in real time and converts the dimensional information and other data into digital data. This data is then sent to the server and stored.

[0422] Input: Room image data

[0423] Data processing: Analyze image data and extract dimensional and positional information

[0424] Output: Digital data sent to the server

[0425] Step 3:

[0426] The server generates a list of existing furniture based on the user profile information and spatial information. This generated furniture information is displayed on the terminal, and the user can enter details of each piece of furniture and receive suggestions for new furniture. The entered information is sent to the server in real time and saved.

[0427] Input: User profile information, spatial information

[0428] Data processing: Creating a list of existing furniture and entering detailed information

[0429] Output: Furniture list displayed on the device, furniture information stored on the server

[0430] Step 4:

[0431] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the server and then visually displayed on the device.

[0432] Input: User profile, space information, furniture information

[0433] Data processing: Calculating optimal furniture placement using a generative AI model

[0434] Output: Furniture layout proposal displayed on the device

[0435] Step 5:

[0436] When the user confirms the placement proposal, the device uses the camera and microphone to recognize the user's emotions in real time. The emotion engine analyzes image and voice data and transmits the user's emotional data to the server.

[0437] Input: image data, audio data

[0438] Data processing: Emotion analysis using an emotion engine

[0439] Output: Emotion data sent to the server

[0440] Step 6:

[0441] The server adjusts the furniture layout proposals made by the generative AI based on the emotion data received from the emotion engine. New proposals are generated, and the recalculated optimal layout plan is sent to the terminal and visually displayed to the user.

[0442] Input: Emotion data, initial placement proposal

[0443] Data processing: Recalculation and alignment using generative AI models

[0444] Output: Re-proposed furniture layout displayed on the device

[0445] Step 7:

[0446] When the user is satisfied with the proposed furniture arrangement, they press the confirm button to finalize the furniture arrangement. The confirmed arrangement information is sent from the device to the server and stored in a database. It can be used for future readjustments or as reference information for other users.

[0447] Input: Confirmed placement information

[0448] Data processing: Confirmed placement information is saved in the database

[0449] Output: Final placement information saved on the server

[0450] 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.

[0451] 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.

[0452] 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.

[0453] [Second embodiment]

[0454] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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).

[0460] 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. 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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."

[0466] The system for implementing the present invention is implemented in a form that includes multiple means for optimizing furniture arrangement in a home according to the user's physical limitations and cognitive status. This system uses generative AI to provide a safe and comfortable living environment for the elderly.

[0467] Program processing explanation

[0468] 1. Create a user profile

[0469] The user launches a dedicated application on the device. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server, which stores this information in a database for later processing.

[0470] 2. Collecting spatial information

[0471] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[0472] 3. Furniture selection assistance

[0473] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[0474] 4. Placement suggestions using generative AI

[0475] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[0476] 5. Viewing and adjusting results

[0477] The device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal as needed. If the user feels it is optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database for future adjustments and as reference information for other users.

[0478] Specific examples

[0479] 1. Create a user profile

[0480] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0481] 2. Collecting spatial information

[0482] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0483] 3. Furniture selection assistance

[0484] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0485] 4. Placement suggestions using generative AI

[0486] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0487] 5. Viewing and adjusting results

[0488] The device visually displays the AI's proposed placement to the user and performs a virtual simulation. After the user makes some fine adjustments and presses the "Confirm" button, the placement information is sent to the server and stored in a database.

[0489] This system will enable elderly people to have a safe and comfortable living environment in their own homes.

[0490] The processing flow will be explained below.

[0491] Step 1:

[0492] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[0493] Step 2:

[0494] Users answer questions on the device and enter information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[0495] Step 3:

[0496] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[0497] Step 4:

[0498] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[0499] Step 5:

[0500] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[0501] Step 6:

[0502] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[0503] Step 7:

[0504] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[0505] Step 8:

[0506] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[0507] Step 9:

[0508] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[0509] Step 10:

[0510] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[0511] Step 11:

[0512] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[0513] Step 12:

[0514] When the user is satisfied with the arrangement, he / she presses the "confirm" button on the device, and the device sends the final arrangement information to the server as feedback.

[0515] Step 13:

[0516] The server stores the determined placement information in a database and makes it available for future readjustments or as reference for other users, thereby improving the safety and comfort of users in their homes.

[0517] Example 1

[0518] 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."

[0519] Optimizing furniture arrangement in the home to accommodate the physical and cognitive functions of elderly people is important for providing a safe and comfortable living environment. However, traditional manual furniture arrangement methods have the drawback of being difficult to consider the specific needs and limitations of elderly people, making the process of achieving optimal furniture arrangement cumbersome and time-consuming. Furthermore, future changes or readjustments require manually collecting new information and reconsidering the arrangement, which is inefficient.

[0520] 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.

[0521] In this invention, the server includes a means for inputting information about the user's physical limitations and cognitive state, a means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data, and a means for inputting existing furniture information and proposing new furniture. This allows the generative AI to propose optimal furniture layouts that take ergonomics and behavioral patterns into consideration. The resulting layouts generated by the generative AI are visually displayed to the user, providing a virtual simulation, allowing the user to make fine adjustments and finalize the layout. This information can then be fed back to the server for further adjustments or as reference information.

[0522] A "user profile" is data that includes information about a user's physical limitations and cognitive state.

[0523] "Generative AI" is an artificial intelligence system that calculates and suggests optimal furniture layouts taking into account ergonomics and behavioral patterns.

[0524] "Ergonomics" is the science of optimizing the layout of work environments and tools to improve human efficiency and comfort.

[0525] A "virtual simulation" is a digital simulation that allows users to visually review and fine-tune the proposed furniture arrangement.

[0526] "Feedback" is the process by which the user sends the final placement information to the server.

[0527] The "database" is a system that stores user profile information, spatial information, furniture information, etc., and can be used for future readjustments or as reference information.

[0528] The "server" is a central processing unit that manages user profile information, spatial information, and furniture information, and exchanges data with the generating AI.

[0529] A "terminal" is a device that allows a user to input information using a dedicated application and exchange data with a server.

[0530] "Scanning" is the act of converting information such as room dimensions, the location of doors and windows, and the location of power sources into digital data using a camera function.

[0531] The term "means" refers to individual elements or devices that perform a particular function for carrying out the invention.

[0532] The present invention provides a system that utilizes generative AI to optimize the furniture arrangement in a home based on the user's physical limitations and cognitive status, providing a safe and comfortable living environment for the elderly.

[0533] First, the user installs and launches a dedicated application on a device such as a smartphone or tablet. The device then displays questions about the user's physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences. The user answers the questions on the screen and enters this information into the device. The device then sends the collected user profile information to a server, which stores the information in a database.

[0534] Next, the process moves to the spatial information collection phase. The user scans their room using a device such as a smartphone or tablet. Specifically, the camera function is used to scan the room's dimensions, the location of doors and windows, and the location of power sources, and this is converted into digital data. The device then analyzes the scanned image in real time and records it as digital data. The acquired spatial information data is immediately sent to a server and saved.

[0535] When selecting furniture, the server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for their confirmation. The user can enter details of the displayed furniture and receive suggestions for new furniture if necessary. This information is sent to the server in real time and stored in a database.

[0536] In the next step, the server provides all collected information—user profile, spatial information, and furniture information—as input data to a generative AI model. The generative AI calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns. The server outputs the optimal layout proposal calculated by the generative AI in data format and sends it to the device.

[0537] Finally, the device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal if necessary. If the user feels it is finally optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database, allowing it to be used for future adjustments or as reference information for other users.

[0538] Specific examples

[0539] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0540] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0541] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0542] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0543] Finally, the device visually displays the AI's proposed layout to the user and performs a virtual simulation. After making fine adjustments, the user presses the "Confirm" button, and the layout information is sent to the server and stored in a database. By using this system, users can achieve a safe and comfortable living environment in their own homes.

[0544] Prompt Sentence Examples

[0545] "Ask your generative AI to suggest optimal furniture arrangements for a 70-year-old with visual limitations to live safely in their home."

[0546] "Explain how to calculate the optimal furniture placement for a living room, including the placement of a sofa, TV stand, and dining table."

[0547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0548] Specific processing steps of the program

[0549] Step 1:

[0550] The user launches the dedicated application on a device such as a smartphone or tablet. The device then displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. Specifically, the user enters their answers into checkboxes and text boxes on the screen and presses the send button. The input data is profile information including the user's physical limitations and lifestyle habits, and the output data is a data packet that organizes this information.

[0551] Step 2:

[0552] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a database. Specifically, the terminal encodes the user input data and sends it over the network to the server. The server decodes the received data and stores it in a structured format in the database. The input of this step is the user profile information, and the output is the user profile stored in the database.

[0553] Step 3:

[0554] The user scans a room using a device such as a smartphone or tablet. The device uses its camera to scan the room's dimensions, the locations of doors and windows, and power outlets, and converts the data into digital data. Specifically, the user operates the camera while walking around the room, capturing images of the room in real time. The input data is the camera image, and the output data is digital data including the room's dimensions and structural information.

[0555] Step 4:

[0556] The device sends the scanned spatial information data to a server. The server receives this information and stores it in a database. Specifically, the device analyzes the captured video data, identifies the room dimensions and the locations of doors, windows, and power sources, and converts it into a dataset. This dataset is then sent to the server, which receives it and stores it in the database. The input to this step is the spatial information of the room, and the output is the spatial information stored in the database.

[0557] Step 5:

[0558] The server generates a list of existing furniture based on the user profile information and spatial information. The terminal displays this generated furniture list to the user. Specifically, the server compares the user profile and spatial information in the database and generates a list of appropriate furniture. The generated list is sent to the terminal, which displays it to the user. The input of this step is the user profile and spatial information, and the output is a list of furniture.

[0559] Step 6:

[0560] The user enters details of existing furniture and suggests new furniture if necessary. The device sends the information entered by the user to the server. Specifically, the user checks the displayed list of existing furniture and uses tabs and text boxes to enter detailed information and information about new furniture. The device then sends this information to the server. The input to this step is the furniture information entered by the user, and the output is the furniture information stored in the database.

[0561] Step 7:

[0562] The server provides the collected user profile, spatial information, and furniture information to the generation AI. The generation AI considers ergonomics and the user's behavioral patterns to calculate the optimal furniture layout. Specifically, the server inputs all relevant information into the generation AI model, and the generation AI starts calculations. This calculation generates data on the optimal furniture layout. The inputs for this step are the user profile, spatial information, and furniture information, and the output is a dataset containing the optimal furniture layout.

[0563] Step 8:

[0564] The server sends the optimal layout proposal calculated by the generative AI to the device. The device visually displays the proposed furniture layout to the user, providing a virtual simulation. Specifically, the server sends the layout data from the generative AI to the device, which then visually displays it to the user. The user can view and manipulate the layout on the screen. The input of this step is a dataset containing the optimal furniture layout, and the output is a visual layout proposal displayed to the user.

[0565] Step 9:

[0566] The user checks the displayed suggestions and makes fine adjustments as necessary. The device then sends the finalized layout information to the server. Specifically, the user adjusts the furniture layout on the screen by tapping and dragging, and finally presses the "Confirm" button. The device then sends this final layout information to the server. The input to this step is the user's layout adjustment information, and the output is the finalized layout information sent to the server.

[0567] Step 10:

[0568] The server stores the final placement information in a database and uses it for future readjustments and as reference information for other users. Specifically, the server stores the received final placement information in a database and links it with related data as needed. The input of this step is the final placement information, and the output is the placement information stored in the database.

[0569] (Application example 1)

[0570] 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."

[0571] It is necessary to provide a safe and comfortable living environment for the elderly by optimizing the furniture arrangement in their homes to accommodate their physical and cognitive functions. In addition, it is necessary to efficiently support users in physical stores in selecting and arranging the optimal furniture based on their physical limitations and preferences.

[0572] 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.

[0573] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the dimensions of the room, the positions of doors and windows, and the positions of power sources and converting them into digital data; means for inputting information about existing furniture and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results calculated by the generation AI to the user and allowing the user to make adjustments; and means for displaying a list of existing furniture from a furniture store and viewing and selecting furniture details to support the user's interior selection in a physical store, thereby enabling elderly people and users with physical limitations to enjoy a safe and comfortable living environment both inside and outside their homes.

[0574] "Information about the user's physical limitations and cognitive status" refers to information about the user's visual and hearing abilities, physical function status, cognitive function status, and daily living needs and preferences.

[0575] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a method of using a device such as a smartphone or tablet to measure the physical structure of a room through its camera function and convert this into digital data.

[0576] "Means for inputting existing furniture information and making suggestions for new furniture" refers to a method for recording information about furniture that a user currently owns and making suggestions for additional or new furniture based on that information.

[0577] "Generative AI" refers to a system that uses artificial intelligence technology to calculate optimal furniture layouts, taking into account ergonomics and user behavior patterns.

[0578] "Means for visually displaying the placement results of the generative AI to the user and allowing them to make adjustments" refers to an interface that graphically displays the optimal furniture placement calculated by the generative AI to the user, allowing the user to visually check the placement and make fine adjustments.

[0579] "A means for displaying a list of existing furniture in a furniture store and viewing and selecting furniture details to assist users in selecting interior items in a physical store" refers to a method in a furniture shop that allows users to view a list of furniture available in the store and select furniture while checking detailed information.

[0580] A system for implementing the present invention provides various functions to enable elderly people and users with physical limitations to have a safe and comfortable living environment both inside and outside their homes. This system includes an information input means adapted to the user's physical limitations and cognitive state, a means for scanning room dimensions and the locations of doors, windows, and power sources, a means for inputting existing furniture information and proposing new furniture, a means for calculating the optimal furniture layout using a generative AI, a means for visually displaying the layout results generated by the generative AI so that the user can make adjustments, and a means for supporting interior design selection in a physical store.

[0581] Creating a User Profile

[0582] The device (smartphone or tablet) provides an interface through which users can input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences through a dedicated application, which is then sent to a server and stored in a database.

[0583] Collection of spatial information

[0584] Users can use the device's camera to scan the dimensions of their rooms, the locations of doors and windows, and power outlets, and convert this information into digital data. The acquired spatial information is then immediately sent to a server and stored. This processing is done using the camera module and the open-source library "OpenCV."

[0585] Assistance with furniture selection

[0586] The server uses the user profile information and spatial information to generate a list of existing furniture and sends it to the device. The user can then check the existing furniture on the device and receive suggestions for new furniture if necessary.

[0587] Placement suggestions by generative AI

[0588] The server uses a generative AI to calculate the optimal furniture layout based on the collected user profile information, spatial information, and furniture information. The generative AI takes ergonomics and user behavior patterns into account to generate the optimal furniture layout plan. This generative AI uses deep learning libraries such as "PyTorch" or "TensorFlow."

[0589] Viewing and adjusting results

[0590] The device visually displays the placement results generated by the AI, allowing the user to check them through a virtual simulation. After the user makes fine adjustments as needed and confirms the final placement, the information is fed back to the server and stored in a database.

[0591] Support for choosing interior decor in a physical store

[0592] When users visit a physical store, they can check the furniture store's existing furniture list through the application on their device, browse detailed information, select the furniture they like, and incorporate it directly into their layout plan.

[0593] As a concrete example, by inputting the following prompt sentence into the generative AI model, optimal furniture layout suggestions suitable for the user can be obtained.

[0594] Example prompt sentence:

[0595] User profile: Age: 70, Vision limitations: Yes, Mobility: Weak legs, Interior preferences: Kitchen and living room

[0596] Space information: Room dimensions: width 5.0m, height 5.0m, door location: x1.0m, y0.5m, window location: x4.0m, y0.5m, power location: x2.0m, y1.0m

[0597] Furniture list: sofa, TV stand, dining table

[0598] This allows seniors to get furniture arrangement plans that suit their needs and limitations.

[0599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0600] Step 1:

[0601] The user installs and launches a dedicated application on their device (smartphone or tablet).

[0602] Input: Information such as the user's physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences.

[0603] How it works: The application collects this information through the user interface and formats it as digital data.

[0604] Output: User profile data is generated and sent to the server.

[0605] Step 2:

[0606] The device helps users scan their home to determine the dimensions of rooms, the location of doors and windows, and the location of power outlets.

[0607] Input: Room video data collected using the device's camera function.

[0608] How it works: It uses OpenCV to analyze camera footage and converts the room dimensions, the location of doors and windows, and the location of power sources into digital data.

[0609] Output: Spatial information data is generated and sent to the server.

[0610] Step 3:

[0611] The server receives the user profile data and spatial information data and stores them in a database.

[0612] Input: User profile data and spatial information data.

[0613] What it does: Efficiently stores incoming data and saves it in a database to serve as an input dataset for generative AI.

[0614] Output: User profile data and spatial information data stored in a database.

[0615] Step 4:

[0616] The server provides the user with a list of existing furniture based on the generated data.

[0617] Input: User profile data and spatial information data in the database.

[0618] Operation: Generates a list of existing furniture and sends the list to the user's device.

[0619] Output: A list of existing furniture displayed on the device.

[0620] Step 5:

[0621] Users can review their existing furniture list and receive suggestions for new furniture.

[0622] Input: Existing furniture list and user furniture selection information.

[0623] How it works: The user sees the furniture list on their device and uses the interface to add / modify new furniture.

[0624] Output: The updated furniture list is sent to the server.

[0625] Step 6:

[0626] The server provides the collected data to a generative AI model to calculate the optimal furniture layout.

[0627] Input: User profile data, spatial information data, updated furniture list.

[0628] How it works: Data is fed into a generative AI model (PyTorch or TensorFlow) to calculate optimal furniture layouts, taking into account ergonomics and behavioral patterns.

[0629] Output: The optimal furniture layout plan is generated and stored on the server.

[0630] Step 7:

[0631] The server transmits the generated placement plan to the user's terminal and displays it visually.

[0632] Input: Furniture layout ideas generated by a generative AI model.

[0633] What it does: Loads furniture layout ideas and sends them to the user's device.

[0634] Output: Furniture layout proposals visually displayed on the device.

[0635] Step 8:

[0636] Users can check the layout plan through a virtual simulation and make adjustments as necessary.

[0637] Input: Furniture layout suggestions displayed on the device.

[0638] How it works: The user uses the virtual simulation to view furniture placement, make adjustments as needed, and finalize the layout.

[0639] Output: The final placement proposal is fine-tuned and fed back to the server.

[0640] Step 9:

[0641] The server stores the final placement plan in a database for future reference and readjustment.

[0642] Input: Final, fine-tuned layout proposal.

[0643] How it works: Saves the final placement plan to a database for future refinements and as a reference for other users.

[0644] Output: Final placement proposal stored in database.

[0645] These processing steps allow the user to plan an efficient and optimal furniture arrangement.

[0646] 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.

[0647] The system for implementing the present invention is implemented as a combination of a means for optimizing furniture arrangement in the home according to the user's physical limitations and cognitive state, and an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions accordingly. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[0648] Program processing explanation

[0649] 1. Create a user profile

[0650] The user launches a dedicated application on the device. The device then displays a questionnaire about the user's physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server. The server stores this information in a database for later processing.

[0651] 2. Collecting spatial information

[0652] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[0653] 3. Furniture selection assistance

[0654] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[0655] 4. Placement suggestions using generative AI

[0656] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[0657] 5. Emotion Recognition by Emotion Engine

[0658] When a user receives furniture layout suggestions, the device recognizes the user's emotions in real time using the device's camera and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions.

[0659] 6. Adjusting and displaying the proposed results

[0660] The emotion engine sends the emotional data it recognizes to the server and stores it. The server then uses this emotional data to adjust the placement proposals made by the generation AI. For example, if the user is dissatisfied, the generation AI will review and recalculate the placement proposals. The server then sends the adjusted results to the device, which then visually displays them to the user.

[0661] 7. Finalize and save

[0662] If the user is satisfied with the proposed placement and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The device then sends the confirmed placement information to the server as feedback. The server stores this final placement information in a database and uses it for future readjustments and as reference information for other users.

[0663] Specific examples

[0664] 1. Create a user profile

[0665] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0666] 2. Collecting spatial information

[0667] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, which stores it.

[0668] 3. Furniture selection assistance

[0669] The server generates existing furniture information based on the user profile and spatial information. The terminal prompts the user to input existing furniture information such as "sofa," "TV stand," and "dining table," and will also suggest new furniture if necessary. The input information is sent to the server and saved in a database.

[0670] 4. Placement suggestions using generative AI

[0671] The server provides the collected information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0672] 5. Emotion Recognition by Emotion Engine

[0673] When a user receives a placement suggestion, the device analyzes the user's emotions in real time through the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the suggestion.

[0674] 6. Adjusting and displaying the proposed results

[0675] The emotion data recognized by the emotion engine is sent to the server, which then provides feedback to the generation AI, recalculating and adjusting it as needed. The adjusted results are then sent back to the device and displayed visually to the user.

[0676] 7. Finalize and save

[0677] When the user is satisfied with the adjustment results and finalizes the placement, they press the "Confirm" button on their device to send the placement information to the server. The server then stores the final placement information in a database, which can be used for future readjustments or as reference information for other users.

[0678] This system will enable elderly people to have a safe and comfortable living environment that also takes into consideration their emotional satisfaction.

[0679] The processing flow will be explained below.

[0680] Step 1:

[0681] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[0682] Step 2:

[0683] Users answer questions on the device and input information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[0684] Step 3:

[0685] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[0686] Step 4:

[0687] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[0688] Step 5:

[0689] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[0690] Step 6:

[0691] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[0692] Step 7:

[0693] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[0694] Step 8:

[0695] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[0696] Step 9:

[0697] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[0698] Step 10:

[0699] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[0700] Step 11:

[0701] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[0702] Step 12:

[0703] While the user is reviewing the placement proposal, the device's camera and microphone are used to collect the user's emotions in real time. The emotion engine analyzes the user's emotional data and determines how the user feels about the proposal.

[0704] Step 13:

[0705] The emotion engine sends the recognized emotion data to the server, which then adjusts the placement proposals of the generation AI based on this data. If the user is dissatisfied, the generation AI will review the proposals and recalculate.

[0706] Step 14:

[0707] The server sends the adjusted placement results to the terminal, which visually displays them to the user, allowing them to confirm the improved suggestions.

[0708] Step 15:

[0709] If the user is satisfied with the adjusted proposal, he / she presses the confirm button on the device to confirm the final arrangement, and the device sends the confirmed arrangement information to the server as feedback.

[0710] Step 16:

[0711] The server stores the final placement information in a database for future readjustments and as reference for other users.

[0712] In this way, the system of the present invention provides a safe and comfortable living environment while also taking into account the user's emotional state.

[0713] Example 2

[0714] 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."

[0715] Elderly people often have difficulty arranging furniture in their daily lives due to physical limitations and cognitive conditions. Furthermore, declining visual, auditory, and motor functions make it difficult to ensure a safe and comfortable living space. Furthermore, existing systems do not consider the user's emotions when proposing furniture arrangements, which may result in low user satisfaction. Therefore, a new system is needed that can propose appropriate furniture arrangements for elderly people and also consider their emotional satisfaction.

[0716] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power source locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for recognizing the user's emotional data regarding the proposed furniture layout in real time; means including an emotion engine for adjusting the layout proposal based on the emotional data; and means for visually displaying the layout results calculated by the generation AI and emotion engine to the user and allowing the user to make adjustments. This allows the elderly to not only receive the optimal furniture layout based on their physical limitations and cognitive state, but also to enjoy a safe and comfortable living environment that takes emotional satisfaction into consideration.

[0717] "Information about the user's physical limitations and cognitive status" refers to data about the user's physical limitations and cognitive capabilities.

[0718] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to technology that uses a scanning device such as a camera to measure the location and dimensions of each element in a room and converts that information into a digital format.

[0719] "Means for inputting existing furniture information and proposing new furniture" refers to technology that allows users to input information about furniture they already own and then suggests the most suitable new furniture based on that information.

[0720] "Generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to artificial intelligence technology that calculates effective and efficient furniture layout within a living space based on ergonomics and user behavioral patterns.

[0721] "Means for recognizing the user's emotional data regarding the proposed furniture layout in real time" refers to technology that uses sensors such as cameras and microphones to analyze in real time how the user feels about the presented furniture layout.

[0722] "Emotion engine for adjusting furniture placement suggestions based on emotional data" refers to technology that analyzes a user's emotional data and optimizes furniture placement suggestions based on the results.

[0723] "Means for visually displaying the placement results of the generative AI and emotion engine to the user and allowing adjustments" refers to technology that displays the furniture placement calculated by the generative AI and emotion engine to the user in a graphical format and allows the user to change the placement as needed.

[0724] "Means of storing the calculation results of the generative AI and emotion engine on a server and using them for future readjustments" refers to technology that stores the placement results calculated by the generative AI and emotion engine on a server, and reuses that data at a later date to make appropriate adjustments.

[0725] "Proposals to provide users with a safe and comfortable living environment" refers to technology that suggests furniture arrangements and living environment improvements necessary for users to live safely and comfortably.

[0726] A system for implementing this invention combines a means for optimizing furniture arrangement in a home according to a user's physical limitations and cognitive state with an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[0727] First, the user launches a dedicated application that can be used at home on a device such as a smartphone. This application displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences, and the user answers the questions. The response data is sent from the device to a server and stored in a database.

[0728] Next, the user scans a room in their home using a device such as a smartphone or tablet. The camera function captures the dimensions of the room, the location of doors and windows, the location of power outlets, and other information, and records this data digitally. The scanned data is also sent to a server and stored.

[0729] The server generates a list of existing furniture based on the user profile information and spatial information. This list is displayed on the terminal, and the user inputs details of each piece of furniture. New furniture items are also suggested as needed. The information entered by the user is sent to the server in real time and stored in a database.

[0730] The server then provides the collected user profile, spatial information, and furniture information as input data to the generation AI, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the device via the server in a data format such as JSON.

[0731] When receiving furniture layout suggestions, the device recognizes the user's emotions in real time using camera functions and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions. The recognized emotional data is sent to the server and stored.

[0732] The server adjusts the placement proposals made by the generation AI based on the emotional data. For example, if the user is dissatisfied, the generation AI will review the placement proposal and recalculate. The adjusted results are then sent back to the device by the server, where the user can visually confirm them.

[0733] If the user is satisfied with the placement proposal and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The confirmation information sent from the device is sent to the server as feedback and saved in the database as the final placement information. This information can be used for future readjustments or as reference information for other users.

[0734] Specific examples

[0735] Users launch a dedicated application on their smartphone and enter information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0736] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the room and the location of doors, windows, and power outlets, which is then sent from the device to a server where it is stored.

[0737] The server then generates a list of existing furniture based on the user profile and spatial information. The list includes items such as a sofa, TV stand, and dining table, and the user inputs details of these items. New furniture is also suggested as needed, and the information is also saved on the server.

[0738] The server provides the collected information to the AI ​​generator, which calculates the optimal layout taking into account ergonomics and behavioral patterns. For example, it suggests "placing the TV in a location that is easy to watch" or "placing the TV in a location with few obstacles when walking." The calculation results are sent to the device via the server and can be confirmed by the user.

[0739] While the user is reviewing the placement proposal, the device uses a camera and microphone to analyze the user's emotions in real time, which are then analyzed by the emotion engine. For example, if the user looks at the placement with a smile, it is judged to be "satisfied." The emotion data is sent to the server and stored.

[0740] The server provides feedback to the AI ​​based on the emotion data, and performs recalculation and adjustments. The adjusted placement is then sent back to the device and visually displayed to the user.

[0741] When the user is satisfied with the final arrangement and presses the confirm button, the arrangement information is sent to the server and stored in a database.

[0742] Prompt Sentence Examples

[0743] "Please suggest the optimal furniture arrangement that meets the following requirements so that the elderly can live safely and comfortably."

[0744] User profile: Limited vision, weak legs, frequent kitchen users

[0745] Spatial information: dimensions of living room, kitchen, bedrooms, and locations of doors, windows, and power outlets

[0746] Furniture information: sofa, TV stand, dining table

[0747] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0748] Step 1:

[0749] The user launches a dedicated application on the device and enters information about their physical limitations and cognitive status.

[0750] Specific operations: The user launches a dedicated smartphone app and answers questions on a screen about things like "visual limitations," "hearing limitations," and "daily life needs."

[0751] Input: Information about physical limitations and cognitive status (e.g., limited vision, weak legs)

[0752] Output: User profile information is sent to the server and stored in the database.

[0753] Step 2:

[0754] The user uses the device to scan the room's dimensions, the location of doors and windows, and the location of power sources.

[0755] How it works: A user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the location of doors, windows, and power outlets.

[0756] Input: Room spatial information from camera images

[0757] Output: Sent as digital data to a server and stored in a database.

[0758] Step 3:

[0759] The server generates a list of existing furniture based on the user profile information and the spatial information.

[0760] Specific operation: The server generates a list of existing furniture such as "sofa," "TV stand," and "dining table" based on the user profile and room information.

[0761] Input: User profile information, spatial information

[0762] Output: Generate a list of existing furniture and send it to the device.

[0763] Step 4:

[0764] The device displays a list of existing furniture to the user, provides detailed information, and suggests new furniture.

[0765] Specific operation: The device displays the generated furniture list to the user, and the user enters details for each piece of furniture. New furniture pieces are also suggested as needed.

[0766] Input: Existing furniture list

[0767] Output: The furniture details entered by the user are sent to the server and stored in the database.

[0768] Step 5:

[0769] The server provides the collected information to the generation AI, which calculates the optimal furniture layout.

[0770] Specific operation: The server inputs the user profile, spatial information, and furniture information into the generative AI model, which then calculates the optimal furniture layout.

[0771] Input: User profile information, space information, furniture information

[0772] Output: The generated AI sends the optimal placement proposal data to the device.

[0773] Step 6:

[0774] The device uses a camera and microphone to recognize the user's emotions in real time.

[0775] Specific operation: While the user is viewing the placement suggestions, the device uses the camera and microphone to analyze the user's emotions.

[0776] Input: User's facial expressions and voice

[0777] Output: Emotion data is sent to the server and analyzed by the emotion engine.

[0778] Step 7:

[0779] The server adjusts placement suggestions made by the generative AI based on the emotional data.

[0780] Specific operation: The server feeds emotion data back to the generation AI, which then recalculates and adjusts the placement proposal.

[0781] Input: Emotion data

[0782] Output: The adjusted placement proposal data is sent to the terminal.

[0783] Step 8:

[0784] The terminal visually displays the adjusted placement proposal to the user and asks for reconfirmation.

[0785] Specific behavior: The device displays the adjusted furniture layout to the user, who then confirms it.

[0786] Input: Adjusted placement proposal

[0787] Output: User enters feedback for review and final adjustment.

[0788] Step 9:

[0789] The user confirms the final arrangement and presses the "confirm" button on the terminal.

[0790] Specific operation: The user confirms the final adjusted placement and presses the "Confirm" button on the device.

[0791] Input: User confirmation

[0792] Output: The final placement information is sent to the server and stored in the database.

[0793] In this way, a system is realized that proposes optimal furniture arrangements according to the physical limitations and cognitive state of the elderly, and provides a safe and comfortable living environment that also takes into account the user's emotional satisfaction.

[0794] (Application example 2)

[0795] 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."

[0796] To provide a safe and comfortable living environment that accommodates the physical and cognitive functions of elderly people, it is necessary to optimize furniture arrangement within the home. However, conventional methods for furniture arrangement do not fully consider the physical limitations, cognitive state, and emotions of elderly people, making it difficult to increase user satisfaction. Furthermore, there is a problem in that feedback on the proposed furniture arrangement is not provided in real time, making it difficult to make appropriate adjustments.

[0797] 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.

[0798] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results generated by the generation AI to the user and allowing the user to make adjustments; means for recognizing the user's emotions in real time using an emotion engine and adjusting the proposal results; and means for performing a final confirmation of the proposal results and saving the confirmed layout information on the server. This makes it possible to propose and adjust a safe and comfortable furniture layout that comprehensively takes into consideration the user's physical limitations, cognitive state, and emotions.

[0799] The "means for inputting information about the user's physical limitations and cognitive status" is an interface that collects information about the user's physical and cognitive functions and inputs it as digital data.

[0800] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a technology that uses a smartphone or tablet camera to scan the dimensions and structure of a room and converts it into digital data.

[0801] The "means for inputting existing furniture information and proposing new furniture" is an interface that allows the user to input information about furniture they already own and then suggests new furniture based on that information.

[0802] "Means including a generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to a system that incorporates a generative AI that calculates optimal furniture layout taking into account ergonomics and user behavioral patterns.

[0803] "Means for visually displaying the placement results of the generative AI to the user and allowing adjustments" refers to an interface that visually displays the furniture placement results calculated by the generative AI to the user and allows adjustments to be made based on the user's opinions and feedback.

[0804] "Means for recognizing user emotions in real time using an emotion engine and adjusting the proposed results" is a system that uses sensors such as cameras and microphones to recognize user emotions in real time and adjusts furniture placement proposals based on that emotional data.

[0805] The "means for making a final confirmation of the proposed furniture arrangement and storing the confirmed arrangement information on the server" is a means for the user to make a final confirmation of the proposed furniture arrangement and store the confirmed information on the server.

[0806] This invention uses a server, terminals, generative AI models, and emotion engines to optimize furniture placement according to the user's physical limitations and cognitive state, providing a comfortable and safe living environment.

[0807] Hardware and software used

[0808] Device: Smartphone or tablet

[0809] Server: Amazon Web Services (AWS), MySQL

[0810] Generative AI model: OpenAI GPT-4

[0811] Emotion engine: IBM Watson Tone Analyzer

[0812] Image analysis: ARKit (iOS) / ARCore (Android), OpenCV

[0813] Program processing explanation

[0814] 1. Create a user profile

[0815] The server allows users to launch a dedicated application on their device and input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences, which is then sent to the server in JSON format and stored in a database.

[0816] 2. Collecting spatial information

[0817] The device uses its camera to scan the dimensions of the room, the location of doors and windows, and the location of power sources, and converts this data into digital data, which is also sent to a server and stored.

[0818] 3. Furniture selection assistance

[0819] The server generates existing furniture information based on the user profile information and spatial information. This information is displayed on the terminal, and the user can add or modify it. This data is also saved on the server in real time.

[0820] 4. Placement suggestions using generative AI

[0821] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model. The generative AI model calculates the optimal furniture layout based on this information and returns the results to the server. The results are then visually displayed on the device.

[0822] 5. Emotion Recognition by Emotion Engine

[0823] The device uses a camera and microphone to recognize the user's emotions in real time when the user is checking the placement proposal. The emotion engine analyzes this data and transmits the user's emotion data to the server.

[0824] 6. Adjusting and displaying the proposed results

[0825] The server adjusts the placement proposals made by the generative AI based on the emotional data recognized by the emotion engine. The recalculated optimal placement proposal is sent back to the device and visually displayed to the user.

[0826] 7. Finalize and save

[0827] If the user is satisfied with the proposed placement and confirms it, they press the "Confirm" button on their device. The confirmed placement information is saved on the server and can be used for future readjustments or as reference information for other users.

[0828] Specific examples

[0829] A 70-year-old user launches a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device sends the entered information to a server and stores it in a database. The user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, where it is stored. The server generates existing furniture information based on the user profile and spatial information. The device then prompts the user to enter existing furniture information such as a sofa, TV stand, and dining table, and suggests new furniture if necessary. The input information is sent to the server and stored in a database. The server then provides the collected information to a generation AI, which calculates the optimal furniture layout. The generation AI generates layout proposals that take ergonomics and behavioral patterns into account and sends the data to the device via the server. When the user receives the layout proposals, the device analyzes the user's emotions in real time using the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the proposals. The emotion data recognized by the emotion engine is sent to the server, which provides feedback to the generation AI and performs recalculations and adjustments as appropriate. The adjusted results are sent back to the device and visually displayed to the user. When the user is satisfied with the adjustment results and has finalized the placement, they press the "Confirm" button on the device, which sends the placement information to the server. The server saves the final placement information in a database and uses it for future readjustments and as reference information for other users.

[0830] Prompt Sentence Examples

[0831] User: 75-year-old female, weak legs, normal vision. Scan data of the room is as follows.

[0832] Living room: 4m wide, 5m deep, 2.5m high, window located in the center, power outlet on the left wall.

[0833] Current furniture: sofa, TV stand, low table.

[0834] Suggestion: I have weak legs, so I would like low furniture. Please suggest adding a height-adjustable bed and a chair with soft cushions.

[0835] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0836] Step 1:

[0837] The user starts up the device and opens the dedicated application. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The information entered by the user is sent to the server in JSON format, which is then stored in a database.

[0838] Input: Information about the user's physical limitations, cognitive state, and preferences

[0839] Data processing: Convert input information into JSON format

[0840] Output: User profile data sent to the server

[0841] Step 2:

[0842] The user uses the camera function of their smartphone to scan the dimensions of the room, the location of doors and windows, and the location of power sources. The device analyzes the captured image data in real time and converts the dimensional information and other data into digital data. This data is then sent to the server and stored.

[0843] Input: Room image data

[0844] Data processing: Analyze image data and extract dimensional and positional information

[0845] Output: Digital data sent to the server

[0846] Step 3:

[0847] The server generates a list of existing furniture based on the user profile information and spatial information. This generated furniture information is displayed on the terminal, and the user can enter details of each piece of furniture and receive suggestions for new furniture. The entered information is sent to the server in real time and saved.

[0848] Input: User profile information, spatial information

[0849] Data processing: Creating a list of existing furniture and entering detailed information

[0850] Output: Furniture list displayed on the device, furniture information stored on the server

[0851] Step 4:

[0852] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the server and then visually displayed on the device.

[0853] Input: User profile, space information, furniture information

[0854] Data processing: Calculating optimal furniture placement using a generative AI model

[0855] Output: Furniture layout proposal displayed on the device

[0856] Step 5:

[0857] When the user confirms the placement proposal, the device uses the camera and microphone to recognize the user's emotions in real time. The emotion engine analyzes image and voice data and transmits the user's emotional data to the server.

[0858] Input: image data, audio data

[0859] Data processing: Emotion analysis using an emotion engine

[0860] Output: Emotion data sent to the server

[0861] Step 6:

[0862] The server adjusts the furniture layout proposals made by the generative AI based on the emotion data received from the emotion engine. New proposals are generated, and the recalculated optimal layout plan is sent to the terminal and visually displayed to the user.

[0863] Input: Emotion data, initial placement proposal

[0864] Data processing: Recalculation and alignment using generative AI models

[0865] Output: Re-proposed furniture layout displayed on the device

[0866] Step 7:

[0867] When the user is satisfied with the proposed furniture arrangement, they press the confirm button to finalize the furniture arrangement. The confirmed arrangement information is sent from the device to the server and stored in a database. It can be used for future readjustments or as reference information for other users.

[0868] Input: Confirmed placement information

[0869] Data processing: Confirmed placement information is saved in the database

[0870] Output: Final placement information saved on the server

[0871] 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.

[0872] 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.

[0873] 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.

[0874] [Third embodiment]

[0875] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0876] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0877] 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).

[0878] 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.

[0879] 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.

[0880] 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).

[0881] 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. 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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."

[0887] The system for implementing the present invention is implemented in a form that includes multiple means for optimizing furniture arrangement in a home according to the user's physical limitations and cognitive status. This system uses generative AI to provide a safe and comfortable living environment for the elderly.

[0888] Program processing explanation

[0889] 1. Create a user profile

[0890] The user launches a dedicated application on the device. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server, which stores this information in a database for later processing.

[0891] 2. Collecting spatial information

[0892] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[0893] 3. Furniture selection assistance

[0894] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[0895] 4. Placement suggestions using generative AI

[0896] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[0897] 5. Viewing and adjusting results

[0898] The device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal as needed. If the user feels it is optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database for future adjustments and as reference information for other users.

[0899] Specific examples

[0900] 1. Create a user profile

[0901] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0902] 2. Collecting spatial information

[0903] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0904] 3. Furniture selection assistance

[0905] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0906] 4. Placement suggestions using generative AI

[0907] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0908] 5. Viewing and adjusting results

[0909] The device visually displays the AI's proposed placement to the user and performs a virtual simulation. After the user makes some fine adjustments and presses the "Confirm" button, the placement information is sent to the server and stored in a database.

[0910] This system will enable elderly people to have a safe and comfortable living environment in their own homes.

[0911] The processing flow will be explained below.

[0912] Step 1:

[0913] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[0914] Step 2:

[0915] Users answer questions on the device and enter information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[0916] Step 3:

[0917] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[0918] Step 4:

[0919] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[0920] Step 5:

[0921] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[0922] Step 6:

[0923] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[0924] Step 7:

[0925] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[0926] Step 8:

[0927] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[0928] Step 9:

[0929] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[0930] Step 10:

[0931] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[0932] Step 11:

[0933] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[0934] Step 12:

[0935] When the user is satisfied with the arrangement, he / she presses the "confirm" button on the device, and the device sends the final arrangement information to the server as feedback.

[0936] Step 13:

[0937] The server stores the determined placement information in a database and makes it available for future readjustments or as reference for other users, thereby improving the safety and comfort of users in their homes.

[0938] Example 1

[0939] 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."

[0940] Optimizing furniture arrangement in the home to accommodate the physical and cognitive functions of elderly people is important for providing a safe and comfortable living environment. However, traditional manual furniture arrangement methods have the drawback of being difficult to consider the specific needs and limitations of elderly people, making the process of achieving optimal furniture arrangement cumbersome and time-consuming. Furthermore, future changes or readjustments require manually collecting new information and reconsidering the arrangement, which is inefficient.

[0941] 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.

[0942] In this invention, the server includes a means for inputting information about the user's physical limitations and cognitive state, a means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data, and a means for inputting existing furniture information and proposing new furniture. This allows the generative AI to propose optimal furniture layouts that take ergonomics and behavioral patterns into consideration. The resulting layouts generated by the generative AI are visually displayed to the user, providing a virtual simulation, allowing the user to make fine adjustments and finalize the layout. This information can then be fed back to the server for further adjustments or as reference information.

[0943] A "user profile" is data that includes information about a user's physical limitations and cognitive state.

[0944] "Generative AI" is an artificial intelligence system that calculates and suggests optimal furniture layouts taking into account ergonomics and behavioral patterns.

[0945] "Ergonomics" is the science of optimizing the layout of work environments and tools to improve human efficiency and comfort.

[0946] A "virtual simulation" is a digital simulation that allows users to visually review and fine-tune the proposed furniture arrangement.

[0947] "Feedback" is the process by which the user sends the final placement information to the server.

[0948] The "database" is a system that stores user profile information, spatial information, furniture information, etc., and can be used for future readjustments or as reference information.

[0949] The "server" is a central processing unit that manages user profile information, spatial information, and furniture information, and exchanges data with the generating AI.

[0950] A "terminal" is a device that allows a user to input information using a dedicated application and exchange data with a server.

[0951] "Scanning" is the act of converting information such as room dimensions, the location of doors and windows, and the location of power sources into digital data using a camera function.

[0952] The term "means" refers to individual elements or devices that perform a particular function for carrying out the invention.

[0953] The present invention provides a system that utilizes generative AI to optimize the furniture arrangement in a home based on the user's physical limitations and cognitive status, providing a safe and comfortable living environment for the elderly.

[0954] First, the user installs and launches a dedicated application on a device such as a smartphone or tablet. The device then displays questions about the user's physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences. The user answers the questions on the screen and enters this information into the device. The device then sends the collected user profile information to a server, which stores the information in a database.

[0955] Next, the process moves to the spatial information collection phase. The user scans their room using a device such as a smartphone or tablet. Specifically, the camera function is used to scan the room's dimensions, the location of doors and windows, and the location of power sources, and this is converted into digital data. The device then analyzes the scanned image in real time and records it as digital data. The acquired spatial information data is immediately sent to a server and saved.

[0956] When selecting furniture, the server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for their confirmation. The user can enter details of the displayed furniture and receive suggestions for new furniture if necessary. This information is sent to the server in real time and stored in a database.

[0957] In the next step, the server provides all collected information—user profile, spatial information, and furniture information—as input data to a generative AI model. The generative AI calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns. The server outputs the optimal layout proposal calculated by the generative AI in data format and sends it to the device.

[0958] Finally, the device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal if necessary. If the user feels it is finally optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database, allowing it to be used for future adjustments or as reference information for other users.

[0959] Specific examples

[0960] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[0961] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[0962] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[0963] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[0964] Finally, the device visually displays the AI's proposed layout to the user and performs a virtual simulation. After making fine adjustments, the user presses the "Confirm" button, and the layout information is sent to the server and stored in a database. By using this system, users can achieve a safe and comfortable living environment in their own homes.

[0965] Prompt Sentence Examples

[0966] "Ask your generative AI to suggest optimal furniture arrangements for a 70-year-old with visual limitations to live safely in their home."

[0967] "Explain how to calculate the optimal furniture placement for a living room, including the placement of a sofa, TV stand, and dining table."

[0968] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0969] Specific processing steps of the program

[0970] Step 1:

[0971] The user launches the dedicated application on a device such as a smartphone or tablet. The device then displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. Specifically, the user enters their answers into checkboxes and text boxes on the screen and presses the send button. The input data is profile information including the user's physical limitations and lifestyle habits, and the output data is a data packet that organizes this information.

[0972] Step 2:

[0973] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a database. Specifically, the terminal encodes the user input data and sends it over the network to the server. The server decodes the received data and stores it in a structured format in the database. The input of this step is the user profile information, and the output is the user profile stored in the database.

[0974] Step 3:

[0975] The user scans a room using a device such as a smartphone or tablet. The device uses its camera to scan the room's dimensions, the locations of doors and windows, and power outlets, and converts the data into digital data. Specifically, the user operates the camera while walking around the room, capturing images of the room in real time. The input data is the camera image, and the output data is digital data including the room's dimensions and structural information.

[0976] Step 4:

[0977] The device sends the scanned spatial information data to a server. The server receives this information and stores it in a database. Specifically, the device analyzes the captured video data, identifies the room dimensions and the locations of doors, windows, and power sources, and converts it into a dataset. This dataset is then sent to the server, which receives it and stores it in the database. The input to this step is the spatial information of the room, and the output is the spatial information stored in the database.

[0978] Step 5:

[0979] The server generates a list of existing furniture based on the user profile information and spatial information. The terminal displays this generated furniture list to the user. Specifically, the server compares the user profile and spatial information in the database and generates a list of appropriate furniture. The generated list is sent to the terminal, which displays it to the user. The input of this step is the user profile and spatial information, and the output is a list of furniture.

[0980] Step 6:

[0981] The user enters details of existing furniture and suggests new furniture if necessary. The device sends the information entered by the user to the server. Specifically, the user checks the displayed list of existing furniture and uses tabs and text boxes to enter detailed information and information about new furniture. The device then sends this information to the server. The input to this step is the furniture information entered by the user, and the output is the furniture information stored in the database.

[0982] Step 7:

[0983] The server provides the collected user profile, spatial information, and furniture information to the generation AI. The generation AI considers ergonomics and the user's behavioral patterns to calculate the optimal furniture layout. Specifically, the server inputs all relevant information into the generation AI model, and the generation AI starts calculations. This calculation generates data on the optimal furniture layout. The inputs for this step are the user profile, spatial information, and furniture information, and the output is a dataset containing the optimal furniture layout.

[0984] Step 8:

[0985] The server sends the optimal layout proposal calculated by the generative AI to the device. The device visually displays the proposed furniture layout to the user, providing a virtual simulation. Specifically, the server sends the layout data from the generative AI to the device, which then visually displays it to the user. The user can view and manipulate the layout on the screen. The input of this step is a dataset containing the optimal furniture layout, and the output is a visual layout proposal displayed to the user.

[0986] Step 9:

[0987] The user checks the displayed suggestions and makes fine adjustments as necessary. The device then sends the finalized layout information to the server. Specifically, the user adjusts the furniture layout on the screen by tapping and dragging, and finally presses the "Confirm" button. The device then sends this final layout information to the server. The input to this step is the user's layout adjustment information, and the output is the finalized layout information sent to the server.

[0988] Step 10:

[0989] The server stores the final placement information in a database and uses it for future readjustments and as reference information for other users. Specifically, the server stores the received final placement information in a database and links it with related data as needed. The input of this step is the final placement information, and the output is the placement information stored in the database.

[0990] (Application example 1)

[0991] 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."

[0992] It is necessary to provide a safe and comfortable living environment for the elderly by optimizing the furniture arrangement in their homes to accommodate their physical and cognitive functions. In addition, it is necessary to efficiently support users in physical stores in selecting and arranging the optimal furniture based on their physical limitations and preferences.

[0993] 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.

[0994] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the dimensions of the room, the positions of doors and windows, and the positions of power sources and converting them into digital data; means for inputting information about existing furniture and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results calculated by the generation AI to the user and allowing the user to make adjustments; and means for displaying a list of existing furniture from a furniture store and viewing and selecting furniture details to support the user's interior selection in a physical store, thereby enabling elderly people and users with physical limitations to enjoy a safe and comfortable living environment both inside and outside their homes.

[0995] "Information about the user's physical limitations and cognitive status" refers to information about the user's visual and hearing abilities, physical function status, cognitive function status, and daily living needs and preferences.

[0996] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a method of using a device such as a smartphone or tablet to measure the physical structure of a room through its camera function and convert this into digital data.

[0997] "Means for inputting existing furniture information and making suggestions for new furniture" refers to a method for recording information about furniture that a user currently owns and making suggestions for additional or new furniture based on that information.

[0998] "Generative AI" refers to a system that uses artificial intelligence technology to calculate optimal furniture layouts, taking into account ergonomics and user behavior patterns.

[0999] "Means for visually displaying the placement results of the generative AI to the user and allowing them to make adjustments" refers to an interface that graphically displays the optimal furniture placement calculated by the generative AI to the user, allowing the user to visually check the placement and make fine adjustments.

[1000] "A means for displaying a list of existing furniture in a furniture store and viewing and selecting furniture details to assist users in selecting interior items in a physical store" refers to a method in a furniture shop that allows users to view a list of furniture available in the store and select furniture while checking detailed information.

[1001] A system for implementing the present invention provides various functions to enable elderly people and users with physical limitations to have a safe and comfortable living environment both inside and outside their homes. This system includes an information input means adapted to the user's physical limitations and cognitive state, a means for scanning room dimensions and the locations of doors, windows, and power sources, a means for inputting existing furniture information and proposing new furniture, a means for calculating the optimal furniture layout using a generative AI, a means for visually displaying the layout results generated by the generative AI so that the user can make adjustments, and a means for supporting interior design selection in a physical store.

[1002] Creating a User Profile

[1003] The device (smartphone or tablet) provides an interface through which users can input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences through a dedicated application, which is then sent to a server and stored in a database.

[1004] Collection of spatial information

[1005] Users can use the device's camera to scan the dimensions of their rooms, the locations of doors and windows, and power outlets, and convert this information into digital data. The acquired spatial information is then immediately sent to a server and stored. This processing is done using the camera module and the open-source library "OpenCV."

[1006] Assistance with furniture selection

[1007] The server uses the user profile information and spatial information to generate a list of existing furniture and sends it to the device. The user can then check the existing furniture on the device and receive suggestions for new furniture if necessary.

[1008] Placement suggestions by generative AI

[1009] The server uses a generative AI to calculate the optimal furniture layout based on the collected user profile information, spatial information, and furniture information. The generative AI takes ergonomics and user behavior patterns into account to generate the optimal furniture layout plan. This generative AI uses deep learning libraries such as "PyTorch" or "TensorFlow."

[1010] Viewing and adjusting results

[1011] The device visually displays the placement results generated by the AI, allowing the user to check them through a virtual simulation. After the user makes fine adjustments as needed and confirms the final placement, the information is fed back to the server and stored in a database.

[1012] Support for choosing interior decor in a physical store

[1013] When users visit a physical store, they can check the furniture store's existing furniture list through the application on their device, browse detailed information, select the furniture they like, and incorporate it directly into their layout plan.

[1014] As a concrete example, by inputting the following prompt sentence into the generative AI model, optimal furniture layout suggestions suitable for the user can be obtained.

[1015] Example prompt sentence:

[1016] User profile: Age: 70, Vision limitations: Yes, Mobility: Weak legs, Interior preferences: Kitchen and living room

[1017] Space information: Room dimensions: width 5.0m, height 5.0m, door location: x1.0m, y0.5m, window location: x4.0m, y0.5m, power location: x2.0m, y1.0m

[1018] Furniture list: sofa, TV stand, dining table

[1019] This allows seniors to get furniture arrangement plans that suit their needs and limitations.

[1020] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1021] Step 1:

[1022] The user installs and launches a dedicated application on their device (smartphone or tablet).

[1023] Input: Information such as the user's physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences.

[1024] How it works: The application collects this information through the user interface and formats it as digital data.

[1025] Output: User profile data is generated and sent to the server.

[1026] Step 2:

[1027] The device helps users scan their home to determine the dimensions of rooms, the location of doors and windows, and the location of power outlets.

[1028] Input: Room video data collected using the device's camera function.

[1029] How it works: It uses OpenCV to analyze camera footage and converts the room dimensions, the location of doors and windows, and the location of power sources into digital data.

[1030] Output: Spatial information data is generated and sent to the server.

[1031] Step 3:

[1032] The server receives the user profile data and spatial information data and stores them in a database.

[1033] Input: User profile data and spatial information data.

[1034] What it does: Efficiently stores incoming data and saves it in a database to serve as an input dataset for generative AI.

[1035] Output: User profile data and spatial information data stored in a database.

[1036] Step 4:

[1037] The server provides the user with a list of existing furniture based on the generated data.

[1038] Input: User profile data and spatial information data in the database.

[1039] Operation: Generates a list of existing furniture and sends the list to the user's device.

[1040] Output: A list of existing furniture displayed on the device.

[1041] Step 5:

[1042] Users can review their existing furniture list and receive suggestions for new furniture.

[1043] Input: Existing furniture list and user furniture selection information.

[1044] How it works: The user sees the furniture list on their device and uses the interface to add / modify new furniture.

[1045] Output: The updated furniture list is sent to the server.

[1046] Step 6:

[1047] The server provides the collected data to a generative AI model to calculate the optimal furniture layout.

[1048] Input: User profile data, spatial information data, updated furniture list.

[1049] How it works: Data is fed into a generative AI model (PyTorch or TensorFlow) to calculate optimal furniture layouts, taking into account ergonomics and behavioral patterns.

[1050] Output: The optimal furniture layout plan is generated and stored on the server.

[1051] Step 7:

[1052] The server transmits the generated placement plan to the user's terminal and displays it visually.

[1053] Input: Furniture layout ideas generated by a generative AI model.

[1054] What it does: Loads furniture layout ideas and sends them to the user's device.

[1055] Output: Furniture layout proposals visually displayed on the device.

[1056] Step 8:

[1057] Users can check the layout plan through a virtual simulation and make adjustments as necessary.

[1058] Input: Furniture layout suggestions displayed on the device.

[1059] How it works: The user uses the virtual simulation to view furniture placement, make adjustments as needed, and finalize the layout.

[1060] Output: The final placement proposal is fine-tuned and fed back to the server.

[1061] Step 9:

[1062] The server stores the final placement plan in a database for future reference and readjustment.

[1063] Input: Final, fine-tuned layout proposal.

[1064] How it works: Saves the final placement plan to a database for future refinements and as a reference for other users.

[1065] Output: Final placement proposal stored in database.

[1066] These processing steps allow the user to plan an efficient and optimal furniture arrangement.

[1067] 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.

[1068] The system for implementing the present invention is implemented as a combination of a means for optimizing furniture arrangement in the home according to the user's physical limitations and cognitive state, and an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions accordingly. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[1069] Program processing explanation

[1070] 1. Create a user profile

[1071] The user launches a dedicated application on the device. The device then displays a questionnaire about the user's physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server. The server stores this information in a database for later processing.

[1072] 2. Collecting spatial information

[1073] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[1074] 3. Furniture selection assistance

[1075] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[1076] 4. Placement suggestions using generative AI

[1077] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[1078] 5. Emotion Recognition by Emotion Engine

[1079] When a user receives furniture layout suggestions, the device recognizes the user's emotions in real time using the device's camera and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions.

[1080] 6. Adjusting and displaying the proposed results

[1081] The emotion engine sends the emotional data it recognizes to the server and stores it. The server then uses this emotional data to adjust the placement proposals made by the generation AI. For example, if the user is dissatisfied, the generation AI will review and recalculate the placement proposals. The server then sends the adjusted results to the device, which then visually displays them to the user.

[1082] 7. Finalize and save

[1083] If the user is satisfied with the proposed placement and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The device then sends the confirmed placement information to the server as feedback. The server stores this final placement information in a database and uses it for future readjustments and as reference information for other users.

[1084] Specific examples

[1085] 1. Create a user profile

[1086] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1087] 2. Collecting spatial information

[1088] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, which stores it.

[1089] 3. Furniture selection assistance

[1090] The server generates existing furniture information based on the user profile and spatial information. The terminal prompts the user to input existing furniture information such as "sofa," "TV stand," and "dining table," and will also suggest new furniture if necessary. The input information is sent to the server and saved in a database.

[1091] 4. Placement suggestions using generative AI

[1092] The server provides the collected information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[1093] 5. Emotion Recognition by Emotion Engine

[1094] When a user receives a placement suggestion, the device analyzes the user's emotions in real time through the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the suggestion.

[1095] 6. Adjusting and displaying the proposed results

[1096] The emotion data recognized by the emotion engine is sent to the server, which then provides feedback to the generation AI, recalculating and adjusting it as needed. The adjusted results are then sent back to the device and displayed visually to the user.

[1097] 7. Finalize and save

[1098] When the user is satisfied with the adjustment results and finalizes the placement, they press the "Confirm" button on their device to send the placement information to the server. The server then stores the final placement information in a database, which can be used for future readjustments or as reference information for other users.

[1099] This system will enable elderly people to have a safe and comfortable living environment that also takes into consideration their emotional satisfaction.

[1100] The processing flow will be explained below.

[1101] Step 1:

[1102] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[1103] Step 2:

[1104] Users answer questions on the device and input information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[1105] Step 3:

[1106] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[1107] Step 4:

[1108] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[1109] Step 5:

[1110] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[1111] Step 6:

[1112] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[1113] Step 7:

[1114] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[1115] Step 8:

[1116] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[1117] Step 9:

[1118] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[1119] Step 10:

[1120] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[1121] Step 11:

[1122] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[1123] Step 12:

[1124] While the user is reviewing the placement proposal, the device's camera and microphone are used to collect the user's emotions in real time. The emotion engine analyzes the user's emotional data and determines how the user feels about the proposal.

[1125] Step 13:

[1126] The emotion engine sends the recognized emotion data to the server, which then adjusts the placement proposals of the generation AI based on this data. If the user is dissatisfied, the generation AI will review the proposals and recalculate.

[1127] Step 14:

[1128] The server sends the adjusted placement results to the terminal, which visually displays them to the user, allowing them to confirm the improved suggestions.

[1129] Step 15:

[1130] If the user is satisfied with the adjusted proposal, he / she presses the confirm button on the device to confirm the final arrangement, and the device sends the confirmed arrangement information to the server as feedback.

[1131] Step 16:

[1132] The server stores the final placement information in a database for future readjustments and as reference for other users.

[1133] In this way, the system of the present invention provides a safe and comfortable living environment while also taking into account the user's emotional state.

[1134] Example 2

[1135] 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."

[1136] Elderly people often have difficulty arranging furniture in their daily lives due to physical limitations and cognitive conditions. Furthermore, declining visual, auditory, and motor functions make it difficult to ensure a safe and comfortable living space. Furthermore, existing systems do not consider the user's emotions when proposing furniture arrangements, which may result in low user satisfaction. Therefore, a new system is needed that can propose appropriate furniture arrangements for elderly people and also consider their emotional satisfaction.

[1137] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power source locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for recognizing the user's emotional data regarding the proposed furniture layout in real time; means including an emotion engine for adjusting the layout proposal based on the emotional data; and means for visually displaying the layout results calculated by the generation AI and emotion engine to the user and allowing the user to make adjustments. This allows the elderly to not only receive the optimal furniture layout based on their physical limitations and cognitive state, but also to enjoy a safe and comfortable living environment that takes emotional satisfaction into consideration.

[1138] "Information about the user's physical limitations and cognitive status" refers to data about the user's physical limitations and cognitive capabilities.

[1139] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to technology that uses a scanning device such as a camera to measure the location and dimensions of each element in a room and converts that information into a digital format.

[1140] "Means for inputting existing furniture information and proposing new furniture" refers to technology that allows users to input information about furniture they already own and then suggests the most suitable new furniture based on that information.

[1141] "Generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to artificial intelligence technology that calculates effective and efficient furniture layout within a living space based on ergonomics and user behavioral patterns.

[1142] "Means for recognizing the user's emotional data regarding the proposed furniture layout in real time" refers to technology that uses sensors such as cameras and microphones to analyze in real time how the user feels about the presented furniture layout.

[1143] "Emotion engine for adjusting furniture placement suggestions based on emotional data" refers to technology that analyzes a user's emotional data and optimizes furniture placement suggestions based on the results.

[1144] "Means for visually displaying the placement results of the generative AI and emotion engine to the user and allowing adjustments" refers to technology that displays the furniture placement calculated by the generative AI and emotion engine to the user in a graphical format and allows the user to change the placement as needed.

[1145] "Means of storing the calculation results of the generative AI and emotion engine on a server and using them for future readjustments" refers to technology that stores the placement results calculated by the generative AI and emotion engine on a server, and reuses that data at a later date to make appropriate adjustments.

[1146] "Proposals to provide users with a safe and comfortable living environment" refers to technology that suggests furniture arrangements and living environment improvements necessary for users to live safely and comfortably.

[1147] A system for implementing this invention combines a means for optimizing furniture arrangement in a home according to a user's physical limitations and cognitive state with an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[1148] First, the user launches a dedicated application that can be used at home on a device such as a smartphone. This application displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences, and the user answers the questions. The response data is sent from the device to a server and stored in a database.

[1149] Next, the user scans a room in their home using a device such as a smartphone or tablet. The camera function captures the dimensions of the room, the location of doors and windows, the location of power outlets, and other information, and records this data digitally. The scanned data is also sent to a server and stored.

[1150] The server generates a list of existing furniture based on the user profile information and spatial information. This list is displayed on the terminal, and the user inputs details of each piece of furniture. New furniture items are also suggested as needed. The information entered by the user is sent to the server in real time and stored in a database.

[1151] The server then provides the collected user profile, spatial information, and furniture information as input data to the generation AI, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the device via the server in a data format such as JSON.

[1152] When receiving furniture layout suggestions, the device recognizes the user's emotions in real time using camera functions and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions. The recognized emotional data is sent to the server and stored.

[1153] The server adjusts the placement proposals made by the generation AI based on the emotional data. For example, if the user is dissatisfied, the generation AI will review the placement proposal and recalculate. The adjusted results are then sent back to the device by the server, where the user can visually confirm them.

[1154] If the user is satisfied with the placement proposal and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The confirmation information sent from the device is sent to the server as feedback and saved in the database as the final placement information. This information can be used for future readjustments or as reference information for other users.

[1155] Specific examples

[1156] Users launch a dedicated application on their smartphone and enter information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1157] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the room and the location of doors, windows, and power outlets, which is then sent from the device to a server where it is stored.

[1158] The server then generates a list of existing furniture based on the user profile and spatial information. The list includes items such as a sofa, TV stand, and dining table, and the user inputs details of these items. New furniture is also suggested as needed, and the information is also saved on the server.

[1159] The server provides the collected information to the AI ​​generator, which calculates the optimal layout taking into account ergonomics and behavioral patterns. For example, it suggests "placing the TV in a location that is easy to watch" or "placing the TV in a location with few obstacles when walking." The calculation results are sent to the device via the server and can be confirmed by the user.

[1160] While the user is reviewing the placement proposal, the device uses a camera and microphone to analyze the user's emotions in real time, which are then analyzed by the emotion engine. For example, if the user looks at the placement with a smile, it is judged to be "satisfied." The emotion data is sent to the server and stored.

[1161] The server provides feedback to the AI ​​based on the emotion data, and performs recalculation and adjustments. The adjusted placement is then sent back to the device and visually displayed to the user.

[1162] When the user is satisfied with the final arrangement and presses the confirm button, the arrangement information is sent to the server and stored in a database.

[1163] Prompt Sentence Examples

[1164] "Please suggest the optimal furniture arrangement that meets the following requirements so that the elderly can live safely and comfortably."

[1165] User profile: Limited vision, weak legs, frequent kitchen users

[1166] Spatial information: dimensions of living room, kitchen, bedrooms, and locations of doors, windows, and power outlets

[1167] Furniture information: sofa, TV stand, dining table

[1168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1169] Step 1:

[1170] The user launches a dedicated application on the device and enters information about their physical limitations and cognitive status.

[1171] Specific operations: The user launches a dedicated smartphone app and answers questions on a screen about things like "visual limitations," "hearing limitations," and "daily life needs."

[1172] Input: Information about physical limitations and cognitive status (e.g., limited vision, weak legs)

[1173] Output: User profile information is sent to the server and stored in the database.

[1174] Step 2:

[1175] The user uses the device to scan the room's dimensions, the location of doors and windows, and the location of power sources.

[1176] How it works: A user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the location of doors, windows, and power outlets.

[1177] Input: Room spatial information from camera images

[1178] Output: Sent as digital data to a server and stored in a database.

[1179] Step 3:

[1180] The server generates a list of existing furniture based on the user profile information and the spatial information.

[1181] Specific operation: The server generates a list of existing furniture such as "sofa," "TV stand," and "dining table" based on the user profile and room information.

[1182] Input: User profile information, spatial information

[1183] Output: Generate a list of existing furniture and send it to the device.

[1184] Step 4:

[1185] The device displays a list of existing furniture to the user, provides detailed information, and suggests new furniture.

[1186] Specific operation: The device displays the generated furniture list to the user, and the user enters details for each piece of furniture. New furniture pieces are also suggested as needed.

[1187] Input: Existing furniture list

[1188] Output: The furniture details entered by the user are sent to the server and stored in the database.

[1189] Step 5:

[1190] The server provides the collected information to the generation AI, which calculates the optimal furniture layout.

[1191] Specific operation: The server inputs the user profile, spatial information, and furniture information into the generative AI model, which then calculates the optimal furniture layout.

[1192] Input: User profile information, space information, furniture information

[1193] Output: The generated AI sends the optimal placement proposal data to the device.

[1194] Step 6:

[1195] The device uses a camera and microphone to recognize the user's emotions in real time.

[1196] Specific operation: While the user is viewing the placement suggestions, the device uses the camera and microphone to analyze the user's emotions.

[1197] Input: User's facial expressions and voice

[1198] Output: Emotion data is sent to the server and analyzed by the emotion engine.

[1199] Step 7:

[1200] The server adjusts placement suggestions made by the generative AI based on the emotional data.

[1201] Specific operation: The server feeds emotion data back to the generation AI, which then recalculates and adjusts the placement proposal.

[1202] Input: Emotion data

[1203] Output: The adjusted placement proposal data is sent to the terminal.

[1204] Step 8:

[1205] The terminal visually displays the adjusted placement proposal to the user and asks for reconfirmation.

[1206] Specific behavior: The device displays the adjusted furniture layout to the user, who then confirms it.

[1207] Input: Adjusted placement proposal

[1208] Output: User enters feedback for review and final adjustment.

[1209] Step 9:

[1210] The user confirms the final arrangement and presses the "confirm" button on the terminal.

[1211] Specific operation: The user confirms the final adjusted placement and presses the "Confirm" button on the device.

[1212] Input: User confirmation

[1213] Output: The final placement information is sent to the server and stored in the database.

[1214] In this way, a system is realized that proposes optimal furniture arrangements according to the physical limitations and cognitive state of the elderly, and provides a safe and comfortable living environment that also takes into account the user's emotional satisfaction.

[1215] (Application example 2)

[1216] 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."

[1217] To provide a safe and comfortable living environment that accommodates the physical and cognitive functions of elderly people, it is necessary to optimize furniture arrangement within the home. However, conventional methods for furniture arrangement do not fully consider the physical limitations, cognitive state, and emotions of elderly people, making it difficult to increase user satisfaction. Furthermore, there is a problem in that feedback on the proposed furniture arrangement is not provided in real time, making it difficult to make appropriate adjustments.

[1218] 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.

[1219] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results generated by the generation AI to the user and allowing the user to make adjustments; means for recognizing the user's emotions in real time using an emotion engine and adjusting the proposal results; and means for performing a final confirmation of the proposal results and saving the confirmed layout information on the server. This makes it possible to propose and adjust a safe and comfortable furniture layout that comprehensively takes into consideration the user's physical limitations, cognitive state, and emotions.

[1220] The "means for inputting information about the user's physical limitations and cognitive status" is an interface that collects information about the user's physical and cognitive functions and inputs it as digital data.

[1221] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a technology that uses a smartphone or tablet camera to scan the dimensions and structure of a room and converts it into digital data.

[1222] The "means for inputting existing furniture information and proposing new furniture" is an interface that allows the user to input information about furniture they already own and then suggests new furniture based on that information.

[1223] "Means including a generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to a system that incorporates a generative AI that calculates optimal furniture layout taking into account ergonomics and user behavioral patterns.

[1224] "Means for visually displaying the placement results of the generative AI to the user and allowing adjustments" refers to an interface that visually displays the furniture placement results calculated by the generative AI to the user and allows adjustments to be made based on the user's opinions and feedback.

[1225] "Means for recognizing user emotions in real time using an emotion engine and adjusting the proposed results" is a system that uses sensors such as cameras and microphones to recognize user emotions in real time and adjusts furniture placement proposals based on that emotional data.

[1226] The "means for making a final confirmation of the proposed furniture arrangement and storing the confirmed arrangement information on the server" is a means for the user to make a final confirmation of the proposed furniture arrangement and store the confirmed information on the server.

[1227] This invention uses a server, terminals, generative AI models, and emotion engines to optimize furniture placement according to the user's physical limitations and cognitive state, providing a comfortable and safe living environment.

[1228] Hardware and software used

[1229] Device: Smartphone or tablet

[1230] Server: Amazon Web Services (AWS), MySQL

[1231] Generative AI model: OpenAI GPT-4

[1232] Emotion engine: IBM Watson Tone Analyzer

[1233] Image analysis: ARKit (iOS) / ARCore (Android), OpenCV

[1234] Program processing explanation

[1235] 1. Create a user profile

[1236] The server allows users to launch a dedicated application on their device and input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences, which is then sent to the server in JSON format and stored in a database.

[1237] 2. Collecting spatial information

[1238] The device uses its camera to scan the dimensions of the room, the location of doors and windows, and the location of power sources, and converts this data into digital data, which is also sent to a server and stored.

[1239] 3. Furniture selection assistance

[1240] The server generates existing furniture information based on the user profile information and spatial information. This information is displayed on the terminal, and the user can add or modify it. This data is also saved on the server in real time.

[1241] 4. Placement suggestions using generative AI

[1242] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model. The generative AI model calculates the optimal furniture layout based on this information and returns the results to the server. The results are then visually displayed on the device.

[1243] 5. Emotion Recognition by Emotion Engine

[1244] The device uses a camera and microphone to recognize the user's emotions in real time when the user is checking the placement proposal. The emotion engine analyzes this data and transmits the user's emotion data to the server.

[1245] 6. Adjusting and displaying the proposed results

[1246] The server adjusts the placement proposals made by the generative AI based on the emotional data recognized by the emotion engine. The recalculated optimal placement proposal is sent back to the device and visually displayed to the user.

[1247] 7. Finalize and save

[1248] If the user is satisfied with the proposed placement and confirms it, they press the "Confirm" button on their device. The confirmed placement information is saved on the server and can be used for future readjustments or as reference information for other users.

[1249] Specific examples

[1250] A 70-year-old user launches a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device sends the entered information to a server and stores it in a database. The user uses their smartphone camera to scan their living room, kitchen, and bedroom, recording the room dimensions and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, where it is stored. The server generates existing furniture information based on the user profile and spatial information. The device then prompts the user to enter existing furniture information such as a sofa, TV stand, and dining table, and suggests new furniture if necessary. The input information is sent to the server and stored in a database. The server then provides the collected information to a generation AI, which calculates the optimal furniture layout. The generation AI generates layout proposals that take ergonomics and behavioral patterns into account and sends the data to the device via the server. When the user receives the layout proposals, the device analyzes the user's emotions in real time using the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the proposals. The emotion data recognized by the emotion engine is sent to the server, which provides feedback to the generation AI and performs recalculations and adjustments as appropriate. The adjusted results are sent back to the device and visually displayed to the user. When the user is satisfied with the adjustment results and has finalized the placement, they press the "Confirm" button on the device, which sends the placement information to the server. The server saves the final placement information in a database and uses it for future readjustments and as reference information for other users.

[1251] Prompt Sentence Examples

[1252] User: 75-year-old female, weak legs, normal vision. Scan data of the room is as follows.

[1253] Living room: 4m wide, 5m deep, 2.5m high, window located in the center, power outlet on the left wall.

[1254] Current furniture: sofa, TV stand, low table.

[1255] Suggestion: I have weak legs, so I would like low furniture. Please suggest adding a height-adjustable bed and a chair with soft cushions.

[1256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1257] Step 1:

[1258] The user starts up the device and opens the dedicated application. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The information entered by the user is sent to the server in JSON format, which is then stored in a database.

[1259] Input: Information about the user's physical limitations, cognitive state, and preferences

[1260] Data processing: Convert input information into JSON format

[1261] Output: User profile data sent to the server

[1262] Step 2:

[1263] The user uses the camera function of their smartphone to scan the dimensions of the room, the location of doors and windows, and the location of power sources. The device analyzes the captured image data in real time and converts the dimensional information and other data into digital data. This data is then sent to the server and stored.

[1264] Input: Room image data

[1265] Data processing: Analyze image data and extract dimensional and positional information

[1266] Output: Digital data sent to the server

[1267] Step 3:

[1268] The server generates a list of existing furniture based on the user profile information and spatial information. This generated furniture information is displayed on the terminal, and the user can enter details of each piece of furniture and receive suggestions for new furniture. The entered information is sent to the server in real time and saved.

[1269] Input: User profile information, spatial information

[1270] Data processing: Creating a list of existing furniture and entering detailed information

[1271] Output: Furniture list displayed on the device, furniture information stored on the server

[1272] Step 4:

[1273] The server provides the collected user profile, spatial information, and furniture information as input data to the generative AI model, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the server and then visually displayed on the device.

[1274] Input: User profile, space information, furniture information

[1275] Data processing: Calculating optimal furniture placement using a generative AI model

[1276] Output: Furniture layout proposal displayed on the device

[1277] Step 5:

[1278] When the user confirms the placement proposal, the device uses the camera and microphone to recognize the user's emotions in real time. The emotion engine analyzes image and voice data and transmits the user's emotional data to the server.

[1279] Input: image data, audio data

[1280] Data processing: Emotion analysis using an emotion engine

[1281] Output: Emotion data sent to the server

[1282] Step 6:

[1283] The server adjusts the furniture layout proposals made by the generative AI based on the emotion data received from the emotion engine. New proposals are generated, and the recalculated optimal layout plan is sent to the terminal and visually displayed to the user.

[1284] Input: Emotion data, initial placement proposal

[1285] Data processing: Recalculation and alignment using generative AI models

[1286] Output: Re-proposed furniture layout displayed on the device

[1287] Step 7:

[1288] When the user is satisfied with the proposed furniture arrangement, they press the confirm button to finalize the furniture arrangement. The confirmed arrangement information is sent from the device to the server and stored in a database. It can be used for future readjustments or as reference information for other users.

[1289] Input: Confirmed placement information

[1290] Data processing: Confirmed placement information is saved in the database

[1291] Output: Final placement information saved on the server

[1292] 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.

[1293] 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.

[1294] 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.

[1295] [Fourth embodiment]

[1296] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1297] 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.

[1298] 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).

[1299] 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.

[1300] 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.

[1301] 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).

[1302] 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. 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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.

[1308] 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."

[1309] The system for implementing the present invention is implemented in a form that includes multiple means for optimizing furniture arrangement in a home according to the user's physical limitations and cognitive status. This system uses generative AI to provide a safe and comfortable living environment for the elderly.

[1310] Program processing explanation

[1311] 1. Create a user profile

[1312] The user launches a dedicated application on the device. The device then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server, which stores this information in a database for later processing.

[1313] 2. Collecting spatial information

[1314] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[1315] 3. Furniture selection assistance

[1316] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[1317] 4. Placement suggestions using generative AI

[1318] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[1319] 5. Viewing and adjusting results

[1320] The device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal as needed. If the user feels it is optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database for future adjustments and as reference information for other users.

[1321] Specific examples

[1322] 1. Create a user profile

[1323] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1324] 2. Collecting spatial information

[1325] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[1326] 3. Furniture selection assistance

[1327] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[1328] 4. Placement suggestions using generative AI

[1329] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[1330] 5. Viewing and adjusting results

[1331] The device visually displays the AI's proposed placement to the user and performs a virtual simulation. After the user makes some fine adjustments and presses the "Confirm" button, the placement information is sent to the server and stored in a database.

[1332] This system will enable elderly people to have a safe and comfortable living environment in their own homes.

[1333] The processing flow will be explained below.

[1334] Step 1:

[1335] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[1336] Step 2:

[1337] Users answer questions on the device and enter information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[1338] Step 3:

[1339] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[1340] Step 4:

[1341] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[1342] Step 5:

[1343] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[1344] Step 6:

[1345] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[1346] Step 7:

[1347] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[1348] Step 8:

[1349] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[1350] Step 9:

[1351] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[1352] Step 10:

[1353] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[1354] Step 11:

[1355] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[1356] Step 12:

[1357] When the user is satisfied with the arrangement, he / she presses the "confirm" button on the device, and the device sends the final arrangement information to the server as feedback.

[1358] Step 13:

[1359] The server stores the determined placement information in a database and makes it available for future readjustments or as reference for other users, thereby improving the safety and comfort of users in their homes.

[1360] Example 1

[1361] 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."

[1362] Optimizing furniture arrangement in the home to accommodate the physical and cognitive functions of elderly people is important for providing a safe and comfortable living environment. However, traditional manual furniture arrangement methods have the drawback of being difficult to consider the specific needs and limitations of elderly people, making the process of achieving optimal furniture arrangement cumbersome and time-consuming. Furthermore, future changes or readjustments require manually collecting new information and reconsidering the arrangement, which is inefficient.

[1363] 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.

[1364] In this invention, the server includes a means for inputting information about the user's physical limitations and cognitive state, a means for scanning the room dimensions, door and window locations, and power outlet locations and converting them into digital data, and a means for inputting existing furniture information and proposing new furniture. This allows the generative AI to propose optimal furniture layouts that take ergonomics and behavioral patterns into consideration. The resulting layouts generated by the generative AI are visually displayed to the user, providing a virtual simulation, allowing the user to make fine adjustments and finalize the layout. This information can then be fed back to the server for further adjustments or as reference information.

[1365] A "user profile" is data that includes information about a user's physical limitations and cognitive state.

[1366] "Generative AI" is an artificial intelligence system that calculates and suggests optimal furniture layouts taking into account ergonomics and behavioral patterns.

[1367] "Ergonomics" is the science of optimizing the layout of work environments and tools to improve human efficiency and comfort.

[1368] A "virtual simulation" is a digital simulation that allows users to visually review and fine-tune the proposed furniture arrangement.

[1369] "Feedback" is the process by which the user sends the final placement information to the server.

[1370] The "database" is a system that stores user profile information, spatial information, furniture information, etc., and can be used for future readjustments or as reference information.

[1371] The "server" is a central processing unit that manages user profile information, spatial information, and furniture information, and exchanges data with the generating AI.

[1372] A "terminal" is a device that allows a user to input information using a dedicated application and exchange data with a server.

[1373] "Scanning" is the act of converting information such as room dimensions, the location of doors and windows, and the location of power sources into digital data using a camera function.

[1374] The term "means" refers to individual elements or devices that perform a particular function for carrying out the invention.

[1375] The present invention provides a system that utilizes generative AI to optimize the furniture arrangement in a home based on the user's physical limitations and cognitive status, providing a safe and comfortable living environment for the elderly.

[1376] First, the user installs and launches a dedicated application on a device such as a smartphone or tablet. The device then displays questions about the user's physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences. The user answers the questions on the screen and enters this information into the device. The device then sends the collected user profile information to a server, which stores the information in a database.

[1377] Next, the process moves to the spatial information collection phase. The user scans their room using a device such as a smartphone or tablet. Specifically, the camera function is used to scan the room's dimensions, the location of doors and windows, and the location of power sources, and this is converted into digital data. The device then analyzes the scanned image in real time and records it as digital data. The acquired spatial information data is immediately sent to a server and saved.

[1378] When selecting furniture, the server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for their confirmation. The user can enter details of the displayed furniture and receive suggestions for new furniture if necessary. This information is sent to the server in real time and stored in a database.

[1379] In the next step, the server provides all collected information—user profile, spatial information, and furniture information—as input data to a generative AI model. The generative AI calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns. The server outputs the optimal layout proposal calculated by the generative AI in data format and sends it to the device.

[1380] Finally, the device visually displays the proposed furniture arrangement to the user, providing a virtual simulation. The user can review the simulation and make fine adjustments to the proposal if necessary. If the user feels it is finally optimal, they press the "Confirm" button to confirm the arrangement. The device then sends the confirmed arrangement information to the server as feedback. The server stores this final arrangement in a database, allowing it to be used for future adjustments or as reference information for other users.

[1381] Specific examples

[1382] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1383] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data, which the device then sends to a server where it is stored.

[1384] The server automatically generates information about existing furniture, and the device prompts the user to check existing furniture information such as "sofa," "TV stand," and "dining table," and suggests new furniture if necessary. Once the user enters the information, the device sends it to the server and stores it in a database.

[1385] The server provides all the information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator then generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[1386] Finally, the device visually displays the AI's proposed layout to the user and performs a virtual simulation. After making fine adjustments, the user presses the "Confirm" button, and the layout information is sent to the server and stored in a database. By using this system, users can achieve a safe and comfortable living environment in their own homes.

[1387] Prompt Sentence Examples

[1388] "Ask your generative AI to suggest optimal furniture arrangements for a 70-year-old with visual limitations to live safely in their home."

[1389] "Explain how to calculate the optimal furniture placement for a living room, including the placement of a sofa, TV stand, and dining table."

[1390] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1391] Specific processing steps of the program

[1392] Step 1:

[1393] The user launches the dedicated application on a device such as a smartphone or tablet. The device then displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. Specifically, the user enters their answers into checkboxes and text boxes on the screen and presses the send button. The input data is profile information including the user's physical limitations and lifestyle habits, and the output data is a data packet that organizes this information.

[1394] Step 2:

[1395] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a database. Specifically, the terminal encodes the user input data and sends it over the network to the server. The server decodes the received data and stores it in a structured format in the database. The input of this step is the user profile information, and the output is the user profile stored in the database.

[1396] Step 3:

[1397] The user scans a room using a device such as a smartphone or tablet. The device uses its camera to scan the room's dimensions, the locations of doors and windows, and power outlets, and converts the data into digital data. Specifically, the user operates the camera while walking around the room, capturing images of the room in real time. The input data is the camera image, and the output data is digital data including the room's dimensions and structural information.

[1398] Step 4:

[1399] The device sends the scanned spatial information data to a server. The server receives this information and stores it in a database. Specifically, the device analyzes the captured video data, identifies the room dimensions and the locations of doors, windows, and power sources, and converts it into a dataset. This dataset is then sent to the server, which receives it and stores it in the database. The input to this step is the spatial information of the room, and the output is the spatial information stored in the database.

[1400] Step 5:

[1401] The server generates a list of existing furniture based on the user profile information and spatial information. The terminal displays this generated furniture list to the user. Specifically, the server compares the user profile and spatial information in the database and generates a list of appropriate furniture. The generated list is sent to the terminal, which displays it to the user. The input of this step is the user profile and spatial information, and the output is a list of furniture.

[1402] Step 6:

[1403] The user enters details of existing furniture and suggests new furniture if necessary. The device sends the information entered by the user to the server. Specifically, the user checks the displayed list of existing furniture and uses tabs and text boxes to enter detailed information and information about new furniture. The device then sends this information to the server. The input to this step is the furniture information entered by the user, and the output is the furniture information stored in the database.

[1404] Step 7:

[1405] The server provides the collected user profile, spatial information, and furniture information to the generation AI. The generation AI considers ergonomics and the user's behavioral patterns to calculate the optimal furniture layout. Specifically, the server inputs all relevant information into the generation AI model, and the generation AI starts calculations. This calculation generates data on the optimal furniture layout. The inputs for this step are the user profile, spatial information, and furniture information, and the output is a dataset containing the optimal furniture layout.

[1406] Step 8:

[1407] The server sends the optimal layout proposal calculated by the generative AI to the device. The device visually displays the proposed furniture layout to the user, providing a virtual simulation. Specifically, the server sends the layout data from the generative AI to the device, which then visually displays it to the user. The user can view and manipulate the layout on the screen. The input of this step is a dataset containing the optimal furniture layout, and the output is a visual layout proposal displayed to the user.

[1408] Step 9:

[1409] The user checks the displayed suggestions and makes fine adjustments as necessary. The device then sends the finalized layout information to the server. Specifically, the user adjusts the furniture layout on the screen by tapping and dragging, and finally presses the "Confirm" button. The device then sends this final layout information to the server. The input to this step is the user's layout adjustment information, and the output is the finalized layout information sent to the server.

[1410] Step 10:

[1411] The server stores the final placement information in a database and uses it for future readjustments and as reference information for other users. Specifically, the server stores the received final placement information in a database and links it with related data as needed. The input of this step is the final placement information, and the output is the placement information stored in the database.

[1412] (Application example 1)

[1413] 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."

[1414] It is necessary to provide a safe and comfortable living environment for the elderly by optimizing the furniture arrangement in their homes to accommodate their physical and cognitive functions. In addition, it is necessary to efficiently support users in physical stores in selecting and arranging the optimal furniture based on their physical limitations and preferences.

[1415] 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.

[1416] In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the dimensions of the room, the positions of doors and windows, and the positions of power sources and converting them into digital data; means for inputting information about existing furniture and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for visually displaying the layout results calculated by the generation AI to the user and allowing the user to make adjustments; and means for displaying a list of existing furniture from a furniture store and viewing and selecting furniture details to support the user's interior selection in a physical store, thereby enabling elderly people and users with physical limitations to enjoy a safe and comfortable living environment both inside and outside their homes.

[1417] "Information about the user's physical limitations and cognitive status" refers to information about the user's visual and hearing abilities, physical function status, cognitive function status, and daily living needs and preferences.

[1418] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to a method of using a device such as a smartphone or tablet to measure the physical structure of a room through its camera function and convert this into digital data.

[1419] "Means for inputting existing furniture information and making suggestions for new furniture" refers to a method for recording information about furniture that a user currently owns and making suggestions for additional or new furniture based on that information.

[1420] "Generative AI" refers to a system that uses artificial intelligence technology to calculate optimal furniture layouts, taking into account ergonomics and user behavior patterns.

[1421] "Means for visually displaying the placement results of the generative AI to the user and allowing them to make adjustments" refers to an interface that graphically displays the optimal furniture placement calculated by the generative AI to the user, allowing the user to visually check the placement and make fine adjustments.

[1422] "A means for displaying a list of existing furniture in a furniture store and viewing and selecting furniture details to assist users in selecting interior items in a physical store" refers to a method in a furniture shop that allows users to view a list of furniture available in the store and select furniture while checking detailed information.

[1423] A system for implementing the present invention provides various functions to enable elderly people and users with physical limitations to have a safe and comfortable living environment both inside and outside their homes. This system includes an information input means adapted to the user's physical limitations and cognitive state, a means for scanning room dimensions and the locations of doors, windows, and power sources, a means for inputting existing furniture information and proposing new furniture, a means for calculating the optimal furniture layout using a generative AI, a means for visually displaying the layout results generated by the generative AI so that the user can make adjustments, and a means for supporting interior design selection in a physical store.

[1424] Creating a User Profile

[1425] The device (smartphone or tablet) provides an interface through which users can input information about their physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences through a dedicated application, which is then sent to a server and stored in a database.

[1426] Collection of spatial information

[1427] Users can use the device's camera to scan the dimensions of their rooms, the locations of doors and windows, and power outlets, and convert this information into digital data. The acquired spatial information is then immediately sent to a server and stored. This processing is done using the camera module and the open-source library "OpenCV."

[1428] Assistance with furniture selection

[1429] The server uses the user profile information and spatial information to generate a list of existing furniture and sends it to the device. The user can then check the existing furniture on the device and receive suggestions for new furniture if necessary.

[1430] Placement suggestions by generative AI

[1431] The server uses a generative AI to calculate the optimal furniture layout based on the collected user profile information, spatial information, and furniture information. The generative AI takes ergonomics and user behavior patterns into account to generate the optimal furniture layout plan. This generative AI uses deep learning libraries such as "PyTorch" or "TensorFlow."

[1432] Viewing and adjusting results

[1433] The device visually displays the placement results generated by the AI, allowing the user to check them through a virtual simulation. After the user makes fine adjustments as needed and confirms the final placement, the information is fed back to the server and stored in a database.

[1434] Support for choosing interior decor in a physical store

[1435] When users visit a physical store, they can check the furniture store's existing furniture list through the application on their device, browse detailed information, select the furniture they like, and incorporate it directly into their layout plan.

[1436] As a concrete example, by inputting the following prompt sentence into the generative AI model, optimal furniture layout suggestions suitable for the user can be obtained.

[1437] Example prompt sentence:

[1438] User profile: Age: 70, Vision limitations: Yes, Mobility: Weak legs, Interior preferences: Kitchen and living room

[1439] Space information: Room dimensions: width 5.0m, height 5.0m, door location: x1.0m, y0.5m, window location: x4.0m, y0.5m, power location: x2.0m, y1.0m

[1440] Furniture list: sofa, TV stand, dining table

[1441] This allows seniors to get furniture arrangement plans that suit their needs and limitations.

[1442] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1443] Step 1:

[1444] The user installs and launches a dedicated application on their device (smartphone or tablet).

[1445] Input: Information such as the user's physical limitations, visual and hearing abilities, cognitive status, daily living needs and preferences.

[1446] How it works: The application collects this information through the user interface and formats it as digital data.

[1447] Output: User profile data is generated and sent to the server.

[1448] Step 2:

[1449] The device helps users scan their home to determine the dimensions of rooms, the location of doors and windows, and the location of power outlets.

[1450] Input: Room video data collected using the device's camera function.

[1451] How it works: It uses OpenCV to analyze camera footage and converts the room dimensions, the location of doors and windows, and the location of power sources into digital data.

[1452] Output: Spatial information data is generated and sent to the server.

[1453] Step 3:

[1454] The server receives the user profile data and spatial information data and stores them in a database.

[1455] Input: User profile data and spatial information data.

[1456] What it does: Efficiently stores incoming data and saves it in a database to serve as an input dataset for generative AI.

[1457] Output: User profile data and spatial information data stored in a database.

[1458] Step 4:

[1459] The server provides the user with a list of existing furniture based on the generated data.

[1460] Input: User profile data and spatial information data in the database.

[1461] Operation: Generates a list of existing furniture and sends the list to the user's device.

[1462] Output: A list of existing furniture displayed on the device.

[1463] Step 5:

[1464] Users can review their existing furniture list and receive suggestions for new furniture.

[1465] Input: Existing furniture list and user furniture selection information.

[1466] How it works: The user sees the furniture list on their device and uses the interface to add / modify new furniture.

[1467] Output: The updated furniture list is sent to the server.

[1468] Step 6:

[1469] The server provides the collected data to a generative AI model to calculate the optimal furniture layout.

[1470] Input: User profile data, spatial information data, updated furniture list.

[1471] How it works: Data is fed into a generative AI model (PyTorch or TensorFlow) to calculate optimal furniture layouts, taking into account ergonomics and behavioral patterns.

[1472] Output: The optimal furniture layout plan is generated and stored on the server.

[1473] Step 7:

[1474] The server transmits the generated placement plan to the user's terminal and displays it visually.

[1475] Input: Furniture layout ideas generated by a generative AI model.

[1476] What it does: Loads furniture layout ideas and sends them to the user's device.

[1477] Output: Furniture layout proposals visually displayed on the device.

[1478] Step 8:

[1479] Users can check the layout plan through a virtual simulation and make adjustments as necessary.

[1480] Input: Furniture layout suggestions displayed on the device.

[1481] How it works: The user uses the virtual simulation to view furniture placement, make adjustments as needed, and finalize the layout.

[1482] Output: The final placement proposal is fine-tuned and fed back to the server.

[1483] Step 9:

[1484] The server stores the final placement plan in a database for future reference and readjustment.

[1485] Input: Final, fine-tuned layout proposal.

[1486] How it works: Saves the final placement plan to a database for future refinements and as a reference for other users.

[1487] Output: Final placement proposal stored in database.

[1488] These processing steps allow the user to plan an efficient and optimal furniture arrangement.

[1489] 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.

[1490] The system for implementing the present invention is implemented as a combination of a means for optimizing furniture arrangement in the home according to the user's physical limitations and cognitive state, and an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions accordingly. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[1491] Program processing explanation

[1492] 1. Create a user profile

[1493] The user launches a dedicated application on the device. The device then displays a questionnaire about the user's physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The user answers these questions and enters the information into the device. The device then sends the collected user profile information to the server. The server stores this information in a database for later processing.

[1494] 2. Collecting spatial information

[1495] The user walks around a room with a device such as a smartphone or tablet and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device analyzes the camera footage and records the room's dimensions, the locations of doors and windows, and the locations of power outlets as digital data. The acquired spatial information data is immediately sent to a server and stored.

[1496] 3. Furniture selection assistance

[1497] The server generates a list of existing furniture based on the user profile information and spatial information. The device displays this list to the user and asks for confirmation. The user enters details of each piece of furniture and is suggested new furniture as needed. This information is sent to the server in real time and stored in a database.

[1498] 4. Placement suggestions using generative AI

[1499] The server provides the collected user profile, spatial information, and furniture information as input data to the generation AI. The generation AI calculates the optimal furniture layout taking into account ergonomics and the user's behavioral patterns. The server outputs the optimal layout proposal calculated by the generation AI in a data format such as JSON and sends it to the terminal.

[1500] 5. Emotion Recognition by Emotion Engine

[1501] When a user receives furniture layout suggestions, the device recognizes the user's emotions in real time using the device's camera and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions.

[1502] 6. Adjusting and displaying the proposed results

[1503] The emotion engine sends the emotional data it recognizes to the server and stores it. The server then uses this emotional data to adjust the placement proposals made by the generation AI. For example, if the user is dissatisfied, the generation AI will review and recalculate the placement proposals. The server then sends the adjusted results to the device, which then visually displays them to the user.

[1504] 7. Finalize and save

[1505] If the user is satisfied with the proposed placement and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The device then sends the confirmed placement information to the server as feedback. The server stores this final placement information in a database and uses it for future readjustments and as reference information for other users.

[1506] Specific examples

[1507] 1. Create a user profile

[1508] A 70-year-old user starts a dedicated application on their smartphone and enters information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1509] 2. Collecting spatial information

[1510] Users scan their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the rooms and the locations of doors, windows, and power outlets as digital data. The device then sends this information to a server, which stores it.

[1511] 3. Furniture selection assistance

[1512] The server generates existing furniture information based on the user profile and spatial information. The terminal prompts the user to input existing furniture information such as "sofa," "TV stand," and "dining table," and will also suggest new furniture if necessary. The input information is sent to the server and saved in a database.

[1513] 4. Placement suggestions using generative AI

[1514] The server provides the collected information to the AI ​​generator, which then calculates the optimal furniture layout. The AI ​​generator generates layout suggestions that take ergonomics and behavioral patterns into account, and sends the data to the device via the server.

[1515] 5. Emotion Recognition by Emotion Engine

[1516] When a user receives a placement suggestion, the device analyzes the user's emotions in real time through the camera and microphone. The emotion engine recognizes the user's emotions and determines their satisfaction with the suggestion.

[1517] 6. Adjusting and displaying the proposed results

[1518] The emotion data recognized by the emotion engine is sent to the server, which then provides feedback to the generation AI, recalculating and adjusting it as needed. The adjusted results are then sent back to the device and displayed visually to the user.

[1519] 7. Finalize and save

[1520] When the user is satisfied with the adjustment results and finalizes the placement, they press the "Confirm" button on their device to send the placement information to the server. The server then stores the final placement information in a database, which can be used for future readjustments or as reference information for other users.

[1521] This system will enable elderly people to have a safe and comfortable living environment that also takes into consideration their emotional satisfaction.

[1522] The processing flow will be explained below.

[1523] Step 1:

[1524] The user launches a dedicated application on the device, which then prompts the user with questions about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences.

[1525] Step 2:

[1526] Users answer questions on the device and input information about their physical limitations, visual and hearing abilities, cognitive status, and daily living needs and preferences. The device then organizes the information and sends it to the server.

[1527] Step 3:

[1528] The server stores the received user profile information in a database, which manages information about the user's physical limitations and cognitive status.

[1529] Step 4:

[1530] The user walks around the room with the device and uses the camera to scan the room's dimensions, the locations of doors and windows, and power outlets. The device collects and analyzes this data and records it as digital data.

[1531] Step 5:

[1532] The device sends the collected spatial information data to a server, which stores the data in a database and makes it available for later processing.

[1533] Step 6:

[1534] The server generates a list of existing furniture based on the user profile and spatial information. The device retrieves this information and displays a question screen for the user to input information about the existing furniture.

[1535] Step 7:

[1536] The user inputs existing furniture information and accepts new furniture suggestions as needed. The terminal transmits the furniture information input by the user to the server.

[1537] Step 8:

[1538] The server stores the received furniture information in a database and prepares to provide data to the generation AI based on that information.

[1539] Step 9:

[1540] The server combines user profiles, spatial information, and furniture information and provides them as input data to the AI ​​generator, which then calculates the optimal furniture layout, taking into account ergonomics and behavioral patterns.

[1541] Step 10:

[1542] The generation AI calculates the optimal furniture layout data and sends it to the server, which then sends this data to the device.

[1543] Step 11:

[1544] The device visually displays the AI-generated furniture layout proposal to the user, providing a virtual simulation. The user can then review the simulation and make fine adjustments to the proposed layout.

[1545] Step 12:

[1546] While the user is reviewing the placement proposal, the device's camera and microphone are used to collect the user's emotions in real time. The emotion engine analyzes the user's emotional data and determines how the user feels about the proposal.

[1547] Step 13:

[1548] The emotion engine sends the recognized emotion data to the server, which then adjusts the placement proposals of the generation AI based on this data. If the user is dissatisfied, the generation AI will review the proposals and recalculate.

[1549] Step 14:

[1550] The server sends the adjusted placement results to the terminal, which visually displays them to the user, allowing them to confirm the improved suggestions.

[1551] Step 15:

[1552] If the user is satisfied with the adjusted proposal, he / she presses the confirm button on the device to confirm the final arrangement, and the device sends the confirmed arrangement information to the server as feedback.

[1553] Step 16:

[1554] The server stores the final placement information in a database for future readjustments and as reference for other users.

[1555] In this way, the system of the present invention provides a safe and comfortable living environment while also taking into account the user's emotional state.

[1556] Example 2

[1557] 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."

[1558] Elderly people often have difficulty arranging furniture in their daily lives due to physical limitations and cognitive conditions. Furthermore, declining visual, auditory, and motor functions make it difficult to ensure a safe and comfortable living space. Furthermore, existing systems do not consider the user's emotions when proposing furniture arrangements, which may result in low user satisfaction. Therefore, a new system is needed that can propose appropriate furniture arrangements for elderly people and also consider their emotional satisfaction.

[1559] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about the user's physical limitations and cognitive state; means for scanning the room dimensions, door and window locations, and power source locations and converting them into digital data; means for inputting existing furniture information and proposing new furniture; means including a generation AI that calculates the optimal furniture layout taking ergonomics and behavioral patterns into consideration; means for recognizing the user's emotional data regarding the proposed furniture layout in real time; means including an emotion engine for adjusting the layout proposal based on the emotional data; and means for visually displaying the layout results calculated by the generation AI and emotion engine to the user and allowing the user to make adjustments. This allows the elderly to not only receive the optimal furniture layout based on their physical limitations and cognitive state, but also to enjoy a safe and comfortable living environment that takes emotional satisfaction into consideration.

[1560] "Information about the user's physical limitations and cognitive status" refers to data about the user's physical limitations and cognitive capabilities.

[1561] "Means of scanning the dimensions of a room, the location of doors and windows, and the location of power sources and converting them into digital data" refers to technology that uses a scanning device such as a camera to measure the location and dimensions of each element in a room and converts that information into a digital format.

[1562] "Means for inputting existing furniture information and proposing new furniture" refers to technology that allows users to input information about furniture they already own and then suggests the most suitable new furniture based on that information.

[1563] "Generative AI that calculates optimal furniture layout taking into account ergonomics and behavioral patterns" refers to artificial intelligence technology that calculates effective and efficient furniture layout within a living space based on ergonomics and user behavioral patterns.

[1564] "Means for recognizing the user's emotional data regarding the proposed furniture layout in real time" refers to technology that uses sensors such as cameras and microphones to analyze in real time how the user feels about the presented furniture layout.

[1565] "Emotion engine for adjusting furniture placement suggestions based on emotional data" refers to technology that analyzes a user's emotional data and optimizes furniture placement suggestions based on the results.

[1566] "Means for visually displaying the placement results of the generative AI and emotion engine to the user and allowing adjustments" refers to technology that displays the furniture placement calculated by the generative AI and emotion engine to the user in a graphical format and allows the user to change the placement as needed.

[1567] "Means of storing the calculation results of the generative AI and emotion engine on a server and using them for future readjustments" refers to technology that stores the placement results calculated by the generative AI and emotion engine on a server, and reuses that data at a later date to make appropriate adjustments.

[1568] "Proposals to provide users with a safe and comfortable living environment" refers to technology that suggests furniture arrangements and living environment improvements necessary for users to live safely and comfortably.

[1569] A system for implementing this invention combines a means for optimizing furniture arrangement in a home according to a user's physical limitations and cognitive state with an emotion engine that recognizes the user's emotions and adjusts furniture arrangement suggestions. This system uses generative AI and the emotion engine to provide a safe and comfortable living environment for the elderly.

[1570] First, the user launches a dedicated application that can be used at home on a device such as a smartphone. This application displays a screen asking the user questions about their physical limitations, visual and hearing abilities, cognitive status, and daily life needs and preferences, and the user answers the questions. The response data is sent from the device to a server and stored in a database.

[1571] Next, the user scans a room in their home using a device such as a smartphone or tablet. The camera function captures the dimensions of the room, the location of doors and windows, the location of power outlets, and other information, and records this data digitally. The scanned data is also sent to a server and stored.

[1572] The server generates a list of existing furniture based on the user profile information and spatial information. This list is displayed on the terminal, and the user inputs details of each piece of furniture. New furniture items are also suggested as needed. The information entered by the user is sent to the server in real time and stored in a database.

[1573] The server then provides the collected user profile, spatial information, and furniture information as input data to the generation AI, which then calculates the optimal furniture layout, taking into account ergonomics and the user's behavioral patterns. The calculation results are sent to the device via the server in a data format such as JSON.

[1574] When receiving furniture layout suggestions, the device recognizes the user's emotions in real time using camera functions and voice analysis. The emotion engine analyzes the user's emotional data and determines whether the user is satisfied or dissatisfied with the suggestions. The recognized emotional data is sent to the server and stored.

[1575] The server adjusts the placement proposals made by the generation AI based on the emotional data. For example, if the user is dissatisfied, the generation AI will review the placement proposal and recalculate. The adjusted results are then sent back to the device by the server, where the user can visually confirm them.

[1576] If the user is satisfied with the placement proposal and feels that no adjustments are necessary, they can confirm the final placement by pressing the "Confirm" button on their device. The confirmation information sent from the device is sent to the server as feedback and saved in the database as the final placement information. This information can be used for future readjustments or as reference information for other users.

[1577] Specific examples

[1578] Users launch a dedicated application on their smartphone and enter information such as "visual limitations," "weak legs," and "frequent use of the kitchen." The device then sends the entered information to a server and stores it in a database.

[1579] Next, the user scans their living room, kitchen, or bedroom with their smartphone camera, recording the dimensions of the room and the location of doors, windows, and power outlets, which is then sent from the device to a server where it is stored.

[1580] The server then generates a list of existing furniture based on the user profile and spatial information. The list includes items such as a sofa, TV stand, and dining table, and the user inputs details of these items. New furniture is also suggested as needed, and the information is also saved on ...

Claims

1. A system for optimizing furniture arrangement in a home in response to physical and cognitive functions of an elderly person, comprising: means for inputting information regarding the user's physical limitations and cognitive status; A means of scanning the dimensions of the room, the location of doors and windows, and the location of power sources and converting them into digital data; A means to input existing furniture information and propose new furniture; a means including a generative AI that calculates optimal furniture placement taking into account ergonomics and behavioral patterns; A means for visually displaying the placement results generated by the generation AI to the user and allowing them to make adjustments; A system including:

2. The system of claim 1, further comprising means for storing the results of the calculations by the generating AI on a server and using them for future readjustment.

3. 3. The system according to claim 1, further comprising suggestions for providing a safe and comfortable living environment to the user.

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