System

Abstract

To provide a system.SOLUTION: Provided is a system comprising: means for analyzing, on the basis of environmental data including soil terrain, geological features and climate, collected using a specific sensor and camera, the terrain and geological features of a hard-to-reach or disaster-hit area; an emotion engine for recognizing the emotion of a user who hopes to have a house constructed in the area; means for designing, with a specific prompt text inputted to a generative AI model, a house with a shape and materials best suitable for the user on the basis of the analysis result and the user's emotion; and means for creating a construction plan necessary for construction of the house, and transmitting the created construction plan to a robot or a construction company that will construct the house.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] It is difficult to build structures quickly and effectively in places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, with the increasing expansion into space, there is a demand for technology to generate optimally shaped buildings using only the elements available on site. [Means for solving the problem]

[0005] The system disclosed herein includes: means for analyzing the topography and geology of places that are difficult for people to reach and places destroyed by disasters based on environmental data, which is data including the topography, geology, and climate of the soil collected using specific sensors and cameras; an emotion engine that recognizes the emotions of a user who wishes to build a house in said place; means for designing a house with a shape and materials that are optimal for the user based on the results of the analysis and the emotions of the user by inputting specific prompt sentences into a generative AI model; and means for creating a construction plan necessary for building the house based on the design, and transmitting the created construction plan to a robot that will build the house or a construction company that will build the house. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] This embodiment of the present invention is equipped with devices such as sensors and cameras that analyze the elements present in the area. For example, in places that are difficult for people to reach or have been destroyed by disaster, information on the topography, geology, climate, and existing resources is collected. This information becomes the basis for designing a dwelling with the optimal shape and materials.

[0029] "Example 2"

[0030] Next, a home is designed with the optimal shape and materials based on the collected information. This design is carried out by generative AI. The generative AI designs a home with the optimal shape and materials based on the collected information. For example, if the terrain is steep, it will design a home with a shape that follows the terrain. Also, if the geology is weak, it will design a home with materials that are earthquake-resistant.

[0031] "Example 3"

[0032] Finally, the home is constructed based on the design. This construction is carried out by devices such as robots and 3D printers. For example, a robot uses resources available on-site to build the home based on the blueprint. A 3D printer also uses resources available on-site to manufacture the home's components based on the blueprint, and then assembles them to build the home.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0036] Step 2: Input the collected information into the generative AI.

[0037] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[0038] "Example 2"

[0039] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0040] Step 2: Input the collected information into the generative AI.

[0041] Step 3: The generative AI designs a dwelling with the optimal shape and materials based on the input information. If the terrain is steep, it will design a dwelling with a shape that follows the terrain. If the geology is weak, it will design a dwelling made of earthquake-resistant materials.

[0042] "Example 3"

[0043] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0044] Step 2: Input the collected information into the generative AI.

[0045] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[0046] Step 4: Based on the blueprint, the home is constructed using resources available on site. This construction is carried out by devices such as robots and 3D printers. The robots use resources available on site to construct the home based on the blueprint. The 3D printers use resources available on site to manufacture the home's components based on the blueprint, and then assemble them to construct the home.

[0047] Example 1

[0048] Next, a description will be given of Example 1 of Form 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."

[0049] With conventional technology, it was difficult to efficiently analyze the elements of hard-to-reach places or places destroyed by disasters, and to design homes with optimal shapes and materials. Furthermore, there was a lack of means to analyze the collected data and provide it visually to users, making it difficult to use it as basic data for design.

[0050] 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.

[0051] In this invention, the server includes means for analyzing elements present at the site, means for analyzing the analysis results using data analysis software, means for designing a dwelling with an optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, and means for transmitting the analysis results to a terminal and displaying them to the user. This makes it possible to efficiently analyze elements in places that are difficult for people to reach or places destroyed by disasters, design an optimal dwelling based on the analysis results, and visually present the design to the user.

[0052] The saver includes: means for analyzing the topography and geology of places that are difficult for people to reach and places destroyed by disasters based on environmental data, which is data including the topography, geology, and climate of the soil collected using specific sensors and cameras; an emotion engine that recognizes the emotions of users who wish to build a house in said places; means for designing a house with a shape and materials that are optimal for the user based on the results of the analysis and the emotions of the user by inputting specific prompt sentences into a generative AI model; and means for creating a construction plan necessary for building the house based on the design, and transmitting the created construction plan to a robot that will build the house or a construction company that will build the house.

[0053] The server includes an environmental analysis means for analyzing the work environment and work conditions at the location where the construction company will build the residence based on data collected using specific sensors and cameras, an emotion engine for recognizing the emotions of the workers building the residence, and a means for inputting specific prompt sentences into a generative AI model to suggest the optimal work procedures for the workers and the layout of equipment to be used in the construction based on the results of the analysis by the environmental analysis means and the emotions of the workers.

[0054] The server includes means for monitoring the construction progress of the dwelling, and means for notifying a specific person or location of an alert when a problem occurs in the construction progress.

[0055] "Local factors" refers to the physical and environmental information of a particular location, such as topography, geology, climate, and the resources present.

[0056] "Means of analysis" refers to the means of using devices such as sensors and cameras to collect elements present in the location and obtain them as data.

[0057] "Data analysis software" refers to software used to process collected data and extract necessary information. Specifically, it includes programming languages ​​such as Python and R and their libraries.

[0058] "Means for designing a dwelling with optimal shape and materials" refers to means for determining the shape and materials of a dwelling based on collected and analyzed data, including the use of generative AI models.

[0059] "Means for construction" refers to the means for actually constructing a dwelling based on a design, including construction machinery and methods.

[0060] "Means for transmitting analysis results to the terminal and displaying them to the user" refers to the means by which the server transmits analysis results to the terminal and enables the user to visually confirm the results, including communication protocols and display software.

[0061] "Generative AI" refers to a model that uses artificial intelligence technology to automatically generate optimal shapes and materials from data.

[0062] This invention is a system that uses devices such as sensors and cameras to analyze the elements present in a location, analyzes the collected data, and provides it to users. Specifically, in places that are difficult for people to reach or have been destroyed by disaster, the system collects information on the topography, geology, climate, and existing resources, and provides basic data for designing homes with optimal shapes and materials.

[0063] The server receives data sent from sensors and cameras. This data includes information on topography, geology, climate, and existing resources. The server analyzes the received data and extracts the necessary information. This analysis is performed using data analysis software such as Python and R. Specifically, the data is processed using Python's NumPy and Pandas libraries, and visualized using Matplotlib.

[0064] The device receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the device screen, and the user can rotate and zoom in and out to check the details.

[0065] As a concrete example, drones equipped with sensors and cameras are used in areas devastated by disasters. The drones collect information on the terrain, geology, climate, and existing resources, and send it to a server. The server analyzes the collected data and extracts a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This information is then sent to a device and displayed to the user.

[0066] An example of a prompt is as follows:

[0067] "Please explain the system that collects information on the topography, geology, climate, and existing resources of an area destroyed by a disaster, and provides the basic data for designing housing with optimal shapes and materials."

[0068] This system uses sensors and cameras to analyze elements present in the area, analyzes the collected data, and provides it to the user. Specific hardware used is a drone, sensors, and cameras, and software is Python and R.

[0069] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0070] Step 1: Data collection

[0071] The server controls sensors and cameras to collect data from a specified area. The sensors acquire information about the terrain and geology, and the cameras take high-resolution images and videos. For example, sensors and cameras mounted on a drone collect data while flying over a disaster area. The input is raw data from the sensors and cameras, and the output is collected data on the terrain, geology, climate, and existing resources.

[0072] Step 2: Send data

[0073] The server receives the collected data in real time. Data sent from drones and sensors is sent to the server via wireless communication. The server temporarily stores the received data and prepares it for analysis. The input is the data stream from the drones and sensors, and the output is the data stored on the server.

[0074] Step 3: Data analysis

[0075] The server analyzes the received data. Using data analysis software such as Python or R, it generates a 3D model of the terrain, evaluates geological properties, and analyzes climatic conditions. For example, it processes the data using Python's NumPy and Pandas libraries and visualizes it with Matplotlib. The input is the raw data stored on the server, and the output is the analyzed 3D model of the terrain, geological properties, and climatic conditions data.

[0076] Step 4: Send results

[0077] The server sends the analysis results to the terminal. The analysis results include a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This data is sent in a standard data format such as JSON. The input is the analyzed data, and the output is the JSON data sent to the terminal.

[0078] Step 5: View the results

[0079] The terminal receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the terminal screen, and the user can rotate and zoom in and out to check the details. The input is JSON data sent from the server, and the output is the visual information displayed to the user.

[0080] (Application example 1)

[0081] Next, a description will be given of Application Example 1 of Embodiment 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."

[0082] At disaster sites, there is a need to quickly and accurately collect information on the topography, geology, climate, existing resources, etc., and provide basic data for formulating optimal rescue operations and recovery plans. However, the conditions at disaster sites are extremely harsh, and it is often difficult for people to reach them directly. Therefore, a means of collecting information efficiently and safely is required.

[0083] 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.

[0084] In this invention, the server includes means for analyzing elements present at the site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for collecting information on the topography, geology, climate, existing resources, etc. at the disaster site, and means for transmitting the collected information in real time. This allows for the rapid and accurate collection of information at the disaster site, enabling the formulation of optimal rescue operations and recovery plans.

[0085] "Means for analyzing elements present at the site" refers to devices and systems that use sensors and cameras installed on-site to collect and analyze information on topography, geology, climate, existing resources, etc.

[0086] "Means for designing a dwelling with optimal shape and materials" refers to a design process or software for determining the shape and materials of a dwelling based on collected data.

[0087] "Means for constructing the dwelling based on the design" refers to the machinery, technology, and construction methods required to actually construct the designed dwelling.

[0088] "Means for collecting information on the topography, geology, climate, existing resources, etc. at disaster sites" refers to a system for collecting detailed information on the site using devices such as robots and drones dispatched to the disaster site.

[0089] "Means for transmitting collected information in real time" refers to communication devices and network technologies for instantly transmitting collected data to a remote server or command center.

[0090] The system for implementing this invention collects information on the topography, geology, climate, and existing resources at the disaster site, and provides basic data for formulating optimal rescue operations and recovery plans. A specific embodiment of this system is shown below.

[0091] System configuration

[0092] The system consists of the following main components:

[0093] 1. Sensors and cameras: These are installed at disaster sites to collect information on the topography, geology, climate, and existing resources. These include temperature sensors, humidity sensors, geological sensors, and high-resolution cameras.

[0094] 2. Data collection robots: These are deployed to disaster sites and equipped with sensors and cameras to collect information. The robots can operate remotely or autonomously.

[0095] 3. Data transmission device: A communication device for transmitting collected information to a server in real time. Specifically, this includes Wi-Fi and 4G / 5G communication modules.

[0096] 4. Server: A central processing unit for receiving and analyzing collected data. The server contains a database, analysis software, and generative AI models.

[0097] 5. Generative AI model: An artificial intelligence model that designs homes with optimal shapes and materials based on collected data.

[0098] Program processing

[0099] The server performs the following process.

[0100] 1. Data reception: Receives information transmitted from the data transmission device, including image data, temperature data, humidity data, and geological data.

[0101] 2. Data analysis: Analyze the received data and understand the situation at the disaster site. For the analysis, use image processing software (e.g., OpenCV) and data analysis libraries (e.g., NumPy, Pandas).

[0102] 3. Application of generative AI model: Based on the analysis results, a generative AI model is used to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network.

[0103] 4. Design data output: The data of the designed house is output and provided to the construction means, which enables the house to be constructed quickly and efficiently.

[0104] Specific examples

[0105] For example, a robot exploring the interior of a building that collapsed in an earthquake collects the following information:

[0106] Image: Image of the interior of the collapsed building

[0107] Temperature: On-site temperature (e.g. 25.3°C)

[0108] Humidity: Humidity at the site (e.g. 45.7%)

[0109] Geology: Site geology (e.g. bedrock)

[0110] This information is sent in real time to a server, which uses generative AI models to develop optimal rescue operations and recovery plans.

[0111] Prompt Sentence Examples

[0112] "Write a program for a robot to be sent to a disaster site to capture images of the interior of buildings that have collapsed due to an earthquake, collect temperature, humidity, and geological data, and send it to a server."

[0113] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0114] Step 1:

[0115] Data collection

[0116] The terminal (robot) arrives at the disaster site and uses sensors and cameras to collect information on the topography, geology, climate, existing resources, etc. Specifically, it acquires temperature data with a temperature sensor, humidity data with a humidity sensor, geological data with a geological sensor, and captures images of the site with a high-resolution camera.

[0117] Input: Environmental information of the disaster site

[0118] Output: Temperature data, humidity data, geological data, image data

[0119] Step 2:

[0120] Data transmission

[0121] The terminal (robot) transmits the collected data to the server in real time. Using a communication device (Wi-Fi, 4G / 5G communication module), the data is divided into packets and sent to a specified IP address on the server.

[0122] Input: Temperature data, humidity data, geological data, image data

[0123] Output: Data packet sent to the server

[0124] Step 3:

[0125] Data reception

[0126] The server receives data packets sent from the terminal, reconstructs the received packets, and stores them as temperature data, humidity data, geological data, and image data.

[0127] Input: Data packets sent from the device

[0128] Output: Stored temperature data, humidity data, geological data, image data

[0129] Step 4:

[0130] Data analysis

[0131] The server analyzes the received data. Specifically, it analyzes the image data using image processing software (e.g., OpenCV), and analyzes the temperature data, humidity data, and geological data using data analysis libraries (e.g., NumPy, Pandas).

[0132] Input: Stored temperature data, humidity data, geological data, image data

[0133] Output: Analysis results (detailed site conditions)

[0134] Step 5:

[0135] Applying generative AI models

[0136] The server then applies a generative AI model based on the analysis results to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network to design based on input data.

[0137] Input: Analysis results

[0138] Output: Design data (house with optimal shape and materials)

[0139] Step 6:

[0140] Design data output

[0141] The server outputs data on the house designed by the generative AI model and provides it to the construction method. The design data is output as CAD files and architectural drawings.

[0142] Input: Design data

[0143] Output: CAD files, architectural drawings

[0144] The above processing steps enable rapid and accurate collection of information at the disaster site, enabling optimal rescue operations and recovery plans to be formulated.

[0145] Example 2

[0146] Next, a description will be given of Example 2 of Form 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."

[0147] Conventional residential design systems have difficulty in designing with sufficient consideration of topographical and geological characteristics, making it particularly difficult to create optimal residential designs in places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, flexible design changes in response to user requests are not easy to make, so an efficient design process is required.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0149] In this invention, the server includes: a means for a user to input topographical data and geological data; a means for a terminal to transmit the input data to the server; a means for the server to generate a prompt to the generative AI model and request an optimal house design based on the input data; a means for the generative AI model to generate a design proposal; a means for the server to receive the generated design proposal and transmit it to the terminal; a means for the terminal to display the design proposal to the user; a means for the user to check the design proposal and input corrections or additional conditions as necessary; and a means for the terminal to transmit the corrections or additional conditions to the server and request a new design. This enables optimal house designs that take into account topographical and geological characteristics, and also enables flexible and efficient design changes to be made in response to user requests.

[0150] "Means for analyzing local elements" refers to equipment and software for collecting and analyzing local environmental information, such as topographical and geological data.

[0151] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the shape and materials of a residence based on collected data.

[0152] "Means for constructing the dwelling based on the design" refers to the construction methods and machinery used to actually build the designed dwelling.

[0153] "Means for user input of topographical and geological data" refers to an interface or device that allows a user to input topographical and geological information into the system.

[0154] "Means for the terminal to transmit input data to the server" refers to a communication device or software for transmitting data input by the user to the server.

[0155] "Means for the server to generate prompt text for the generative AI model and request the optimal home design based on the input data" refers to the function that creates prompt text based on the data collected by the server and requests the generative AI model to design.

[0156] "Means by which the generative AI model generates design proposals" refers to the algorithms and software that the generative AI model uses to create residential design proposals based on prompt statements.

[0157] "Means for the server to receive the generated design proposals and send them to the terminal" refers to the communications equipment and software used to send the design proposals received from the generative AI model to the terminal.

[0158] "Means by which the terminal displays the design proposal to the user" refers to a display or interface for displaying the design proposal received from the server to the user.

[0159] "Means for the user to review the design proposal and input corrections or additional conditions as necessary" refers to an interface or device that allows the user to review the displayed design proposal and input corrections or additional conditions.

[0160] "Means for the terminal to send corrections or additional conditions to the server and request a redesign" refers to communication devices or software that send corrections or additional conditions entered by the user to the server and request the generative AI model to design again.

[0161] This invention is a system that allows a user to input topographical and geological data and, based on that data, designs a dwelling with optimal shape and materials. A specific embodiment of this system will be described below.

[0162] First, the user inputs topographical and geological data through the system interface. For example, the topographical data is "steep mountainous area" and the geological data is "weak geology." This data is then sent from the user's device to the server. The device then converts the input data into JSON format and sends it to the server using an HTTP POST request.

[0163] The server generates a prompt based on the received topographical and geological data. Specifically, it generates the following prompt:

[0164] Terrain data: steep mountainous area

[0165] Geological data: Weak geology

[0166] Condition: Design a home that is earthquake-resistant

[0167] Based on these conditions, design a home with the optimal shape and materials.

[0168] The generated prompt sentence is sent to a generative AI model to request a design. For example, OpenAI's GPT-4 (registered trademark) can be used as the generative AI model.

[0169] The generative AI model generates optimal housing design proposals based on the prompt text. For example, it designs a stepped house that follows the terrain, or a house made of reinforced concrete that is earthquake-resistant. The generated design proposals are returned to the server in the following format:

[0170] Shape: Terraced housing that follows the terrain

[0171] Material: Reinforced concrete

[0172] Features: Earthquake-resistant and designed to adapt to steep terrain

[0173] The server sends the design proposal received from the generative AI model to the device. The device displays the received design proposal to the user. The user checks the design proposal through the interface and inputs corrections or additional conditions as necessary. For example, the user can input conditions such as "make the living room larger" or "change the roof material."

[0174] The device then sends any modifications or additional conditions entered by the user back to the server, which then generates a prompt for the generative AI model and requests a design. This process is repeated until the optimal home design is completed.

[0175] This system enables optimal residential design that takes into account the characteristics of the terrain and geology, and also allows for flexible and efficient design changes to be made according to the user's requests.The hardware used is a high-performance server (e.g., a server equipped with an NVIDIA GPU), and the software used is a generative AI model (e.g., OpenAI's GPT-4).

[0176] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0177] Step 1:

[0178] The user inputs topographical and geological data.

[0179] Specifically, the user inputs "steep mountainous area" into the "topography data" field and "weak geology" into the "geology data" field on the system interface.

[0180] Input: Topographical data, geological data

[0181] Output: Input data is saved on the user's device

[0182] Step 2:

[0183] The terminal sends the input data to the server.

[0184] Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request.

[0185] Input: User-entered topographic and geological data

[0186] Output: JSON formatted data sent to the server

[0187] Step 3:

[0188] The server generates a prompt for the generative AI model and requests the optimal home design based on the input data.

[0189] Specifically, the server analyzes the received JSON data and generates a prompt like the following:

[0190] Terrain data: steep mountainous area

[0191] Geological data: Weak geology

[0192] Condition: Design a home that is earthquake-resistant

[0193] Based on these conditions, design a home with the optimal shape and materials.

[0194] The generated prompt sentence is sent to the generative AI model.

[0195] Input: JSON format data sent to the server

[0196] Output: The prompt sent to the generative AI model

[0197] Step 4:

[0198] A generative AI model generates design proposals.

[0199] Specifically, the generative AI model generates optimal housing design proposals based on prompts, such as a stepped house that follows the terrain or a house made of reinforced concrete that is earthquake-resistant.

[0200] Input: A prompt sent to the generative AI model

[0201] Output: Generated residential design proposal

[0202] Step 5:

[0203] The server receives the generated design proposal and sends it to the terminal.

[0204] Specifically, the server sends the design proposal received from the generative AI model to the terminal in JSON format.

[0205] Input: Design proposals received from the generative AI model

[0206] Output: Design proposal in JSON format sent to the terminal

[0207] Step 6:

[0208] The terminal displays the design proposal to the user.

[0209] Specifically, the device analyzes the received JSON data and displays it to the user as follows:

[0210] Design proposal:

[0211] Shape: Terraced housing that follows the terrain

[0212] Material: Reinforced concrete

[0213] Features: Earthquake-resistant and designed to adapt to steep terrain

[0214] Input: Design proposal in JSON format sent to the terminal

[0215] Output: Design proposal displayed to the user

[0216] Step 7:

[0217] The user checks the design proposal and enters corrections or additional conditions as necessary.

[0218] Specifically, the user checks the displayed design proposal and inputs modifications or additional conditions, such as "make the living room larger" or "change the roof material."

[0219] Input: Design proposal displayed to the user

[0220] Output: Any corrections or additional conditions entered by the user

[0221] Step 8:

[0222] The device sends any corrections or additional conditions to the server and requests a new design.

[0223] Specifically, the device converts the corrections and additional conditions entered by the user into JSON format and sends it back to the server. The server then generates a prompt for the AI ​​model and requests it to design.

[0224] Input: Any corrections or additional conditions entered by the user

[0225] Output: Modifications and additional conditions sent to the server, and prompts sent back to the AI ​​model

[0226] (Application example 2)

[0227] Next, a description will be given of Application Example 2 of Form 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."

[0228] Conventional residential design systems have difficulty creating optimal residential designs that take into account environmental information such as topography and geology. Furthermore, optimization of factory layouts and equipment placement is often done manually, making it difficult to build efficient production lines. This has led to problems such as insufficient efficiency and safety in residential and factory designs.

[0229] 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.

[0230] In this invention, the server includes means for analyzing elements present on site, means for designing a residence with an optimal shape and materials based on the analysis results, means for constructing the residence based on the design, means for collecting information on the topography and equipment layout within the factory, means for designing an optimal factory layout and equipment layout based on the collected information, and means for generating an optimal layout using generative AI. This makes it possible to design an optimal residence that takes environmental information into consideration and to design an efficient factory layout.

[0231] "Elements present in situ" refers to physical and environmental information such as topography, geology, and facilities in a particular location or environment.

[0232] "Means for analysis" refers to devices or software used to analyze collected information and extract data for specific purposes.

[0233] "Means for designing a dwelling with optimal shape and materials" refers to design tools and software for optimizing the shape and materials of a dwelling based on collected and analyzed information.

[0234] "Means for constructing the dwelling based on the design" refers to machinery, equipment, or the process for actually constructing the designed dwelling.

[0235] "Means for collecting information on the topography and equipment layout within the factory" refers to sensors and data collection devices for collecting information on the topography and equipment layout within the factory.

[0236] "Means for designing optimal factory layouts and equipment placement based on collected information" refers to design tools and software for analyzing collected information and optimizing the layout and equipment placement within a factory.

[0237] "Generative AI" refers to artificial intelligence technology that generates optimal designs and layouts based on collected and analyzed information.

[0238] "Means for generating an optimal layout" refers to devices or software that use generative AI to generate an optimal layout based on collected and analyzed information.

[0239] To implement this invention, the server, the terminal, and the user must cooperate to operate the system. A specific embodiment of this is shown below.

[0240] System Program

[0241] The server first uses a means to analyze the elements present on the site to collect information on the topography, geology, facilities, etc. This information is acquired using sensors and data collection devices. Next, using a means to design a home with the optimal shape and materials based on the collected information, it utilizes generative AI to create the optimal home design. Then, using a means to build the home based on the design, it proceeds with the actual construction process.

[0242] Additionally, information about the factory's topography and equipment layout is collected using a method to gather information about the factory's interior. Based on the collected information, generative AI is used to design the optimal factory layout and equipment layout, generating the optimal layout.

[0243] Program processing explanation

[0244] The server uses software such as Python and OpenAI API to analyze the collected data and generate an optimal design. Specifically, it formats the topographical and facility data in JSON format and inputs it into a generative AI model. The generative AI model then generates the optimal design and layout based on this data.

[0245] The hardware used is suitable for servers and cloud environments (e.g., AWS (registered trademark), Google (registered trademark) Cloud), and the software used is Python and OpenAI API.

[0246] Specific examples

[0247] For example, consider a factory with a flat terrain, an area of ​​1,000 square meters, and two machines, Machine A (10x10) and Machine B (15x15), respectively. Based on this information, the following prompt sentence is input to the generative AI model:

[0248] Example prompt sentence:

[0249] Terrain data inside the factory: {"Terrain": "Flat", "Area": ​​"1000 square meters"}

[0250] Facility data: {"Facility 1": {"Type": "Machine A", "Size": "10x10"}, "Facility 2": {"Type": "Machine B", "Size": "15x15"}}

[0251] Use the above information to design the optimal factory layout.

[0252] By inputting this prompt into the generative AI model, the optimal factory layout is generated. The generated layout is sent from the server to the terminal, where the user can check and implement it.

[0253] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0254] Step 1:

[0255] The server uses sensors and data collection devices to collect information on elements present in the site (topography, geology, facilities, etc.). The input is raw data obtained from the sensors and data collection devices, and the output is a dataset of the collected environmental information. This dataset is used for subsequent analysis.

[0256] Step 2:

[0257] The server analyzes the collected environmental information. Specifically, it formats the data using a programming language such as Python and extracts the necessary information. The input is the dataset of environmental information collected in step 1, and the output is the analyzed data. This analyzed data forms the basis for generating an optimal design.

[0258] Step 3:

[0259] The server inputs a prompt to the generative AI model based on the analyzed data. The input is the analyzed data and a prompt for the generative AI model, and the output is the optimal design proposal obtained from the generative AI model. Specifically, the server uses the OpenAI API to call the generative AI model and inputs a prompt.

[0260] Step 4:

[0261] The server receives the optimal design proposal obtained from the generative AI model and provides it to the user. The input is the design proposal from the generative AI model, and the output is the design proposal provided to the user. Specifically, the server sends the design proposal to the terminal so that the user can check it.

[0262] Step 5:

[0263] The user checks the provided design proposal and makes corrections or approvals as necessary. The input is the design proposal provided by the server, and the output is the corrected or approved design proposal. Specifically, the user checks the design proposal using a terminal and sends feedback to the server.

[0264] Step 6:

[0265] The server receives feedback from the user and finalizes the design. The input is the user feedback, and the output is the finalized design. Specifically, the server analyzes the feedback, makes any necessary modifications, and then generates the final design.

[0266] Step 7:

[0267] The server starts the construction process of the house or factory based on the final design proposal that has been confirmed. The input is the final design proposal that has been confirmed, and the output is the start of the construction process. Specifically, it arranges for the resources required for construction and carries out the construction work.

[0268] Example 3

[0269] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0270] In conventional housing construction systems, the analysis of blueprint data, the generation of resource lists, and the generation of control codes for robots and 3D printers are often done manually, resulting in inefficiencies. Furthermore, there is insufficient automation to effectively utilize on-site resources, making the construction process complex and time-consuming.

[0271] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0272] In this invention, the server includes means for receiving and analyzing design drawing data, means for generating a required resource list, means for generating control code for the robot, and means for generating control code for the 3D printer, which enables automatic analysis of design drawing data, automatic generation of a resource list, and automatic generation of control codes for the robot and the 3D printer.

[0273] "Local factors" refer to the resources and environmental conditions available at the construction site.

[0274] "Analytical means" refers to equipment and software used to evaluate the elements present at the site and extract the necessary information.

[0275] "Design means" refers to devices and software for planning a home with the optimal shape and materials based on the analysis results.

[0276] "Means for receiving and analyzing design drawing data" refers to devices and software for receiving design drawing data provided by a user and analyzing its contents.

[0277] "Means for generating a list of required resources" refers to a device or software for creating a list of resources required for construction based on the results of analyzing the blueprint data.

[0278] "Means for generating control code for a robot" refers to a device or software for creating code containing instructions for a robot to operate according to a blueprint.

[0279] "Means for generating control code for a 3D printer" means a device or software that generates code containing instructions for a 3D printer to manufacture a part based on a design.

[0280] "Means for construction" refers to the equipment and machinery used to actually build a dwelling based on a blueprint.

[0281] This invention is a system that analyzes blueprint data for a house, creates a list of required resources, and automatically generates control codes for a robot and a 3D printer. Specific embodiments of this system are described below.

[0282] First, the user uploads the design data using the terminal. Through the terminal interface, the user selects the design file (e.g., "house_design.dwg") and clicks the upload button. This design data is then sent to the server.

[0283] The server uses a CAD analysis tool (e.g., AutoCAD) to analyze the received blueprint data. The server identifies each part of the blueprint and determines the resources required for each part. Based on the results of this analysis, the server generates a list of required resources. For example, resources such as wood, metal, and plastic may be listed.

[0284] Next, the server generates a control code for the robot. This control code contains instructions for the robot to operate according to the blueprint. The server uses a control code generation tool (e.g., ROS - Robot Operating System) to generate the control code for the robot. For example, a file called "robot_instructions.txt" is generated.

[0285] Similarly, the server generates control code for the 3D printer. This control code contains instructions for the 3D printer to manufacture the part based on the design. The server uses software to generate control code for the 3D printer. For example, a file called "3dprinter_instructions.gcode" is generated.

[0286] As a concrete example, we will explain the process of a user uploading design data. The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The server receives this data and starts analyzing it.

[0287] Once the analysis is complete, the server generates control codes for the robot (e.g., "robot_instructions.txt") and the 3D printer (e.g., "3dprinter_instructions.gcode"), which are then sent to the robot and the 3D printer to begin building the home.

[0288] Example prompts to input to a generative AI model:

[0289] "Please explain the process of the system that uploads blueprint data and builds a house using a robot and a 3D printer, including specific operations." The flow of the specific process in Example 3 will be explained using Figure 15.

[0290] Step 1:

[0291] The user uploads the blueprint data.

[0292] The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The input is the design data, and the output is the design data sent to the server.

[0293] Step 2:

[0294] The server receives the blueprint data and begins analysis.

[0295] The server opens the received blueprint data using a CAD analysis tool (e.g., AutoCAD). The input is the uploaded blueprint data, and the output is the analyzed data for each part of the blueprint. Specifically, the server identifies each part of the blueprint and specifies the resources required for each part.

[0296] Step 3:

[0297] The server generates a list of required resources.

[0298] The server generates a list of resources such as wood, metal, and plastic based on the analysis results. The input is the analyzed design data, and the output is a list of required resources (e.g., "resource_list.txt"). Specifically, the server lists the types and quantities of resources required for each part.

[0299] Step 4:

[0300] The server generates the control code for the robot.

[0301] The server generates control code for the robot based on the resource list and blueprint data. The input is the resource list and blueprint data, and the output is the control code for the robot (e.g., "robot_instructions.txt"). For specific operations, the server uses ROS to describe the robot's operation instructions in detail.

[0302] Step 5:

[0303] The server generates control codes for the 3D printer.

[0304] The server also generates control code for the 3D printer. The input is the resource list and blueprint data, and the output is the control code for the 3D printer (e.g., "3dprinter_instructions.gcode"). As a specific operation, the server describes the operation instructions for the 3D printer in detail.

[0305] Step 6:

[0306] The robot begins construction according to the control code.

[0307] The robot follows the control code received from the server and uses resources available on-site to build a house. The input is the control code for the robot, and the output is the parts of the house that are built. Specifically, the robot cuts wood and assembles walls.

[0308] Step 7:

[0309] The 3D printer manufactures and assembles the parts according to the control code.

[0310] The 3D printer manufactures parts based on the blueprint according to the control code received from the server. The input is the control code for the 3D printer, and the output is the manufactured part. In concrete terms, the 3D printer prints walls using plastic and assembles them.

[0311] (Application example 3)

[0312] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0313] In conventional housing construction systems, the management of blueprints, on-site resource scanning, control of construction equipment, real-time monitoring of construction progress, and alert notifications when problems occur are all performed individually, making integrated management difficult. Furthermore, there was no system for centrally managing these functions, making efficient housing construction difficult.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0315] In this invention, the server includes a means for uploading and managing blueprints, a means for scanning and managing on-site resources, a means for controlling construction equipment, a means for monitoring construction progress in real time, and a means for issuing alerts when problems occur in the construction progress. This allows for centralized management of blueprints, monitoring of construction progress, and responding to problems. Problems in the construction progress can occur when the expected weather worsens, when it becomes difficult to procure materials used for the housing due to changes in global conditions, when the arrival of materials at the construction site is delayed, or when there are fewer workers than planned.

[0316] "Means for analyzing elements present at the site" refers to devices and software for detecting resources and environmental conditions present at the site and analyzing that information.

[0317] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the optimal shape and materials of a residence based on the analyzed data.

[0318] "Means for constructing the residence based on the design" refers to devices such as robots and 3D printers for actually constructing the residence according to the design drawings.

[0319] "Means for uploading and managing blueprints" refers to software or an interface for uploading blueprints in digital format to a server and managing them.

[0320] The "means for scanning and managing on-site resources" refers to devices and software for scanning on-site resources and managing the data.

[0321] "Means for controlling construction equipment" refers to software or interfaces for controlling construction equipment such as robots and 3D printers.

[0322] "Means for monitoring construction progress in real time" refers to software or interfaces for monitoring the construction progress in real time and checking the progress.

[0323] "Means for issuing alerts when problems occur" refers to software or interfaces that issue alerts and notify relevant parties when problems occur during construction.

[0324] This invention is a system for centrally managing blueprints, scanning on-site resources, controlling construction equipment, monitoring construction progress in real time, and sending alerts when problems occur in a residential construction system.

[0325] Hardware and software used

[0326] Hardware: smartphones, robots, 3D printers

[0327] Software: Python, Flask (web framework), OpenCV (image processing library), NumPy (numerical calculation library)

[0328] System configuration

[0329] 1. Upload and manage blueprints:

[0330] Users take a photo of the blueprint using their smartphone and upload it to the server via the application.

[0331] The server stores and manages the uploaded blueprints.

[0332] 2. On-site resource scanning and management:

[0333] Users take photos of the site using their smartphone camera and send them to the server via the application.

[0334] The server uses OpenCV to process images, scan on-site resources, and manage the data.

[0335] 3. Control of construction equipment:

[0336] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[0337] The server sends the received commands to the construction equipment and controls it.

[0338] 4. Real-time monitoring of construction progress:

[0339] The server receives data from the construction equipment in real time and monitors progress.

[0340] Users can check their progress through the application.

[0341] 5. Alert notifications when problems occur:

[0342] The server generates alerts and notifies the user if any problems occur during construction.

[0343] Users can receive and respond to alerts through the application.

[0344] Specific examples

[0345] When uploading a blueprint:

[0346] Users take a photo of the blueprint with their smartphone camera and upload it through the application.

[0347] Example prompt: "Please upload the blueprint."

[0348] When scanning for resources in the field:

[0349] Users take a photo of the site using their smartphone camera and scan it through the application.

[0350] Example prompt: "Use your camera to take a photo of the site to scan for on-site resources."

[0351] When controlling a construction device:

[0352] The user enters and sends commands through the application's interface.

[0353] Example prompt: "Enter the command you want to send to your robot or 3D printer."

[0354] When checking construction progress:

[0355] The user can check the progress through the application.

[0356] Example prompt: "Press the monitoring button to check the construction progress."

[0357] If you encounter problems:

[0358] The server generates an alert and notifies the user.

[0359] Example prompt: "There's a problem. Please check your alerts."

[0360] In this way, it becomes possible to centrally manage everything from managing blueprints to monitoring construction progress and responding when problems arise.

[0361] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0362] Step 1:

[0363] Users take a photo of the blueprint with their smartphone camera and upload it to the server via the application.

[0364] Input: Blueprint image file

[0365] Output: Blueprint file saved on the server

[0366] Specific operation: A user launches the application, takes a picture of a blueprint, and presses the "Upload" button. The application sends the image file to the server, and the server saves the received file.

[0367] Step 2:

[0368] Users take photos of the site using their smartphone camera and send them to the server via the application.

[0369] Input: Photo file of the scene

[0370] Output: On-site resource data stored on a server

[0371] Specific operation: The user takes a photo of the site and presses the "Scan" button. The application sends the photo file to the server, which processes the image using OpenCV, extracts and stores the site resource data.

[0372] Step 3:

[0373] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[0374] Input: Command to construction device

[0375] Output: Command sent to the construction device

[0376] Specific operation: The user inputs a command into the application interface and presses the "Send" button. The application sends the command to the server, and the server sends the received command to the construction device.

[0377] Step 4:

[0378] The server receives data from the construction equipment in real time and monitors progress.

[0379] Input: Progress data from construction device

[0380] Output: Real-time progress updates

[0381] Specific operation: The construction device sends progress data to the server, the server analyzes the received data and updates the progress status. The user can check the progress status through the application.

[0382] Step 5:

[0383] The server generates alerts and notifies the user if any problems occur during construction.

[0384] Input: Data on the problem occurrence

[0385] Output: An alert to notify the user

[0386] Specific operation: The server monitors data from the construction equipment and generates an alert if a problem occurs. The alert is notified to the user through the application. The user checks the alert and takes action.

[0387] 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.

[0388] "Example 1"

[0389] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[0390] "Example 2"

[0391] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[0392] "Example 3"

[0393] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[0394] The processing flow of each embodiment will be described below.

[0395] "Example 1"

[0396] Step 1: The emotion engine recognizes the user's emotions from their tone of voice, facial expressions, and language.

[0397] Step 2: The user's emotions recognized by the emotion engine are input into a means for designing a house with optimal shape and materials.

[0398] Step 3: The design means designs a dwelling with an optimal shape and materials based on the input user's emotions. For example, if the user feels that they are looking for a sense of security, the design means designs a dwelling with a shape and materials that will give them a sense of security.

[0399] Step 4: The means for constructing the house based on the design operates. At this time, the construction means also takes into account the user's emotions recognized by the emotion engine. For example, if the user feels that they are looking for a sense of security, the construction means uses that information to construct a house that provides a sense of security.

[0400] Example 1

[0401] Next, a description will be given of Example 1 of Form 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."

[0402] Conventional residential design systems have limitations in collecting and analyzing environmental data, making it particularly difficult to collect data from places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, residential design does not take into account the user's emotions, making it impossible to increase the user's psychological satisfaction. This has led to the issue that residential design and construction do not adequately meet the user's needs.

[0403] 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.

[0404] In this invention, the server includes means for analyzing elements present at the site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for recognizing a user's emotions, means for reflecting the recognized emotions in the design, and means for reflecting the recognized emotions in the construction. This allows for efficient collection and analysis of environmental data and enables the design and construction of a dwelling that takes the user's emotions into consideration.

[0405] "Local factors" refers to the physical and environmental information of a particular location, such as topography, geology, climate, and the resources present.

[0406] "Means of analysis" refers to the means of collecting and analyzing elements present in the location using devices such as sensors and cameras.

[0407] "Designing means" refers to means for designing a dwelling with optimal shape and materials based on collected and analyzed data.

[0408] "Means to construct" refers to the means to actually construct the designed dwelling.

[0409] "Means for recognizing a user's emotions" refers to means for recognizing emotions from the user's tone of voice, facial expressions, choice of words, etc.

[0410] "Means for reflecting recognized emotions in the design" refers to means for reflecting the user's emotions in the design of the shape and materials of the home.

[0411] "Means for reflecting recognized emotions in construction" refers to means for taking into account the user's emotions and reflecting them in the construction process of a home.

[0412] "Generative AI" refers to a system that uses artificial intelligence technology to automatically design homes with optimal shapes and materials based on data.

[0413] This invention is a system that uses devices such as sensors and cameras to analyze elements present in a location and designs and constructs a residence that takes into account the user's emotions. A specific embodiment of this system will be described below.

[0414] System configuration

[0415] The system consists of the following major components:

[0416] 1. Data Collection Equipment:

[0417] The server uses sensors and cameras to collect environmental data such as topography, geology, climate, and existing resources. Specifically, it remotely controls cameras and geological sensors mounted on drones to acquire data.

[0418] 2. Emotion recognition device:

[0419] The device uses an emotion engine to analyze the user's tone of voice, facial expression, and choice of words to recognize their emotions. For example, if a user says, "I want a sense of security," the device will recognize that they are seeking a sense of security based on their tone of voice and facial expression.

[0420] 3. Design equipment:

[0421] The server integrates the collected environmental data with the user's emotional data and uses generative AI to design a home with the optimal shape and materials. For example, it may generate a warm design that makes extensive use of wood to create a sense of security.

[0422] 4. Construction equipment:

[0423] The server creates a construction plan based on the design data, i.e., sends construction instructions to the construction robot based on the construction plan required to build the residence. Specifically, to build a residence that provides a sense of security using wood, the server may instruct the construction robot on how to procure high-quality materials, the process for building the residence, the cost of building the residence, the number of workers required to build the residence, and details of various processes from the foundation to the roof. Note that the server may send construction instructions to a construction company instead of the construction robot, causing the construction company and its affiliated companies to build the residence.

[0424] Hardware and software used

[0425] Sensors: Geological sensors, climate sensors

[0426] Camera: High-resolution camera, drone-mounted camera

[0427] Emotion engine: Voice analysis software, facial expression recognition software

[0428] Generative AI: Residential Design Algorithm

[0429] Construction Robot: Autonomous Building Robot

[0430] Specific examples

[0431] For example, in a disaster area, the server collects topographical data using a drone's camera and analyzes data from geological sensors to identify geological structures. Next, when a user speaks to the device saying, "I want a sense of security," the device analyzes the user's tone of voice and facial expression to recognize that the user is seeking a sense of security. The server integrates this data and uses generative AI to design a home with a warm design that makes extensive use of wood. Finally, the server instructs a construction robot to build a home that provides a sense of security using wood.

[0432] Prompt Sentence Examples

[0433] An example of a prompt sentence to be input to the generative AI model is shown below.

[0434] Prompt: "Describe a system that collects topographical data from disaster areas and designs and builds optimal housing for users seeking safety."

[0435] By feeding this prompt into a generative AI model, a detailed description of the system is obtained.

[0436] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0437] Step 1:

[0438] Starting Data Collection

[0439] The server activates the sensors and cameras and begins collecting data.

[0440] Input: Sensor and camera activation instructions

[0441] Specific operation: The server remotely controls the camera mounted on the drone to take aerial photographs of the disaster area.

[0442] Output: Collected data on topography, geology, climate, and existing resources.

[0443] Step 2:

[0444] Environmental data collection

[0445] The server collects data from sensors and cameras on the terrain, geology, climate, and existing resources.

[0446] Input: Data from sensors and cameras

[0447] What it does: The server performs 3D mapping of terrain data and analyzes data from geological sensors to identify geological structures.

[0448] Output: Parsed environmental data

[0449] Step 3:

[0450] User Interaction

[0451] The user speaks into the terminal.

[0452] Input: User's voice and facial expressions

[0453] Specific action: The user speaks to the device, "I want a sense of security."

[0454] Output: User's voice and facial expression data

[0455] Step 4:

[0456] Activating the Emotion Engine

[0457] The device uses an emotion engine to analyze the user's tone of voice, facial expressions, and language to recognize emotions.

[0458] Input: User's voice and facial expression data

[0459] Specific operation: The device captures the user's tone of voice and facial expressions using a camera and microphone, and analyzes them using an emotion engine.

[0460] Output: Recognized user emotion data

[0461] Step 5:

[0462] Data Integration

[0463] The server integrates the collected environmental data with the recognized user emotion data.

[0464] Input: Environmental data and user emotion data

[0465] Specific operation: The server combines the terrain data and the user's emotion data into a single dataset.

[0466] Output: A consolidated dataset

[0467] Step 6:

[0468] Execution of design algorithms

[0469] The server runs an algorithm to design a home with optimal shape and materials based on the integrated data.

[0470] Input: Integrated dataset

[0471] What it does: The server runs an algorithm that generates a warm design that makes extensive use of wood to create a sense of security.

[0472] Output: Design data

[0473] Step 7:

[0474] Creation of construction plans

[0475] The server creates a construction plan based on the design data.

[0476] Input: Design data

[0477] Specific behavior: The server creates a plan that tells the construction robot which materials to use and in what order.

[0478] Output: Construction plan

[0479] Step 8:

[0480] Sending construction orders

[0481] The server sends the construction plan to the construction robot and causes it to begin construction.

[0482] Input: Construction Plan

[0483] Specific behavior: The server sends instructions to the construction robot to build a safe habitat using wood.

[0484] Output: Completed house

[0485] (Application example 1)

[0486] Next, a description will be given of Application Example 1 of Embodiment 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."

[0487] Conventional housing design systems can design housing with optimal shapes and materials based on the analysis of environmental factors, but they do not take into account the work environment or the emotions of workers, which can lead to problems such as reduced work efficiency and worker satisfaction.In addition, they do not adequately optimize the work environment during disasters or in places that are difficult for people to reach, which can compromise work safety and efficiency.

[0488] 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.

[0489] In this invention, the server includes means for analyzing elements present on site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for analyzing the work environment and work situation, means for recognizing worker emotions, and means for proposing optimal work procedures and layouts based on the analysis results and emotion recognition results. This makes it possible to propose optimal work procedures and layouts that take into account the work environment and worker emotions, thereby improving work efficiency and worker satisfaction. It also makes it possible to optimize the work environment during disasters or in places that are difficult for people to reach, thereby improving work safety and efficiency.

[0490] "Means for analyzing elements present in the location" refers to devices and methods that use sensors and cameras to collect and analyze information about the environment and objects present in a specific location.

[0491] The "means for designing a dwelling with optimal shape and materials" refers to a device or method for designing an optimal shape and materials for a dwelling based on collected environmental information.

[0492] "Means for constructing the dwelling based on the design" refers to devices and methods for actually constructing the designed dwelling.

[0493] "Means for analyzing the work environment and work status" refers to devices and methods that use sensors and cameras to collect and analyze the environment and work progress in factories and work sites.

[0494] "Means for recognizing the emotions of workers" refers to devices or methods for recognizing emotions from the tone of voice, facial expressions, and language of workers.

[0495] The "means for proposing optimal work procedures and layouts" refers to a device or method that proposes optimal work procedures and layouts to improve work efficiency and worker satisfaction based on collected environmental information and emotional information.

[0496] The system for implementing this invention has the following configuration. First, a means for analyzing the elements present in the location using sensors and cameras is required. This allows for the collection and analysis of information about the environment and objects present in a specific location. Specifically, a Logitech C920 or similar device is used as the camera, and an Arduino sensor kit is used as the sensor.

[0497] Next, we need a method to design a home with the optimal shape and materials based on the collected environmental information. This method uses generative AI to design a home with the optimal shape and materials. For example, a generative AI model can be used to design a home based on the collected data.

[0498] Additionally, a means is needed for actually constructing the designed dwelling, including an apparatus and method for constructing the dwelling based on the design.

[0499] In addition, a method for analyzing the work environment and work situation in factories and work sites is also required. This will enable real-time analysis of the work environment and work situation and suggest optimal work procedures and layouts. Specifically, OpenCV is used to acquire images from a camera in real time, and FactoryOptimizer is used to analyze the environmental information.

[0500] Furthermore, a means for recognizing the emotions of workers is also required. This means includes devices and methods for recognizing emotions from the worker's tone of voice, facial expressions, and language. Specifically, the Emotion Engine is used to recognize the emotions of workers.

[0501] Finally, a means is needed to propose optimal work procedures and layouts based on the collected environmental and emotional information, including devices and methods for proposing optimal work procedures and layouts to improve work efficiency and worker satisfaction.

[0502] For example, if a worker feels fatigued, the system can suggest simplifying work procedures and encouraging them to take a break. Also, if the layout of machines in a factory is inefficient, the system can suggest optimal layout.

[0503] An example of a prompt is as follows:

[0504] "Develop an application that analyzes the environment and worker emotions within the factory and proposes optimal work procedures and layouts. The application will collect data in real time using cameras and sensors, and recognize the emotions of workers using an emotion engine. Specific proposals will include simplifying work procedures and optimizing machine layouts."

[0505] In this way, it becomes possible to propose optimal work procedures and layouts that take into account the work environment and worker emotions, improving work efficiency and worker satisfaction. It can also optimize the work environment during disasters or in places that are difficult for people to reach, improving work safety and efficiency.

[0506] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0507] Step 1:

[0508] The server collects the elements present in the location in real time using cameras and sensors. Specifically, it acquires video data from cameras (e.g., Logitech C920) and environmental data from sensors (e.g., Arduino sensor kit). The inputs are video data and environmental data, and the output is a combination of these data.

[0509] Step 2:

[0510] The server analyzes the collected video data and environmental data. Specifically, it processes the video data using OpenCV and analyzes the environmental data using FactoryOptimizer. The input is the data obtained in step 1, and the output is the analysis results. The analysis results include details of the work environment and work situation.

[0511] Step 3:

[0512] The server uses EmotionEngine to recognize the worker's emotions. Specifically, it analyzes the worker's tone of voice, facial expressions, and language from the video data to identify their emotions. The input is the video data obtained in Step 1, and the output is the emotion recognition results.

[0513] Step 4:

[0514] The server proposes optimal work procedures and layouts based on the analysis results and emotion recognition results. Specifically, it uses FactoryOptimizer to calculate optimal work procedures and layouts to improve work efficiency and worker satisfaction. The input is the data obtained in Step 2 and Step 3, and the output is an optimization proposal.

[0515] Step 5:

[0516] The server presents optimization proposals to the user. Specifically, it displays proposals such as simplification of work procedures and optimization of machine placement via a display or smartphone app. The input is the optimization proposal obtained in step 4, and the output is the information presented to the user.

[0517] Step 6:

[0518] The user checks the optimization proposals presented by the server and changes the work procedures and layout as necessary. Specifically, the user adjusts the work environment based on the proposals to improve work efficiency and satisfaction. The input is the information presented in Step 5, and the output is the adjusted work environment.

[0519] Example 2

[0520] Next, a description will be given of Example 2 of Form 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."

[0521] Conventional residential design systems base their designs solely on environmental information, without taking into account the user's emotions or psychological factors, resulting in low user satisfaction. Another issue is that it is difficult to analyze the elements of places destroyed by disasters or places that are difficult for people to reach. Furthermore, due to a lack of technology to design homes with optimal shapes and materials, the safety and comfort of homes may not be fully ensured.

[0522] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0523] In this invention, the server includes a means for analyzing elements present at the site, a means for designing a dwelling with optimal shape and materials based on the analysis results, a means for constructing the dwelling based on the design, a means for recognizing a user's emotions, and a means for designing the dwelling while taking the recognized emotions into consideration. This enables dwelling design that simultaneously takes into consideration environmental information and the user's emotions, thereby increasing user satisfaction. Furthermore, by analyzing elements in places destroyed by disasters or places that are difficult for people to reach, it becomes possible to provide safer and more comfortable dwellings. Furthermore, by using a generative AI model, dwellings with optimal shape and materials can be efficiently designed.

[0524] "Means for analyzing elements" refers to devices and software for collecting and analyzing environmental information such as the topography and geology present in a given area.

[0525] The "means for designing a dwelling with optimal shape and materials" refers to a device or software for determining the shape and materials of a dwelling based on collected environmental information and the user's emotions.

[0526] "Means for constructing a dwelling" refers to the equipment and methods for actually constructing the designed dwelling.

[0527] "Means for recognizing user emotions" refers to devices or software that analyze the user's tone of voice, facial expressions, choice of words, etc., to identify the user's emotions.

[0528] "Means for designing a residence taking into consideration recognized emotions" refers to devices or software that determine the shape and materials of a residence based on the user's emotional information in a way that increases the user's psychological satisfaction.

[0529] A "generative AI model" is an artificial intelligence model that generates optimal housing designs based on collected data.

[0530] A "prompt" is an instruction entered into a generative AI model, which specifically indicates the design requirements and conditions.

[0531] The present invention relates to a residential design system that takes into account the user's emotions. Specific embodiments of this system will be described below.

[0532] Information gathering

[0533] When a user requests a house design, the device first collects environmental information such as topography and geology. Specifically, the device uses GPS and a geographic information system (GIS) to obtain information on the topography and geology of the specified location. For example, the device might obtain data such as "This area has steep topography and fragile geology."

[0534] emotion recognition

[0535] Next, the device uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotions based on their tone of voice, facial expressions, and choice of words. For example, if the user says, "I'm looking for reassurance," the emotion engine will recognize that the user is looking for reassurance based on their choice of words and tone of voice.

[0536] Residential Design

[0537] Based on the collected environmental information and the user's emotions recognized by the emotion engine, the server uses generative AI to design a home with the optimal shape and materials. Specifically, the server inputs the collected data into a generative AI model to generate the optimal home design. For example, the prompt could be "Design a home with a shape suitable for steep terrain, made of earthquake-resistant materials, and designed to give a sense of security."

[0538] Housing construction

[0539] Once the design is complete, the server uses a construction tool to build the residence. Specifically, the server sends the blueprint to a construction company, which then builds the residence using the specified materials and design. The construction company then actually carries out the construction work on-site.

[0540] Specific examples

[0541] For example, suppose a user wishes to build a home in a mountainous region and desires a sense of security. The device collects information about the steep terrain and fragile geology of the mountainous region, and uses its emotion engine to recognize that the user desires a sense of security. Based on this information, the server designs a home that conforms to the terrain, uses earthquake-resistant materials, and has a design that provides a sense of security. The server then uses construction tools to actually build the home.

[0542] Prompt Sentence Examples

[0543] "I want to build a house in the mountains. The terrain is steep and the geology is fragile. I want a sense of security. Please design a house with the optimal shape and materials."

[0544] In this way, this invention is a system that designs and constructs the optimal residence based on the user's requirements and environmental information.

[0545] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0546] Step 1:

[0547] A user requests a design for a house.

[0548] The user types into the terminal interface, "I want to build a house in the mountains."

[0549] Input: User's request (e.g., "I want to build a house in the mountains.")

[0550] Output: User request data

[0551] Step 2:

[0552] The device collects environmental information such as topography and geology.

[0553] The device activates the GPS to obtain topographical data for the specified location and accesses a GIS database to obtain geological information.

[0554] Input: User request data

[0555] Output: Topographical data, geological data

[0556] Step 3:

[0557] The terminal recognizes the user's emotions using an emotion engine.

[0558] The device records the user's voice and analyzes the tone of the voice using voice analysis software, and also captures the user's facial expressions using a camera and analyzes them using facial expression analysis software.

[0559] Input: User's tone of voice, facial expressions, and language

[0560] Output: User emotion data (e.g., desire for reassurance)

[0561] Step 4:

[0562] Based on the environmental information collected by the server and the user's emotions recognized by the emotion engine, a generative AI is used to design a home with the optimal shape and materials.

[0563] The server inputs the collected data into a generative AI model to generate an optimal home design. For example, a prompt might be entered: "Design a home that is suitable for steep terrain, uses earthquake-resistant materials, and has a design that gives a sense of security."

[0564] Input: Topographical data, geological data, user emotional data

[0565] Output: Residential design data

[0566] Step 5:

[0567] The server will build the house based on the design.

[0568] The server sends the blueprints to a builder, who then builds the house using the specified materials and design. The builder then actually carries out the construction work on-site.

[0569] Input: Residential design data

[0570] Output: Completed house

[0571] (Application example 2)

[0572] Next, a description will be given of Application Example 2 of Form 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."

[0573] Conventional residential design systems can take into account environmental factors such as topography and geology, but it is difficult to create designs that reflect the user's emotions. In addition, there is a demand for optimal designs that reflect the user's emotions and real-time environmental data, even in the design of brick-and-mortar stores. This will increase user satisfaction while also achieving safe designs that are suited to the environment.

[0574] 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.

[0575] In this invention, the server includes means for analyzing elements present on the site, means for designing a residence with an optimal shape and materials based on the analysis results, means for constructing the residence based on the design, means for recognizing a user's emotions, means for adjusting the design based on the recognized emotions, means for capturing environmental data using a smart device, and means for proposing an optimal design using generative AI. This enables the design of an optimal residence or physical store that reflects the user's emotions and real-time environmental data.

[0576] "Means for analyzing elements present in the area" refers to devices and software for collecting environmental data and analyzing elements such as topography and geology.

[0577] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the optimal shape and materials based on collected environmental data.

[0578] "Means for constructing the dwelling based on the design" refers to the machinery and construction methods used to actually construct the designed dwelling.

[0579] "Means for recognizing the user's emotions" refers to sensors and software for analyzing emotions from the user's facial expressions, tone of voice, etc.

[0580] "Means for adjusting the design based on recognized emotions" refers to algorithms and tools for modifying the design based on user emotion data.

[0581] "Means for capturing environmental data using a smart device" refers to equipment or software for collecting surrounding environmental data using devices such as smart glasses or smartphones.

[0582] "Means of proposing optimal designs using generative AI" refers to algorithms and systems that utilize generative AI to automatically generate optimal designs based on collected data and user emotions.

[0583] A system for implementing the present invention has the following configuration.

[0584] First, a user puts on smart glasses and designs a physical store. The smart glasses are equipped with a camera that captures data on the surrounding environment. This data includes information on topography and geology. The smart glasses then analyze the captured data using image processing software such as OpenCV.

[0585] Next, an emotion engine is used to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice to recognize emotions such as relief or satisfaction. This emotion data is obtained using software such as EmotionRecognizer.

[0586] The server uses generative AI to propose optimal designs based on the collected environmental and emotional data. The generative AI uses algorithms such as AIDesign to determine shapes and materials suitable for the terrain and geology, and generates designs that reflect the user's emotions.

[0587] As a concrete example, when a user wears smart glasses and designs a physical store, the camera in the glasses captures the surrounding terrain and geology. The emotion engine recognizes from the user's facial expression and tone of voice that they are seeking a sense of security, and the generative AI proposes a store design with a shape that suits the terrain and materials that will give them a sense of security.

[0588] An example prompt is, "If the user is looking for a sense of security, please design a brick-and-mortar store with the right shape and materials for an area with steep terrain and fragile geology."

[0589] This system will enable optimal design of homes and physical stores that reflect user emotions and real-time environmental data.

[0590] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0591] Step 1:

[0592] A user puts on the smart glasses and starts designing a brick-and-mortar store. The camera in the smart glasses captures the surrounding environment data. The input is the video data from the camera in the smart glasses, and the output is the captured environmental data. Specifically, the camera in the smart glasses continuously captures video and transmits the data to the server in real time.

[0593] Step 2:

[0594] The server analyzes the captured environmental data using image processing software such as OpenCV. The input is the video data sent from the smart glasses, and the output is the analyzed topographical and geological information. Specifically, the server splits the video data into frames and applies algorithms to extract topographical and geological features.

[0595] Step 3:

[0596] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions and tone of voice. The input is the user's facial expression and tone of voice data acquired from the camera and microphone of the smart glasses, and the output is the recognized emotion data. Specifically, the emotion engine uses a facial expression recognition algorithm and a voice analysis algorithm to analyze the user's emotions in real time.

[0597] Step 4:

[0598] The server uses generative AI to propose optimal designs based on the collected environmental data and emotional data. The input is analyzed topographical and geological information and recognized emotional data, and the output is a design proposal for the optimal shape and materials. Specifically, the generative AI generates a prompt statement and then generates a design proposal based on that prompt statement.

[0599] Step 5:

[0600] The generated design proposal is presented to the user. The input is the design proposal from the generative AI, and the output is the design proposal presented to the user. Specifically, the server displays the design proposal on the smart glasses display so that the user can check it.

[0601] Step 6:

[0602] The user provides feedback on the design proposal. The input is the user's feedback, and the output is the design proposal adjusted based on the feedback. Specifically, the user inputs feedback through the interface of the smart glasses, and the server readjusts the design proposal based on that feedback.

[0603] Step 7:

[0604] Construction of the physical store begins based on the final design plan. The input is the final, adjusted design plan, and the output is the constructed physical store. In concrete terms, the construction company carries out construction based on the design plan and builds the physical store.

[0605] Example 3

[0606] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0607] Conventional housing design and construction systems have been unable to take into account the user's emotions and have been unable to sufficiently increase the user's psychological satisfaction. Furthermore, it has been difficult to provide appropriate housing in times of disaster or special circumstances. This has made it difficult to respond to the diverse needs of users, and it has been impossible to provide a comfortable and secure living environment.

[0608] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0609] In this invention, the server includes means for recognizing a user's emotion, means for designing a residence taking into consideration the recognized user's emotion, and means for constructing a residence taking into consideration the recognized user's emotion, thereby enabling the design and construction of an optimal residence that reflects the user's emotion.

[0610] "Elements present in place" refers to the physical elements such as the natural environment, man-made objects, and resources at the location where the dwelling is to be built.

[0611] "Means for analyzing" refers to equipment or software for analyzing the element and assessing its properties or condition.

[0612] "Design means" refers to devices and software for determining the shape and materials of a residence and creating blueprints based on the analysis results and other conditions.

[0613] "Means for construction" refers to the equipment and machinery used to actually build a dwelling based on a blueprint.

[0614] "Means for recognizing user emotions" refers to devices or software that analyze the user's tone of voice, facial expressions, choice of words, etc. to identify the user's emotions.

[0615] "Means for designing a residence taking into consideration the recognized emotions of a user" refers to devices and software for designing a residence with the optimal shape and materials based on the user's emotional information.

[0616] "Means for constructing a residence taking into consideration the recognized emotions of a user" refers to a device or machine for constructing a residence based on a blueprint, using the user's emotional information.

[0617] "Generative AI" refers to algorithms and software that use artificial intelligence technology to generate optimal designs and solutions from data.

[0618] MODE FOR CARRYING OUT THE INVENTION

[0619] This invention is a system that recognizes a user's emotions, designs a home with the optimal shape and materials based on those emotions, and builds it using robots and 3D printers. A specific embodiment of this system is described below.

[0620] User Emotion Recognition

[0621] The user speaks to the system, for example, "I want a safe home." The device captures the user's voice with a microphone and generates audio data. The device sends the audio data to the server. The server converts the audio data into text using speech recognition software (e.g., a speech recognition API). The server inputs the text data into an emotion engine to analyze the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, and choice of words and recognizes that the user wants a sense of security.

[0622] Designing a home using design tools

[0623] The server sends the user's emotional information obtained from the emotion engine to the design tool. The server uses architectural design software (e.g., design software) to design a home based on the emotional information. The server generates blueprints and selects shapes and materials that will give a sense of security. For example, the server creates blueprints using sturdy, warm materials.

[0624] Building a dwelling by construction means

[0625] The server sends the blueprint to the construction means. The terminal receives the blueprint and issues instructions to the robots and 3D printers. The robots build the dwelling using resources available on site based on the blueprint. For example, the robots assemble wood and metal to create the framework of the dwelling. The 3D printers manufacture parts based on the blueprint and assemble them to build the dwelling. For example, the 3D printers manufacture wall and roof parts using plastic and concrete, which are then assembled by the robots.

[0626] Hardware and software used

[0627] Emotion engine: Software for recognizing user emotions. Specifically, it uses voice recognition software (e.g., voice recognition API) and facial expression recognition software (e.g., facial expression recognition API).

[0628] Design method: Using architectural design software (e.g., design software), a residence is designed based on information from the emotion engine.

[0629] Construction method: Using robots (e.g., construction robots) or 3D printers (e.g., 3D printers) to build a dwelling based on a blueprint.

[0630] Specific examples

[0631] User input: "I want a safe home."

[0632] Emotion engine recognition results: Recognizing that the user is seeking reassurance

[0633] Design output: A design using sturdy and warm materials

[0634] How the construction method works: A 3D printer produces parts based on a blueprint, and a robot assembles them to build a home.

[0635] Example prompts for generative AI models

[0636] "If users want a sense of security, what kind of shape and materials should a home be designed with?"

[0637] This system aims to provide a more comfortable and satisfying living environment by designing and constructing a residence taking into consideration the user's emotions. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[0638] Step 1:

[0639] User Emotion Recognition

[0640] Input: The user speaks to the system, for example, "I want a safe home."

[0641] Specific operation: The device captures the user's voice with a microphone and generates audio data.

[0642] Data processing: The device sends the voice data to the server, which converts it into text using voice recognition software (e.g., a voice recognition API).

[0643] Output: Text data is generated.

[0644] Step 2:

[0645] Emotion analysis

[0646] Input: The text data generated in step 1.

[0647] Specific operation: The server inputs text data into the emotion engine and analyzes the user's emotions.

[0648] Data calculations: The emotion engine analyzes the user's tone of voice, facial expressions, and language to recognize that the user is seeking reassurance.

[0649] Output: User's emotion information is generated.

[0650] Step 3:

[0651] Residential Design

[0652] Input: User emotion information generated in step 2.

[0653] Specific operation: The server transmits the user's emotion information obtained from the emotion engine to the design means.

[0654] Data processing: The server uses architectural design software (e.g., design software) to design a house based on the emotional information.

[0655] Output: A design drawing is generated with shapes and materials selected to give a sense of security.

[0656] Step 4:

[0657] Submitting blueprints

[0658] Input: The blueprint generated in step 3.

[0659] Specific operation: The server sends the blueprint to the construction method.

[0660] Data processing: Sends blueprint data to the device.

[0661] Output: The blueprint data is sent to the device.

[0662] Step 5:

[0663] Building a residence

[0664] Input: Blueprint data submitted in step 4.

[0665] Specific operation: The terminal receives the blueprint and issues instructions to the robot and 3D printer.

[0666] Data computation: Robots build homes based on blueprints using resources available on-site. For example, robots assemble wood and metal to create the framework of a home. 3D printers manufacture parts based on blueprints and assemble them to build a home.

[0667] Output: A completed house is generated.

[0668] (Application example 3)

[0669] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0670] In conventional housing construction systems, the design and construction did not take into account the user's emotions, making it difficult to increase the user's psychological satisfaction. Furthermore, the work environment in factories was not optimized to take into account the emotions of the workers, making it difficult to improve work efficiency and safety.

[0671] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for analyzing elements present on site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for recognizing emotions, and means for optimizing the work environment and work content based on the recognized emotions. This makes it possible to design and construct a dwelling taking into account the user's emotions, and to optimize the work environment taking into account the emotions of workers.

[0672] "Means for analyzing elements present on site" refers to devices and methods for detecting resources and environmental conditions present on site and analyzing this information.

[0673] "Means for designing a dwelling with optimal shape and materials" refers to a device or method for determining the shape of a dwelling and the materials to be used based on the analysis results.

[0674] "Means for constructing the dwelling based on the design" refers to a device or method for actually constructing the dwelling according to the design drawings.

[0675] "Means for recognizing emotions" refers to a device or method for detecting and analyzing emotions from the user's tone of voice, facial expressions, and choice of words.

[0676] "Means for optimizing the work environment and work content based on the recognized emotions" refers to a device or method for adjusting and optimizing the work environment and work content based on the results of emotion recognition.

[0677] As an embodiment of the present invention, an emotion-responsive factory robot system will be described as an example. This system is installed on robots that perform work in a factory, recognizes the emotions of workers, and optimizes the work environment and work content based on those emotions.

[0678] Hardware used

[0679] Camera: Used to capture the worker's facial expressions in real time. An example is a webcam such as the Logitech C920.

[0680] Factory Robot: A robot used to perform tasks. An example is the Universal Robots UR5.

[0681] Software used

[0682] OpenCV: An image processing library used to process the images from the camera.

[0683] EmotionRecognizer: An emotion recognition library used to recognize emotions from workers' facial expressions.

[0684] RobotController: A robot control library used to control robot behavior based on recognized emotions.

[0685] Data processing and calculation

[0686] 1. Camera input: Obtain images from the camera in real time. Capture images using OpenCV and process them as image data.

[0687] 2. Face detection and emotion recognition: EmotionRecognizer is used to detect faces in the video and recognize emotions, allowing us to grasp the emotional state of workers in real time.

[0688] 3. Robot control: Based on the recognized emotion, the RobotController controls the robot's behavior. For example, if the worker shows "sad" emotion, the robot will perform the "comfort" task.

[0689] Specific examples

[0690] If the worker is tired: If the emotion recognition engine detects that the worker is tired, the robot will pause the work and take action to encourage the worker to take a break.

[0691] If the worker is angry: If the emotion recognition engine detects that the worker is angry, the robot will slow down its work speed and take measures to strengthen safety checks.

[0692] Prompt Sentence Examples

[0693] "Design a system where robots working in factories can recognize the emotions of workers and optimize the work environment and tasks based on those emotions. For example, if a worker senses fatigue, the robot will pause its work and take action to encourage the worker to take a break."

[0694] In this way, the emotion-responsive factory robot system can improve work efficiency and safety by optimizing the work environment taking into account the emotions of workers.

[0695] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0696] Step 1:

[0697] The server acquires images from the camera in real time. Specifically, it uses OpenCV to capture images from the camera and processes them as image data. The input is the image from the camera, and the output is image data.

[0698] Step 2:

[0699] The server uses EmotionRecognizer to detect faces in the video and recognize emotions. Specifically, it applies a face detection algorithm and analyzes emotions from the detected face area. The input is the image data obtained in step 1, and the output is the recognized emotion data.

[0700] Step 3:

[0701] The server uses the RobotController to control the robot's behavior based on the recognized emotion data. Specifically, it generates behavior commands based on the emotion data and sends them to the robot. The input is the emotion data obtained in step 2, and the output is behavior commands for the robot.

[0702] Step 4:

[0703] The robot performs its actual actions based on the action commands received from the server. Specifically, it performs tasks according to the commands and adjusts the working environment as necessary. The input is the action command obtained in step 3, and the output is the actual robot action.

[0704] Step 5:

[0705] The server monitors the results of the robot's operations and provides feedback as necessary. Specifically, it monitors the robot's operating status and takes appropriate measures if an abnormality is detected. The input is the robot's operation results, and the output is feedback information.

[0706] In this way, an emotion-responsive factory robot system is realized through the specific actions performed at each step.

[0707] 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.

[0708] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0709] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0710] 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.

[0711] [Second embodiment]

[0712] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0713] 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.

[0714] 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.

[0715] The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and 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).

[0716] 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.

[0717] 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.

[0718] 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).

[0719] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] In the smart glasses 214, the 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.

[0724] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0725] "Example 1"

[0726] This embodiment of the present invention is equipped with devices such as sensors and cameras that analyze the elements present in the area. For example, in places that are difficult for people to reach or have been destroyed by disaster, information on the topography, geology, climate, and existing resources is collected. This information becomes the basis for designing a dwelling with the optimal shape and materials.

[0727] "Example 2"

[0728] Next, a home is designed with the optimal shape and materials based on the collected information. This design is carried out by generative AI. The generative AI designs a home with the optimal shape and materials based on the collected information. For example, if the terrain is steep, it will design a home with a shape that follows the terrain. Also, if the geology is weak, it will design a home with materials that are earthquake-resistant.

[0729] "Example 3"

[0730] Finally, the home is constructed based on the design. This construction is carried out by devices such as robots and 3D printers. For example, a robot uses resources available on-site to build the home based on the blueprint. A 3D printer also uses resources available on-site to manufacture the home's components based on the blueprint, and then assembles them to build the home.

[0731] The processing flow of each embodiment will be described below.

[0732] "Example 1"

[0733] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0734] Step 2: Input the collected information into the generative AI.

[0735] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[0736] "Example 2"

[0737] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0738] Step 2: Input the collected information into the generative AI.

[0739] Step 3: The generative AI designs a dwelling with the optimal shape and materials based on the input information. If the terrain is steep, it will design a dwelling with a shape that follows the terrain. If the geology is weak, it will design a dwelling made of earthquake-resistant materials.

[0740] "Example 3"

[0741] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[0742] Step 2: Input the collected information into the generative AI.

[0743] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[0744] Step 4: Based on the blueprint, the home is constructed using resources available on site. This construction is carried out by devices such as robots and 3D printers. The robots use resources available on site to construct the home based on the blueprint. The 3D printers use resources available on site to manufacture the home's components based on the blueprint, and then assemble them to construct the home.

[0745] Example 1

[0746] Next, a description will be given of Example 1 of Form 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."

[0747] With conventional technology, it was difficult to efficiently analyze the elements of hard-to-reach places or places destroyed by disasters, and to design homes with optimal shapes and materials. Furthermore, there was a lack of means to analyze the collected data and provide it visually to users, making it difficult to use it as basic data for design.

[0748] 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.

[0749] In this invention, the server includes means for analyzing elements present at the site, means for analyzing the analysis results using data analysis software, means for designing a dwelling with an optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, and means for transmitting the analysis results to a terminal and displaying them to the user. This makes it possible to efficiently analyze elements in places that are difficult for people to reach or places destroyed by disasters, design an optimal dwelling based on the analysis results, and visually present the design to the user.

[0750] "Local factors" refers to the physical and environmental information of a particular location, such as topography, geology, climate, and the resources present.

[0751] "Means of analysis" refers to the means of using devices such as sensors and cameras to collect elements present in the location and obtain them as data.

[0752] "Data analysis software" refers to software used to process collected data and extract necessary information. Specifically, it includes programming languages ​​such as Python and R and their libraries.

[0753] "Means for designing a dwelling with optimal shape and materials" refers to means for determining the shape and materials of a dwelling based on collected and analyzed data, including the use of generative AI models.

[0754] "Means for construction" refers to the means for actually constructing a dwelling based on a design, including construction machinery and methods.

[0755] "Means for transmitting analysis results to the terminal and displaying them to the user" refers to the means by which the server transmits analysis results to the terminal and enables the user to visually confirm the results, including communication protocols and display software.

[0756] "Generative AI" refers to a model that uses artificial intelligence technology to automatically generate optimal shapes and materials from data.

[0757] This invention is a system that uses devices such as sensors and cameras to analyze the elements present in a location, analyzes the collected data, and provides it to users. Specifically, in places that are difficult for people to reach or have been destroyed by disaster, the system collects information on the topography, geology, climate, and existing resources, and provides basic data for designing homes with optimal shapes and materials.

[0758] The server receives data sent from sensors and cameras. This data includes information on topography, geology, climate, and existing resources. The server analyzes the received data and extracts the necessary information. This analysis is performed using data analysis software such as Python and R. Specifically, the data is processed using Python's NumPy and Pandas libraries, and visualized using Matplotlib.

[0759] The device receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the device screen, and the user can rotate and zoom in and out to check the details.

[0760] As a concrete example, drones equipped with sensors and cameras are used in areas devastated by disasters. The drones collect information on the terrain, geology, climate, and existing resources, and send it to a server. The server analyzes the collected data and extracts a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This information is then sent to a device and displayed to the user.

[0761] An example of a prompt is as follows:

[0762] "Please explain the system that collects information on the topography, geology, climate, and existing resources of an area destroyed by a disaster, and provides the basic data for designing housing with optimal shapes and materials."

[0763] This system uses sensors and cameras to analyze elements present in the area, analyzes the collected data, and provides it to the user. Specific hardware used is a drone, sensors, and cameras, and software is Python and R.

[0764] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0765] Step 1: Data collection

[0766] The server controls sensors and cameras to collect data from a specified area. The sensors acquire information about the terrain and geology, and the cameras take high-resolution images and videos. For example, sensors and cameras mounted on a drone collect data while flying over a disaster area. The input is raw data from the sensors and cameras, and the output is collected data on the terrain, geology, climate, and existing resources.

[0767] Step 2: Send data

[0768] The server receives the collected data in real time. Data sent from drones and sensors is sent to the server via wireless communication. The server temporarily stores the received data and prepares it for analysis. The input is the data stream from the drones and sensors, and the output is the data stored on the server.

[0769] Step 3: Data analysis

[0770] The server analyzes the received data. Using data analysis software such as Python or R, it generates a 3D model of the terrain, evaluates geological properties, and analyzes climatic conditions. For example, it processes the data using Python's NumPy and Pandas libraries and visualizes it with Matplotlib. The input is the raw data stored on the server, and the output is the analyzed 3D model of the terrain, geological properties, and climatic conditions data.

[0771] Step 4: Send results

[0772] The server sends the analysis results to the terminal. The analysis results include a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This data is sent in a standard data format such as JSON. The input is the analyzed data, and the output is the JSON data sent to the terminal.

[0773] Step 5: View the results

[0774] The terminal receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the terminal screen, and the user can rotate and zoom in and out to check the details. The input is JSON data sent from the server, and the output is the visual information displayed to the user.

[0775] (Application example 1)

[0776] Next, a description will be given of Application Example 1 of Form 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."

[0777] At disaster sites, there is a need to quickly and accurately collect information on the topography, geology, climate, existing resources, etc., and provide basic data for formulating optimal rescue operations and recovery plans. However, the conditions at disaster sites are extremely harsh, and it is often difficult for people to reach them directly. Therefore, a means of collecting information efficiently and safely is required.

[0778] 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.

[0779] In this invention, the server includes means for analyzing elements present at the site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for collecting information on the topography, geology, climate, existing resources, etc. at the disaster site, and means for transmitting the collected information in real time. This allows for the rapid and accurate collection of information at the disaster site, enabling the formulation of optimal rescue operations and recovery plans.

[0780] "Means for analyzing elements present at the site" refers to devices and systems that use sensors and cameras installed on-site to collect and analyze information on topography, geology, climate, existing resources, etc.

[0781] "Means for designing a dwelling with optimal shape and materials" refers to a design process or software for determining the shape and materials of a dwelling based on collected data.

[0782] "Means for constructing the dwelling based on the design" refers to the machinery, technology, and construction methods required to actually construct the designed dwelling.

[0783] "Means for collecting information on the topography, geology, climate, existing resources, etc. at disaster sites" refers to a system for collecting detailed information on the site using devices such as robots and drones dispatched to the disaster site.

[0784] "Means for transmitting collected information in real time" refers to communication devices and network technologies for instantly transmitting collected data to a remote server or command center.

[0785] The system for implementing this invention collects information on the topography, geology, climate, and existing resources at the disaster site, and provides basic data for formulating optimal rescue operations and recovery plans. A specific embodiment of this system is shown below.

[0786] System configuration

[0787] The system consists of the following main components:

[0788] 1. Sensors and cameras: These are installed at disaster sites to collect information on the topography, geology, climate, and existing resources. These include temperature sensors, humidity sensors, geological sensors, and high-resolution cameras.

[0789] 2. Data collection robots: These are deployed to disaster sites and equipped with sensors and cameras to collect information. The robots can operate remotely or autonomously.

[0790] 3. Data transmission device: A communication device for transmitting collected information to a server in real time. Specifically, this includes Wi-Fi and 4G / 5G communication modules.

[0791] 4. Server: A central processing unit for receiving and analyzing collected data. The server contains a database, analysis software, and generative AI models.

[0792] 5. Generative AI model: An artificial intelligence model that designs homes with optimal shapes and materials based on collected data.

[0793] Program processing

[0794] The server performs the following process.

[0795] 1. Data reception: Receives information transmitted from the data transmission device, including image data, temperature data, humidity data, and geological data.

[0796] 2. Data analysis: Analyze the received data and understand the situation at the disaster site. For the analysis, use image processing software (e.g., OpenCV) and data analysis libraries (e.g., NumPy, Pandas).

[0797] 3. Application of generative AI model: Based on the analysis results, a generative AI model is used to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network.

[0798] 4. Design data output: The data of the designed house is output and provided to the construction means, which enables the house to be constructed quickly and efficiently.

[0799] Specific examples

[0800] For example, a robot exploring the interior of a building that collapsed in an earthquake collects the following information:

[0801] Image: Image of the interior of the collapsed building

[0802] Temperature: On-site temperature (e.g. 25.3°C)

[0803] Humidity: Humidity at the site (e.g. 45.7%)

[0804] Geology: Site geology (e.g. bedrock)

[0805] This information is sent in real time to a server, which uses generative AI models to develop optimal rescue operations and recovery plans.

[0806] Prompt Sentence Examples

[0807] "Write a program for a robot to be sent to a disaster site to capture images of the interior of buildings that have collapsed due to an earthquake, collect temperature, humidity, and geological data, and send it to a server."

[0808] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0809] Step 1:

[0810] Data collection

[0811] The terminal (robot) arrives at the disaster site and uses sensors and cameras to collect information on the topography, geology, climate, existing resources, etc. Specifically, it acquires temperature data with a temperature sensor, humidity data with a humidity sensor, geological data with a geological sensor, and captures images of the site with a high-resolution camera.

[0812] Input: Environmental information of the disaster site

[0813] Output: Temperature data, humidity data, geological data, image data

[0814] Step 2:

[0815] Data transmission

[0816] The terminal (robot) transmits the collected data to the server in real time. Using a communication device (Wi-Fi, 4G / 5G communication module), the data is divided into packets and sent to a specified IP address on the server.

[0817] Input: Temperature data, humidity data, geological data, image data

[0818] Output: Data packet sent to the server

[0819] Step 3:

[0820] Data reception

[0821] The server receives data packets sent from the terminal, reconstructs the received packets, and stores them as temperature data, humidity data, geological data, and image data.

[0822] Input: Data packets sent from the device

[0823] Output: Stored temperature data, humidity data, geological data, image data

[0824] Step 4:

[0825] Data analysis

[0826] The server analyzes the received data. Specifically, it analyzes the image data using image processing software (e.g., OpenCV), and analyzes the temperature data, humidity data, and geological data using data analysis libraries (e.g., NumPy, Pandas).

[0827] Input: Stored temperature data, humidity data, geological data, image data

[0828] Output: Analysis results (detailed site conditions)

[0829] Step 5:

[0830] Applying generative AI models

[0831] The server then applies a generative AI model based on the analysis results to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network to design based on input data.

[0832] Input: Analysis results

[0833] Output: Design data (house with optimal shape and materials)

[0834] Step 6:

[0835] Design data output

[0836] The server outputs data on the house designed by the generative AI model and provides it to the construction method. The design data is output as CAD files and architectural drawings.

[0837] Input: Design data

[0838] Output: CAD files, architectural drawings

[0839] The above processing steps enable rapid and accurate collection of information at the disaster site, enabling optimal rescue operations and recovery plans to be formulated.

[0840] Example 2

[0841] Next, a description will be given of Example 2 of Form 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."

[0842] Conventional residential design systems have difficulty in designing with sufficient consideration of topographical and geological characteristics, making it particularly difficult to create optimal residential designs in places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, flexible design changes in response to user requests are not easy to make, so an efficient design process is required.

[0843] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0844] In this invention, the server includes: a means for a user to input topographical data and geological data; a means for a terminal to transmit the input data to the server; a means for the server to generate a prompt to the generative AI model and request an optimal house design based on the input data; a means for the generative AI model to generate a design proposal; a means for the server to receive the generated design proposal and transmit it to the terminal; a means for the terminal to display the design proposal to the user; a means for the user to check the design proposal and input corrections or additional conditions as necessary; and a means for the terminal to transmit the corrections or additional conditions to the server and request a new design. This enables optimal house designs that take into account topographical and geological characteristics, and also enables flexible and efficient design changes to be made in response to user requests.

[0845] "Means for analyzing local elements" refers to equipment and software for collecting and analyzing local environmental information, such as topographical and geological data.

[0846] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the shape and materials of a residence based on collected data.

[0847] "Means for constructing the dwelling based on the design" refers to the construction methods and machinery used to actually build the designed dwelling.

[0848] "Means for user input of topographical and geological data" refers to an interface or device that allows a user to input topographical and geological information into the system.

[0849] "Means for the terminal to transmit input data to the server" refers to a communication device or software for transmitting data input by the user to the server.

[0850] "Means for the server to generate prompt text for the generative AI model and request the optimal home design based on the input data" refers to the function that creates prompt text based on the data collected by the server and requests the generative AI model to design.

[0851] "Means by which the generative AI model generates design proposals" refers to the algorithms and software that the generative AI model uses to create residential design proposals based on prompt statements.

[0852] "Means for the server to receive the generated design proposals and send them to the terminal" refers to the communications equipment and software used to send the design proposals received from the generative AI model to the terminal.

[0853] "Means by which the terminal displays the design proposal to the user" refers to a display or interface for displaying the design proposal received from the server to the user.

[0854] "Means for the user to review the design proposal and input corrections or additional conditions as necessary" refers to an interface or device that allows the user to review the displayed design proposal and input corrections or additional conditions.

[0855] "Means for the terminal to send corrections or additional conditions to the server and request a redesign" refers to communication devices or software that send corrections or additional conditions entered by the user to the server and request the generative AI model to design again.

[0856] This invention is a system that allows a user to input topographical and geological data and, based on that data, designs a dwelling with optimal shape and materials. A specific embodiment of this system will be described below.

[0857] First, the user inputs topographical and geological data through the system interface. For example, the topographical data is "steep mountainous area" and the geological data is "weak geology." This data is then sent from the user's device to the server. The device then converts the input data into JSON format and sends it to the server using an HTTP POST request.

[0858] The server generates a prompt based on the received topographical and geological data. Specifically, it generates the following prompt:

[0859] Terrain data: steep mountainous area

[0860] Geological data: Weak geology

[0861] Condition: Design a home that is earthquake-resistant

[0862] Based on these conditions, design a home with the optimal shape and materials.

[0863] The generated prompt sentence is sent to a generative AI model to request a design. For example, OpenAI's GPT-4 can be used as the generative AI model.

[0864] The generative AI model generates optimal housing design proposals based on the prompt text. For example, it designs a stepped house that follows the terrain, or a house made of reinforced concrete that is earthquake-resistant. The generated design proposals are returned to the server in the following format:

[0865] Shape: Terraced housing that follows the terrain

[0866] Material: Reinforced concrete

[0867] Features: Earthquake-resistant and designed to adapt to steep terrain

[0868] The server sends the design proposal received from the generative AI model to the device. The device displays the received design proposal to the user. The user checks the design proposal through the interface and inputs corrections or additional conditions as necessary. For example, the user can input conditions such as "make the living room larger" or "change the roof material."

[0869] The device then sends any modifications or additional conditions entered by the user back to the server, which then generates a prompt for the generative AI model and requests a design. This process is repeated until the optimal home design is completed.

[0870] This system enables optimal residential design that takes into account the characteristics of the terrain and geology, and also allows for flexible and efficient design changes to be made according to the user's requests.The hardware used is a high-performance server (e.g., a server equipped with an NVIDIA GPU), and the software used is a generative AI model (e.g., OpenAI's GPT-4).

[0871] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0872] Step 1:

[0873] The user inputs topographical and geological data.

[0874] Specifically, the user inputs "steep mountainous area" into the "topography data" field and "weak geology" into the "geology data" field on the system interface.

[0875] Input: Topographical data, geological data

[0876] Output: Input data is saved on the user's device

[0877] Step 2:

[0878] The terminal sends the input data to the server.

[0879] Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request.

[0880] Input: User-entered topographic and geological data

[0881] Output: JSON formatted data sent to the server

[0882] Step 3:

[0883] The server generates a prompt for the generative AI model and requests the optimal home design based on the input data.

[0884] Specifically, the server analyzes the received JSON data and generates a prompt like the following:

[0885] Terrain data: steep mountainous area

[0886] Geological data: Weak geology

[0887] Condition: Design a home that is earthquake-resistant

[0888] Based on these conditions, design a home with the optimal shape and materials.

[0889] The generated prompt sentence is sent to the generative AI model.

[0890] Input: JSON format data sent to the server

[0891] Output: The prompt sent to the generative AI model

[0892] Step 4:

[0893] A generative AI model generates design proposals.

[0894] Specifically, the generative AI model generates optimal housing design proposals based on prompts, such as a stepped house that follows the terrain or a house made of reinforced concrete that is earthquake-resistant.

[0895] Input: A prompt sent to the generative AI model

[0896] Output: Generated residential design proposal

[0897] Step 5:

[0898] The server receives the generated design proposal and sends it to the terminal.

[0899] Specifically, the server sends the design proposal received from the generative AI model to the terminal in JSON format.

[0900] Input: Design proposals received from the generative AI model

[0901] Output: Design proposal in JSON format sent to the terminal

[0902] Step 6:

[0903] The terminal displays the design proposal to the user.

[0904] Specifically, the device analyzes the received JSON data and displays it to the user as follows:

[0905] Design proposal:

[0906] Shape: Terraced housing that follows the terrain

[0907] Material: Reinforced concrete

[0908] Features: Earthquake-resistant and designed to adapt to steep terrain

[0909] Input: Design proposal in JSON format sent to the terminal

[0910] Output: Design proposal displayed to the user

[0911] Step 7:

[0912] The user checks the design proposal and enters corrections or additional conditions as necessary.

[0913] Specifically, the user checks the displayed design proposal and inputs modifications or additional conditions, such as "make the living room larger" or "change the roof material."

[0914] Input: Design proposal displayed to the user

[0915] Output: Any corrections or additional conditions entered by the user

[0916] Step 8:

[0917] The device sends any corrections or additional conditions to the server and requests a new design.

[0918] Specifically, the device converts the corrections and additional conditions entered by the user into JSON format and sends it back to the server. The server then generates a prompt for the AI ​​model and requests it to design.

[0919] Input: Any corrections or additional conditions entered by the user

[0920] Output: Modifications and additional conditions sent to the server, and prompts sent back to the AI ​​model

[0921] (Application example 2)

[0922] Next, a description will be given of Application Example 2 of Form 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."

[0923] Conventional residential design systems have difficulty creating optimal residential designs that take into account environmental information such as topography and geology. Furthermore, optimization of factory layouts and equipment placement is often done manually, making it difficult to build efficient production lines. This has led to problems such as insufficient efficiency and safety in residential and factory designs.

[0924] 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.

[0925] In this invention, the server includes means for analyzing elements present on site, means for designing a residence with an optimal shape and materials based on the analysis results, means for constructing the residence based on the design, means for collecting information on the topography and equipment layout within the factory, means for designing an optimal factory layout and equipment layout based on the collected information, and means for generating an optimal layout using generative AI. This makes it possible to design an optimal residence that takes environmental information into consideration and to design an efficient factory layout.

[0926] "Elements present in situ" refers to physical and environmental information such as topography, geology, and facilities in a particular location or environment.

[0927] "Means for analysis" refers to devices or software used to analyze collected information and extract data for specific purposes.

[0928] "Means for designing a dwelling with optimal shape and materials" refers to design tools and software for optimizing the shape and materials of a dwelling based on collected and analyzed information.

[0929] "Means for constructing the dwelling based on the design" refers to machinery, equipment, or the process for actually constructing the designed dwelling.

[0930] "Means for collecting information on the topography and equipment layout within the factory" refers to sensors and data collection devices for collecting information on the topography and equipment layout within the factory.

[0931] "Means for designing optimal factory layouts and equipment placement based on collected information" refers to design tools and software for analyzing collected information and optimizing the layout and equipment placement within a factory.

[0932] "Generative AI" refers to artificial intelligence technology that generates optimal designs and layouts based on collected and analyzed information.

[0933] "Means for generating an optimal layout" refers to devices or software that use generative AI to generate an optimal layout based on collected and analyzed information.

[0934] To implement this invention, the server, the terminal, and the user must cooperate to operate the system. A specific embodiment of this is shown below.

[0935] System Program

[0936] The server first uses a means to analyze the elements present on the site to collect information on the topography, geology, facilities, etc. This information is acquired using sensors and data collection devices. Next, using a means to design a home with the optimal shape and materials based on the collected information, it utilizes generative AI to create the optimal home design. Then, using a means to build the home based on the design, it proceeds with the actual construction process.

[0937] Additionally, information about the factory's topography and equipment layout is collected using a method to gather information about the factory's interior. Based on the collected information, generative AI is used to design the optimal factory layout and equipment layout, generating the optimal layout.

[0938] Program processing explanation

[0939] The server uses software such as Python and OpenAI API to analyze the collected data and generate an optimal design. Specifically, it formats the topographical and facility data in JSON format and inputs it into a generative AI model. The generative AI model then generates the optimal design and layout based on this data.

[0940] The hardware used is suitable for servers and cloud environments (e.g., AWS, Google Cloud), and the software uses Python and the OpenAI API.

[0941] Specific examples

[0942] For example, consider a factory with a flat terrain, an area of ​​1,000 square meters, and two machines, Machine A (10x10) and Machine B (15x15), respectively. Based on this information, the following prompt sentence is input to the generative AI model:

[0943] Example prompt sentence:

[0944] Terrain data inside the factory: {"Terrain": "Flat", "Area": ​​"1000 square meters"}

[0945] Facility data: {"Facility 1": {"Type": "Machine A", "Size": "10x10"}, "Facility 2": {"Type": "Machine B", "Size": "15x15"}}

[0946] Use the above information to design the optimal factory layout.

[0947] By inputting this prompt into the generative AI model, the optimal factory layout is generated. The generated layout is sent from the server to the terminal, where the user can check and implement it.

[0948] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0949] Step 1:

[0950] The server uses sensors and data collection devices to collect information on elements present in the site (topography, geology, facilities, etc.). The input is raw data obtained from the sensors and data collection devices, and the output is a dataset of the collected environmental information. This dataset is used for subsequent analysis.

[0951] Step 2:

[0952] The server analyzes the collected environmental information. Specifically, it formats the data using a programming language such as Python and extracts the necessary information. The input is the dataset of environmental information collected in step 1, and the output is the analyzed data. This analyzed data forms the basis for generating an optimal design.

[0953] Step 3:

[0954] The server inputs a prompt to the generative AI model based on the analyzed data. The input is the analyzed data and a prompt for the generative AI model, and the output is the optimal design proposal obtained from the generative AI model. Specifically, the server uses the OpenAI API to call the generative AI model and inputs a prompt.

[0955] Step 4:

[0956] The server receives the optimal design proposal obtained from the generative AI model and provides it to the user. The input is the design proposal from the generative AI model, and the output is the design proposal provided to the user. Specifically, the server sends the design proposal to the terminal so that the user can check it.

[0957] Step 5:

[0958] The user checks the provided design proposal and makes corrections or approvals as necessary. The input is the design proposal provided by the server, and the output is the corrected or approved design proposal. Specifically, the user checks the design proposal using a terminal and sends feedback to the server.

[0959] Step 6:

[0960] The server receives feedback from the user and finalizes the design. The input is the user feedback, and the output is the finalized design. Specifically, the server analyzes the feedback, makes any necessary modifications, and then generates the final design.

[0961] Step 7:

[0962] The server starts the construction process of the house or factory based on the final design proposal that has been confirmed. The input is the final design proposal that has been confirmed, and the output is the start of the construction process. Specifically, it arranges for the resources required for construction and carries out the construction work.

[0963] Example 3

[0964] Next, a description will be given of Example 3 of Form Example 3. 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."

[0965] In conventional housing construction systems, the analysis of blueprint data, the generation of resource lists, and the generation of control codes for robots and 3D printers are often done manually, resulting in inefficiencies. Furthermore, there is insufficient automation to effectively utilize on-site resources, making the construction process complex and time-consuming.

[0966] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0967] In this invention, the server includes means for receiving and analyzing design drawing data, means for generating a required resource list, means for generating control code for the robot, and means for generating control code for the 3D printer, which enables automatic analysis of design drawing data, automatic generation of a resource list, and automatic generation of control codes for the robot and the 3D printer.

[0968] "Local factors" refer to the resources and environmental conditions available at the construction site.

[0969] "Analytical means" refers to equipment and software used to evaluate the elements present at the site and extract the necessary information.

[0970] "Design means" refers to devices and software for planning a home with the optimal shape and materials based on the analysis results.

[0971] "Means for receiving and analyzing design drawing data" refers to devices and software for receiving design drawing data provided by a user and analyzing its contents.

[0972] "Means for generating a list of required resources" refers to a device or software for creating a list of resources required for construction based on the results of analyzing the blueprint data.

[0973] "Means for generating control code for a robot" refers to a device or software for creating code containing instructions for a robot to operate according to a blueprint.

[0974] "Means for generating control code for a 3D printer" means a device or software that generates code containing instructions for a 3D printer to manufacture a part based on a design.

[0975] "Means for construction" refers to the equipment and machinery used to actually build a dwelling based on a blueprint.

[0976] This invention is a system that analyzes blueprint data for a house, creates a list of required resources, and automatically generates control codes for a robot and a 3D printer. Specific embodiments of this system are described below.

[0977] First, the user uploads the design data using the terminal. Through the terminal interface, the user selects the design file (e.g., "house_design.dwg") and clicks the upload button. This design data is then sent to the server.

[0978] The server uses a CAD analysis tool (e.g., AutoCAD) to analyze the received blueprint data. The server identifies each part of the blueprint and determines the resources required for each part. Based on the results of this analysis, the server generates a list of required resources. For example, resources such as wood, metal, and plastic may be listed.

[0979] Next, the server generates a control code for the robot. This control code contains instructions for the robot to operate according to the blueprint. The server uses a control code generation tool (e.g., ROS - Robot Operating System) to generate the control code for the robot. For example, a file called "robot_instructions.txt" is generated.

[0980] Similarly, the server generates control code for the 3D printer. This control code contains instructions for the 3D printer to manufacture the part based on the design. The server uses software to generate control code for the 3D printer. For example, a file called "3dprinter_instructions.gcode" is generated.

[0981] As a concrete example, we will explain the process of a user uploading design data. The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The server receives this data and starts analyzing it.

[0982] Once the analysis is complete, the server generates control codes for the robot (e.g., "robot_instructions.txt") and the 3D printer (e.g., "3dprinter_instructions.gcode"), which are then sent to the robot and the 3D printer to begin building the home.

[0983] Example prompts to input to a generative AI model:

[0984] "Please explain the process of the system that uploads blueprint data and builds a house using a robot and a 3D printer, including specific operations." The flow of the specific process in Example 3 will be explained using Figure 15.

[0985] Step 1:

[0986] The user uploads the blueprint data.

[0987] The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The input is the design data, and the output is the design data sent to the server.

[0988] Step 2:

[0989] The server receives the blueprint data and begins analysis.

[0990] The server opens the received blueprint data using a CAD analysis tool (e.g., AutoCAD). The input is the uploaded blueprint data, and the output is the analyzed data for each part of the blueprint. Specifically, the server identifies each part of the blueprint and specifies the resources required for each part.

[0991] Step 3:

[0992] The server generates a list of required resources.

[0993] The server generates a list of resources such as wood, metal, and plastic based on the analysis results. The input is the analyzed design data, and the output is a list of required resources (e.g., "resource_list.txt"). Specifically, the server lists the types and quantities of resources required for each part.

[0994] Step 4:

[0995] The server generates the control code for the robot.

[0996] The server generates control code for the robot based on the resource list and blueprint data. The input is the resource list and blueprint data, and the output is the control code for the robot (e.g., "robot_instructions.txt"). For specific operations, the server uses ROS to describe the robot's operation instructions in detail.

[0997] Step 5:

[0998] The server generates control codes for the 3D printer.

[0999] The server also generates control code for the 3D printer. The input is the resource list and blueprint data, and the output is the control code for the 3D printer (e.g., "3dprinter_instructions.gcode"). As a specific operation, the server describes the operation instructions for the 3D printer in detail.

[1000] Step 6:

[1001] The robot begins construction according to the control code.

[1002] The robot follows the control code received from the server and uses resources available on-site to build a house. The input is the control code for the robot, and the output is the parts of the house that are built. Specifically, the robot cuts wood and assembles walls.

[1003] Step 7:

[1004] The 3D printer manufactures and assembles the parts according to the control code.

[1005] The 3D printer manufactures parts based on the blueprint according to the control code received from the server. The input is the control code for the 3D printer, and the output is the manufactured part. In concrete terms, the 3D printer prints walls using plastic and assembles them.

[1006] (Application example 3)

[1007] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1008] In conventional housing construction systems, the management of blueprints, on-site resource scanning, control of construction equipment, real-time monitoring of construction progress, and alert notifications when problems occur are all performed individually, making integrated management difficult. Furthermore, there was no system for centrally managing these functions, making efficient housing construction difficult.

[1009] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1010] In this invention, the server includes a means for uploading and managing blueprints, a means for scanning and managing on-site resources, a means for controlling construction equipment, a means for monitoring construction progress in real time, and a means for issuing alerts when problems occur. This makes it possible to centrally manage everything from blueprint management to monitoring construction progress and responding to problems when they occur.

[1011] "Means for analyzing elements present at the site" refers to devices and software for detecting resources and environmental conditions present at the site and analyzing that information.

[1012] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the optimal shape and materials of a residence based on the analyzed data.

[1013] "Means for constructing the residence based on the design" refers to devices such as robots and 3D printers for actually constructing the residence according to the design drawings.

[1014] "Means for uploading and managing blueprints" refers to software or an interface for uploading blueprints in digital format to a server and managing them.

[1015] The "means for scanning and managing on-site resources" refers to devices and software for scanning on-site resources and managing the data.

[1016] "Means for controlling construction equipment" refers to software or interfaces for controlling construction equipment such as robots and 3D printers.

[1017] "Means for monitoring construction progress in real time" refers to software or interfaces for monitoring the construction progress in real time and checking the progress.

[1018] "Means for issuing alerts when problems occur" refers to software or interfaces that issue alerts and notify relevant parties when problems occur during construction.

[1019] This invention is a system for centrally managing blueprints, scanning on-site resources, controlling construction equipment, monitoring construction progress in real time, and sending alerts when problems occur in a residential construction system.

[1020] Hardware and software used

[1021] Hardware: smartphones, robots, 3D printers

[1022] Software: Python, Flask (web framework), OpenCV (image processing library), NumPy (numerical calculation library)

[1023] System configuration

[1024] 1. Upload and manage blueprints:

[1025] Users take a photo of the blueprint using their smartphone and upload it to the server via the application.

[1026] The server stores and manages the uploaded blueprints.

[1027] 2. On-site resource scanning and management:

[1028] Users take photos of the site using their smartphone camera and send them to the server via the application.

[1029] The server uses OpenCV to process images, scan on-site resources, and manage the data.

[1030] 3. Control of construction equipment:

[1031] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[1032] The server sends the received commands to the construction equipment and controls it.

[1033] 4. Real-time monitoring of construction progress:

[1034] The server receives data from the construction equipment in real time and monitors progress.

[1035] Users can check their progress through the application.

[1036] 5. Alert notifications when problems occur:

[1037] The server generates alerts and notifies the user if any problems occur during construction.

[1038] Users can receive and respond to alerts through the application.

[1039] Specific examples

[1040] When uploading a blueprint:

[1041] Users take a photo of the blueprint with their smartphone camera and upload it through the application.

[1042] Example prompt: "Please upload the blueprint."

[1043] When scanning for resources in the field:

[1044] Users take a photo of the site using their smartphone camera and scan it through the application.

[1045] Example prompt: "Use your camera to take a photo of the site to scan for on-site resources."

[1046] When controlling a construction device:

[1047] The user enters and sends commands through the application's interface.

[1048] Example prompt: "Enter the command you want to send to your robot or 3D printer."

[1049] When checking construction progress:

[1050] The user can check the progress through the application.

[1051] Example prompt: "Press the monitoring button to check the construction progress."

[1052] If you encounter problems:

[1053] The server generates an alert and notifies the user.

[1054] Example prompt: "There's a problem. Please check your alerts."

[1055] In this way, it becomes possible to centrally manage everything from managing blueprints to monitoring construction progress and responding when problems arise.

[1056] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1057] Step 1:

[1058] Users take a photo of the blueprint with their smartphone camera and upload it to the server via the application.

[1059] Input: Blueprint image file

[1060] Output: Blueprint file saved on the server

[1061] Specific operation: A user launches the application, takes a picture of a blueprint, and presses the "Upload" button. The application sends the image file to the server, and the server saves the received file.

[1062] Step 2:

[1063] Users take photos of the site using their smartphone camera and send them to the server via the application.

[1064] Input: Photo file of the scene

[1065] Output: On-site resource data stored on a server

[1066] Specific operation: The user takes a photo of the site and presses the "Scan" button. The application sends the photo file to the server, which processes the image using OpenCV, extracts and stores the site resource data.

[1067] Step 3:

[1068] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[1069] Input: Command to construction device

[1070] Output: Command sent to the construction device

[1071] Specific operation: The user inputs a command into the application interface and presses the "Send" button. The application sends the command to the server, and the server sends the received command to the construction device.

[1072] Step 4:

[1073] The server receives data from the construction equipment in real time and monitors progress.

[1074] Input: Progress data from construction device

[1075] Output: Real-time progress updates

[1076] Specific operation: The construction device sends progress data to the server, the server analyzes the received data and updates the progress status. The user can check the progress status through the application.

[1077] Step 5:

[1078] The server generates alerts and notifies the user if any problems occur during construction.

[1079] Input: Data on the problem occurrence

[1080] Output: An alert to notify the user

[1081] Specific operation: The server monitors data from the construction equipment and generates an alert if a problem occurs. The alert is notified to the user through the application. The user checks the alert and takes action.

[1082] 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.

[1083] "Example 1"

[1084] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[1085] "Example 2"

[1086] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[1087] "Example 3"

[1088] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for designing a dwelling with an optimal shape and materials based on the analysis results, and a means for constructing the dwelling based on the design. This system includes an emotion engine that recognizes a user's emotions. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expression, and language. The user's emotions recognized by the emotion engine are taken into consideration when designing a dwelling with an optimal shape and materials. For example, if the user feels that they are seeking a sense of security, the emotion engine recognizes this, and the design means uses this information to design a dwelling with a shape and materials that will provide a sense of security. The construction means also takes into consideration the user's emotions recognized by the emotion engine. For example, if the user feels that they are seeking a sense of security, the construction means uses this information to construct a dwelling that will provide a sense of security.

[1089] The processing flow of each embodiment will be described below.

[1090] "Example 1"

[1091] Step 1: The emotion engine recognizes the user's emotions from their tone of voice, facial expressions, and language.

[1092] Step 2: The user's emotions recognized by the emotion engine are input into a means for designing a house with optimal shape and materials.

[1093] Step 3: The design means designs a dwelling with an optimal shape and materials based on the input user's emotions. For example, if the user feels that they are looking for a sense of security, the design means designs a dwelling with a shape and materials that will give them a sense of security.

[1094] Step 4: The means for constructing the house based on the design operates. At this time, the construction means also takes into account the user's emotions recognized by the emotion engine. For example, if the user feels that they are looking for a sense of security, the construction means uses that information to construct a house that provides a sense of security.

[1095] Example 1

[1096] Next, a description will be given of Example 1 of Form 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."

[1097] Conventional residential design systems have limitations in collecting and analyzing environmental data, making it particularly difficult to collect data from places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, residential design does not take into account the user's emotions, making it impossible to increase the user's psychological satisfaction. This has led to the issue that residential design and construction do not adequately meet the user's needs.

[1098] 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.

[1099] In this invention, the server includes means for analyzing elements present at the site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for recognizing a user's emotions, means for reflecting the recognized emotions in the design, and means for reflecting the recognized emotions in the construction. This allows for efficient collection and analysis of environmental data and enables the design and construction of a dwelling that takes the user's emotions into consideration.

[1100] "Local factors" refers to the physical and environmental information of a particular location, such as topography, geology, climate, and the resources present.

[1101] "Means of analysis" refers to the means of collecting and analyzing elements present in the location using devices such as sensors and cameras.

[1102] "Designing means" refers to means for designing a dwelling with optimal shape and materials based on collected and analyzed data.

[1103] "Means to construct" refers to the means to actually construct the designed dwelling.

[1104] "Means for recognizing a user's emotions" refers to means for recognizing emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1105] "Means for reflecting recognized emotions in the design" refers to means for reflecting the user's emotions in the design of the shape and materials of the home.

[1106] "Means for reflecting recognized emotions in construction" refers to means for taking into account the user's emotions and reflecting them in the construction process of a home.

[1107] "Generative AI" refers to a system that uses artificial intelligence technology to automatically design homes with optimal shapes and materials based on data.

[1108] This invention is a system that uses devices such as sensors and cameras to analyze elements present in a location and designs and constructs a residence that takes into account the user's emotions. A specific embodiment of this system will be described below.

[1109] System configuration

[1110] The system consists of the following major components:

[1111] 1. Data Collection Equipment:

[1112] The server uses sensors and cameras to collect environmental data such as topography, geology, climate, and existing resources. Specifically, it remotely controls cameras and geological sensors mounted on drones to acquire data.

[1113] 2. Emotion recognition device:

[1114] The device uses an emotion engine to analyze the user's tone of voice, facial expression, and choice of words to recognize their emotions. For example, if a user says, "I want a sense of security," the device will recognize that they are seeking a sense of security based on their tone of voice and facial expression.

[1115] 3. Design equipment:

[1116] The server integrates the collected environmental data with the user's emotional data and uses generative AI to design a home with the optimal shape and materials. For example, it may generate a warm design that makes extensive use of wood to create a sense of security.

[1117] 4. Construction equipment:

[1118] The server creates a construction plan based on the design data and sends construction instructions to the construction robot, specifically instructing it to build a safe and secure dwelling using wood.

[1119] Hardware and software used

[1120] Sensors: Geological sensors, climate sensors

[1121] Camera: High-resolution camera, drone-mounted camera

[1122] Emotion engine: Voice analysis software, facial expression recognition software

[1123] Generative AI: Residential Design Algorithm

[1124] Construction Robot: Autonomous Building Robot

[1125] Specific examples

[1126] For example, in a disaster area, the server collects topographical data using a drone's camera and analyzes data from geological sensors to identify geological structures. Next, when a user speaks to the device saying, "I want a sense of security," the device analyzes the user's tone of voice and facial expression to recognize that the user is seeking a sense of security. The server integrates this data and uses generative AI to design a home with a warm design that makes extensive use of wood. Finally, the server instructs a construction robot to build a home that provides a sense of security using wood.

[1127] Prompt Sentence Examples

[1128] An example of a prompt sentence to be input to the generative AI model is shown below.

[1129] Prompt: "Describe a system that collects topographical data from disaster areas and designs and builds optimal housing for users seeking safety."

[1130] By feeding this prompt into a generative AI model, a detailed description of the system is obtained.

[1131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1132] Step 1:

[1133] Starting Data Collection

[1134] The server activates the sensors and cameras and begins collecting data.

[1135] Input: Sensor and camera activation instructions

[1136] Specific operation: The server remotely controls the camera mounted on the drone to take aerial photographs of the disaster area.

[1137] Output: Collected data on topography, geology, climate, and existing resources.

[1138] Step 2:

[1139] Environmental data collection

[1140] The server collects data from sensors and cameras on the terrain, geology, climate, and existing resources.

[1141] Input: Data from sensors and cameras

[1142] What it does: The server performs 3D mapping of terrain data and analyzes data from geological sensors to identify geological structures.

[1143] Output: Parsed environmental data

[1144] Step 3:

[1145] User Interaction

[1146] The user speaks into the terminal.

[1147] Input: User's voice and facial expressions

[1148] Specific action: The user speaks to the device, "I want a sense of security."

[1149] Output: User's voice and facial expression data

[1150] Step 4:

[1151] Activating the Emotion Engine

[1152] The device uses an emotion engine to analyze the user's tone of voice, facial expressions, and language to recognize emotions.

[1153] Input: User's voice and facial expression data

[1154] Specific operation: The device captures the user's tone of voice and facial expressions using a camera and microphone, and analyzes them using an emotion engine.

[1155] Output: Recognized user emotion data

[1156] Step 5:

[1157] Data Integration

[1158] The server integrates the collected environmental data with the recognized user emotion data.

[1159] Input: Environmental data and user emotion data

[1160] Specific operation: The server combines the terrain data and the user's emotion data into a single dataset.

[1161] Output: A consolidated dataset

[1162] Step 6:

[1163] Execution of design algorithms

[1164] The server runs an algorithm to design a home with optimal shape and materials based on the integrated data.

[1165] Input: Integrated dataset

[1166] What it does: The server runs an algorithm that generates a warm design that makes extensive use of wood to create a sense of security.

[1167] Output: Design data

[1168] Step 7:

[1169] Creation of construction plans

[1170] The server creates a construction plan based on the design data.

[1171] Input: Design data

[1172] Specific behavior: The server creates a plan that tells the construction robot which materials to use and in what order.

[1173] Output: Construction plan

[1174] Step 8:

[1175] Sending construction orders

[1176] The server sends the construction plan to the construction robot and causes it to begin construction.

[1177] Input: Construction Plan

[1178] Specific behavior: The server sends instructions to the construction robot to build a safe habitat using wood.

[1179] Output: Completed house

[1180] (Application example 1)

[1181] Next, a description will be given of Application Example 1 of Form 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."

[1182] Conventional housing design systems can design housing with optimal shapes and materials based on the analysis of environmental factors, but they do not take into account the work environment or the emotions of workers, which can lead to problems such as reduced work efficiency and worker satisfaction.In addition, they do not adequately optimize the work environment during disasters or in places that are difficult for people to reach, which can compromise work safety and efficiency.

[1183] 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.

[1184] In this invention, the server includes means for analyzing elements present on site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for analyzing the work environment and work situation, means for recognizing worker emotions, and means for proposing optimal work procedures and layouts based on the analysis results and emotion recognition results. This makes it possible to propose optimal work procedures and layouts that take into account the work environment and worker emotions, thereby improving work efficiency and worker satisfaction. It also makes it possible to optimize the work environment during disasters or in places that are difficult for people to reach, thereby improving work safety and efficiency.

[1185] "Means for analyzing elements present in the location" refers to devices and methods that use sensors and cameras to collect and analyze information about the environment and objects present in a specific location.

[1186] The "means for designing a dwelling with optimal shape and materials" refers to a device or method for designing an optimal shape and materials for a dwelling based on collected environmental information.

[1187] "Means for constructing the dwelling based on the design" refers to devices and methods for actually constructing the designed dwelling.

[1188] "Means for analyzing the work environment and work status" refers to devices and methods that use sensors and cameras to collect and analyze the environment and work progress in factories and work sites.

[1189] "Means for recognizing the emotions of workers" refers to devices or methods for recognizing emotions from the tone of voice, facial expressions, and language of workers.

[1190] The "means for proposing optimal work procedures and layouts" refers to a device or method that proposes optimal work procedures and layouts to improve work efficiency and worker satisfaction based on collected environmental information and emotional information.

[1191] The system for implementing this invention has the following configuration. First, a means for analyzing the elements present in the location using sensors and cameras is required. This allows for the collection and analysis of information about the environment and objects present in a specific location. Specifically, a Logitech C920 or similar device is used as the camera, and an Arduino sensor kit is used as the sensor.

[1192] Next, we need a method to design a home with the optimal shape and materials based on the collected environmental information. This method uses generative AI to design a home with the optimal shape and materials. For example, a generative AI model can be used to design a home based on the collected data.

[1193] Additionally, a means is needed for actually constructing the designed dwelling, including an apparatus and method for constructing the dwelling based on the design.

[1194] In addition, a method for analyzing the work environment and work situation in factories and work sites is also required. This will enable real-time analysis of the work environment and work situation and suggest optimal work procedures and layouts. Specifically, OpenCV is used to acquire images from a camera in real time, and FactoryOptimizer is used to analyze the environmental information.

[1195] Furthermore, a means for recognizing the emotions of workers is also required. This means includes devices and methods for recognizing emotions from the worker's tone of voice, facial expressions, and language. Specifically, the Emotion Engine is used to recognize the emotions of workers.

[1196] Finally, a means is needed to propose optimal work procedures and layouts based on the collected environmental and emotional information, including devices and methods for proposing optimal work procedures and layouts to improve work efficiency and worker satisfaction.

[1197] For example, if a worker feels fatigued, the system can suggest simplifying work procedures and encouraging them to take a break. Also, if the layout of machines in a factory is inefficient, the system can suggest optimal layout.

[1198] An example of a prompt is as follows:

[1199] "Develop an application that analyzes the environment and worker emotions within the factory and proposes optimal work procedures and layouts. The application will collect data in real time using cameras and sensors, and recognize the emotions of workers using an emotion engine. Specific proposals will include simplifying work procedures and optimizing machine layouts."

[1200] In this way, it becomes possible to propose optimal work procedures and layouts that take into account the work environment and worker emotions, improving work efficiency and worker satisfaction. It can also optimize the work environment during disasters or in places that are difficult for people to reach, improving work safety and efficiency.

[1201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1202] Step 1:

[1203] The server collects the elements present in the location in real time using cameras and sensors. Specifically, it acquires video data from cameras (e.g., Logitech C920) and environmental data from sensors (e.g., Arduino sensor kit). The inputs are video data and environmental data, and the output is a combination of these data.

[1204] Step 2:

[1205] The server analyzes the collected video data and environmental data. Specifically, it processes the video data using OpenCV and analyzes the environmental data using FactoryOptimizer. The input is the data obtained in step 1, and the output is the analysis results. The analysis results include details of the work environment and work situation.

[1206] Step 3:

[1207] The server uses EmotionEngine to recognize the worker's emotions. Specifically, it analyzes the worker's tone of voice, facial expressions, and language from the video data to identify their emotions. The input is the video data obtained in Step 1, and the output is the emotion recognition results.

[1208] Step 4:

[1209] The server proposes optimal work procedures and layouts based on the analysis results and emotion recognition results. Specifically, it uses FactoryOptimizer to calculate optimal work procedures and layouts to improve work efficiency and worker satisfaction. The input is the data obtained in Step 2 and Step 3, and the output is an optimization proposal.

[1210] Step 5:

[1211] The server presents optimization proposals to the user. Specifically, it displays proposals such as simplification of work procedures and optimization of machine placement via a display or smartphone app. The input is the optimization proposal obtained in step 4, and the output is the information presented to the user.

[1212] Step 6:

[1213] The user checks the optimization proposals presented by the server and changes the work procedures and layout as necessary. Specifically, the user adjusts the work environment based on the proposals to improve work efficiency and satisfaction. The input is the information presented in Step 5, and the output is the adjusted work environment.

[1214] Example 2

[1215] Next, a description will be given of Example 2 of Form 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."

[1216] Conventional residential design systems base their designs solely on environmental information, without taking into account the user's emotions or psychological factors, resulting in low user satisfaction. Another issue is that it is difficult to analyze the elements of places destroyed by disasters or places that are difficult for people to reach. Furthermore, due to a lack of technology to design homes with optimal shapes and materials, the safety and comfort of homes may not be fully ensured.

[1217] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1218] In this invention, the server includes a means for analyzing elements present at the site, a means for designing a dwelling with optimal shape and materials based on the analysis results, a means for constructing the dwelling based on the design, a means for recognizing a user's emotions, and a means for designing the dwelling while taking the recognized emotions into consideration. This enables dwelling design that simultaneously takes into consideration environmental information and the user's emotions, thereby increasing user satisfaction. Furthermore, by analyzing elements in places destroyed by disasters or places that are difficult for people to reach, it becomes possible to provide safer and more comfortable dwellings. Furthermore, by using a generative AI model, dwellings with optimal shape and materials can be efficiently designed.

[1219] "Means for analyzing elements" refers to devices and software for collecting and analyzing environmental information such as the topography and geology present in a given area.

[1220] The "means for designing a dwelling with optimal shape and materials" refers to a device or software for determining the shape and materials of a dwelling based on collected environmental information and the user's emotions.

[1221] "Means for constructing a dwelling" refers to the equipment and methods for actually constructing the designed dwelling.

[1222] "Means for recognizing user emotions" refers to devices or software that analyze the user's tone of voice, facial expressions, choice of words, etc., to identify the user's emotions.

[1223] "Means for designing a residence taking into consideration recognized emotions" refers to devices or software that determine the shape and materials of a residence based on the user's emotional information in a way that increases the user's psychological satisfaction.

[1224] A "generative AI model" is an artificial intelligence model that generates optimal housing designs based on collected data.

[1225] A "prompt" is an instruction entered into a generative AI model, which specifically indicates the design requirements and conditions.

[1226] The present invention relates to a residential design system that takes into account the user's emotions. Specific embodiments of this system will be described below.

[1227] Information gathering

[1228] When a user requests a house design, the device first collects environmental information such as topography and geology. Specifically, the device uses GPS and a geographic information system (GIS) to obtain information on the topography and geology of the specified location. For example, the device might obtain data such as "This area has steep topography and fragile geology."

[1229] emotion recognition

[1230] Next, the device uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotions based on their tone of voice, facial expressions, and choice of words. For example, if the user says, "I'm looking for reassurance," the emotion engine will recognize that the user is looking for reassurance based on their choice of words and tone of voice.

[1231] Residential Design

[1232] Based on the collected environmental information and the user's emotions recognized by the emotion engine, the server uses generative AI to design a home with the optimal shape and materials. Specifically, the server inputs the collected data into a generative AI model to generate the optimal home design. For example, the prompt could be "Design a home with a shape suitable for steep terrain, made of earthquake-resistant materials, and designed to give a sense of security."

[1233] Housing construction

[1234] Once the design is complete, the server uses a construction tool to build the residence. Specifically, the server sends the blueprint to a construction company, which then builds the residence using the specified materials and design. The construction company then actually carries out the construction work on-site.

[1235] Specific examples

[1236] For example, suppose a user wishes to build a home in a mountainous region and desires a sense of security. The device collects information about the steep terrain and fragile geology of the mountainous region, and uses its emotion engine to recognize that the user desires a sense of security. Based on this information, the server designs a home that conforms to the terrain, uses earthquake-resistant materials, and has a design that provides a sense of security. The server then uses construction tools to actually build the home.

[1237] Prompt Sentence Examples

[1238] "I want to build a house in the mountains. The terrain is steep and the geology is fragile. I want a sense of security. Please design a house with the optimal shape and materials."

[1239] In this way, this invention is a system that designs and constructs the optimal residence based on the user's requirements and environmental information.

[1240] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1241] Step 1:

[1242] A user requests a design for a house.

[1243] The user types into the terminal interface, "I want to build a house in the mountains."

[1244] Input: User's request (e.g., "I want to build a house in the mountains.")

[1245] Output: User request data

[1246] Step 2:

[1247] The device collects environmental information such as topography and geology.

[1248] The device activates the GPS to obtain topographical data for the specified location and accesses a GIS database to obtain geological information.

[1249] Input: User request data

[1250] Output: Topographical data, geological data

[1251] Step 3:

[1252] The terminal recognizes the user's emotions using an emotion engine.

[1253] The device records the user's voice and analyzes the tone of the voice using voice analysis software, and also captures the user's facial expressions using a camera and analyzes them using facial expression analysis software.

[1254] Input: User's tone of voice, facial expressions, and language

[1255] Output: User emotion data (e.g., desire for reassurance)

[1256] Step 4:

[1257] Based on the environmental information collected by the server and the user's emotions recognized by the emotion engine, a generative AI is used to design a home with the optimal shape and materials.

[1258] The server inputs the collected data into a generative AI model to generate an optimal home design. For example, a prompt might be entered: "Design a home that is suitable for steep terrain, uses earthquake-resistant materials, and has a design that gives a sense of security."

[1259] Input: Topographical data, geological data, user emotional data

[1260] Output: Residential design data

[1261] Step 5:

[1262] The server will build the house based on the design.

[1263] The server sends the blueprints to a builder, who then builds the house using the specified materials and design. The builder then actually carries out the construction work on-site.

[1264] Input: Residential design data

[1265] Output: Completed house

[1266] (Application example 2)

[1267] Next, a description will be given of Application Example 2 of Form 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."

[1268] Conventional residential design systems can take into account environmental factors such as topography and geology, but it is difficult to create designs that reflect the user's emotions. In addition, there is a demand for optimal designs that reflect the user's emotions and real-time environmental data, even in the design of brick-and-mortar stores. This will increase user satisfaction while also achieving safe designs that are suited to the environment.

[1269] 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.

[1270] In this invention, the server includes means for analyzing elements present on the site, means for designing a residence with an optimal shape and materials based on the analysis results, means for constructing the residence based on the design, means for recognizing a user's emotions, means for adjusting the design based on the recognized emotions, means for capturing environmental data using a smart device, and means for proposing an optimal design using generative AI. This enables the design of an optimal residence or physical store that reflects the user's emotions and real-time environmental data.

[1271] "Means for analyzing elements present in the area" refers to devices and software for collecting environmental data and analyzing elements such as topography and geology.

[1272] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the optimal shape and materials based on collected environmental data.

[1273] "Means for constructing the dwelling based on the design" refers to the machinery and construction methods used to actually construct the designed dwelling.

[1274] "Means for recognizing the user's emotions" refers to sensors and software for analyzing emotions from the user's facial expressions, tone of voice, etc.

[1275] "Means for adjusting the design based on recognized emotions" refers to algorithms and tools for modifying the design based on user emotion data.

[1276] "Means for capturing environmental data using a smart device" refers to equipment or software for collecting surrounding environmental data using devices such as smart glasses or smartphones.

[1277] "Means of proposing optimal designs using generative AI" refers to algorithms and systems that utilize generative AI to automatically generate optimal designs based on collected data and user emotions.

[1278] A system for implementing the present invention has the following configuration.

[1279] First, a user puts on smart glasses and designs a physical store. The smart glasses are equipped with a camera that captures data on the surrounding environment. This data includes information on topography and geology. The smart glasses then analyze the captured data using image processing software such as OpenCV.

[1280] Next, an emotion engine is used to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and tone of voice to recognize emotions such as relief or satisfaction. This emotion data is obtained using software such as EmotionRecognizer.

[1281] The server uses generative AI to propose optimal designs based on the collected environmental and emotional data. The generative AI uses algorithms such as AIDesign to determine shapes and materials suitable for the terrain and geology, and generates designs that reflect the user's emotions.

[1282] As a concrete example, when a user wears smart glasses and designs a physical store, the camera in the glasses captures the surrounding terrain and geology. The emotion engine recognizes from the user's facial expression and tone of voice that they are seeking a sense of security, and the generative AI proposes a store design with a shape that suits the terrain and materials that will give them a sense of security.

[1283] An example prompt is, "If the user is looking for a sense of security, please design a brick-and-mortar store with the right shape and materials for an area with steep terrain and fragile geology."

[1284] This system will enable optimal design of homes and physical stores that reflect user emotions and real-time environmental data.

[1285] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1286] Step 1:

[1287] A user puts on the smart glasses and starts designing a brick-and-mortar store. The camera in the smart glasses captures the surrounding environment data. The input is the video data from the camera in the smart glasses, and the output is the captured environmental data. Specifically, the camera in the smart glasses continuously captures video and transmits the data to the server in real time.

[1288] Step 2:

[1289] The server analyzes the captured environmental data using image processing software such as OpenCV. The input is the video data sent from the smart glasses, and the output is the analyzed topographical and geological information. Specifically, the server splits the video data into frames and applies algorithms to extract topographical and geological features.

[1290] Step 3:

[1291] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions and tone of voice. The input is the user's facial expression and tone of voice data acquired from the camera and microphone of the smart glasses, and the output is the recognized emotion data. Specifically, the emotion engine uses a facial expression recognition algorithm and a voice analysis algorithm to analyze the user's emotions in real time.

[1292] Step 4:

[1293] The server uses generative AI to propose optimal designs based on the collected environmental data and emotional data. The input is analyzed topographical and geological information and recognized emotional data, and the output is a design proposal for the optimal shape and materials. Specifically, the generative AI generates a prompt statement and then generates a design proposal based on that prompt statement.

[1294] Step 5:

[1295] The generated design proposal is presented to the user. The input is the design proposal from the generative AI, and the output is the design proposal presented to the user. Specifically, the server displays the design proposal on the smart glasses display so that the user can check it.

[1296] Step 6:

[1297] The user provides feedback on the design proposal. The input is the user's feedback, and the output is the design proposal adjusted based on the feedback. Specifically, the user inputs feedback through the interface of the smart glasses, and the server readjusts the design proposal based on that feedback.

[1298] Step 7:

[1299] Construction of the physical store begins based on the final design plan. The input is the final, adjusted design plan, and the output is the constructed physical store. In concrete terms, the construction company carries out construction based on the design plan and builds the physical store.

[1300] Example 3

[1301] Next, a description will be given of Example 3 of Form Example 3. 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."

[1302] Conventional housing design and construction systems have been unable to take into account the user's emotions and have been unable to sufficiently increase the user's psychological satisfaction. Furthermore, it has been difficult to provide appropriate housing in times of disaster or special circumstances. This has made it difficult to respond to the diverse needs of users, and it has been impossible to provide a comfortable and secure living environment.

[1303] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1304] In this invention, the server includes means for recognizing a user's emotion, means for designing a residence taking into consideration the recognized user's emotion, and means for constructing a residence taking into consideration the recognized user's emotion, thereby enabling the design and construction of an optimal residence that reflects the user's emotion.

[1305] "Elements present in place" refers to the physical elements such as the natural environment, man-made objects, and resources at the location where the dwelling is to be built.

[1306] "Means for analyzing" refers to equipment or software for analyzing the element and assessing its properties or condition.

[1307] "Design means" refers to devices and software for determining the shape and materials of a residence and creating blueprints based on the analysis results and other conditions.

[1308] "Means for construction" refers to the equipment and machinery used to actually build a dwelling based on a blueprint.

[1309] "Means for recognizing user emotions" refers to devices or software that analyze the user's tone of voice, facial expressions, choice of words, etc. to identify the user's emotions.

[1310] "Means for designing a residence taking into consideration the recognized emotions of a user" refers to devices and software for designing a residence with the optimal shape and materials based on the user's emotional information.

[1311] "Means for constructing a residence taking into consideration the recognized emotions of a user" refers to a device or machine for constructing a residence based on a blueprint, using the user's emotional information.

[1312] "Generative AI" refers to algorithms and software that use artificial intelligence technology to generate optimal designs and solutions from data.

[1313] MODE FOR CARRYING OUT THE INVENTION

[1314] This invention is a system that recognizes a user's emotions, designs a home with the optimal shape and materials based on those emotions, and builds it using robots and 3D printers. A specific embodiment of this system is described below.

[1315] User Emotion Recognition

[1316] The user speaks to the system, for example, "I want a safe home." The device captures the user's voice with a microphone and generates audio data. The device sends the audio data to the server. The server converts the audio data into text using speech recognition software (e.g., a speech recognition API). The server inputs the text data into an emotion engine to analyze the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, and choice of words and recognizes that the user wants a sense of security.

[1317] Designing a home using design tools

[1318] The server sends the user's emotional information obtained from the emotion engine to the design tool. The server uses architectural design software (e.g., design software) to design a home based on the emotional information. The server generates blueprints and selects shapes and materials that will give a sense of security. For example, the server creates blueprints using sturdy, warm materials.

[1319] Building a dwelling by construction means

[1320] The server sends the blueprint to the construction means. The terminal receives the blueprint and issues instructions to the robots and 3D printers. The robots build the dwelling using resources available on site based on the blueprint. For example, the robots assemble wood and metal to create the framework of the dwelling. The 3D printers manufacture parts based on the blueprint and assemble them to build the dwelling. For example, the 3D printers manufacture wall and roof parts using plastic and concrete, which are then assembled by the robots.

[1321] Hardware and software used

[1322] Emotion engine: Software for recognizing user emotions. Specifically, it uses voice recognition software (e.g., voice recognition API) and facial expression recognition software (e.g., facial expression recognition API).

[1323] Design method: Using architectural design software (e.g., design software), a residence is designed based on information from the emotion engine.

[1324] Construction method: Using robots (e.g., construction robots) or 3D printers (e.g., 3D printers) to build a dwelling based on a blueprint.

[1325] Specific examples

[1326] User input: "I want a safe home."

[1327] Emotion engine recognition results: Recognizing that the user is seeking reassurance

[1328] Design output: A design using sturdy and warm materials

[1329] How the construction method works: A 3D printer produces parts based on a blueprint, and a robot assembles them to build a home.

[1330] Example prompts for generative AI models

[1331] "If users want a sense of security, what kind of shape and materials should a home be designed with?"

[1332] This system aims to provide a more comfortable and satisfying living environment by designing and constructing a residence taking into consideration the user's emotions. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[1333] Step 1:

[1334] User Emotion Recognition

[1335] Input: The user speaks to the system, for example, "I want a safe home."

[1336] Specific operation: The device captures the user's voice with a microphone and generates audio data.

[1337] Data processing: The device sends the voice data to the server, which converts it into text using voice recognition software (e.g., a voice recognition API).

[1338] Output: Text data is generated.

[1339] Step 2:

[1340] Emotion analysis

[1341] Input: The text data generated in step 1.

[1342] Specific operation: The server inputs text data into the emotion engine and analyzes the user's emotions.

[1343] Data calculations: The emotion engine analyzes the user's tone of voice, facial expressions, and language to recognize that the user is seeking reassurance.

[1344] Output: User's emotion information is generated.

[1345] Step 3:

[1346] Residential Design

[1347] Input: User emotion information generated in step 2.

[1348] Specific operation: The server transmits the user's emotion information obtained from the emotion engine to the design means.

[1349] Data processing: The server uses architectural design software (e.g., design software) to design a house based on the emotional information.

[1350] Output: A design drawing is generated with shapes and materials selected to give a sense of security.

[1351] Step 4:

[1352] Submitting blueprints

[1353] Input: The blueprint generated in step 3.

[1354] Specific operation: The server sends the blueprint to the construction method.

[1355] Data processing: Sends blueprint data to the device.

[1356] Output: The blueprint data is sent to the device.

[1357] Step 5:

[1358] Building a residence

[1359] Input: Blueprint data submitted in step 4.

[1360] Specific operation: The terminal receives the blueprint and issues instructions to the robot and 3D printer.

[1361] Data computation: Robots build homes based on blueprints using resources available on-site. For example, robots assemble wood and metal to create the framework of a home. 3D printers manufacture parts based on blueprints and assemble them to build a home.

[1362] Output: A completed house is generated.

[1363] (Application example 3)

[1364] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1365] In conventional housing construction systems, the design and construction did not take into account the user's emotions, making it difficult to increase the user's psychological satisfaction. Furthermore, the work environment in factories was not optimized to take into account the emotions of the workers, making it difficult to improve work efficiency and safety.

[1366] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for analyzing elements present on site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for recognizing emotions, and means for optimizing the work environment and work content based on the recognized emotions. This makes it possible to design and construct a dwelling taking into account the user's emotions, and to optimize the work environment taking into account the emotions of workers.

[1367] "Means for analyzing elements present on site" refers to devices and methods for detecting resources and environmental conditions present on site and analyzing this information.

[1368] "Means for designing a dwelling with optimal shape and materials" refers to a device or method for determining the shape of a dwelling and the materials to be used based on the analysis results.

[1369] "Means for constructing the dwelling based on the design" refers to a device or method for actually constructing the dwelling according to the design drawings.

[1370] "Means for recognizing emotions" refers to a device or method for detecting and analyzing emotions from the user's tone of voice, facial expressions, and choice of words.

[1371] "Means for optimizing the work environment and work content based on the recognized emotions" refers to a device or method for adjusting and optimizing the work environment and work content based on the results of emotion recognition.

[1372] As an embodiment of the present invention, an emotion-responsive factory robot system will be described as an example. This system is installed on robots that perform work in a factory, recognizes the emotions of workers, and optimizes the work environment and work content based on those emotions.

[1373] Hardware used

[1374] Camera: Used to capture the worker's facial expressions in real time. An example is a webcam such as the Logitech C920.

[1375] Factory Robot: A robot used to perform tasks. An example is the Universal Robots UR5.

[1376] Software used

[1377] OpenCV: An image processing library used to process the images from the camera.

[1378] EmotionRecognizer: An emotion recognition library used to recognize emotions from workers' facial expressions.

[1379] RobotController: A robot control library used to control robot behavior based on recognized emotions.

[1380] Data processing and calculation

[1381] 1. Camera input: Obtain images from the camera in real time. Capture images using OpenCV and process them as image data.

[1382] 2. Face detection and emotion recognition: EmotionRecognizer is used to detect faces in the video and recognize emotions, allowing us to grasp the emotional state of workers in real time.

[1383] 3. Robot control: Based on the recognized emotion, the RobotController controls the robot's behavior. For example, if the worker shows "sad" emotion, the robot will perform the "comfort" task.

[1384] Specific examples

[1385] If the worker is tired: If the emotion recognition engine detects that the worker is tired, the robot will pause the work and take action to encourage the worker to take a break.

[1386] If the worker is angry: If the emotion recognition engine detects that the worker is angry, the robot will slow down its work speed and take measures to strengthen safety checks.

[1387] Prompt Sentence Examples

[1388] "Design a system where robots working in factories can recognize the emotions of workers and optimize the work environment and tasks based on those emotions. For example, if a worker senses fatigue, the robot will pause its work and take action to encourage the worker to take a break."

[1389] In this way, the emotion-responsive factory robot system can improve work efficiency and safety by optimizing the work environment taking into account the emotions of workers.

[1390] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1391] Step 1:

[1392] The server acquires images from the camera in real time. Specifically, it uses OpenCV to capture images from the camera and processes them as image data. The input is the image from the camera, and the output is image data.

[1393] Step 2:

[1394] The server uses EmotionRecognizer to detect faces in the video and recognize emotions. Specifically, it applies a face detection algorithm and analyzes emotions from the detected face area. The input is the image data obtained in step 1, and the output is the recognized emotion data.

[1395] Step 3:

[1396] The server uses the RobotController to control the robot's behavior based on the recognized emotion data. Specifically, it generates behavior commands based on the emotion data and sends them to the robot. The input is the emotion data obtained in step 2, and the output is behavior commands for the robot.

[1397] Step 4:

[1398] The robot performs its actual actions based on the action commands received from the server. Specifically, it performs tasks according to the commands and adjusts the working environment as necessary. The input is the action command obtained in step 3, and the output is the actual robot action.

[1399] Step 5:

[1400] The server monitors the results of the robot's operations and provides feedback as necessary. Specifically, it monitors the robot's operating status and takes appropriate measures if an abnormality is detected. The input is the robot's operation results, and the output is feedback information.

[1401] In this way, an emotion-responsive factory robot system is realized through the specific actions performed at each step.

[1402] 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.

[1403] 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> ) 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.

[1404] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1405] 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.

[1406] [Third embodiment]

[1407] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1408] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1409] 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).

[1410] 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.

[1411] 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.

[1412] 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).

[1413] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] 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.

[1418] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1419] "Example 1"

[1420] This embodiment of the present invention is equipped with devices such as sensors and cameras that analyze the elements present in the area. For example, in places that are difficult for people to reach or have been destroyed by disaster, information on the topography, geology, climate, and existing resources is collected. This information becomes the basis for designing a dwelling with the optimal shape and materials.

[1421] "Example 2"

[1422] Next, a home is designed with the optimal shape and materials based on the collected information. This design is carried out by generative AI. The generative AI designs a home with the optimal shape and materials based on the collected information. For example, if the terrain is steep, it will design a home with a shape that follows the terrain. Also, if the geology is weak, it will design a home with materials that are earthquake-resistant.

[1423] "Example 3"

[1424] Finally, the home is constructed based on the design. This construction is carried out by devices such as robots and 3D printers. For example, a robot uses resources available on-site to build the home based on the blueprint. A 3D printer also uses resources available on-site to manufacture the home's components based on the blueprint, and then assembles them to build the home.

[1425] The processing flow of each embodiment will be described below.

[1426] "Example 1"

[1427] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[1428] Step 2: Input the collected information into the generative AI.

[1429] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[1430] "Example 2"

[1431] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[1432] Step 2: Input the collected information into the generative AI.

[1433] Step 3: The generative AI designs a dwelling with the optimal shape and materials based on the input information. If the terrain is steep, it will design a dwelling with a shape that follows the terrain. If the geology is weak, it will design a dwelling made of earthquake-resistant materials.

[1434] "Example 3"

[1435] Step 1: Use devices (e.g., sensors and cameras) to analyze the elements present in the area and collect information on the terrain, geology, climate, and existing resources.

[1436] Step 2: Input the collected information into the generative AI.

[1437] Step 3: The generative AI designs a home with the optimal shape and materials based on the input information.

[1438] Step 4: Based on the blueprint, the home is constructed using resources available on site. This construction is carried out by devices such as robots and 3D printers. The robots use resources available on site to construct the home based on the blueprint. The 3D printers use resources available on site to manufacture the home's components based on the blueprint, and then assemble them to construct the home.

[1439] Example 1

[1440] Next, a description will be given of Example 1 of Form 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."

[1441] With conventional technology, it was difficult to efficiently analyze the elements of hard-to-reach places or places destroyed by disasters, and to design homes with optimal shapes and materials. Furthermore, there was a lack of means to analyze the collected data and provide it visually to users, making it difficult to use it as basic data for design.

[1442] 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.

[1443] In this invention, the server includes means for analyzing elements present at the site, means for analyzing the analysis results using data analysis software, means for designing a dwelling with an optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, and means for transmitting the analysis results to a terminal and displaying them to the user. This makes it possible to efficiently analyze elements in places that are difficult for people to reach or places destroyed by disasters, design an optimal dwelling based on the analysis results, and visually present the design to the user.

[1444] "Local factors" refers to the physical and environmental information of a particular location, such as topography, geology, climate, and the resources present.

[1445] "Means of analysis" refers to the means of using devices such as sensors and cameras to collect elements present in the location and obtain them as data.

[1446] "Data analysis software" refers to software used to process collected data and extract necessary information. Specifically, it includes programming languages ​​such as Python and R and their libraries.

[1447] "Means for designing a dwelling with optimal shape and materials" refers to means for determining the shape and materials of a dwelling based on collected and analyzed data, including the use of generative AI models.

[1448] "Means for construction" refers to the means for actually constructing a dwelling based on a design, including construction machinery and methods.

[1449] "Means for transmitting analysis results to the terminal and displaying them to the user" refers to the means by which the server transmits analysis results to the terminal and enables the user to visually confirm the results, including communication protocols and display software.

[1450] "Generative AI" refers to a model that uses artificial intelligence technology to automatically generate optimal shapes and materials from data.

[1451] This invention is a system that uses devices such as sensors and cameras to analyze the elements present in a location, analyzes the collected data, and provides it to users. Specifically, in places that are difficult for people to reach or have been destroyed by disaster, the system collects information on the topography, geology, climate, and existing resources, and provides basic data for designing homes with optimal shapes and materials.

[1452] The server receives data sent from sensors and cameras. This data includes information on topography, geology, climate, and existing resources. The server analyzes the received data and extracts the necessary information. This analysis is performed using data analysis software such as Python and R. Specifically, the data is processed using Python's NumPy and Pandas libraries, and visualized using Matplotlib.

[1453] The device receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the device screen, and the user can rotate and zoom in and out to check the details.

[1454] As a concrete example, drones equipped with sensors and cameras are used in areas devastated by disasters. The drones collect information on the terrain, geology, climate, and existing resources, and send it to a server. The server analyzes the collected data and extracts a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This information is then sent to a device and displayed to the user.

[1455] An example of a prompt is as follows:

[1456] "Please explain the system that collects information on the topography, geology, climate, and existing resources of an area destroyed by a disaster, and provides the basic data for designing housing with optimal shapes and materials."

[1457] This system uses sensors and cameras to analyze elements present in the area, analyzes the collected data, and provides it to the user. Specific hardware used is a drone, sensors, and cameras, and software is Python and R.

[1458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1459] Step 1: Data collection

[1460] The server controls sensors and cameras to collect data from a specified area. The sensors acquire information about the terrain and geology, and the cameras take high-resolution images and videos. For example, sensors and cameras mounted on a drone collect data while flying over a disaster area. The input is raw data from the sensors and cameras, and the output is collected data on the terrain, geology, climate, and existing resources.

[1461] Step 2: Send data

[1462] The server receives the collected data in real time. Data sent from drones and sensors is sent to the server via wireless communication. The server temporarily stores the received data and prepares it for analysis. The input is the data stream from the drones and sensors, and the output is the data stored on the server.

[1463] Step 3: Data analysis

[1464] The server analyzes the received data. Using data analysis software such as Python or R, it generates a 3D model of the terrain, evaluates geological properties, and analyzes climatic conditions. For example, it processes the data using Python's NumPy and Pandas libraries and visualizes it with Matplotlib. The input is the raw data stored on the server, and the output is the analyzed 3D model of the terrain, geological properties, and climatic conditions data.

[1465] Step 4: Send results

[1466] The server sends the analysis results to the terminal. The analysis results include a 3D model of the terrain, geological characteristics, climatic conditions, and the types of resources present. This data is sent in a standard data format such as JSON. The input is the analyzed data, and the output is the JSON data sent to the terminal.

[1467] Step 5: View the results

[1468] The terminal receives the analysis results sent from the server and displays them to the user. Based on the displayed information, the user can obtain basic data for designing a home with the optimal shape and materials. For example, a 3D model of the terrain is displayed on the terminal screen, and the user can rotate and zoom in and out to check the details. The input is JSON data sent from the server, and the output is the visual information displayed to the user.

[1469] (Application example 1)

[1470] Next, a description will be given of Application Example 1 of Form 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."

[1471] At disaster sites, there is a need to quickly and accurately collect information on the topography, geology, climate, existing resources, etc., and provide basic data for formulating optimal rescue operations and recovery plans. However, the conditions at disaster sites are extremely harsh, and it is often difficult for people to reach them directly. Therefore, a means of collecting information efficiently and safely is required.

[1472] 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.

[1473] In this invention, the server includes means for analyzing elements present at the site, means for designing a dwelling with optimal shape and materials based on the analysis results, means for constructing the dwelling based on the design, means for collecting information on the topography, geology, climate, existing resources, etc. at the disaster site, and means for transmitting the collected information in real time. This allows for the rapid and accurate collection of information at the disaster site, enabling the formulation of optimal rescue operations and recovery plans.

[1474] "Means for analyzing elements present at the site" refers to devices and systems that use sensors and cameras installed on-site to collect and analyze information on topography, geology, climate, existing resources, etc.

[1475] "Means for designing a dwelling with optimal shape and materials" refers to a design process or software for determining the shape and materials of a dwelling based on collected data.

[1476] "Means for constructing the dwelling based on the design" refers to the machinery, technology, and construction methods required to actually construct the designed dwelling.

[1477] "Means for collecting information on the topography, geology, climate, existing resources, etc. at disaster sites" refers to a system for collecting detailed information on the site using devices such as robots and drones dispatched to the disaster site.

[1478] "Means for transmitting collected information in real time" refers to communication devices and network technologies for instantly transmitting collected data to a remote server or command center.

[1479] The system for implementing this invention collects information on the topography, geology, climate, and existing resources at the disaster site, and provides basic data for formulating optimal rescue operations and recovery plans. A specific embodiment of this system is shown below.

[1480] System configuration

[1481] The system consists of the following main components:

[1482] 1. Sensors and cameras: These are installed at disaster sites to collect information on the topography, geology, climate, and existing resources. These include temperature sensors, humidity sensors, geological sensors, and high-resolution cameras.

[1483] 2. Data collection robots: These are deployed to disaster sites and equipped with sensors and cameras to collect information. The robots can operate remotely or autonomously.

[1484] 3. Data transmission device: A communication device for transmitting collected information to a server in real time. Specifically, this includes Wi-Fi and 4G / 5G communication modules.

[1485] 4. Server: A central processing unit for receiving and analyzing collected data. The server contains a database, analysis software, and generative AI models.

[1486] 5. Generative AI model: An artificial intelligence model that designs homes with optimal shapes and materials based on collected data.

[1487] Program processing

[1488] The server performs the following process.

[1489] 1. Data reception: Receives information transmitted from the data transmission device, including image data, temperature data, humidity data, and geological data.

[1490] 2. Data analysis: Analyze the received data and understand the situation at the disaster site. For the analysis, use image processing software (e.g., OpenCV) and data analysis libraries (e.g., NumPy, Pandas).

[1491] 3. Application of generative AI model: Based on the analysis results, a generative AI model is used to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network.

[1492] 4. Design data output: The data of the designed house is output and provided to the construction means, which enables the house to be constructed quickly and efficiently.

[1493] Specific examples

[1494] For example, a robot exploring the interior of a building that collapsed in an earthquake collects the following information:

[1495] Image: Image of the interior of the collapsed building

[1496] Temperature: On-site temperature (e.g. 25.3°C)

[1497] Humidity: Humidity at the site (e.g. 45.7%)

[1498] Geology: Site geology (e.g. bedrock)

[1499] This information is sent in real time to a server, which uses generative AI models to develop optimal rescue operations and recovery plans.

[1500] Prompt Sentence Examples

[1501] "Write a program for a robot to be sent to a disaster site to capture images of the interior of buildings that have collapsed due to an earthquake, collect temperature, humidity, and geological data, and send it to a server."

[1502] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1503] Step 1:

[1504] Data collection

[1505] The terminal (robot) arrives at the disaster site and uses sensors and cameras to collect information on the topography, geology, climate, existing resources, etc. Specifically, it acquires temperature data with a temperature sensor, humidity data with a humidity sensor, geological data with a geological sensor, and captures images of the site with a high-resolution camera.

[1506] Input: Environmental information of the disaster site

[1507] Output: Temperature data, humidity data, geological data, image data

[1508] Step 2:

[1509] Data transmission

[1510] The terminal (robot) transmits the collected data to the server in real time. Using a communication device (Wi-Fi, 4G / 5G communication module), the data is divided into packets and sent to a specified IP address on the server.

[1511] Input: Temperature data, humidity data, geological data, image data

[1512] Output: Data packet sent to the server

[1513] Step 3:

[1514] Data reception

[1515] The server receives data packets sent from the terminal, reconstructs the received packets, and stores them as temperature data, humidity data, geological data, and image data.

[1516] Input: Data packets sent from the device

[1517] Output: Stored temperature data, humidity data, geological data, image data

[1518] Step 4:

[1519] Data analysis

[1520] The server analyzes the received data. Specifically, it analyzes the image data using image processing software (e.g., OpenCV), and analyzes the temperature data, humidity data, and geological data using data analysis libraries (e.g., NumPy, Pandas).

[1521] Input: Stored temperature data, humidity data, geological data, image data

[1522] Output: Analysis results (detailed site conditions)

[1523] Step 5:

[1524] Applying generative AI models

[1525] The server then applies a generative AI model based on the analysis results to design a home with the optimal shape and materials. The generative AI model uses a pre-trained neural network to design based on input data.

[1526] Input: Analysis results

[1527] Output: Design data (house with optimal shape and materials)

[1528] Step 6:

[1529] Design data output

[1530] The server outputs data on the house designed by the generative AI model and provides it to the construction method. The design data is output as CAD files and architectural drawings.

[1531] Input: Design data

[1532] Output: CAD files, architectural drawings

[1533] The above processing steps enable rapid and accurate collection of information at the disaster site, enabling optimal rescue operations and recovery plans to be formulated.

[1534] Example 2

[1535] Next, a description will be given of Example 2 of Form 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."

[1536] Conventional residential design systems have difficulty in designing with sufficient consideration of topographical and geological characteristics, making it particularly difficult to create optimal residential designs in places that are difficult for people to reach or that have been destroyed by disasters. Furthermore, flexible design changes in response to user requests are not easy to make, so an efficient design process is required.

[1537] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1538] In this invention, the server includes: a means for a user to input topographical data and geological data; a means for a terminal to transmit the input data to the server; a means for the server to generate a prompt to the generative AI model and request an optimal house design based on the input data; a means for the generative AI model to generate a design proposal; a means for the server to receive the generated design proposal and transmit it to the terminal; a means for the terminal to display the design proposal to the user; a means for the user to check the design proposal and input corrections or additional conditions as necessary; and a means for the terminal to transmit the corrections or additional conditions to the server and request a new design. This enables optimal house designs that take into account topographical and geological characteristics, and also enables flexible and efficient design changes to be made in response to user requests.

[1539] "Means for analyzing local elements" refers to equipment and software for collecting and analyzing local environmental information, such as topographical and geological data.

[1540] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the shape and materials of a residence based on collected data.

[1541] "Means for constructing the dwelling based on the design" refers to the construction methods and machinery used to actually build the designed dwelling.

[1542] "Means for user input of topographical and geological data" refers to an interface or device that allows a user to input topographical and geological information into the system.

[1543] "Means for the terminal to transmit input data to the server" refers to a communication device or software for transmitting data input by the user to the server.

[1544] "Means for the server to generate prompt text for the generative AI model and request the optimal home design based on the input data" refers to the function that creates prompt text based on the data collected by the server and requests the generative AI model to design.

[1545] "Means by which the generative AI model generates design proposals" refers to the algorithms and software that the generative AI model uses to create residential design proposals based on prompt statements.

[1546] "Means for the server to receive the generated design proposals and send them to the terminal" refers to the communications equipment and software used to send the design proposals received from the generative AI model to the terminal.

[1547] "Means by which the terminal displays the design proposal to the user" refers to a display or interface for displaying the design proposal received from the server to the user.

[1548] "Means for the user to review the design proposal and input corrections or additional conditions as necessary" refers to an interface or device that allows the user to review the displayed design proposal and input corrections or additional conditions.

[1549] "Means for the terminal to send corrections or additional conditions to the server and request a redesign" refers to communication devices or software that send corrections or additional conditions entered by the user to the server and request the generative AI model to design again.

[1550] This invention is a system that allows a user to input topographical and geological data and, based on that data, designs a dwelling with optimal shape and materials. A specific embodiment of this system will be described below.

[1551] First, the user inputs topographical and geological data through the system interface. For example, the topographical data is "steep mountainous area" and the geological data is "weak geology." This data is then sent from the user's device to the server. The device then converts the input data into JSON format and sends it to the server using an HTTP POST request.

[1552] The server generates a prompt based on the received topographical and geological data. Specifically, it generates the following prompt:

[1553] Terrain data: steep mountainous area

[1554] Geological data: Weak geology

[1555] Condition: Design a home that is earthquake-resistant

[1556] Based on these conditions, design a home with the optimal shape and materials.

[1557] The generated prompt sentence is sent to a generative AI model to request a design. For example, OpenAI's GPT-4 can be used as the generative AI model.

[1558] The generative AI model generates optimal housing design proposals based on the prompt text. For example, it designs a stepped house that follows the terrain, or a house made of reinforced concrete that is earthquake-resistant. The generated design proposals are returned to the server in the following format:

[1559] Shape: Terraced housing that follows the terrain

[1560] Material: Reinforced concrete

[1561] Features: Earthquake-resistant and designed to adapt to steep terrain

[1562] The server sends the design proposal received from the generative AI model to the device. The device displays the received design proposal to the user. The user checks the design proposal through the interface and inputs corrections or additional conditions as necessary. For example, the user can input conditions such as "make the living room larger" or "change the roof material."

[1563] The device then sends any modifications or additional conditions entered by the user back to the server, which then generates a prompt for the generative AI model and requests a design. This process is repeated until the optimal home design is completed.

[1564] This system enables optimal residential design that takes into account the characteristics of the terrain and geology, and also allows for flexible and efficient design changes to be made according to the user's requests.The hardware used is a high-performance server (e.g., a server equipped with an NVIDIA GPU), and the software used is a generative AI model (e.g., OpenAI's GPT-4).

[1565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1566] Step 1:

[1567] The user inputs topographical and geological data.

[1568] Specifically, the user inputs "steep mountainous area" into the "topography data" field and "weak geology" into the "geology data" field on the system interface.

[1569] Input: Topographical data, geological data

[1570] Output: Input data is saved on the user's device

[1571] Step 2:

[1572] The terminal sends the input data to the server.

[1573] Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request.

[1574] Input: User-entered topographic and geological data

[1575] Output: JSON formatted data sent to the server

[1576] Step 3:

[1577] The server generates a prompt for the generative AI model and requests the optimal home design based on the input data.

[1578] Specifically, the server analyzes the received JSON data and generates a prompt like the following:

[1579] Terrain data: steep mountainous area

[1580] Geological data: Weak geology

[1581] Condition: Design a home that is earthquake-resistant

[1582] Based on these conditions, design a home with the optimal shape and materials.

[1583] The generated prompt sentence is sent to the generative AI model.

[1584] Input: JSON format data sent to the server

[1585] Output: The prompt sent to the generative AI model

[1586] Step 4:

[1587] A generative AI model generates design proposals.

[1588] Specifically, the generative AI model generates optimal housing design proposals based on prompts, such as a stepped house that follows the terrain or a house made of reinforced concrete that is earthquake-resistant.

[1589] Input: A prompt sent to the generative AI model

[1590] Output: Generated residential design proposal

[1591] Step 5:

[1592] The server receives the generated design proposal and sends it to the terminal.

[1593] Specifically, the server sends the design proposal received from the generative AI model to the terminal in JSON format.

[1594] Input: Design proposals received from the generative AI model

[1595] Output: Design proposal in JSON format sent to the terminal

[1596] Step 6:

[1597] The terminal displays the design proposal to the user.

[1598] Specifically, the device analyzes the received JSON data and displays it to the user as follows:

[1599] Design proposal:

[1600] Shape: Terraced housing that follows the terrain

[1601] Material: Reinforced concrete

[1602] Features: Earthquake-resistant and designed to adapt to steep terrain

[1603] Input: Design proposal in JSON format sent to the terminal

[1604] Output: Design proposal displayed to the user

[1605] Step 7:

[1606] The user checks the design proposal and enters corrections or additional conditions as necessary.

[1607] Specifically, the user checks the displayed design proposal and inputs modifications or additional conditions, such as "make the living room larger" or "change the roof material."

[1608] Input: Design proposal displayed to the user

[1609] Output: Any corrections or additional conditions entered by the user

[1610] Step 8:

[1611] The device sends any corrections or additional conditions to the server and requests a new design.

[1612] Specifically, the device converts the corrections and additional conditions entered by the user into JSON format and sends it back to the server. The server then generates a prompt for the AI ​​model and requests it to design.

[1613] Input: Any corrections or additional conditions entered by the user

[1614] Output: Modifications and additional conditions sent to the server, and prompts sent back to the AI ​​model

[1615] (Application example 2)

[1616] Next, a description will be given of Application Example 2 of Form 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."

[1617] Conventional residential design systems have difficulty creating optimal residential designs that take into account environmental information such as topography and geology. Furthermore, optimization of factory layouts and equipment placement is often done manually, making it difficult to build efficient production lines. This has led to problems such as insufficient efficiency and safety in residential and factory designs.

[1618] 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.

[1619] In this invention, the server includes means for analyzing elements present on site, means for designing a residence with an optimal shape and materials based on the analysis results, means for constructing the residence based on the design, means for collecting information on the topography and equipment layout within the factory, means for designing an optimal factory layout and equipment layout based on the collected information, and means for generating an optimal layout using generative AI. This makes it possible to design an optimal residence that takes environmental information into consideration and to design an efficient factory layout.

[1620] "Elements present in situ" refers to physical and environmental information such as topography, geology, and facilities in a particular location or environment.

[1621] "Means for analysis" refers to devices or software used to analyze collected information and extract data for specific purposes.

[1622] "Means for designing a dwelling with optimal shape and materials" refers to design tools and software for optimizing the shape and materials of a dwelling based on the collected and analyzed information.

[1623] "Means for constructing the dwelling based on the design" refers to machinery, equipment, or the process for actually constructing the designed dwelling.

[1624] "Means for collecting information on the topography and equipment layout within the factory" refers to sensors and data collection devices for collecting information on the topography and equipment layout within the factory.

[1625] "Means for designing optimal factory layouts and equipment placement based on collected information" refers to design tools and software for analyzing collected information and optimizing the layout and equipment placement within a factory.

[1626] "Generative AI" refers to artificial intelligence technology that generates optimal designs and layouts based on collected and analyzed information.

[1627] "Means for generating an optimal layout" refers to devices or software that use generative AI to generate an optimal layout based on collected and analyzed information.

[1628] To implement this invention, the server, the terminal, and the user must cooperate to operate the system. A specific embodiment of this is shown below.

[1629] System Program

[1630] The server first uses a means to analyze the elements present on the site to collect information on the topography, geology, facilities, etc. This information is acquired using sensors and data collection devices. Next, using a means to design a home with the optimal shape and materials based on the collected information, it utilizes generative AI to create the optimal home design. Then, using a means to build the home based on the design, it proceeds with the actual construction process.

[1631] Additionally, information about the factory's topography and equipment layout is collected using a method to gather information about the factory's interior. Based on the collected information, generative AI is used to design the optimal factory layout and equipment layout, generating the optimal layout.

[1632] Program processing explanation

[1633] The server uses software such as Python and the OpenAI API to analyze the collected data and generate an optimal design. Specifically, it formats the topographical and facility data in JSON format and inputs it into a generative AI model. The generative AI model then generates the optimal design and layout based on this data.

[1634] The hardware used is suitable for servers and cloud environments (e.g., AWS, Google Cloud), and the software uses Python and the OpenAI API.

[1635] Specific examples

[1636] For example, consider a factory with a flat terrain, an area of ​​1,000 square meters, and two machines, Machine A (10x10) and Machine B (15x15), respectively. Based on this information, the following prompt sentence is input to the generative AI model:

[1637] Example prompt sentence:

[1638] Terrain data inside the factory: {"Terrain": "Flat", "Area": ​​"1000 square meters"}

[1639] Facility data: {"Facility 1": {"Type": "Machine A", "Size": "10x10"}, "Facility 2": {"Type": "Machine B", "Size": "15x15"}}

[1640] Use the above information to design the optimal factory layout.

[1641] By inputting this prompt into the generative AI model, the optimal factory layout is generated. The generated layout is sent from the server to the terminal, where the user can check and implement it.

[1642] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1643] Step 1:

[1644] The server uses sensors and data collection devices to collect information on elements present in the site (topography, geology, facilities, etc.). The input is raw data obtained from the sensors and data collection devices, and the output is a dataset of the collected environmental information. This dataset is used for subsequent analysis.

[1645] Step 2:

[1646] The server analyzes the collected environmental information. Specifically, it formats the data using a programming language such as Python and extracts the necessary information. The input is the dataset of environmental information collected in step 1, and the output is the analyzed data. This analyzed data forms the basis for generating an optimal design.

[1647] Step 3:

[1648] The server inputs a prompt to the generative AI model based on the analyzed data. The input is the analyzed data and a prompt for the generative AI model, and the output is the optimal design proposal obtained from the generative AI model. Specifically, the server uses the OpenAI API to call the generative AI model and inputs a prompt.

[1649] Step 4:

[1650] The server receives the optimal design proposal obtained from the generative AI model and provides it to the user. The input is the design proposal from the generative AI model, and the output is the design proposal provided to the user. Specifically, the server sends the design proposal to the terminal so that the user can check it.

[1651] Step 5:

[1652] The user checks the provided design proposal and makes corrections or approvals as necessary. The input is the design proposal provided by the server, and the output is the corrected or approved design proposal. Specifically, the user checks the design proposal using a terminal and sends feedback to the server.

[1653] Step 6:

[1654] The server receives feedback from the user and finalizes the design. The input is the user feedback, and the output is the finalized design. Specifically, the server analyzes the feedback, makes any necessary modifications, and then generates the final design.

[1655] Step 7:

[1656] The server starts the construction process of the house or factory based on the final design proposal that has been confirmed. The input is the final design proposal that has been confirmed, and the output is the start of the construction process. Specifically, it arranges for the resources required for construction and carries out the construction work.

[1657] Example 3

[1658] Next, a third embodiment of the third embodiment will be described. 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."

[1659] In conventional housing construction systems, the analysis of blueprint data, the generation of resource lists, and the generation of control codes for robots and 3D printers are often done manually, resulting in inefficiencies. Furthermore, there is insufficient automation to effectively utilize on-site resources, making the construction process complex and time-consuming.

[1660] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1661] In this invention, the server includes means for receiving and analyzing design drawing data, means for generating a required resource list, means for generating control code for the robot, and means for generating control code for the 3D printer, which enables automatic analysis of design drawing data, automatic generation of a resource list, and automatic generation of control codes for the robot and the 3D printer.

[1662] "Local factors" refer to the resources and environmental conditions available at the construction site.

[1663] "Analytical means" refers to equipment and software used to evaluate the elements present at the site and extract the necessary information.

[1664] "Design means" refers to devices and software for planning a home with the optimal shape and materials based on the analysis results.

[1665] "Means for receiving and analyzing design drawing data" refers to devices and software for receiving design drawing data provided by a user and analyzing its contents.

[1666] "Means for generating a list of required resources" refers to a device or software for creating a list of resources required for construction based on the results of analyzing the blueprint data.

[1667] "Means for generating control code for a robot" refers to a device or software for creating code containing instructions for a robot to operate according to a blueprint.

[1668] "Means for generating control code for a 3D printer" means a device or software that generates code containing instructions for a 3D printer to manufacture a part based on a design.

[1669] "Means for construction" refers to the equipment and machinery used to actually build a dwelling based on a blueprint.

[1670] This invention is a system that analyzes blueprint data for a house, creates a list of required resources, and automatically generates control codes for a robot and a 3D printer. Specific embodiments of this system are described below.

[1671] First, the user uploads the design data using the terminal. Through the terminal interface, the user selects the design file (e.g., "house_design.dwg") and clicks the upload button. This design data is then sent to the server.

[1672] The server uses a CAD analysis tool (e.g., AutoCAD) to analyze the received blueprint data. The server identifies each part of the blueprint and determines the resources required for each part. Based on the results of this analysis, the server generates a list of required resources. For example, resources such as wood, metal, and plastic may be listed.

[1673] Next, the server generates a control code for the robot. This control code contains instructions for the robot to operate according to the blueprint. The server uses a control code generation tool (e.g., ROS - Robot Operating System) to generate the control code for the robot. For example, a file called "robot_instructions.txt" is generated.

[1674] Similarly, the server generates control code for the 3D printer. This control code contains instructions for the 3D printer to manufacture the part based on the design. The server uses software to generate control code for the 3D printer. For example, a file called "3dprinter_instructions.gcode" is generated.

[1675] As a concrete example, we will explain the process of a user uploading design data. The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The server receives this data and starts analyzing it.

[1676] Once the analysis is complete, the server generates control codes for the robot (e.g., "robot_instructions.txt") and the 3D printer (e.g., "3dprinter_instructions.gcode"), which are then sent to the robot and the 3D printer to begin building the home.

[1677] Example prompts to input to a generative AI model:

[1678] "Please explain the process of the system that uploads blueprint data and builds a house using a robot and a 3D printer, including specific operations." The flow of the specific process in Example 3 will be explained using Figure 15.

[1679] Step 1:

[1680] The user uploads the blueprint data.

[1681] The user selects the design data (e.g., "house_design.dwg") using the terminal interface and clicks the upload button. The input is the design data, and the output is the design data sent to the server.

[1682] Step 2:

[1683] The server receives the blueprint data and begins analysis.

[1684] The server opens the received blueprint data using a CAD analysis tool (e.g., AutoCAD). The input is the uploaded blueprint data, and the output is the analyzed data for each part of the blueprint. Specifically, the server identifies each part of the blueprint and specifies the resources required for each part.

[1685] Step 3:

[1686] The server generates a list of required resources.

[1687] The server generates a list of resources such as wood, metal, and plastic based on the analysis results. The input is the analyzed design data, and the output is a list of required resources (e.g., "resource_list.txt"). Specifically, the server lists the types and quantities of resources required for each part.

[1688] Step 4:

[1689] The server generates the control code for the robot.

[1690] The server generates control code for the robot based on the resource list and blueprint data. The input is the resource list and blueprint data, and the output is the control code for the robot (e.g., "robot_instructions.txt"). For specific operations, the server uses ROS to describe the robot's operation instructions in detail.

[1691] Step 5:

[1692] The server generates control codes for the 3D printer.

[1693] The server also generates control code for the 3D printer. The input is the resource list and blueprint data, and the output is the control code for the 3D printer (e.g., "3dprinter_instructions.gcode"). As a specific operation, the server describes the operation instructions for the 3D printer in detail.

[1694] Step 6:

[1695] The robot begins construction according to the control code.

[1696] The robot follows the control code received from the server and uses resources available on-site to build a house. The input is the control code for the robot, and the output is the parts of the house that are built. Specifically, the robot cuts wood and assembles walls.

[1697] Step 7:

[1698] The 3D printer manufactures and assembles the parts according to the control code.

[1699] The 3D printer manufactures parts based on the blueprint according to the control code received from the server. The input is the control code for the 3D printer, and the output is the manufactured part. In concrete terms, the 3D printer prints walls using plastic and assembles them.

[1700] (Application example 3)

[1701] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1702] In conventional housing construction systems, the management of blueprints, on-site resource scanning, control of construction equipment, real-time monitoring of construction progress, and alert notifications when problems occur are all performed individually, making integrated management difficult. Furthermore, there was no system for centrally managing these functions, making efficient housing construction difficult.

[1703] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1704] In this invention, the server includes a means for uploading and managing blueprints, a means for scanning and managing on-site resources, a means for controlling construction equipment, a means for monitoring construction progress in real time, and a means for issuing alerts when problems occur. This makes it possible to centrally manage everything from blueprint management to monitoring construction progress and responding to problems when they occur.

[1705] "Means for analyzing elements present at the site" refers to devices and software for detecting resources and environmental conditions present at the site and analyzing that information.

[1706] "Means for designing a residence with optimal shape and materials based on the analysis results" refers to design tools and algorithms for determining the optimal shape and materials of a residence based on the analyzed data.

[1707] "Means for constructing the residence based on the design" refers to devices such as robots and 3D printers for actually constructing the residence according to the design drawings.

[1708] "Means for uploading and managing blueprints" refers to software or an interface for uploading blueprints in digital format to a server and managing them.

[1709] The "means for scanning and managing on-site resources" refers to devices and software for scanning on-site resources and managing the data.

[1710] "Means for controlling construction equipment" refers to software or interfaces for controlling construction equipment such as robots and 3D printers.

[1711] "Means for monitoring construction progress in real time" refers to software or interfaces for monitoring the construction progress in real time and checking the progress.

[1712] "Means for issuing alerts when problems occur" refers to software or interfaces that issue alerts and notify relevant parties when problems occur during construction.

[1713] This invention is a system for centrally managing blueprints, scanning on-site resources, controlling construction equipment, monitoring construction progress in real time, and sending alerts when problems occur in a residential construction system.

[1714] Hardware and software used

[1715] Hardware: smartphones, robots, 3D printers

[1716] Software: Python, Flask (web framework), OpenCV (image processing library), NumPy (numerical calculation library)

[1717] System configuration

[1718] 1. Upload and manage blueprints:

[1719] Users take a photo of the blueprint using their smartphone and upload it to the server via the application.

[1720] The server stores and manages the uploaded blueprints.

[1721] 2. On-site resource scanning and management:

[1722] Users take photos of the site using their smartphone camera and send them to the server via the application.

[1723] The server uses OpenCV to process images, scan on-site resources, and manage the data.

[1724] 3. Control of construction equipment:

[1725] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[1726] The server sends the received commands to the construction equipment and controls it.

[1727] 4. Real-time monitoring of construction progress:

[1728] The server receives data from the construction equipment in real time and monitors progress.

[1729] Users can check their progress through the application.

[1730] 5. Alert notifications when problems occur:

[1731] The server generates alerts and notifies the user if any problems occur during construction.

[1732] Users can receive and respond to alerts through the application.

[1733] Specific examples

[1734] When uploading a blueprint:

[1735] Users take a photo of the blueprint with their smartphone camera and upload it through the application.

[1736] Example prompt: "Please upload the blueprint."

[1737] When scanning for resources in the field:

[1738] Users take a photo of the site using their smartphone camera and scan it through the application.

[1739] Example prompt: "Use your camera to take a photo of the site to scan for on-site resources."

[1740] When controlling a construction device:

[1741] The user enters and sends commands through the application's interface.

[1742] Example prompt: "Enter the command you want to send to your robot or 3D printer."

[1743] When checking construction progress:

[1744] The user can check the progress through the application.

[1745] Example prompt: "Press the monitoring button to check the construction progress."

[1746] If you encounter problems:

[1747] The server generates an alert and notifies the user.

[1748] Example prompt: "There's a problem. Please check your alerts."

[1749] In this way, it becomes possible to centrally manage everything from managing blueprints to monitoring construction progress and responding when problems arise.

[1750] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1751] Step 1:

[1752] Users take a photo of the blueprint with their smartphone camera and upload it to the server via the application.

[1753] Input: Blueprint image file

[1754] Output: Blueprint file saved on the server

[1755] Specific operation: A user launches the application, takes a picture of a blueprint, and presses the "Upload" button. The application sends the image file to the server, and the server saves the received file.

[1756] Step 2:

[1757] Users take photos of the site using their smartphone camera and send them to the server via the application.

[1758] Input: Photo file of the scene

[1759] Output: On-site resource data stored on a server

[1760] Specific operation: The user takes a photo of the site and presses the "Scan" button. The application sends the photo file to the server, which processes the image using OpenCV, extracts and stores the site's resource data.

[1761] Step 3:

[1762] The user enters commands through the application interface to be sent to the construction device (robot or 3D printer).

[1763] Input: Command to construction device

[1764] Output: Command sent to the construction device

[1765] Specific operation: The user inputs a command into the application interface and presses the "Send" button. The application sends the command to the server, and the server sends the received command to the construction device.

[1766] Step 4:

[1767] The server receives data from the construction equipment in real time and monitors progress.

[1768] Input: Progress data from construction device

[1769] Output: Real-time progress updates

[1770] Specific operation: The construction device sends progress data to the server, the server analyzes the received data and updates the progress status. The user can check the progress status through the application.

[1771] Step 5:

[1772] The server generates alerts and notifies the user if any problems occur during construction.

[1773] Input: Data on the problem occurrence

[1774] Output: An alert to notify the user

[1775] Specific operation: The server monitors data from the construction equipment and generates an alert if a problem occurs. The alert is notified to the user through the application. The user checks the alert and takes action.

[1776] 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.

[1777] "Example 1"

[1778] An embodiment of the invention incorporating an emotion engine is a system including a means for analyzing elements present at a location, a means for desig...

Claims

1. A means for analyzing the topography and geology of inaccessible places and places destroyed by disasters based on environmental data including topography, geology, and climate of soil collected using a specific sensor and a camera; An emotion engine that recognizes emotions of a user who wishes to build a house in the location; A means for inputting a specific prompt sentence into a generative AI model to design a house having an optimal shape and material for the user based on the result of the analysis and the user's emotions; A means for creating a construction plan required for constructing the residence based on the design, and transmitting the created construction plan to a robot that constructs the residence or a construction company that constructs the residence; A system including:

2. An environment analysis means for analyzing a work environment and a work situation of a site where the construction company constructs the house based on data collected by using a specific sensor and a camera; an emotion engine that recognizes emotions of workers constructing the dwelling; A means for inputting a specific prompt sentence into a generative AI model, and based on the result of the analysis by the environment analysis means and the emotion of the worker, proposing an optimal work procedure and a layout of equipment to be used in the construction; The system of claim 1 , comprising:

3. A means for monitoring the progress of construction of the residence; A means for notifying a specific person or location of an alert when a problem occurs in the construction progress; The system of claim 1 , comprising:

Images