system

Abstract

This system automatically retrieves floor plans from real estate information sources, uses AI to analyze that information, and extracts data on room size and shape. [Solution] A system comprising: means for automatically acquiring floor plans and spatial information from real estate information sources; means for analyzing the acquired floor plans and extracting data on room size and shape; means for collecting user preferences and budget and generating a user profile; means for selecting the most suitable furniture and home appliances based on the user profile and generating a suggestion list; means for collecting price information and product reviews from multiple sales platforms and optimizing the suggestion list; means for notifying the user of the suggestion list and related information; means for monitoring price fluctuations and inventory status in real time and updating information to the user; and means for checking the compatibility of potential purchase products with existing smart home devices and suggesting settings.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Selecting furniture and home appliances when moving to a new house is a task that requires a lot of effort and time. Conventionally, users had to measure the floor plan themselves, consider the interior style, and select furniture and home appliances individually, so it was difficult to make an efficient and effective choice. In addition, investigating price comparisons and review evaluations of each product was also a heavy burden for users, and the selection of the optimal product was hindered. Furthermore, product selection considering cooperation with smart home devices has been required, and the complexity has increased.

Means for Solving the Problems

[0005] This invention solves the problem by automatically acquiring floor plans from real estate information sources, analyzing that information with AI, and extracting room size and shape data. Furthermore, it provides a means to create a profile based on the user's preferences and budget, and then select and suggest the most suitable furniture and appliances based on that profile. It also supports purchase decisions by collecting price information and product reviews in real time from multiple sales platforms and optimizing and notifying the user of a list of suggestions. For potential purchase products, it checks compatibility with smart home devices and suggests their settings to improve user convenience. This enables users to make efficient and appropriate choices.

[0006] "Real estate information sources" refer to databases and online platforms that provide detailed property information and floor plans.

[0007] A "floor plan" is a diagram illustrating the arrangement of each room or space in a house or building, and refers to a drawing that shows the size and shape of the rooms.

[0008] "Spatial information" refers to data concerning the dimensions, shape, and layout of each room and space within a building.

[0009] A "user" refers to an individual who uses this system to select and consider purchasing furniture and home appliances.

[0010] A "user profile" refers to a dataset that compiles information such as a user's preferences, budget, and past purchase history.

[0011] A "suggestion list" refers to a list of furniture and home appliances that have been determined to be optimal based on the user's profile.

[0012] A "sales platform" refers to an online or offline marketplace that offers and sells products such as furniture and home appliances.

[0013] "Pricing information" refers to the purchase price and related cost information displayed for a specific product.

[0014] "Product reviews" refer to information posted by users based on their experience using a product, including evaluations and comments.

[0015] "Smart home devices" refer to electronic devices used in the home that can be controlled or connected via the internet or other technologies.

[0016] "Compatibility" refers to the ability or compatibility of different products or systems to work together. [Brief explanation of the drawing]

[0017] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine. **Mode for Carrying Out the Invention**

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention provides a system that automatically obtains floor plans from real estate information sources, identifies the size and shape of rooms through analysis, and proposes optimal furniture and home appliances according to the user's needs. Embodiments of this invention are described below.

[0039] This system includes user terminals and server components that operate on the cloud or on dedicated servers. The terminals receive user instructions and transmit them to the server, which then processes the information and generates a list of suggestions.

[0040] The server accesses real estate information sources and retrieves the latest floor plans for specified properties from the database. This process also includes processing URLs of properties provided by the user, as well as floor plans in electronic file format. The retrieved floor plans are processed by an advanced image analysis module on the server, extracting dimension and shape data for each room. This design eliminates the need for users to manually measure the dimensions.

[0041] Next, the device displays an interface for the user to input their preferred interior style and budget, which is then collected manually or via voice input. This data is sent to the server and registered as part of the user profile. In addition, the server also refers to past purchase history data to analyze the user's style trends, and this is also reflected in the profile.

[0042] Next, the server searches a database of furniture and appliances based on the acquired floor plan and user profile, and creates a list of suggestions that are best suited to the specific room. This list includes products that match the user's preferences and are purchasable within their budget.

[0043] Simultaneously, the server collects pricing information and product reviews from multiple online sales platforms. This allows it to evaluate the cost-effectiveness of each product being offered and present users with reasonably priced and reputable options.

[0044] The device notifies the user and presents a list of suggestions and their details. This list includes price, reviews, and stock information, and is designed to allow the user to make an immediate purchase.

[0045] Furthermore, the server checks the compatibility of the selected products with smart home devices and, if possible, suggests setup methods to the user. This allows users to easily integrate new products into their existing home network.

[0046] As a concrete example, suppose a user is looking for a sofa for their living room when moving into a new home. The server identifies the dimensions of the living room from the floor plan and suggests several suitable sofas based on the user's modern interior style preferences and budget. The terminal presents these to the user and supports their selection based on price and reviews. At this time, if one of the suggested sofas is smart home compatible, information on setting it up is also presented.

[0047] Thus, the system of the present invention provides a technology that significantly reduces the various hassles that users face when choosing a residence, and enables them to efficiently and safely arrange their living space.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server accesses real estate information sources to automatically retrieve floor plans for properties. URLs and PDF files of floor plans provided by users are also included in this process, and the server downloads and begins processing them.

[0051] Step 2:

[0052] The server passes the acquired floor plan to an image analysis module to identify the shape and dimensions of each room. This information is stored in a database as detailed data for each room and used in subsequent suggestion processing.

[0053] Step 3:

[0054] The user inputs their interior design preferences and budget through an interface displayed on the device. The device receives this information and sends it to a server, incorporating it into the process of generating a user profile.

[0055] Step 4:

[0056] Based on the received user profile, the server retrieves past purchase history from the database and analyzes the user's style tendencies. This information is integrated into the profile and used to create suggestion lists.

[0057] Step 5:

[0058] The server searches a database of furniture and home appliances based on the analyzed floor plan data and user profile, and generates a list of recommended items for each room. This list includes products that match the user's preferences and budget.

[0059] Step 6:

[0060] The server collects pricing information and product reviews for products proposed from multiple online sales platforms. Based on this information, it evaluates cost-effectiveness and optimizes the recommendations to make the most beneficial choice for the user.

[0061] Step 7:

[0062] The terminal notifies the user of the completed list of suggestions and displays detailed information about the list. This information includes the price of the suggested furniture and appliances, user reviews, and inventory information, allowing the user to consider purchasing based on this information.

[0063] Step 8:

[0064] The server checks the compatibility of the smart home-compatible products included in the suggestion list with the user's current smart home devices and suggests setup methods. This allows the user to smoothly integrate newly purchased products into their existing environment.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] Modern consumers are required to efficiently and accurately select products that meet their needs from a diverse range of housing and home appliance information. However, conventional methods involve manually checking the space and layout of a property and the process of selecting suitable products, which is time-consuming and laborious. Furthermore, considering appropriate cost-effectiveness and product compatibility requires searching for information individually, which is extremely cumbersome. This invention aims to solve these problems.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes means for automatically acquiring spatial design information from real estate information sources, means for analyzing the acquired spatial design information and extracting information on the dimensions and shape of the plots, and means for acquiring the user's preferences and budget and generating a user profile. This enables users to easily and quickly find the product best suited to their space, and further supports them in making real-time purchasing decisions that take into account cost-effectiveness and product compatibility.

[0070] "Real estate information sources" refer to information providers that offer spatial design information and floor plans related to real estate.

[0071] "Spatial design information" refers to data that includes detailed information such as the dimensions, shape, and layout of each room or section of a property.

[0072] A "user profile" refers to a compilation of information such as a user's preferences, budget, and past purchase history, which serves as the foundation for providing optimal suggestions to individual users.

[0073] A "list of proposals" refers to a list of products and services that meet the user's requirements and are deemed optimal.

[0074] A "supply platform" refers to an online business infrastructure that provides products and services.

[0075] "Automated home appliances" refer to household electrical appliances that can communicate and be controlled using the internet.

[0076] "Image analysis technology" refers to the technology of processing digital image data and extracting specific information.

[0077] "Communication operation" refers to an operation for sending and receiving information, and is a means that enables users to purchase products directly through an interface.

[0078] "Cost-effectiveness" refers to a criterion for evaluating the balance between the performance and quality of a potential purchase product and its price.

[0079] This invention is a system that automatically acquires spatial design information from real estate information sources, identifies the dimensions and shape of a plot through analysis, and proposes the optimal product according to the user's needs. This system consists of a server component that operates in a cloud environment or a dedicated server environment, and a terminal that handles the user interface.

[0080] The server accesses real estate information sources and retrieves spatial design information. This process includes URLs and PDF digital data provided by users. The retrieved information is analyzed by an image analysis module on the server, extracting dimension and shape data for each plot. The OpenCV library is primarily used for image analysis.

[0081] Next, the device provides an interface for the user to input their preferred style and budget. The user enters their preferences using a keyboard or voice input, and this data is sent to the server via a secure protocol. The server registers this as part of the user profile and also analyzes past purchase history to reflect the user's style tendencies.

[0082] Subsequently, the server searches the product information database based on the analyzed design information and user profile, and generates a list of suggestions. This list includes products that match the user's preferences and are purchasable within their budget. The server also collects pricing information and product reviews from multiple supply platforms and evaluates the cost-effectiveness of each suggested product.

[0083] The suggested list is notified to the user via the terminal and includes product details, prices, reviews, and stock information. The user can compare products on the screen and consider purchasing the selected products. If there are potential purchases, the server checks the compatibility of the products with the automated home appliances and provides appropriate setup instructions.

[0084] As a concrete example, if the prompt "Please suggest modern style furniture suitable for a new 3LDK apartment" is entered into the generation AI model, the system will extract the dimensions of each room from the floor plan, suggest furniture that fits the budget and style, and present the most suitable products to the user.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server accesses real estate information sources and automatically retrieves spatial design information. This input consists of URLs of properties and floor plans in electronic file format provided by the user, and the data is collected using the HTTP protocol. After data extraction, the retrieved design information is stored on the server in digital format. Specifically, the process involves extracting information using web page scraping techniques and saving it to a database.

[0088] Step 2:

[0089] The server inputs the acquired spatial design information into an image analysis module and extracts dimension and shape data for each section. This analysis utilizes the OpenCV library to process digital image data, detect the outline of rooms, and measure their size. As output, dimension data for each area of ​​the floor plan is obtained and rearranged into the configuration information.

[0090] Step 3:

[0091] The terminal displays an interface for the user to input their interior style and budget. The user enters specific styles, price ranges, etc., using the keyboard or voice, and the terminal sends this information to the server. Specifically, the input data is transmitted to the server using the secure HTTPS communication protocol.

[0092] Step 4:

[0093] The server receives user input and generates a user profile. Next, it retrieves past purchase history from the database and analyzes interior style trends. This process utilizes SQL queries to aggregate relevant data and understand the user's preferences. After profile generation, information based on the user's criteria is included in the profile.

[0094] Step 5:

[0095] The server uses the acquired dimension data and user profile to search the product information database. The database utilizes NoSQL technology to efficiently search large amounts of information. Based on the search results, a list of suggestions is generated, listing products that match the user's preferences and budget. This output consists of the product name, price, and content suitable for the intended use.

[0096] Step 6:

[0097] The server collects pricing information and product reviews from multiple supply platforms for each product in the suggested list. Access to these platforms is via API, and data is retrieved in JSON format. Based on the collected data, cost-effectiveness is evaluated and the list is optimized. The evaluated list is output as a more accurate list of recommended products.

[0098] Step 7:

[0099] The terminal receives a list of suggestions and related information from the server and presents it to the user. The screen displays product details, prices, reviews, and stock availability, making it easier for the user to visually compare products. Specifically, the user selects a product through screen navigation and can access the purchase page immediately.

[0100] Step 8:

[0101] The server checks the compatibility of selected purchase candidates with existing automated home appliances and suggests setup methods. This process queries a database of specifications for each product and collects network configuration information. The resulting setup guide helps users quickly and smoothly connect new products to their home network.

[0102] (Application Example 1)

[0103] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0104] In the traditional furniture and appliance purchasing process, users had to manually select the optimal product from a vast number of options, ensuring consistency with their budget and style. This resulted in a time-consuming and laborious process, making it difficult to achieve their ideal living space. Furthermore, verifying the functionality of purchased products with smart home systems proved challenging, creating technical issues within existing living environments.

[0105] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0106] This invention includes a server that automatically acquires spatial data from real estate information sources, analyzes floor plans to extract dimensions and structural data of parts, collects user preferences and financial information to generate a user profile, and searches a database of furniture and fixtures based on the user profile to generate a list of optimal product suggestions. This makes it possible for users to efficiently select the best products that match their budget and preferences without any hassle, thereby improving their living environment.

[0107] A "real estate information source" refers to a database or platform that provides information about buildings and houses.

[0108] "Spatial data" refers to data that includes information about the layout of a building, the dimensions of rooms, and its structure.

[0109] A "user profile" refers to a dataset that aggregates personalized information, including a user's preferences and financial situation.

[0110] A "database of furniture and appliances" refers to a data structure that stores information about furniture and electrical appliances that consumers can purchase.

[0111] A "product suggestion list" refers to a set of information generated to provide a list of optimized products based on the user's needs.

[0112] An "online sales platform" refers to a platform or system for buying and selling products over the internet.

[0113] A "smart device" refers to a portable device that can connect to the internet and obtain and transmit information.

[0114] A "prompt message" refers to a short sentence containing instructions or suggestions to support the user's choices.

[0115] This invention provides an integrated system for users to efficiently select furniture and appliances. The main components of the system are a server and a terminal. The following describes an embodiment of the system that implements this application example.

[0116] The server uses a cloud-based storage system as the hardware and software used to acquire spatial data from real estate information sources. Cloud storage such as AWS® S3 is utilized, and real estate information is acquired via APIs. For analysis, AWS Rekognition and Google® Cloud Vision API are used as image analysis technologies to identify the dimensions and structure of floor plans. AWS DynamoDB and Firebase Firestore are used for database management.

[0117] On the device side, an interface is provided for users to input their preferences and financial information. Cross-platform applications are developed using Flutter® or React Native. User information is collected through this interface and synchronized with the server.

[0118] Based on this information, the server searches a database of furniture and fixtures to generate a list of optimal product suggestions. The search utilizes a Node.js backend and an efficient search system powered by Elasticsearch®. The suggestion list is generated along with price and reputation information and is updated in real time.

[0119] The device also notifies the user of a list of suggestions and related information. Using the smartphone's push notification function, users can immediately proceed with the purchase. An example of a prompt message is: "We analyze the latest floor plans and suggest the perfect modern furniture for your living room. Find options that fit your budget and preferences!" This prompt message is generated using an AI model to assist the user in their selection.

[0120] Finally, the server verifies the product's compatibility with existing smart devices and provides the user with the necessary configuration information. This feature allows users to seamlessly integrate the purchased product into their existing systems.

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The server retrieves spatial data of floor plans from real estate information sources. Property identification information is used as input, and the server accesses the real estate information sources via an API. The data is stored in cloud storage such as AWS S3 and handled in a secure environment.

[0124] Step 2:

[0125] The server analyzes the acquired floor plans. Using the acquired image data as input, it extracts room dimensions and shape data using AWS Rekognition or Google Cloud Vision API. This processing automates dimension measurements that were previously done manually, enabling rapid data provision.

[0126] Step 3:

[0127] Users input their preferences and financial information through their device. The input screen includes fields for interior style and budget, and this information is collected and sent to the server as a digital profile. This creates an individualized dataset.

[0128] Step 4:

[0129] The server combines data from the user's profile and floor plan to search a database of furniture and fixtures. Based on the entered user data, Node.js and Elasticsearch are used to find relevant products and generate an optimized list of suggestions. The search results include multiple suggestions that fit the user's needs.

[0130] Step 5:

[0131] The server collects information on the pricing and ratings of the proposed products and further optimizes the list of suggestions. Based on data gathered from multiple online sales platforms, it prepares to provide users with cost-effective options.

[0132] Step 6:

[0133] The device notifies the user of a list of suggestions and related information. The generated optimization list is displayed via push notifications and in-app screens, allowing the user to check the information in real time. This speeds up the shopping decision-making process.

[0134] Step 7:

[0135] The server verifies compatibility with existing smart home devices and provides configuration information to the user. The selected product list is used as input for the compatibility check. The results are communicated to the user, facilitating seamless integration of the new product.

[0136] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0137] This invention combines a conventional interior design proposal system with an emotion engine that recognizes the user's emotional state, providing a system that offers more personalized proposals to the user. Embodiments of the present invention will be described in detail below.

[0138] This system consists of a user terminal and a server, and operates on the cloud or a dedicated server. The terminal receives user instructions and simultaneously collects data for the emotion engine to recognize the user's emotional state.

[0139] The server first automatically retrieves floor plans from real estate information sources and analyzes them to extract data on room size and shape. This design reduces the cumbersome process for users when moving into a new home.

[0140] Next, the device displays an interface where the user can input their interior style preferences, budget, and real-time emotional state. The device uses its camera and microphone to collect the necessary data for the emotion engine and sends it to the server. This emotional state reflects how the user feels about the interior items presented.

[0141] Based on this input data, the server updates the user profile and, by adding information about past purchase history, accurately understands the user's interior style preferences and current emotional state. This allows the server to generate a list of furniture and appliances that are best suited to the user, improving the accuracy of the personalization.

[0142] The server retrieves the latest pricing information and user reviews for the proposed products from multiple online sales platforms. Based on this, it evaluates the cost-effectiveness of the products in the proposal list and optimizes the list to make it the most appropriate recommendation.

[0143] Once the suggestion list is complete, the device optimizes how information is presented based on the user's emotional state and notifies the user accordingly. For example, if the user is feeling excited or surprised, it will offer more options and new suggestions; if they are calm, it will select an interface that emphasizes detailed explanations and review points.

[0144] Furthermore, the server verifies the compatibility of smart home-compatible products in the proposed list with existing devices and provides the user with setup instructions. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0145] As a concrete example, suppose a user is looking for a bed for their new bedroom after moving. The server identifies the bedroom size from the floor plan and, if it estimates that the user is in a relaxed emotional state, suggests a bed designed to promote restful sleep. The terminal notifies the user of this and supports their selection based on price and reviews. In this way, the present invention provides a system that helps create a more personalized and comfortable living space by incorporating the user's emotions.

[0146] The following describes the processing flow.

[0147] Step 1:

[0148] The server accesses real estate information sources and automatically retrieves the latest floor plans for the specified property. The retrieved floor plans are then passed to an image analysis module within the server, where they are processed to identify the dimensions and shape of each room.

[0149] Step 2:

[0150] The device displays an interface for the user to input their interior style preferences and budget. The user enters this information, and the device makes that data available for the emotion engine. It also collects data about the user's emotional state using the camera and microphone.

[0151] Step 3:

[0152] The server updates the user profile based on user input data sent from the terminal and emotional state information generated by the emotion engine. During this process, it refines the user's style tendencies by referring to past purchase history.

[0153] Step 4:

[0154] The server uses the analyzed floor plan and updated user profile to generate a list of optimal furniture and appliance suggestions. This list is personalized, taking into account the user's current emotional state.

[0155] Step 5:

[0156] The server collects the latest pricing information and user reviews from online sales platforms for each product included in the suggestion list. This information is used to evaluate the cost-effectiveness of the suggested products and optimize the list.

[0157] Step 6:

[0158] The device displays the suggestion list in the most appropriate format according to the user's emotional state. For example, if the user shows interest, it presents a layout that provides detailed product descriptions and encourages comparison and consideration.

[0159] Step 7:

[0160] The server checks the compatibility of the smart home devices included in the suggestion list with existing devices and provides setup instructions to the user as needed. This allows the user to efficiently integrate new devices into their smart home environment.

[0161] (Example 2)

[0162] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0163] In recent years, there has been a growing demand for interior design to be optimized for each user. However, conventional systems have failed to consider the user's emotional state, making it difficult to accurately reflect individual needs. Furthermore, real-time price information, inventory monitoring, and compatibility checks with smart home devices were insufficient, resulting in inconvenience for users.

[0164] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0165] In this invention, the server includes means for automatically acquiring spatial maps and spatial data from real estate information sources, means for analyzing the acquired spatial maps to extract data on the size and shape of the area, and means for collecting the user's preferences, budget, and emotional state to generate a user profile. This makes it possible to propose interiors that reflect the user's emotional state, enabling the creation of a more personalized and comfortable living space for the user.

[0166] "Real estate information sources" refer to databases and data supply systems that provide spatial data on buildings and land, as well as floor plans and other related information.

[0167] A "spatial diagram" is a visual drawing that shows the layout of rooms or buildings, and it includes the location and dimensions of each room or space.

[0168] "Spatial data" refers to numerical information about the size, shape, and location of rooms extracted from floor plans.

[0169] A "user profile" refers to a collection of user-specific information, including individual user preferences, budget, emotional state, and past purchase history.

[0170] "Emotional state" refers to information that indicates the user's current emotions, and is analyzed based on data collected through cameras and microphones.

[0171] The "Suggestion List" refers to a list of optimal interior design products and home appliances selected based on the user's profile.

[0172] "Automated home devices" refer to smart home devices and household electronic devices that can communicate with each other.

[0173] "Compatibility" refers to the ability of different devices or systems to work together in harmony.

[0174] "Sales outlets" refer to all commercial sources of supply, including online platforms and physical stores, that sell products.

[0175] "Cost-effectiveness" refers to an indicator that evaluates the effectiveness and economic value of the results relative to the costs incurred.

[0176] This interior design proposal system consists of user terminals and servers, and operates on the cloud or a dedicated server.

[0177] First, upon activation, the user is instructed to input their interior design preferences, budget, and real-time emotional state into the device's interface. The device then uses its camera and microphone to collect data for analyzing the user's facial expressions and voice. Image recognition and voice analysis software are used for emotion analysis.

[0178] The collected data is sent to a server. The server uses an emotion engine to identify the user's emotional state and generate emotion data. This technology employs machine learning algorithms that incorporate generative AI models.

[0179] Next, the server automatically retrieves floor plans from real estate information sources and analyzes the spatial data to determine the size and shape of the rooms. CAD analysis software and similar tools are used for this analysis.

[0180] Based on the acquired emotional and spatial data, the server updates the user profile. The user profile also incorporates the user's past purchase history and style preferences, reflecting the user's needs in detail.

[0181] Using a generative AI model, the server selects the most suitable interior items based on the user's emotional state and generates a list of suggestions. Furthermore, the suggestion list is optimized using the latest price information and user reviews from multiple online sales outlets.

[0182] Once the suggestion list is complete, the device selects a method of presenting information that suits the user's emotional state and notifies the user accordingly. For example, if the user is enjoying themselves, the device will highlight a wider range of options; if the user is in a calm emotional state, it will provide more detailed information.

[0183] Examples of prompts include, "Could you recommend some interior design ideas for the living room of my new home? I'm looking for a relaxed atmosphere."

[0184] Furthermore, the server verifies the compatibility of smart home-compatible products with existing devices and provides users with setup instructions. This function is crucial for smoothly integrating smart home systems into users' lives.

[0185] For example, if a user is looking for a new living room sofa, the system will suggest the optimal size sofa based on the room dimensions and select a comfortable design that matches the user's relaxed mood. The terminal screen will display these suggestions along with price information and reviews to support the user's purchase.

[0186] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0187] Step 1:

[0188] The user activates the device and inputs their interior design preferences and budget through the interface. The device also collects data representing their emotional state using the camera and microphone. The input data includes preferences, budget, voice, and video data. Based on this, the device generates a dataset for emotion analysis.

[0189] Step 2:

[0190] The device sends the collected data to the server. The server uses an emotion engine to perform image recognition and voice analysis to determine the user's emotional state. This process outputs the user's emotional state (e.g., pleasant, calm, excited).

[0191] Step 3:

[0192] The server retrieves floor plans from real estate information sources and uses CAD analysis software to extract room size and shape data. The input is floor plan data, and the output is room dimensions and shape information as a result of the analysis.

[0193] Step 4:

[0194] The server integrates past purchase history, user preferences, budget, emotional state, and physical data of the room to update the user profile. Based on this input data, a personalized user profile is output.

[0195] Step 5:

[0196] Using a generative AI model, the server selects the most suitable interior items based on the updated user profile and creates a suggestion list. The model filters items according to the user's emotional state and outputs suitable options as a suggestion list.

[0197] Step 6:

[0198] The server collects the latest pricing information and user reviews from multiple sales locations. Using this collected information, it generates a list optimized for cost-effectiveness. In this step, pricing information and reviews are input, and an optimized list of suggestions is output.

[0199] Step 7:

[0200] After the suggestion list is complete, the device selects a method for presenting information based on the user's emotional state and notifies the user. For example, if the user is enjoying themselves, colorful options will be displayed on the interface. The method of presenting information is customized and output based on the user's emotional state.

[0201] Step 8:

[0202] The server checks the compatibility of smart home compatible products included in the suggestion list with existing devices and provides setup instructions. Device information is taken as input, and the compatibility check results and setup instructions are output. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0203] (Application Example 2)

[0204] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0205] In recent years, there has been a growing demand for personalized product suggestions that reflect consumer emotions and individual preferences. However, conventional interior design suggestion systems have struggled to adequately reflect the emotional states of individual users, making it difficult to efficiently provide personalized suggestions. Therefore, a method is needed to help users make quick and satisfying purchasing decisions.

[0206] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0207] This invention includes a server that analyzes the user's emotional state using emotion recognition technology, selects the most suitable interior decorations and electrical appliances along with the profile, and generates suggestion data; a server that collects price information and product evaluations from multiple e-commerce platforms and optimizes the suggestion data; and a server that checks the compatibility of potential purchase products with existing information appliance technologies and suggests settings. This enables more personalized interior suggestions that are tailored to the user's emotional state.

[0208] "Spatial arrangement" refers to the layout of a living space obtained from real estate information sources.

[0209] "Spatial data" refers to information about the size and shape of living spaces based on acquired spatial arrangements.

[0210] A "user profile" is a dataset formed based on a user's preferences and budget.

[0211] "Emotion recognition technology" is a technology that analyzes a user's emotional state and provides personalized suggestions.

[0212] "Interior decorations" are items used to enhance the aesthetics and functionality of a room.

[0213] "Electrical products" include various products that utilize electricity used in the home.

[0214] "Suggestion data" is a list of optimal product suggestions generated based on the user's profile and emotional state.

[0215] An "e-commerce platform" is a digital platform where goods are bought and sold online.

[0216] "Information appliance technology" refers to smart device technology used in the home.

[0217] The system implementing this invention mainly consists of a server and terminals. The server automatically acquires spatial layout and spatial data from online databases and real estate information sources, analyzes this data to extract information about the size and shape of living spaces. In doing so, the server uses data analysis software to efficiently process the acquired information.

[0218] The terminal is equipped with an interface for receiving user input. Here, information about the user's preferences and budget is collected, and a user profile is formed based on this information. Furthermore, the terminal uses emotion recognition technology to analyze the user's emotional state in real time and transmit it to the server. For this purpose, the terminal is equipped with hardware for emotion analysis (e.g., a camera and microphone).

[0219] The server selects the most suitable interior decorations and electrical appliances based on the user's emotional state and profile, and generates suggestion data. In this process, the server utilizes a generative AI model and provides prompts to make the most appropriate suggestions to the user. It collects the latest pricing information and product reviews from multiple e-commerce platforms to optimize the suggestion data. Finally, this optimized suggestion data is communicated to the user via their device.

[0220] Furthermore, the server verifies the compatibility of potential purchase products with existing consumer electronics technologies and provides users with setup instructions. For this purpose, the server utilizes dedicated software for compatibility verification and organizes and provides the necessary setup information.

[0221] As a concrete example, if the device is worn by the user as smart glasses, when the user browses products in a store, their emotional state is recognized in real time, and personalized product suggestions generated by the server are instantly visualized. In this way, the user can instantly obtain the information they need, thereby increasing their desire to purchase.

[0222] An example of a prompt would be: "If the customer is feeling relaxed, please list the product features necessary to suggest interior items that evoke a sense of calm."

[0223] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0224] Step 1:

[0225] The terminal provides an interface to receive preference and budget information from the user. Based on this input information, it generates a user profile. In doing so, the terminal uses profile generation software to save the information to a database.

[0226] Step 2:

[0227] When a user browses interior design products through their device, the device collects emotional data from the user via its built-in camera and microphone. An emotion recognition engine analyzes this data to identify the user's emotional state (e.g., relaxed, excited, surprised). This information is transmitted to the server in real time.

[0228] Step 3:

[0229] The server provides optimal product recommendations based on the emotional state and user profile transmitted from the terminal. Here, a generative AI model is used to apply prompt sentences to identify interior decorations and electrical appliances that suit the user and create recommendation data.

[0230] Step 4:

[0231] The server accesses multiple e-commerce platforms to collect the latest pricing information and product reviews for selected items. This information is used to optimize suggestion data and provide users with the most valuable choices.

[0232] Step 5:

[0233] The generated suggestion data is sent to the device, allowing the user to view it in real time. The device adjusts the UI according to the user's emotions, visually displaying the necessary information. For example, if the user is in a relaxed emotional state, it might increase the details of products that promote restful sleep.

[0234] Step 6:

[0235] The server checks the compatibility of potential purchase items with existing consumer electronics technologies and provides setup instructions to the terminal so that users can easily set them up. Compatibility check software is used to deliver this information to the user.

[0236] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0237] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0238] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0239] [Second Embodiment]

[0240] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0241] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0242] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0243] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0244] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0245] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0246] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0247] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0248] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0249] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0250] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0251] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0252] This invention provides a system that automatically obtains floor plans from real estate information sources, identifies the size and shape of rooms through analysis, and proposes optimal furniture and home appliances according to the user's needs. Embodiments of this invention are described below.

[0253] This system includes user terminals and server components that operate on the cloud or on dedicated servers. The terminals receive user instructions and transmit them to the server, which then processes the information and generates a list of suggestions.

[0254] The server accesses real estate information sources and retrieves the latest floor plans for specified properties from the database. This process also includes processing URLs of properties provided by the user, as well as floor plans in electronic file format. The retrieved floor plans are processed by an advanced image analysis module on the server, extracting dimension and shape data for each room. This design eliminates the need for users to manually measure the dimensions.

[0255] Next, the device displays an interface for the user to input their preferred interior style and budget, which is then collected manually or via voice input. This data is sent to the server and registered as part of the user profile. In addition, the server also refers to past purchase history data to analyze the user's style trends, and this is also reflected in the profile.

[0256] Next, the server searches a database of furniture and appliances based on the acquired floor plan and user profile, and creates a list of suggestions that are best suited to the specific room. This list includes products that match the user's preferences and are purchasable within their budget.

[0257] Simultaneously, the server collects pricing information and product reviews from multiple online sales platforms. This allows it to evaluate the cost-effectiveness of each product being offered and present users with reasonably priced and reputable options.

[0258] The device notifies the user and presents a list of suggestions and their details. This list includes price, reviews, and stock information, and is designed to allow the user to make an immediate purchase.

[0259] Furthermore, the server checks the compatibility of the selected products with smart home devices and, if possible, suggests setup methods to the user. This allows users to easily integrate new products into their existing home network.

[0260] As a concrete example, suppose a user is looking for a sofa for their living room when moving into a new home. The server identifies the dimensions of the living room from the floor plan and suggests several suitable sofas based on the user's modern interior style preferences and budget. The terminal presents these to the user and supports their selection based on price and reviews. At this time, if one of the suggested sofas is smart home compatible, information on setting it up is also presented.

[0261] Thus, the system of the present invention provides a technology that significantly reduces the various hassles that users face when choosing a residence, and enables them to efficiently and safely arrange their living space.

[0262] The following describes the processing flow.

[0263] Step 1:

[0264] The server accesses real estate information sources to automatically retrieve floor plans for properties. URLs and PDF files of floor plans provided by users are also included in this process, and the server downloads and begins processing them.

[0265] Step 2:

[0266] The server passes the acquired floor plan to an image analysis module to identify the shape and dimensions of each room. This information is stored in a database as detailed data for each room and used in subsequent suggestion processing.

[0267] Step 3:

[0268] The user inputs their interior design preferences and budget through an interface displayed on the device. The device receives this information and sends it to a server, incorporating it into the process of generating a user profile.

[0269] Step 4:

[0270] Based on the received user profile, the server retrieves past purchase history from the database and analyzes the user's style tendencies. This information is integrated into the profile and used to create suggestion lists.

[0271] Step 5:

[0272] The server searches a database of furniture and home appliances based on the analyzed floor plan data and user profile, and generates a list of recommended items for each room. This list includes products that match the user's preferences and budget.

[0273] Step 6:

[0274] The server collects pricing information and product reviews for products proposed from multiple online sales platforms. Based on this information, it evaluates cost-effectiveness and optimizes the recommendations to make the most beneficial choice for the user.

[0275] Step 7:

[0276] The terminal notifies the user of the completed list of suggestions and displays detailed information about the list. This information includes the price of the suggested furniture and appliances, user reviews, and inventory information, allowing the user to consider purchasing based on this information.

[0277] Step 8:

[0278] The server checks the compatibility of the smart home-compatible products included in the suggestion list with the user's current smart home devices and suggests setup methods. This allows the user to smoothly integrate newly purchased products into their existing environment.

[0279] (Example 1)

[0280] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0281] Modern consumers are required to make efficient and accurate selections that suit their needs from a variety of housing information and household appliance information. However, in the conventional method, it takes a lot of time and effort to manually check the space and layout of a property and select a suitable product. Furthermore, considering appropriate cost performance and product compatibility requires individually searching for information, which is very cumbersome. The present invention aims to solve these problems.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0283] In this invention, the server includes means for automatically acquiring space design information from a real estate information source, means for analyzing the acquired space design information and extracting information on the dimensions and shapes of compartments, and means for acquiring the preferences and budget of the user and generating a user profile. As a result, the user can easily and quickly find the optimal product for their space, and furthermore, it becomes possible to support making a purchase decision in real time considering cost-effectiveness and product compatibility.

[0284] The "real estate information source" refers to an information providing medium that provides space design information and floor plans related to real estate.

[0285] The "space design information" refers to data including detailed information such as the dimensions, shapes, and layouts of each room and compartment of a property.

[0286] The "user profile" refers to information that summarizes information such as the user's preferences, budget, and past purchase history, and serves as a basis for making optimal proposals for individual users.

[0287] The "proposal list" refers to a list of products and services that meet the user's conditions and are judged to be optimal.

[0288] A "supply platform" refers to an online business infrastructure that provides products and services.

[0289] "Automated home appliances" refer to household electrical appliances that can communicate and be controlled using the internet.

[0290] "Image analysis technology" refers to the technology of processing digital image data and extracting specific information.

[0291] "Communication operation" refers to an operation for sending and receiving information, and is a means that enables users to purchase products directly through an interface.

[0292] "Cost-effectiveness" refers to a criterion for evaluating the balance between the performance and quality of a potential purchase product and its price.

[0293] This invention is a system that automatically acquires spatial design information from real estate information sources, identifies the dimensions and shape of a plot through analysis, and proposes the optimal product according to the user's needs. This system consists of a server component that operates in a cloud environment or a dedicated server environment, and a terminal that handles the user interface.

[0294] The server accesses real estate information sources and retrieves spatial design information. This process includes URLs and PDF digital data provided by users. The retrieved information is analyzed by an image analysis module on the server, extracting dimension and shape data for each plot. The OpenCV library is primarily used for image analysis.

[0295] Next, the device provides an interface for the user to input their preferred style and budget. The user enters their preferences using a keyboard or voice input, and this data is sent to the server via a secure protocol. The server registers this as part of the user profile and also analyzes past purchase history to reflect the user's style tendencies.

[0296] Subsequently, the server searches the product information database based on the analyzed design information and user profile, and generates a list of suggestions. This list includes products that match the user's preferences and are purchasable within their budget. The server also collects pricing information and product reviews from multiple supply platforms and evaluates the cost-effectiveness of each suggested product.

[0297] The suggested list is notified to the user via the terminal and includes product details, prices, reviews, and stock information. The user can compare products on the screen and consider purchasing the selected products. If there are potential purchases, the server checks the compatibility of the products with the automated home appliances and provides appropriate setup instructions.

[0298] As a concrete example, if the prompt "Please suggest modern style furniture suitable for a new 3LDK apartment" is entered into the generation AI model, the system will extract the dimensions of each room from the floor plan, suggest furniture that fits the budget and style, and present the most suitable products to the user.

[0299] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0300] Step 1:

[0301] The server accesses real estate information sources and automatically retrieves spatial design information. This input consists of URLs of properties and floor plans in electronic file format provided by the user, and the data is collected using the HTTP protocol. After data extraction, the retrieved design information is stored on the server in digital format. Specifically, the process involves extracting information using web page scraping techniques and saving it to a database.

[0302] Step 2:

[0303] The server inputs the acquired space design information into the image analysis module and extracts the dimension and shape data of each section. In this analysis, the OpenCV library is utilized to process the digital image data, detect the outline of the room, and measure its size. As output, dimension data regarding each area of the floor plan is obtained and rearranged into the configuration information.

[0304] Step 3:

[0305] The terminal displays an interface for the user to input the interior style and budget. The user inputs a specific style or price range, etc. via the keyboard or voice, and the terminal sends this to the server. The specific operation here is to pass the input data to the server using the secure HTTPS communication protocol.

[0306] Step 4:

[0307] The server receives the user input and generates a user profile. Subsequently, it retrieves the past purchase history from the database and analyzes the trend of the interior style. In this process, SQL queries are utilized to aggregate relevant data and understand the user's preferences. After profile generation, information based on the user's conditions is included in the profile.

[0308] Step 5:

[0309] The server uses the acquired dimension data and the user profile to search the product information database. The database uses NoSQL technology and is capable of efficiently searching a large amount of information. Based on the search results, a list of proposals is generated, listing products that match the user's preferences and budget. This output consists of the product name, price, and content suitable for the purpose of use.

[0310] Step 6:

[0311] The server collects pricing information and product reviews from multiple supply platforms for each product in the suggested list. Access to these platforms is via API, and data is retrieved in JSON format. Based on the collected data, cost-effectiveness is evaluated and the list is optimized. The evaluated list is output as a more accurate list of recommended products.

[0312] Step 7:

[0313] The terminal receives a list of suggestions and related information from the server and presents it to the user. The screen displays product details, prices, reviews, and stock availability, making it easier for the user to visually compare products. Specifically, the user selects a product through screen navigation and can access the purchase page immediately.

[0314] Step 8:

[0315] The server checks the compatibility of selected purchase candidates with existing automated home appliances and suggests setup methods. This process queries a database of specifications for each product and collects network configuration information. The resulting setup guide helps users quickly and smoothly connect new products to their home network.

[0316] (Application Example 1)

[0317] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0318] In the traditional furniture and appliance purchasing process, users had to manually select the optimal product from a vast number of options, ensuring consistency with their budget and style. This resulted in a time-consuming and laborious process, making it difficult to achieve their ideal living space. Furthermore, verifying the functionality of purchased products with smart home systems proved challenging, creating technical issues within existing living environments.

[0319] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0320] This invention includes a server that automatically acquires spatial data from real estate information sources, analyzes floor plans to extract dimensions and structural data of parts, collects user preferences and financial information to generate a user profile, and searches a database of furniture and fixtures based on the user profile to generate a list of optimal product suggestions. This makes it possible for users to efficiently select the best products that match their budget and preferences without any hassle, thereby improving their living environment.

[0321] A "real estate information source" refers to a database or platform that provides information about buildings and houses.

[0322] "Spatial data" refers to data that includes information about the layout of a building, the dimensions of rooms, and its structure.

[0323] A "user profile" refers to a dataset that aggregates personalized information, including a user's preferences and financial situation.

[0324] A "database of furniture and appliances" refers to a data structure that stores information about furniture and electrical appliances that consumers can purchase.

[0325] A "product suggestion list" refers to a set of information generated to provide a list of optimized products based on the user's needs.

[0326] An "online sales platform" refers to a platform or system for buying and selling products over the internet.

[0327] A "smart device" refers to a portable device that can connect to the internet and obtain and transmit information.

[0328] A "prompt message" refers to a short sentence containing instructions or suggestions to support the user's choices.

[0329] This invention provides an integrated system for users to efficiently select furniture and appliances. The main components of the system are a server and a terminal. The following describes an embodiment of the system that implements this application example.

[0330] The server uses a cloud-based storage system as the hardware and software used to acquire spatial data from real estate information sources. Cloud storage such as AWS S3 is utilized, and real estate information is acquired via APIs. For analysis, AWS Rekognition and Google Cloud Vision API are used as image analysis technologies to identify the dimensions and structure of floor plans. AWS DynamoDB and Firebase Firestore are used for database management.

[0331] On the device side, an interface is provided for users to input their preferences and financial information. A cross-platform application will be developed using Flutter or React Native. Through this interface, user information will be collected and synchronized with the server.

[0332] Based on this information, the server searches a database of furniture and fixtures to generate a list of optimal product suggestions. The search utilizes a Node.js backend and an efficient search system powered by Elasticsearch. The suggestion list is generated along with price and reputation information and is updated in real time.

[0333] The device also notifies the user of a list of suggestions and related information. Using the smartphone's push notification function, users can immediately proceed with the purchase. An example of a prompt message is: "We analyze the latest floor plans and suggest the perfect modern furniture for your living room. Find options that fit your budget and preferences!" This prompt message is generated using an AI model to assist the user in their selection.

[0334] Finally, the server verifies the product's compatibility with existing smart devices and provides the user with the necessary configuration information. This feature allows users to seamlessly integrate the purchased product into their existing systems.

[0335] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0336] Step 1:

[0337] The server retrieves spatial data of floor plans from real estate information sources. Property identification information is used as input, and the server accesses the real estate information sources via an API. The data is stored in cloud storage such as AWS S3 and handled in a secure environment.

[0338] Step 2:

[0339] The server analyzes the acquired floor plans. Using the acquired image data as input, it extracts room dimensions and shape data using AWS Rekognition or Google Cloud Vision API. This processing automates dimension measurements that were previously done manually, enabling rapid data provision.

[0340] Step 3:

[0341] Users input their preferences and financial information through their device. The input screen includes fields for interior style and budget, and this information is collected and sent to the server as a digital profile. This creates an individualized dataset.

[0342] Step 4:

[0343] The server combines data from the user's profile and floor plan to search a database of furniture and fixtures. Based on the entered user data, Node.js and Elasticsearch are used to find relevant products and generate an optimized list of suggestions. The search results include multiple suggestions that fit the user's needs.

[0344] Step 5:

[0345] The server collects information on the pricing and ratings of the proposed products and further optimizes the list of suggestions. Based on data gathered from multiple online sales platforms, it prepares to provide users with cost-effective options.

[0346] Step 6:

[0347] The device notifies the user of a list of suggestions and related information. The generated optimization list is displayed via push notifications and in-app screens, allowing the user to check the information in real time. This speeds up the shopping decision-making process.

[0348] Step 7:

[0349] The server verifies compatibility with existing smart home devices and provides configuration information to the user. The selected product list is used as input for the compatibility check. The results are communicated to the user, facilitating seamless integration of the new product.

[0350] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0351] This invention combines a conventional interior design proposal system with an emotion engine that recognizes the user's emotional state, providing a system that offers more personalized proposals to the user. Embodiments of the present invention will be described in detail below.

[0352] This system consists of a user terminal and a server, and operates on the cloud or a dedicated server. The terminal receives user instructions and simultaneously collects data for the emotion engine to recognize the user's emotional state.

[0353] The server first automatically retrieves floor plans from real estate information sources and analyzes them to extract data on room size and shape. This design reduces the cumbersome process for users when moving into a new home.

[0354] Next, the device displays an interface where the user can input their interior style preferences, budget, and real-time emotional state. The device uses its camera and microphone to collect the necessary data for the emotion engine and sends it to the server. This emotional state reflects how the user feels about the interior items presented.

[0355] Based on this input data, the server updates the user profile and, by adding information about past purchase history, accurately understands the user's interior style preferences and current emotional state. This allows the server to generate a list of furniture and appliances that are best suited to the user, improving the accuracy of the personalization.

[0356] The server retrieves the latest pricing information and user reviews for the proposed products from multiple online sales platforms. Based on this, it evaluates the cost-effectiveness of the products in the proposal list and optimizes the list to make it the most appropriate recommendation.

[0357] Once the suggestion list is complete, the device optimizes how information is presented based on the user's emotional state and notifies the user accordingly. For example, if the user is feeling excited or surprised, it will offer more options and new suggestions; if they are calm, it will select an interface that emphasizes detailed explanations and review points.

[0358] Furthermore, the server verifies the compatibility of smart home-compatible products in the proposed list with existing devices and provides the user with setup instructions. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0359] As a concrete example, suppose a user is looking for a bed for their new bedroom after moving. The server identifies the bedroom size from the floor plan and, if it estimates that the user is in a relaxed emotional state, suggests a bed designed to promote restful sleep. The terminal notifies the user of this and supports their selection based on price and reviews. In this way, the present invention provides a system that helps create a more personalized and comfortable living space by incorporating the user's emotions.

[0360] The following describes the processing flow.

[0361] Step 1:

[0362] The server accesses real estate information sources and automatically retrieves the latest floor plans for the specified property. The retrieved floor plans are then passed to an image analysis module within the server, where they are processed to identify the dimensions and shape of each room.

[0363] Step 2:

[0364] The device displays an interface for the user to input their interior style preferences and budget. The user enters this information, and the device makes that data available for the emotion engine. It also collects data about the user's emotional state using the camera and microphone.

[0365] Step 3:

[0366] The server updates the user profile based on user input data sent from the terminal and emotional state information generated by the emotion engine. During this process, it refines the user's style tendencies by referring to past purchase history.

[0367] Step 4:

[0368] The server uses the analyzed floor plan and updated user profile to generate a list of optimal furniture and appliance suggestions. This list is personalized, taking into account the user's current emotional state.

[0369] Step 5:

[0370] The server collects the latest pricing information and user reviews from online sales platforms for each product included in the suggestion list. This information is used to evaluate the cost-effectiveness of the suggested products and optimize the list.

[0371] Step 6:

[0372] The device displays the suggestion list in the most appropriate format according to the user's emotional state. For example, if the user shows interest, it presents a layout that provides detailed product descriptions and encourages comparison and consideration.

[0373] Step 7:

[0374] The server checks the compatibility of the smart home devices included in the suggestion list with existing devices and provides setup instructions to the user as needed. This allows the user to efficiently integrate new devices into their smart home environment.

[0375] (Example 2)

[0376] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0377] In recent years, there has been a growing demand for interior design to be optimized for each user. However, conventional systems have failed to consider the user's emotional state, making it difficult to accurately reflect individual needs. Furthermore, real-time price information, inventory monitoring, and compatibility checks with smart home devices were insufficient, resulting in inconvenience for users.

[0378] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0379] In this invention, the server includes means for automatically acquiring spatial maps and spatial data from real estate information sources, means for analyzing the acquired spatial maps to extract data on the size and shape of the area, and means for collecting the user's preferences, budget, and emotional state to generate a user profile. This makes it possible to propose interiors that reflect the user's emotional state, enabling the creation of a more personalized and comfortable living space for the user.

[0380] "Real estate information sources" refer to databases and data supply systems that provide spatial data on buildings and land, as well as floor plans and other related information.

[0381] A "spatial diagram" is a visual drawing that shows the layout of rooms or buildings, and it includes the location and dimensions of each room or space.

[0382] "Spatial data" refers to numerical information about the size, shape, and location of rooms extracted from floor plans.

[0383] A "user profile" refers to a collection of user-specific information, including individual user preferences, budget, emotional state, and past purchase history.

[0384] "Emotional state" refers to information that indicates the user's current emotions, and is analyzed based on data collected through cameras and microphones.

[0385] The "Suggestion List" refers to a list of optimal interior design products and home appliances selected based on the user's profile.

[0386] "Automated home devices" refer to smart home devices and household electronic devices that can communicate with each other.

[0387] "Compatibility" refers to the ability of different devices or systems to work together in harmony.

[0388] "Sales outlets" refer to all commercial sources of supply, including online platforms and physical stores, that sell products.

[0389] "Cost-effectiveness" refers to an indicator that evaluates the effectiveness and economic value of the results relative to the costs incurred.

[0390] This interior design proposal system consists of user terminals and servers, and operates on the cloud or a dedicated server.

[0391] First, upon activation, the user is instructed to input their interior design preferences, budget, and real-time emotional state into the device's interface. The device then uses its camera and microphone to collect data for analyzing the user's facial expressions and voice. Image recognition and voice analysis software are used for emotion analysis.

[0392] The collected data is sent to a server. The server uses an emotion engine to identify the user's emotional state and generate emotion data. This technology employs machine learning algorithms that incorporate generative AI models.

[0393] Next, the server automatically retrieves floor plans from real estate information sources and analyzes the spatial data to determine the size and shape of the rooms. CAD analysis software and similar tools are used for this analysis.

[0394] Based on the acquired emotional and spatial data, the server updates the user profile. The user profile also incorporates the user's past purchase history and style preferences, reflecting the user's needs in detail.

[0395] Using a generative AI model, the server selects the most suitable interior items based on the user's emotional state and generates a list of suggestions. Furthermore, the suggestion list is optimized using the latest price information and user reviews from multiple online sales outlets.

[0396] Once the suggestion list is complete, the device selects a method of presenting information that suits the user's emotional state and notifies the user accordingly. For example, if the user is enjoying themselves, the device will highlight a wider range of options; if the user is in a calm emotional state, it will provide more detailed information.

[0397] Examples of prompts include, "Could you recommend some interior design ideas for the living room of my new home? I'm looking for a relaxed atmosphere."

[0398] Furthermore, the server verifies the compatibility of smart home-compatible products with existing devices and provides users with setup instructions. This function is crucial for smoothly integrating smart home systems into users' lives.

[0399] For example, if a user is looking for a new living room sofa, the system will suggest the optimal size sofa based on the room dimensions and select a comfortable design that matches the user's relaxed mood. The terminal screen will display these suggestions along with price information and reviews to support the user's purchase.

[0400] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0401] Step 1:

[0402] The user activates the device and inputs their interior design preferences and budget through the interface. The device also collects data representing their emotional state using the camera and microphone. The input data includes preferences, budget, voice, and video data. Based on this, the device generates a dataset for emotion analysis.

[0403] Step 2:

[0404] The device sends the collected data to the server. The server uses an emotion engine to perform image recognition and voice analysis to determine the user's emotional state. This process outputs the user's emotional state (e.g., pleasant, calm, excited).

[0405] Step 3:

[0406] The server retrieves floor plans from real estate information sources and uses CAD analysis software to extract room size and shape data. The input is floor plan data, and the output is room dimensions and shape information as a result of the analysis.

[0407] Step 4:

[0408] The server integrates past purchase history, user preferences, budget, emotional state, and physical data of the room to update the user profile. Based on this input data, a personalized user profile is output.

[0409] Step 5:

[0410] Using a generative AI model, the server selects the most suitable interior items based on the updated user profile and creates a suggestion list. The model filters items according to the user's emotional state and outputs suitable options as a suggestion list.

[0411] Step 6:

[0412] The server collects the latest pricing information and user reviews from multiple sales locations. Using this collected information, it generates a list optimized for cost-effectiveness. In this step, pricing information and reviews are input, and an optimized list of suggestions is output.

[0413] Step 7:

[0414] After the suggestion list is complete, the device selects a method for presenting information based on the user's emotional state and notifies the user. For example, if the user is enjoying themselves, colorful options will be displayed on the interface. The method of presenting information is customized and output based on the user's emotional state.

[0415] Step 8:

[0416] The server checks the compatibility of smart home compatible products included in the suggestion list with existing devices and provides setup instructions. Device information is taken as input, and the compatibility check results and setup instructions are output. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0417] (Application Example 2)

[0418] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0419] In recent years, there has been a growing demand for personalized product suggestions that reflect consumer emotions and individual preferences. However, conventional interior design suggestion systems have struggled to adequately reflect the emotional states of individual users, making it difficult to efficiently provide personalized suggestions. Therefore, a method is needed to help users make quick and satisfying purchasing decisions.

[0420] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0421] This invention includes a server that analyzes the user's emotional state using emotion recognition technology, selects the most suitable interior decorations and electrical appliances along with the profile, and generates suggestion data; a server that collects price information and product evaluations from multiple e-commerce platforms and optimizes the suggestion data; and a server that checks the compatibility of potential purchase products with existing information appliance technologies and suggests settings. This enables more personalized interior suggestions that are tailored to the user's emotional state.

[0422] "Spatial arrangement" refers to the layout of a living space obtained from real estate information sources.

[0423] "Spatial data" refers to information about the size and shape of living spaces based on acquired spatial arrangements.

[0424] A "user profile" is a dataset formed based on a user's preferences and budget.

[0425] "Emotion recognition technology" is a technology that analyzes a user's emotional state and provides personalized suggestions.

[0426] "Interior decorations" are items used to enhance the aesthetics and functionality of a room.

[0427] "Electrical products" include various products that utilize electricity used in the home.

[0428] "Suggestion data" is a list of optimal product suggestions generated based on the user's profile and emotional state.

[0429] An "e-commerce platform" is a digital platform where goods are bought and sold online.

[0430] "Information appliance technology" refers to smart device technology used in the home.

[0431] The system implementing this invention mainly consists of a server and terminals. The server automatically acquires spatial layout and spatial data from online databases and real estate information sources, analyzes this data to extract information about the size and shape of living spaces. In doing so, the server uses data analysis software to efficiently process the acquired information.

[0432] The terminal is equipped with an interface for receiving user input. Here, information about the user's preferences and budget is collected, and a user profile is formed based on this information. Furthermore, the terminal uses emotion recognition technology to analyze the user's emotional state in real time and transmit it to the server. For this purpose, the terminal is equipped with hardware for emotion analysis (e.g., a camera and microphone).

[0433] The server selects the most suitable interior decorations and electrical appliances based on the user's emotional state and profile, and generates suggestion data. In this process, the server utilizes a generative AI model and provides prompts to make the most appropriate suggestions to the user. It collects the latest pricing information and product reviews from multiple e-commerce platforms to optimize the suggestion data. Finally, this optimized suggestion data is communicated to the user via their device.

[0434] Furthermore, the server verifies the compatibility of potential purchase products with existing consumer electronics technologies and provides users with setup instructions. For this purpose, the server utilizes dedicated software for compatibility verification and organizes and provides the necessary setup information.

[0435] As a concrete example, if the device is worn by the user as smart glasses, when the user browses products in a store, their emotional state is recognized in real time, and personalized product suggestions generated by the server are instantly visualized. In this way, the user can instantly obtain the information they need, thereby increasing their desire to purchase.

[0436] An example of a prompt would be: "If the customer is feeling relaxed, please list the product features necessary to suggest interior items that evoke a sense of calm."

[0437] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0438] Step 1:

[0439] The terminal provides an interface to receive preference and budget information from the user. Based on this input information, it generates a user profile. In doing so, the terminal uses profile generation software to save the information to a database.

[0440] Step 2:

[0441] When a user browses interior design products through their device, the device collects emotional data from the user via its built-in camera and microphone. An emotion recognition engine analyzes this data to identify the user's emotional state (e.g., relaxed, excited, surprised). This information is transmitted to the server in real time.

[0442] Step 3:

[0443] The server provides optimal product recommendations based on the emotional state and user profile transmitted from the terminal. Here, a generative AI model is used to apply prompt sentences to identify interior decorations and electrical appliances that suit the user and create recommendation data.

[0444] Step 4:

[0445] The server accesses multiple e-commerce platforms to collect the latest pricing information and product reviews for selected items. This information is used to optimize suggestion data and provide users with the most valuable choices.

[0446] Step 5:

[0447] The generated suggestion data is sent to the device, allowing the user to view it in real time. The device adjusts the UI according to the user's emotions, visually displaying the necessary information. For example, if the user is in a relaxed emotional state, it might increase the details of products that promote restful sleep.

[0448] Step 6:

[0449] The server checks the compatibility of potential purchase items with existing consumer electronics technologies and provides setup instructions to the terminal so that users can easily set them up. Compatibility check software is used to deliver this information to the user.

[0450] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0451] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0452] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0453] [Third Embodiment]

[0454] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0455] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0456] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0457] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0458] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0459] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0460] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0461] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0462] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0463] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0464] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0465] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0466] This invention provides a system that automatically obtains floor plans from real estate information sources, identifies the size and shape of rooms through analysis, and proposes optimal furniture and home appliances according to the user's needs. Embodiments of this invention are described below.

[0467] This system includes user terminals and server components that operate on the cloud or on dedicated servers. The terminals receive user instructions and transmit them to the server, which then processes the information and generates a list of suggestions.

[0468] The server accesses real estate information sources and retrieves the latest floor plans for specified properties from the database. This process also includes processing URLs of properties provided by the user, as well as floor plans in electronic file format. The retrieved floor plans are processed by an advanced image analysis module on the server, extracting dimension and shape data for each room. This design eliminates the need for users to manually measure the dimensions.

[0469] Next, the device displays an interface for the user to input their preferred interior style and budget, which is then collected manually or via voice input. This data is sent to the server and registered as part of the user profile. In addition, the server also refers to past purchase history data to analyze the user's style trends, and this is also reflected in the profile.

[0470] Next, the server searches a database of furniture and appliances based on the acquired floor plan and user profile, and creates a list of suggestions that are best suited to the specific room. This list includes products that match the user's preferences and are purchasable within their budget.

[0471] Simultaneously, the server collects pricing information and product reviews from multiple online sales platforms. This allows it to evaluate the cost-effectiveness of each product being offered and present users with reasonably priced and reputable options.

[0472] The device notifies the user and presents a list of suggestions and their details. This list includes price, reviews, and stock information, and is designed to allow the user to make an immediate purchase.

[0473] Furthermore, the server checks the compatibility of the selected products with smart home devices and, if possible, suggests setup methods to the user. This allows users to easily integrate new products into their existing home network.

[0474] As a concrete example, suppose a user is looking for a sofa for their living room when moving into a new home. The server identifies the dimensions of the living room from the floor plan and suggests several suitable sofas based on the user's modern interior style preferences and budget. The terminal presents these to the user and supports their selection based on price and reviews. At this time, if one of the suggested sofas is smart home compatible, information on setting it up is also presented.

[0475] Thus, the system of the present invention provides a technology that significantly reduces the various hassles that users face when choosing a residence, and enables them to efficiently and safely arrange their living space.

[0476] The following describes the processing flow.

[0477] Step 1:

[0478] The server accesses real estate information sources to automatically retrieve floor plans for properties. URLs and PDF files of floor plans provided by users are also included in this process, and the server downloads and begins processing them.

[0479] Step 2:

[0480] The server passes the acquired floor plan to an image analysis module to identify the shape and dimensions of each room. This information is stored in a database as detailed data for each room and used in subsequent suggestion processing.

[0481] Step 3:

[0482] The user inputs their interior design preferences and budget through an interface displayed on the device. The device receives this information and sends it to a server, incorporating it into the process of generating a user profile.

[0483] Step 4:

[0484] Based on the received user profile, the server retrieves past purchase history from the database and analyzes the user's style tendencies. This information is integrated into the profile and used to create suggestion lists.

[0485] Step 5:

[0486] The server searches a database of furniture and home appliances based on the analyzed floor plan data and user profile, and generates a list of recommended items for each room. This list includes products that match the user's preferences and budget.

[0487] Step 6:

[0488] The server collects pricing information and product reviews for products proposed from multiple online sales platforms. Based on this information, it evaluates cost-effectiveness and optimizes the recommendations to make the most beneficial choice for the user.

[0489] Step 7:

[0490] The terminal notifies the user of the completed list of suggestions and displays detailed information about the list. This information includes the price of the suggested furniture and appliances, user reviews, and inventory information, allowing the user to consider purchasing based on this information.

[0491] Step 8:

[0492] The server checks the compatibility of the smart home-compatible products included in the suggestion list with the user's current smart home devices and suggests setup methods. This allows the user to smoothly integrate newly purchased products into their existing environment.

[0493] (Example 1)

[0494] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0495] Modern consumers are required to efficiently and accurately select products that meet their needs from a diverse range of housing and home appliance information. However, conventional methods involve manually checking the space and layout of a property and the process of selecting suitable products, which is time-consuming and laborious. Furthermore, considering appropriate cost-effectiveness and product compatibility requires searching for information individually, which is extremely cumbersome. This invention aims to solve these problems.

[0496] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0497] In this invention, the server includes means for automatically acquiring spatial design information from real estate information sources, means for analyzing the acquired spatial design information and extracting information on the dimensions and shape of the plots, and means for acquiring the user's preferences and budget and generating a user profile. This enables users to easily and quickly find the product best suited to their space, and further supports them in making real-time purchasing decisions that take into account cost-effectiveness and product compatibility.

[0498] "Real estate information sources" refer to information providers that offer spatial design information and floor plans related to real estate.

[0499] "Spatial design information" refers to data that includes detailed information such as the dimensions, shape, and layout of each room or section of a property.

[0500] A "user profile" refers to a compilation of information such as a user's preferences, budget, and past purchase history, which serves as the foundation for providing optimal suggestions to individual users.

[0501] A "list of proposals" refers to a list of products and services that meet the user's requirements and are deemed optimal.

[0502] A "supply platform" refers to an online business infrastructure that provides products and services.

[0503] "Automated home appliances" refer to household electrical appliances that can communicate and be controlled using the internet.

[0504] "Image analysis technology" refers to the technology of processing digital image data and extracting specific information.

[0505] "Communication operation" refers to an operation for sending and receiving information, and is a means that enables users to purchase products directly through an interface.

[0506] "Cost-effectiveness" refers to a criterion for evaluating the balance between the performance and quality of a potential purchase product and its price.

[0507] This invention is a system that automatically acquires spatial design information from real estate information sources, identifies the dimensions and shape of a plot through analysis, and proposes the optimal product according to the user's needs. This system consists of a server component that operates in a cloud environment or a dedicated server environment, and a terminal that handles the user interface.

[0508] The server accesses real estate information sources and retrieves spatial design information. This process includes URLs and PDF digital data provided by users. The retrieved information is analyzed by an image analysis module on the server, extracting dimension and shape data for each plot. The OpenCV library is primarily used for image analysis.

[0509] Next, the device provides an interface for the user to input their preferred style and budget. The user enters their preferences using a keyboard or voice input, and this data is sent to the server via a secure protocol. The server registers this as part of the user profile and also analyzes past purchase history to reflect the user's style tendencies.

[0510] Subsequently, the server searches the product information database based on the analyzed design information and user profile, and generates a list of suggestions. This list includes products that match the user's preferences and are purchasable within their budget. The server also collects pricing information and product reviews from multiple supply platforms and evaluates the cost-effectiveness of each suggested product.

[0511] The suggested list is notified to the user via the terminal and includes product details, prices, reviews, and stock information. The user can compare products on the screen and consider purchasing the selected products. If there are potential purchases, the server checks the compatibility of the products with the automated home appliances and provides appropriate setup instructions.

[0512] As a concrete example, if the prompt "Please suggest modern style furniture suitable for a new 3LDK apartment" is entered into the generation AI model, the system will extract the dimensions of each room from the floor plan, suggest furniture that fits the budget and style, and present the most suitable products to the user.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] The server accesses real estate information sources and automatically retrieves spatial design information. This input consists of URLs of properties and floor plans in electronic file format provided by the user, and the data is collected using the HTTP protocol. After data extraction, the retrieved design information is stored on the server in digital format. Specifically, the process involves extracting information using web page scraping techniques and saving it to a database.

[0516] Step 2:

[0517] The server inputs the acquired spatial design information into an image analysis module and extracts dimension and shape data for each section. This analysis utilizes the OpenCV library to process digital image data, detect the outline of rooms, and measure their size. As output, dimension data for each area of ​​the floor plan is obtained and rearranged into the configuration information.

[0518] Step 3:

[0519] The terminal displays an interface for the user to input their interior style and budget. The user enters specific styles, price ranges, etc., using the keyboard or voice, and the terminal sends this information to the server. Specifically, the input data is transmitted to the server using the secure HTTPS communication protocol.

[0520] Step 4:

[0521] The server receives user input and generates a user profile. Next, it retrieves past purchase history from the database and analyzes interior style trends. This process utilizes SQL queries to aggregate relevant data and understand the user's preferences. After profile generation, information based on the user's criteria is included in the profile.

[0522] Step 5:

[0523] The server uses the acquired dimension data and user profile to search the product information database. The database utilizes NoSQL technology to efficiently search large amounts of information. Based on the search results, a list of suggestions is generated, listing products that match the user's preferences and budget. This output consists of the product name, price, and content suitable for the intended use.

[0524] Step 6:

[0525] The server collects pricing information and product reviews from multiple supply platforms for each product in the suggested list. Access to these platforms is via API, and data is retrieved in JSON format. Based on the collected data, cost-effectiveness is evaluated and the list is optimized. The evaluated list is output as a more accurate list of recommended products.

[0526] Step 7:

[0527] The terminal receives a list of suggestions and related information from the server and presents it to the user. The screen displays product details, prices, reviews, and stock availability, making it easier for the user to visually compare products. Specifically, the user selects a product through screen navigation and can access the purchase page immediately.

[0528] Step 8:

[0529] The server checks the compatibility of selected purchase candidates with existing automated home appliances and suggests setup methods. This process queries a database of specifications for each product and collects network configuration information. The resulting setup guide helps users quickly and smoothly connect new products to their home network.

[0530] (Application Example 1)

[0531] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0532] In the traditional furniture and appliance purchasing process, users had to manually select the optimal product from a vast number of options, ensuring consistency with their budget and style. This resulted in a time-consuming and laborious process, making it difficult to achieve their ideal living space. Furthermore, verifying the functionality of purchased products with smart home systems proved challenging, creating technical issues within existing living environments.

[0533] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0534] This invention includes a server that automatically acquires spatial data from real estate information sources, analyzes floor plans to extract dimensions and structural data of parts, collects user preferences and financial information to generate a user profile, and searches a database of furniture and fixtures based on the user profile to generate a list of optimal product suggestions. This makes it possible for users to efficiently select the best products that match their budget and preferences without any hassle, thereby improving their living environment.

[0535] A "real estate information source" refers to a database or platform that provides information about buildings and houses.

[0536] "Spatial data" refers to data that includes information about the layout of a building, the dimensions of rooms, and its structure.

[0537] A "user profile" refers to a dataset that aggregates personalized information, including a user's preferences and financial situation.

[0538] A "database of furniture and appliances" refers to a data structure that stores information about furniture and electrical appliances that consumers can purchase.

[0539] A "product suggestion list" refers to a set of information generated to provide a list of optimized products based on the user's needs.

[0540] An "online sales platform" refers to a platform or system for buying and selling products over the internet.

[0541] A "smart device" refers to a portable device that can connect to the internet and obtain and transmit information.

[0542] A "prompt message" refers to a short sentence containing instructions or suggestions to support the user's choices.

[0543] This invention provides an integrated system for users to efficiently select furniture and appliances. The main components of the system are a server and a terminal. The following describes an embodiment of the system that implements this application example.

[0544] The server uses a cloud-based storage system as the hardware and software used to acquire spatial data from real estate information sources. Cloud storage such as AWS S3 is utilized, and real estate information is acquired via APIs. For analysis, AWS Rekognition and Google Cloud Vision API are used as image analysis technologies to identify the dimensions and structure of floor plans. AWS DynamoDB and Firebase Firestore are used for database management.

[0545] On the device side, an interface is provided for users to input their preferences and financial information. A cross-platform application will be developed using Flutter or React Native. Through this interface, user information will be collected and synchronized with the server.

[0546] Based on this information, the server searches a database of furniture and fixtures to generate a list of optimal product suggestions. The search utilizes a Node.js backend and an efficient search system powered by Elasticsearch. The suggestion list is generated along with price and reputation information and is updated in real time.

[0547] The device also notifies the user of a list of suggestions and related information. Using the smartphone's push notification function, users can immediately proceed with the purchase. An example of a prompt message is: "We analyze the latest floor plans and suggest the perfect modern furniture for your living room. Find options that fit your budget and preferences!" This prompt message is generated using an AI model to assist the user in their selection.

[0548] Finally, the server verifies the product's compatibility with existing smart devices and provides the user with the necessary configuration information. This feature allows users to seamlessly integrate the purchased product into their existing systems.

[0549] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0550] Step 1:

[0551] The server retrieves spatial data of floor plans from real estate information sources. Property identification information is used as input, and the server accesses the real estate information sources via an API. The data is stored in cloud storage such as AWS S3 and handled in a secure environment.

[0552] Step 2:

[0553] The server analyzes the acquired floor plans. Using the acquired image data as input, it extracts room dimensions and shape data using AWS Rekognition or Google Cloud Vision API. This processing automates dimension measurements that were previously done manually, enabling rapid data provision.

[0554] Step 3:

[0555] Users input their preferences and financial information through their device. The input screen includes fields for interior style and budget, and this information is collected and sent to the server as a digital profile. This creates an individualized dataset.

[0556] Step 4:

[0557] The server combines data from the user's profile and floor plan to search a database of furniture and fixtures. Based on the entered user data, Node.js and Elasticsearch are used to find relevant products and generate an optimized list of suggestions. The search results include multiple suggestions that fit the user's needs.

[0558] Step 5:

[0559] The server collects information on the pricing and ratings of the proposed products and further optimizes the list of suggestions. Based on data gathered from multiple online sales platforms, it prepares to provide users with cost-effective options.

[0560] Step 6:

[0561] The device notifies the user of a list of suggestions and related information. The generated optimization list is displayed via push notifications and in-app screens, allowing the user to check the information in real time. This speeds up the shopping decision-making process.

[0562] Step 7:

[0563] The server verifies compatibility with existing smart home devices and provides configuration information to the user. The selected product list is used as input for the compatibility check. The results are communicated to the user, facilitating seamless integration of the new product.

[0564] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0565] This invention combines a conventional interior design proposal system with an emotion engine that recognizes the user's emotional state, providing a system that offers more personalized proposals to the user. Embodiments of the present invention will be described in detail below.

[0566] This system consists of a user terminal and a server, and operates on the cloud or a dedicated server. The terminal receives user instructions and simultaneously collects data for the emotion engine to recognize the user's emotional state.

[0567] The server first automatically retrieves floor plans from real estate information sources and analyzes them to extract data on room size and shape. This design reduces the cumbersome process for users when moving into a new home.

[0568] Next, the device displays an interface where the user can input their interior style preferences, budget, and real-time emotional state. The device uses its camera and microphone to collect the necessary data for the emotion engine and sends it to the server. This emotional state reflects how the user feels about the interior items presented.

[0569] Based on this input data, the server updates the user profile and, by adding information about past purchase history, accurately understands the user's interior style preferences and current emotional state. This allows the server to generate a list of furniture and appliances that are best suited to the user, improving the accuracy of the personalization.

[0570] The server retrieves the latest pricing information and user reviews for the proposed products from multiple online sales platforms. Based on this, it evaluates the cost-effectiveness of the products in the proposal list and optimizes the list to make it the most appropriate recommendation.

[0571] Once the suggestion list is complete, the device optimizes how information is presented based on the user's emotional state and notifies the user accordingly. For example, if the user is feeling excited or surprised, it will offer more options and new suggestions; if they are calm, it will select an interface that emphasizes detailed explanations and review points.

[0572] Furthermore, the server verifies the compatibility of smart home-compatible products in the proposed list with existing devices and provides the user with setup instructions. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0573] As a concrete example, suppose a user is looking for a bed for their new bedroom after moving. The server identifies the bedroom size from the floor plan and, if it estimates that the user is in a relaxed emotional state, suggests a bed designed to promote restful sleep. The terminal notifies the user of this and supports their selection based on price and reviews. In this way, the present invention provides a system that helps create a more personalized and comfortable living space by incorporating the user's emotions.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] The server accesses real estate information sources and automatically retrieves the latest floor plans for the specified property. The retrieved floor plans are then passed to an image analysis module within the server, where they are processed to identify the dimensions and shape of each room.

[0577] Step 2:

[0578] The device displays an interface for the user to input their interior style preferences and budget. The user enters this information, and the device makes that data available for the emotion engine. It also collects data about the user's emotional state using the camera and microphone.

[0579] Step 3:

[0580] The server updates the user profile based on user input data sent from the terminal and emotional state information generated by the emotion engine. During this process, it refines the user's style tendencies by referring to past purchase history.

[0581] Step 4:

[0582] The server uses the analyzed floor plan and updated user profile to generate a list of optimal furniture and appliance suggestions. This list is personalized, taking into account the user's current emotional state.

[0583] Step 5:

[0584] The server collects the latest pricing information and user reviews from online sales platforms for each product included in the suggestion list. This information is used to evaluate the cost-effectiveness of the suggested products and optimize the list.

[0585] Step 6:

[0586] The device displays the suggestion list in the most appropriate format according to the user's emotional state. For example, if the user shows interest, it presents a layout that provides detailed product descriptions and encourages comparison and consideration.

[0587] Step 7:

[0588] The server checks the compatibility of the smart home devices included in the suggestion list with existing devices and provides setup instructions to the user as needed. This allows the user to efficiently integrate new devices into their smart home environment.

[0589] (Example 2)

[0590] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0591] In recent years, there has been a growing demand for interior design to be optimized for each user. However, conventional systems have failed to consider the user's emotional state, making it difficult to accurately reflect individual needs. Furthermore, real-time price information, inventory monitoring, and compatibility checks with smart home devices were insufficient, resulting in inconvenience for users.

[0592] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0593] In this invention, the server includes means for automatically acquiring spatial maps and spatial data from real estate information sources, means for analyzing the acquired spatial maps to extract data on the size and shape of the area, and means for collecting the user's preferences, budget, and emotional state to generate a user profile. This makes it possible to propose interiors that reflect the user's emotional state, enabling the creation of a more personalized and comfortable living space for the user.

[0594] "Real estate information sources" refer to databases and data supply systems that provide spatial data on buildings and land, as well as floor plans and other related information.

[0595] A "spatial diagram" is a visual drawing that shows the layout of rooms or buildings, and it includes the location and dimensions of each room or space.

[0596] "Spatial data" refers to numerical information about the size, shape, and location of rooms extracted from floor plans.

[0597] A "user profile" refers to a collection of user-specific information, including individual user preferences, budget, emotional state, and past purchase history.

[0598] "Emotional state" refers to information that indicates the user's current emotions, and is analyzed based on data collected through cameras and microphones.

[0599] The "Suggestion List" refers to a list of optimal interior design products and home appliances selected based on the user's profile.

[0600] "Automated home devices" refer to smart home devices and household electronic devices that can communicate with each other.

[0601] "Compatibility" refers to the ability of different devices or systems to work together in harmony.

[0602] "Sales outlets" refer to all commercial sources of supply, including online platforms and physical stores, that sell products.

[0603] "Cost-effectiveness" refers to an indicator that evaluates the effectiveness and economic value of the results relative to the costs incurred.

[0604] This interior design proposal system consists of user terminals and servers, and operates on the cloud or a dedicated server.

[0605] First, upon activation, the user is instructed to input their interior design preferences, budget, and real-time emotional state into the device's interface. The device then uses its camera and microphone to collect data for analyzing the user's facial expressions and voice. Image recognition and voice analysis software are used for emotion analysis.

[0606] The collected data is sent to a server. The server uses an emotion engine to identify the user's emotional state and generate emotion data. This technology employs machine learning algorithms that incorporate generative AI models.

[0607] Next, the server automatically retrieves floor plans from real estate information sources and analyzes the spatial data to determine the size and shape of the rooms. CAD analysis software and similar tools are used for this analysis.

[0608] Based on the acquired emotional and spatial data, the server updates the user profile. The user profile also incorporates the user's past purchase history and style preferences, reflecting the user's needs in detail.

[0609] Using a generative AI model, the server selects the most suitable interior items based on the user's emotional state and generates a list of suggestions. Furthermore, the suggestion list is optimized using the latest price information and user reviews from multiple online sales outlets.

[0610] Once the suggestion list is complete, the device selects a method of presenting information that suits the user's emotional state and notifies the user accordingly. For example, if the user is enjoying themselves, the device will highlight a wider range of options; if the user is in a calm emotional state, it will provide more detailed information.

[0611] Examples of prompts include, "Could you recommend some interior design ideas for the living room of my new home? I'm looking for a relaxed atmosphere."

[0612] Furthermore, the server verifies the compatibility of smart home-compatible products with existing devices and provides users with setup instructions. This function is crucial for smoothly integrating smart home systems into users' lives.

[0613] For example, if a user is looking for a new living room sofa, the system will suggest the optimal size sofa based on the room dimensions and select a comfortable design that matches the user's relaxed mood. The terminal screen will display these suggestions along with price information and reviews to support the user's purchase.

[0614] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0615] Step 1:

[0616] The user activates the device and inputs their interior design preferences and budget through the interface. The device also collects data representing their emotional state using the camera and microphone. The input data includes preferences, budget, voice, and video data. Based on this, the device generates a dataset for emotion analysis.

[0617] Step 2:

[0618] The device sends the collected data to the server. The server uses an emotion engine to perform image recognition and voice analysis to determine the user's emotional state. This process outputs the user's emotional state (e.g., pleasant, calm, excited).

[0619] Step 3:

[0620] The server retrieves floor plans from real estate information sources and uses CAD analysis software to extract room size and shape data. The input is floor plan data, and the output is room dimensions and shape information as a result of the analysis.

[0621] Step 4:

[0622] The server integrates past purchase history, user preferences, budget, emotional state, and physical data of the room to update the user profile. Based on this input data, a personalized user profile is output.

[0623] Step 5:

[0624] Using a generative AI model, the server selects the most suitable interior items based on the updated user profile and creates a suggestion list. The model filters items according to the user's emotional state and outputs suitable options as a suggestion list.

[0625] Step 6:

[0626] The server collects the latest pricing information and user reviews from multiple sales locations. Using this collected information, it generates a list optimized for cost-effectiveness. In this step, pricing information and reviews are input, and an optimized list of suggestions is output.

[0627] Step 7:

[0628] After the suggestion list is complete, the device selects a method for presenting information based on the user's emotional state and notifies the user. For example, if the user is enjoying themselves, colorful options will be displayed on the interface. The method of presenting information is customized and output based on the user's emotional state.

[0629] Step 8:

[0630] The server checks the compatibility of smart home compatible products included in the suggestion list with existing devices and provides setup instructions. Device information is taken as input, and the compatibility check results and setup instructions are output. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0631] (Application Example 2)

[0632] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0633] In recent years, there has been a growing demand for personalized product suggestions that reflect consumer emotions and individual preferences. However, conventional interior design suggestion systems have struggled to adequately reflect the emotional states of individual users, making it difficult to efficiently provide personalized suggestions. Therefore, a method is needed to help users make quick and satisfying purchasing decisions.

[0634] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0635] This invention includes a server that analyzes the user's emotional state using emotion recognition technology, selects the most suitable interior decorations and electrical appliances along with the profile, and generates suggestion data; a server that collects price information and product evaluations from multiple e-commerce platforms and optimizes the suggestion data; and a server that checks the compatibility of potential purchase products with existing information appliance technologies and suggests settings. This enables more personalized interior suggestions that are tailored to the user's emotional state.

[0636] "Spatial arrangement" refers to the layout of a living space obtained from real estate information sources.

[0637] "Spatial data" refers to information about the size and shape of living spaces based on acquired spatial arrangements.

[0638] A "user profile" is a dataset formed based on a user's preferences and budget.

[0639] "Emotion recognition technology" is a technology that analyzes a user's emotional state and provides personalized suggestions.

[0640] "Interior decorations" are items used to enhance the aesthetics and functionality of a room.

[0641] "Electrical products" include various products that utilize electricity used in the home.

[0642] "Suggestion data" is a list of optimal product suggestions generated based on the user's profile and emotional state.

[0643] An "e-commerce platform" is a digital platform where goods are bought and sold online.

[0644] "Information appliance technology" refers to smart device technology used in the home.

[0645] The system implementing this invention mainly consists of a server and terminals. The server automatically acquires spatial layout and spatial data from online databases and real estate information sources, analyzes this data to extract information about the size and shape of living spaces. In doing so, the server uses data analysis software to efficiently process the acquired information.

[0646] The terminal is equipped with an interface for receiving user input. Here, information about the user's preferences and budget is collected, and a user profile is formed based on this information. Furthermore, the terminal uses emotion recognition technology to analyze the user's emotional state in real time and transmit it to the server. For this purpose, the terminal is equipped with hardware for emotion analysis (e.g., a camera and microphone).

[0647] The server selects the most suitable interior decorations and electrical appliances based on the user's emotional state and profile, and generates suggestion data. In this process, the server utilizes a generative AI model and provides prompts to make the most appropriate suggestions to the user. It collects the latest pricing information and product reviews from multiple e-commerce platforms to optimize the suggestion data. Finally, this optimized suggestion data is communicated to the user via their device.

[0648] Furthermore, the server verifies the compatibility of potential purchase products with existing consumer electronics technologies and provides users with setup instructions. For this purpose, the server utilizes dedicated software for compatibility verification and organizes and provides the necessary setup information.

[0649] As a concrete example, if the device is worn by the user as smart glasses, when the user browses products in a store, their emotional state is recognized in real time, and personalized product suggestions generated by the server are instantly visualized. In this way, the user can instantly obtain the information they need, thereby increasing their desire to purchase.

[0650] An example of a prompt would be: "If the customer is feeling relaxed, please list the product features necessary to suggest interior items that evoke a sense of calm."

[0651] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0652] Step 1:

[0653] The terminal provides an interface to receive preference and budget information from the user. Based on this input information, it generates a user profile. In doing so, the terminal uses profile generation software to save the information to a database.

[0654] Step 2:

[0655] When a user browses interior design products through their device, the device collects emotional data from the user via its built-in camera and microphone. An emotion recognition engine analyzes this data to identify the user's emotional state (e.g., relaxed, excited, surprised). This information is transmitted to the server in real time.

[0656] Step 3:

[0657] The server provides optimal product recommendations based on the emotional state and user profile transmitted from the terminal. Here, a generative AI model is used to apply prompt sentences to identify interior decorations and electrical appliances that suit the user and create recommendation data.

[0658] Step 4:

[0659] The server accesses multiple e-commerce platforms to collect the latest pricing information and product reviews for selected items. This information is used to optimize suggestion data and provide users with the most valuable choices.

[0660] Step 5:

[0661] The generated suggestion data is sent to the device, allowing the user to view it in real time. The device adjusts the UI according to the user's emotions, visually displaying the necessary information. For example, if the user is in a relaxed emotional state, it might increase the details of products that promote restful sleep.

[0662] Step 6:

[0663] The server checks the compatibility of potential purchase items with existing consumer electronics technologies and provides setup instructions to the terminal so that users can easily set them up. Compatibility check software is used to deliver this information to the user.

[0664] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0665] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0666] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0667] [Fourth Embodiment]

[0668] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0669] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0670] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0671] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0672] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0673] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0674] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0675] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0676] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0677] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0678] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0679] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0680] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] This invention provides a system that automatically obtains floor plans from real estate information sources, identifies the size and shape of rooms through analysis, and proposes optimal furniture and home appliances according to the user's needs. Embodiments of this invention are described below.

[0682] This system includes user terminals and server components that operate on the cloud or on dedicated servers. The terminals receive user instructions and transmit them to the server, which then processes the information and generates a list of suggestions.

[0683] The server accesses real estate information sources and retrieves the latest floor plans for specified properties from the database. This process also includes processing URLs of properties provided by the user, as well as floor plans in electronic file format. The retrieved floor plans are processed by an advanced image analysis module on the server, extracting dimension and shape data for each room. This design eliminates the need for users to manually measure the dimensions.

[0684] Next, the device displays an interface for the user to input their preferred interior style and budget, which is then collected manually or via voice input. This data is sent to the server and registered as part of the user profile. In addition, the server also refers to past purchase history data to analyze the user's style trends, and this is also reflected in the profile.

[0685] Next, the server searches a database of furniture and appliances based on the acquired floor plan and user profile, and creates a list of suggestions that are best suited to the specific room. This list includes products that match the user's preferences and are purchasable within their budget.

[0686] Simultaneously, the server collects pricing information and product reviews from multiple online sales platforms. This allows it to evaluate the cost-effectiveness of each product being offered and present users with reasonably priced and reputable options.

[0687] The device notifies the user and presents a list of suggestions and their details. This list includes price, reviews, and stock information, and is designed to allow the user to make an immediate purchase.

[0688] Furthermore, the server checks the compatibility of the selected products with smart home devices and, if possible, suggests setup methods to the user. This allows users to easily integrate new products into their existing home network.

[0689] As a concrete example, suppose a user is looking for a sofa for their living room when moving into a new home. The server identifies the dimensions of the living room from the floor plan and suggests several suitable sofas based on the user's modern interior style preferences and budget. The terminal presents these to the user and supports their selection based on price and reviews. At this time, if one of the suggested sofas is smart home compatible, information on setting it up is also presented.

[0690] Thus, the system of the present invention provides a technology that significantly reduces the various hassles that users face when choosing a residence, and enables them to efficiently and safely arrange their living space.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] The server accesses real estate information sources to automatically retrieve floor plans for properties. URLs and PDF files of floor plans provided by users are also included in this process, and the server downloads and begins processing them.

[0694] Step 2:

[0695] The server passes the acquired floor plan to an image analysis module to identify the shape and dimensions of each room. This information is stored in a database as detailed data for each room and used in subsequent suggestion processing.

[0696] Step 3:

[0697] The user inputs their interior design preferences and budget through an interface displayed on the device. The device receives this information and sends it to a server, incorporating it into the process of generating a user profile.

[0698] Step 4:

[0699] Based on the received user profile, the server retrieves past purchase history from the database and analyzes the user's style tendencies. This information is integrated into the profile and used to create suggestion lists.

[0700] Step 5:

[0701] The server searches a database of furniture and home appliances based on the analyzed floor plan data and user profile, and generates a list of recommended items for each room. This list includes products that match the user's preferences and budget.

[0702] Step 6:

[0703] The server collects pricing information and product reviews for products proposed from multiple online sales platforms. Based on this information, it evaluates cost-effectiveness and optimizes the recommendations to make the most beneficial choice for the user.

[0704] Step 7:

[0705] The terminal notifies the user of the completed list of suggestions and displays detailed information about the list. This information includes the price of the suggested furniture and appliances, user reviews, and inventory information, allowing the user to consider purchasing based on this information.

[0706] Step 8:

[0707] The server checks the compatibility of the smart home-compatible products included in the suggestion list with the user's current smart home devices and suggests setup methods. This allows the user to smoothly integrate newly purchased products into their existing environment.

[0708] (Example 1)

[0709] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0710] Modern consumers are required to efficiently and accurately select products that meet their needs from a diverse range of housing and home appliance information. However, conventional methods involve manually checking the space and layout of a property and the process of selecting suitable products, which is time-consuming and laborious. Furthermore, considering appropriate cost-effectiveness and product compatibility requires searching for information individually, which is extremely cumbersome. This invention aims to solve these problems.

[0711] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0712] In this invention, the server includes means for automatically acquiring spatial design information from real estate information sources, means for analyzing the acquired spatial design information and extracting information on the dimensions and shape of the plots, and means for acquiring the user's preferences and budget and generating a user profile. This enables users to easily and quickly find the product best suited to their space, and further supports them in making real-time purchasing decisions that take into account cost-effectiveness and product compatibility.

[0713] "Real estate information sources" refer to information providers that offer spatial design information and floor plans related to real estate.

[0714] "Spatial design information" refers to data that includes detailed information such as the dimensions, shape, and layout of each room or section of a property.

[0715] A "user profile" refers to a compilation of information such as a user's preferences, budget, and past purchase history, which serves as the foundation for providing optimal suggestions to individual users.

[0716] A "list of proposals" refers to a list of products and services that meet the user's requirements and are deemed optimal.

[0717] A "supply platform" refers to an online business infrastructure that provides products and services.

[0718] "Automated home appliances" refer to household electrical appliances that can communicate and be controlled using the internet.

[0719] "Image analysis technology" refers to the technology of processing digital image data and extracting specific information.

[0720] "Communication operation" refers to an operation for sending and receiving information, and is a means that enables users to purchase products directly through an interface.

[0721] "Cost-effectiveness" refers to a criterion for evaluating the balance between the performance and quality of a potential purchase product and its price.

[0722] This invention is a system that automatically acquires spatial design information from real estate information sources, identifies the dimensions and shape of a plot through analysis, and proposes the optimal product according to the user's needs. This system consists of a server component that operates in a cloud environment or a dedicated server environment, and a terminal that handles the user interface.

[0723] The server accesses real estate information sources and retrieves spatial design information. This process includes URLs and PDF digital data provided by users. The retrieved information is analyzed by an image analysis module on the server, extracting dimension and shape data for each plot. The OpenCV library is primarily used for image analysis.

[0724] Next, the device provides an interface for the user to input their preferred style and budget. The user enters their preferences using a keyboard or voice input, and this data is sent to the server via a secure protocol. The server registers this as part of the user profile and also analyzes past purchase history to reflect the user's style tendencies.

[0725] Subsequently, the server searches the product information database based on the analyzed design information and user profile, and generates a list of suggestions. This list includes products that match the user's preferences and are purchasable within their budget. The server also collects pricing information and product reviews from multiple supply platforms and evaluates the cost-effectiveness of each suggested product.

[0726] The suggested list is notified to the user via the terminal and includes product details, prices, reviews, and stock information. The user can compare products on the screen and consider purchasing the selected products. If there are potential purchases, the server checks the compatibility of the products with the automated home appliances and provides appropriate setup instructions.

[0727] As a concrete example, if the prompt "Please suggest modern style furniture suitable for a new 3LDK apartment" is entered into the generation AI model, the system will extract the dimensions of each room from the floor plan, suggest furniture that fits the budget and style, and present the most suitable products to the user.

[0728] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0729] Step 1:

[0730] The server accesses real estate information sources and automatically retrieves spatial design information. This input consists of URLs of properties and floor plans in electronic file format provided by the user, and the data is collected using the HTTP protocol. After data extraction, the retrieved design information is stored on the server in digital format. Specifically, the process involves extracting information using web page scraping techniques and saving it to a database.

[0731] Step 2:

[0732] The server inputs the acquired spatial design information into an image analysis module and extracts dimension and shape data for each section. This analysis utilizes the OpenCV library to process digital image data, detect the outline of rooms, and measure their size. As output, dimension data for each area of ​​the floor plan is obtained and rearranged into the configuration information.

[0733] Step 3:

[0734] The terminal displays an interface for the user to input their interior style and budget. The user enters specific styles, price ranges, etc., using the keyboard or voice, and the terminal sends this information to the server. Specifically, the input data is transmitted to the server using the secure HTTPS communication protocol.

[0735] Step 4:

[0736] The server receives user input and generates a user profile. Next, it retrieves past purchase history from the database and analyzes interior style trends. This process utilizes SQL queries to aggregate relevant data and understand the user's preferences. After profile generation, information based on the user's criteria is included in the profile.

[0737] Step 5:

[0738] The server uses the acquired dimension data and user profile to search the product information database. The database utilizes NoSQL technology to efficiently search large amounts of information. Based on the search results, a list of suggestions is generated, listing products that match the user's preferences and budget. This output consists of the product name, price, and content suitable for the intended use.

[0739] Step 6:

[0740] The server collects pricing information and product reviews from multiple supply platforms for each product in the suggested list. Access to these platforms is via API, and data is retrieved in JSON format. Based on the collected data, cost-effectiveness is evaluated and the list is optimized. The evaluated list is output as a more accurate list of recommended products.

[0741] Step 7:

[0742] The terminal receives a list of suggestions and related information from the server and presents it to the user. The screen displays product details, prices, reviews, and stock availability, making it easier for the user to visually compare products. Specifically, the user selects a product through screen navigation and can access the purchase page immediately.

[0743] Step 8:

[0744] The server checks the compatibility of selected purchase candidates with existing automated home appliances and suggests setup methods. This process queries a database of specifications for each product and collects network configuration information. The resulting setup guide helps users quickly and smoothly connect new products to their home network.

[0745] (Application Example 1)

[0746] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0747] In the traditional furniture and appliance purchasing process, users had to manually select the optimal product from a vast number of options, ensuring consistency with their budget and style. This resulted in a time-consuming and laborious process, making it difficult to achieve their ideal living space. Furthermore, verifying the functionality of purchased products with smart home systems proved challenging, creating technical issues within existing living environments.

[0748] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0749] This invention includes a server that automatically acquires spatial data from real estate information sources, analyzes floor plans to extract dimensions and structural data of parts, collects user preferences and financial information to generate a user profile, and searches a database of furniture and fixtures based on the user profile to generate a list of optimal product suggestions. This makes it possible for users to efficiently select the best products that match their budget and preferences without any hassle, thereby improving their living environment.

[0750] A "real estate information source" refers to a database or platform that provides information about buildings and houses.

[0751] "Spatial data" refers to data that includes information about the layout of a building, the dimensions of rooms, and its structure.

[0752] A "user profile" refers to a dataset that aggregates personalized information, including a user's preferences and financial situation.

[0753] A "database of furniture and appliances" refers to a data structure that stores information about furniture and electrical appliances that consumers can purchase.

[0754] A "product suggestion list" refers to a set of information generated to provide a list of optimized products based on the user's needs.

[0755] An "online sales platform" refers to a platform or system for buying and selling products over the internet.

[0756] A "smart device" refers to a portable device that can connect to the internet and obtain and transmit information.

[0757] A "prompt message" refers to a short sentence containing instructions or suggestions to support the user's choices.

[0758] This invention provides an integrated system for users to efficiently select furniture and appliances. The main components of the system are a server and a terminal. The following describes an embodiment of the system that implements this application example.

[0759] The server uses a cloud-based storage system as the hardware and software used to acquire spatial data from real estate information sources. Cloud storage such as AWS S3 is utilized, and real estate information is acquired via APIs. For analysis, AWS Rekognition and Google Cloud Vision API are used as image analysis technologies to identify the dimensions and structure of floor plans. AWS DynamoDB and Firebase Firestore are used for database management.

[0760] On the device side, an interface is provided for users to input their preferences and financial information. A cross-platform application will be developed using Flutter or React Native. Through this interface, user information will be collected and synchronized with the server.

[0761] Based on this information, the server searches a database of furniture and fixtures to generate a list of optimal product suggestions. The search utilizes a Node.js backend and an efficient search system powered by Elasticsearch. The suggestion list is generated along with price and reputation information and is updated in real time.

[0762] The device also notifies the user of a list of suggestions and related information. Using the smartphone's push notification function, users can immediately proceed with the purchase. An example of a prompt message is: "We analyze the latest floor plans and suggest the perfect modern furniture for your living room. Find options that fit your budget and preferences!" This prompt message is generated using an AI model to assist the user in their selection.

[0763] Finally, the server verifies the product's compatibility with existing smart devices and provides the user with the necessary configuration information. This feature allows users to seamlessly integrate the purchased product into their existing systems.

[0764] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0765] Step 1:

[0766] The server retrieves spatial data of floor plans from real estate information sources. Property identification information is used as input, and the server accesses the real estate information sources via an API. The data is stored in cloud storage such as AWS S3 and handled in a secure environment.

[0767] Step 2:

[0768] The server analyzes the acquired floor plans. Using the acquired image data as input, it extracts room dimensions and shape data using AWS Rekognition or Google Cloud Vision API. This processing automates dimension measurements that were previously done manually, enabling rapid data provision.

[0769] Step 3:

[0770] Users input their preferences and financial information through their device. The input screen includes fields for interior style and budget, and this information is collected and sent to the server as a digital profile. This creates an individualized dataset.

[0771] Step 4:

[0772] The server combines data from the user's profile and floor plan to search a database of furniture and fixtures. Based on the entered user data, Node.js and Elasticsearch are used to find relevant products and generate an optimized list of suggestions. The search results include multiple suggestions that fit the user's needs.

[0773] Step 5:

[0774] The server collects information on the pricing and ratings of the proposed products and further optimizes the list of suggestions. Based on data gathered from multiple online sales platforms, it prepares to provide users with cost-effective options.

[0775] Step 6:

[0776] The device notifies the user of a list of suggestions and related information. The generated optimization list is displayed via push notifications and in-app screens, allowing the user to check the information in real time. This speeds up the shopping decision-making process.

[0777] Step 7:

[0778] The server verifies compatibility with existing smart home devices and provides configuration information to the user. The selected product list is used as input for the compatibility check. The results are communicated to the user, facilitating seamless integration of the new product.

[0779] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0780] This invention combines a conventional interior design proposal system with an emotion engine that recognizes the user's emotional state, providing a system that offers more personalized proposals to the user. Embodiments of the present invention will be described in detail below.

[0781] This system consists of a user terminal and a server, and operates on the cloud or a dedicated server. The terminal receives user instructions and simultaneously collects data for the emotion engine to recognize the user's emotional state.

[0782] The server first automatically retrieves floor plans from real estate information sources and analyzes them to extract data on room size and shape. This design reduces the cumbersome process for users when moving into a new home.

[0783] Next, the device displays an interface where the user can input their interior style preferences, budget, and real-time emotional state. The device uses its camera and microphone to collect the necessary data for the emotion engine and sends it to the server. This emotional state reflects how the user feels about the interior items presented.

[0784] Based on this input data, the server updates the user profile and, by adding information about past purchase history, accurately understands the user's interior style preferences and current emotional state. This allows the server to generate a list of furniture and appliances that are best suited to the user, improving the accuracy of the personalization.

[0785] The server retrieves the latest pricing information and user reviews for the proposed products from multiple online sales platforms. Based on this, it evaluates the cost-effectiveness of the products in the proposal list and optimizes the list to make it the most appropriate recommendation.

[0786] Once the suggestion list is complete, the device optimizes how information is presented based on the user's emotional state and notifies the user accordingly. For example, if the user is feeling excited or surprised, it will offer more options and new suggestions; if they are calm, it will select an interface that emphasizes detailed explanations and review points.

[0787] Furthermore, the server verifies the compatibility of smart home-compatible products in the proposed list with existing devices and provides the user with setup instructions. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0788] As a concrete example, suppose a user is looking for a bed for their new bedroom after moving. The server identifies the bedroom size from the floor plan and, if it estimates that the user is in a relaxed emotional state, suggests a bed designed to promote restful sleep. The terminal notifies the user of this and supports their selection based on price and reviews. In this way, the present invention provides a system that helps create a more personalized and comfortable living space by incorporating the user's emotions.

[0789] The following describes the processing flow.

[0790] Step 1:

[0791] The server accesses real estate information sources and automatically retrieves the latest floor plans for the specified property. The retrieved floor plans are then passed to an image analysis module within the server, where they are processed to identify the dimensions and shape of each room.

[0792] Step 2:

[0793] The device displays an interface for the user to input their interior style preferences and budget. The user enters this information, and the device makes that data available for the emotion engine. It also collects data about the user's emotional state using the camera and microphone.

[0794] Step 3:

[0795] The server updates the user profile based on user input data sent from the terminal and emotional state information generated by the emotion engine. During this process, it refines the user's style tendencies by referring to past purchase history.

[0796] Step 4:

[0797] The server uses the analyzed floor plan and updated user profile to generate a list of optimal furniture and appliance suggestions. This list is personalized, taking into account the user's current emotional state.

[0798] Step 5:

[0799] The server collects the latest pricing information and user reviews from online sales platforms for each product included in the suggestion list. This information is used to evaluate the cost-effectiveness of the suggested products and optimize the list.

[0800] Step 6:

[0801] The device displays the suggestion list in the most appropriate format according to the user's emotional state. For example, if the user shows interest, it presents a layout that provides detailed product descriptions and encourages comparison and consideration.

[0802] Step 7:

[0803] The server checks the compatibility of the smart home devices included in the suggestion list with existing devices and provides setup instructions to the user as needed. This allows the user to efficiently integrate new devices into their smart home environment.

[0804] (Example 2)

[0805] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0806] In recent years, there has been a growing demand for interior design to be optimized for each user. However, conventional systems have failed to consider the user's emotional state, making it difficult to accurately reflect individual needs. Furthermore, real-time price information, inventory monitoring, and compatibility checks with smart home devices were insufficient, resulting in inconvenience for users.

[0807] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0808] In this invention, the server includes means for automatically acquiring spatial maps and spatial data from real estate information sources, means for analyzing the acquired spatial maps to extract data on the size and shape of the area, and means for collecting the user's preferences, budget, and emotional state to generate a user profile. This makes it possible to propose interiors that reflect the user's emotional state, enabling the creation of a more personalized and comfortable living space for the user.

[0809] "Real estate information sources" refer to databases and data supply systems that provide spatial data on buildings and land, as well as floor plans and other related information.

[0810] A "spatial diagram" is a visual drawing that shows the layout of rooms or buildings, and it includes the location and dimensions of each room or space.

[0811] "Spatial data" refers to numerical information about the size, shape, and location of rooms extracted from floor plans.

[0812] A "user profile" refers to a collection of user-specific information, including individual user preferences, budget, emotional state, and past purchase history.

[0813] "Emotional state" refers to information that indicates the user's current emotions, and is analyzed based on data collected through cameras and microphones.

[0814] The "Suggestion List" refers to a list of optimal interior design products and home appliances selected based on the user's profile.

[0815] "Automated home devices" refer to smart home devices and household electronic devices that can communicate with each other.

[0816] "Compatibility" refers to the ability of different devices or systems to work together in harmony.

[0817] "Sales outlets" refer to all commercial sources of supply, including online platforms and physical stores, that sell products.

[0818] "Cost-effectiveness" refers to an indicator that evaluates the effectiveness and economic value of the results relative to the costs incurred.

[0819] This interior design proposal system consists of user terminals and servers, and operates on the cloud or a dedicated server.

[0820] First, upon activation, the user is instructed to input their interior design preferences, budget, and real-time emotional state into the device's interface. The device then uses its camera and microphone to collect data for analyzing the user's facial expressions and voice. Image recognition and voice analysis software are used for emotion analysis.

[0821] The collected data is sent to a server. The server uses an emotion engine to identify the user's emotional state and generate emotion data. This technology employs machine learning algorithms that incorporate generative AI models.

[0822] Next, the server automatically retrieves floor plans from real estate information sources and analyzes the spatial data to determine the size and shape of the rooms. CAD analysis software and similar tools are used for this analysis.

[0823] Based on the acquired emotional and spatial data, the server updates the user profile. The user profile also incorporates the user's past purchase history and style preferences, reflecting the user's needs in detail.

[0824] Using a generative AI model, the server selects the most suitable interior items based on the user's emotional state and generates a list of suggestions. Furthermore, the suggestion list is optimized using the latest price information and user reviews from multiple online sales outlets.

[0825] Once the suggestion list is complete, the device selects a method of presenting information that suits the user's emotional state and notifies the user accordingly. For example, if the user is enjoying themselves, the device will highlight a wider range of options; if the user is in a calm emotional state, it will provide more detailed information.

[0826] Examples of prompts include, "Could you recommend some interior design ideas for the living room of my new home? I'm looking for a relaxed atmosphere."

[0827] Furthermore, the server verifies the compatibility of smart home-compatible products with existing devices and provides users with setup instructions. This function is crucial for smoothly integrating smart home systems into users' lives.

[0828] For example, if a user is looking for a new living room sofa, the system will suggest the optimal size sofa based on the room dimensions and select a comfortable design that matches the user's relaxed mood. The terminal screen will display these suggestions along with price information and reviews to support the user's purchase.

[0829] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0830] Step 1:

[0831] The user activates the device and inputs their interior design preferences and budget through the interface. The device also collects data representing their emotional state using the camera and microphone. The input data includes preferences, budget, voice, and video data. Based on this, the device generates a dataset for emotion analysis.

[0832] Step 2:

[0833] The device sends the collected data to the server. The server uses an emotion engine to perform image recognition and voice analysis to determine the user's emotional state. This process outputs the user's emotional state (e.g., pleasant, calm, excited).

[0834] Step 3:

[0835] The server retrieves floor plans from real estate information sources and uses CAD analysis software to extract room size and shape data. The input is floor plan data, and the output is room dimensions and shape information as a result of the analysis.

[0836] Step 4:

[0837] The server integrates past purchase history, user preferences, budget, emotional state, and physical data of the room to update the user profile. Based on this input data, a personalized user profile is output.

[0838] Step 5:

[0839] Using a generative AI model, the server selects the most suitable interior items based on the updated user profile and creates a suggestion list. The model filters items according to the user's emotional state and outputs suitable options as a suggestion list.

[0840] Step 6:

[0841] The server collects the latest pricing information and user reviews from multiple sales locations. Using this collected information, it generates a list optimized for cost-effectiveness. In this step, pricing information and reviews are input, and an optimized list of suggestions is output.

[0842] Step 7:

[0843] After the suggestion list is complete, the device selects a method for presenting information based on the user's emotional state and notifies the user. For example, if the user is enjoying themselves, colorful options will be displayed on the interface. The method of presenting information is customized and output based on the user's emotional state.

[0844] Step 8:

[0845] The server checks the compatibility of smart home compatible products included in the suggestion list with existing devices and provides setup instructions. Device information is taken as input, and the compatibility check results and setup instructions are output. This allows users to smoothly integrate newly purchased products into their smart home environment.

[0846] (Application Example 2)

[0847] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0848] In recent years, there has been a growing demand for personalized product suggestions that reflect consumer emotions and individual preferences. However, conventional interior design suggestion systems have struggled to adequately reflect the emotional states of individual users, making it difficult to efficiently provide personalized suggestions. Therefore, a method is needed to help users make quick and satisfying purchasing decisions.

[0849] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0850] This invention includes a server that analyzes the user's emotional state using emotion recognition technology, selects the most suitable interior decorations and electrical appliances along with the profile, and generates suggestion data; a server that collects price information and product evaluations from multiple e-commerce platforms and optimizes the suggestion data; and a server that checks the compatibility of potential purchase products with existing information appliance technologies and suggests settings. This enables more personalized interior suggestions that are tailored to the user's emotional state.

[0851] "Spatial arrangement" refers to the layout of a living space obtained from real estate information sources.

[0852] "Spatial data" refers to information about the size and shape of living spaces based on acquired spatial arrangements.

[0853] A "user profile" is a dataset formed based on a user's preferences and budget.

[0854] "Emotion recognition technology" is a technology that analyzes a user's emotional state and provides personalized suggestions.

[0855] "Interior decorations" are items used to enhance the aesthetics and functionality of a room.

[0856] "Electrical products" include various products that utilize electricity used in the home.

[0857] "Suggestion data" is a list of optimal product suggestions generated based on the user's profile and emotional state.

[0858] An "e-commerce platform" is a digital platform where goods are bought and sold online.

[0859] "Information appliance technology" refers to smart device technology used in the home.

[0860] The system implementing this invention mainly consists of a server and terminals. The server automatically acquires spatial layout and spatial data from online databases and real estate information sources, analyzes this data to extract information about the size and shape of living spaces. In doing so, the server uses data analysis software to efficiently process the acquired information.

[0861] The terminal is equipped with an interface for receiving user input. Here, information about the user's preferences and budget is collected, and a user profile is formed based on this information. Furthermore, the terminal uses emotion recognition technology to analyze the user's emotional state in real time and transmit it to the server. For this purpose, the terminal is equipped with hardware for emotion analysis (e.g., a camera and microphone).

[0862] The server selects the most suitable interior decorations and electrical appliances based on the user's emotional state and profile, and generates suggestion data. In this process, the server utilizes a generative AI model and provides prompts to make the most appropriate suggestions to the user. It collects the latest pricing information and product reviews from multiple e-commerce platforms to optimize the suggestion data. Finally, this optimized suggestion data is communicated to the user via their device.

[0863] Furthermore, the server verifies the compatibility of potential purchase products with existing consumer electronics technologies and provides users with setup instructions. For this purpose, the server utilizes dedicated software for compatibility verification and organizes and provides the necessary setup information.

[0864] As a concrete example, if the device is worn by the user as smart glasses, when the user browses products in a store, their emotional state is recognized in real time, and personalized product suggestions generated by the server are instantly visualized. In this way, the user can instantly obtain the information they need, thereby increasing their desire to purchase.

[0865] An example of a prompt would be: "If the customer is feeling relaxed, please list the product features necessary to suggest interior items that evoke a sense of calm."

[0866] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0867] Step 1:

[0868] The terminal provides an interface to receive preference and budget information from the user. Based on this input information, it generates a user profile. In doing so, the terminal uses profile generation software to save the information to a database.

[0869] Step 2:

[0870] When a user browses interior design products through their device, the device collects emotional data from the user via its built-in camera and microphone. An emotion recognition engine analyzes this data to identify the user's emotional state (e.g., relaxed, excited, surprised). This information is transmitted to the server in real time.

[0871] Step 3:

[0872] The server provides optimal product recommendations based on the emotional state and user profile transmitted from the terminal. Here, a generative AI model is used to apply prompt sentences to identify interior decorations and electrical appliances that suit the user and create recommendation data.

[0873] Step 4:

[0874] The server accesses multiple e-commerce platforms to collect the latest pricing information and product reviews for selected items. This information is used to optimize suggestion data and provide users with the most valuable choices.

[0875] Step 5:

[0876] The generated suggestion data is sent to the device, allowing the user to view it in real time. The device adjusts the UI according to the user's emotions, visually displaying the necessary information. For example, if the user is in a relaxed emotional state, it might increase the details of products that promote restful sleep.

[0877] Step 6:

[0878] The server checks the compatibility of potential purchase items with existing consumer electronics technologies and provides setup instructions to the terminal so that users can easily set them up. Compatibility check software is used to deliver this information to the user.

[0879] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0880] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0881] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0882] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0883] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0884] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0885] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0886] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0887] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0888] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0889] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0890] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0891] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0892] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0893] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0894] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0895] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0896] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0897] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0898] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0899] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0900] The following is further disclosed regarding the embodiments described above.

[0901] (Claim 1)

[0902] A means for automatically obtaining floor plans and spatial information from real estate information sources,

[0903] A means for analyzing acquired floor plans and extracting data on room size and shape,

[0904] A means of collecting user preferences and budgets and generating user profiles,

[0905] A means for selecting the most suitable furniture and home appliances based on a user profile and generating a list of suggestions,

[0906] A means of collecting price information and product reviews from multiple sales platforms and optimizing the suggestion list,

[0907] A means of notifying users of the suggestion list and related information,

[0908] A means of monitoring price fluctuations and inventory status in real time and updating information to users,

[0909] A means to check the compatibility of potential purchase products with existing smart home devices and suggest settings,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, further comprising means for analyzing the user's past purchase history and understanding the user's interior style trends.

[0913] (Claim 3)

[0914] The system according to claim 1, further comprising means for evaluating the cost-effectiveness of products included in the proposal list.

[0915] "Example 1"

[0916] (Claim 1)

[0917] A method for automatically acquiring spatial design information from real estate information sources,

[0918] A means for analyzing acquired spatial design information and extracting information on the dimensions and shape of the section,

[0919] A means of obtaining user preferences and budget, and generating a user profile,

[0920] A means of selecting the most suitable product based on the user profile and generating a list of suggestions,

[0921] A means of collecting price information and product evaluations from multiple supply platforms and optimizing the list of proposals,

[0922] A means of notifying users of the list of proposals and related information,

[0923] A means of monitoring price fluctuations and supply conditions in real time and updating information for users,

[0924] A means to check the compatibility of potential purchase products with existing automated home appliances and to suggest configurations,

[0925] A means of using image analysis technology that enables the omission of unavoidable measurement work,

[0926] A way to securely submit the entered interior design style and budget,

[0927] A means of providing communication operations that allow the proposed product to be purchased directly,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, further comprising means for analyzing the user's past purchase history and understanding the user's interior decoration preferences.

[0931] (Claim 3)

[0932] The system according to claim 1, further comprising means for evaluating the cost-effectiveness of products included in the list of proposals.

[0933] "Application Example 1"

[0934] (Claim 1)

[0935] A means for automatically acquiring spatial data from real estate information sources, analyzing floor plans, and extracting dimensions and structural data of parts,

[0936] A means for collecting user preferences and financial information and generating user profiles,

[0937] A means for searching a database of furniture and fixtures based on a user profile and generating a list of optimal product suggestions,

[0938] A means for collecting price and reputation information from multiple online sales platforms and generating an optimized list of recommendations,

[0939] A means of notifying users of a list of suggestions and related information via a smart device, and assisting them in the purchase process,

[0940] A means of generating prompt messages based on user preferences and supporting the product selection process,

[0941] A means to continuously monitor evaluation results and inventory information and dynamically update the information,

[0942] Means to facilitate integration with smart devices through compatibility checks and setup support,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, further comprising means for analyzing the user's purchase history, understanding the user's interior design preferences, and reflecting that information in a profile.

[0946] (Claim 3)

[0947] The system according to claim 1, further comprising means for evaluating the cost-effectiveness of the product group included in the proposal list and presenting the most effective option.

[0948] "Example 2 of combining an emotion engine"

[0949] (Claim 1)

[0950] A means for automatically acquiring spatial diagrams and spatial data from real estate information sources,

[0951] A method for analyzing acquired spatial maps to extract data on the size and shape of a region,

[0952] A means of generating a user profile by collecting user preferences, budget, and emotional state,

[0953] A means for selecting the most suitable items based on the user profile and generating a list of suggestions,

[0954] A method for optimizing the list of proposals by collecting price information and product reviews from multiple sales locations,

[0955] A means of changing the way information is presented according to the user's emotional state and notifying them of a list of suggestions and related information,

[0956] A means of monitoring price fluctuations and inventory status in real time and updating information for users,

[0957] A means of verifying the compatibility of potential purchase items with existing automated home equipment and proposing configurations,

[0958] A system that includes this.

[0959] (Claim 2)

[0960] The system according to claim 1, further comprising means for analyzing the user's past acquisition history and understanding the user's interior design tendencies.

[0961] (Claim 3)

[0962] The system according to claim 1, further comprising means for evaluating the cost-effectiveness of the items included in the list of proposals.

[0963] "Application example 2 when combining with an emotional engine"

[0964] (Claim 1)

[0965] A means for automatically acquiring spatial arrangement and spatial data from real estate information sources,

[0966] A means for analyzing the acquired spatial arrangement and extracting data on the size and shape of the living space,

[0967] A means of collecting user preferences and budgets and forming user profiles,

[0968] A means for analyzing a user's emotional state using emotion recognition technology, selecting the most suitable interior decorations and electrical appliances along with the profile, and generating suggestion data,

[0969] A means for collecting price information and product evaluations from multiple e-commerce platforms and optimizing proposal data,

[0970] A means of communicating proposed data and related information to users,

[0971] A means of monitoring price fluctuations and supply conditions in real time and updating information for users,

[0972] A means to check the compatibility of potential purchase products with existing consumer electronics technologies and to suggest settings,

[0973] A system that includes this.

[0974] (Claim 2)

[0975] The system according to claim 1, further comprising means for analyzing the user's past purchase history and understanding the user's interior decor style trends.

[0976] (Claim 3)

[0977] The system according to claim 1, further comprising means for evaluating the cost performance of products included in the proposed data. [Explanation of Symbols]

[0978] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for automatically obtaining floor plans and spatial information from real estate information sources, A means for analyzing acquired floor plans and extracting data on room size and shape, A means of collecting user preferences and budgets and generating user profiles, A means for selecting the most suitable furniture and home appliances based on a user profile and generating a list of suggestions, A means of collecting price information and product reviews from multiple sales platforms and optimizing the suggestion list, A means of notifying users of the suggestion list and related information, A means of monitoring price fluctuations and inventory status in real time and updating information to users, A means to check the compatibility of potential purchase products with existing smart home devices and suggest settings, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the user's past purchase history and understanding the user's interior style trends.

3. The system according to claim 1, further comprising means for evaluating the cost-effectiveness of products included in the proposal list.

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