US-12626293-B1 - System and method for real-time augmented reality-based visualization, customization, and transaction of interior design

US12626293B1US 12626293 B1US12626293 B1US 12626293B1US-12626293-B1

Abstract

The invention relates to a software platform designed for real-time augmented reality (AR)-based visualization, customization, and transaction of home furnishings. The platform integrates AR technology with artificial intelligence (AI) and machine learning (ML) to significantly enhance user interaction. The invention provides dynamic virtual product placement, personalized design recommendations, and streamlined transaction processes. The system and methodology of the invention allows users to capture and digitize space dimensions, manipulate virtual furnishings in real-time, and directly purchase integrated designs. By leveraging AI and ML, the platform offers tailored solutions and adaptive functionalities to improve user experience and decision-making in home decor and furnishings.

Inventors

Jessica Mahoney
Geraldine Weiner
Leonard Holzer

Assignees

Jessica Mahoney
Geraldine Weiner
Leonard Holzer

Dates

Publication Date: 20260512
Application Date: 20250612

Claims (20)

1 . A system comprising: a server having memory available for storing user interior design preference data and user demographic data; at least one user device; and computer readable instructions available to the at least one user device and interacting with the server, the instructions operable to collect and store the at least one user's interior design preference data and demographic data on the server, the user device including means for scanning at least one room associated with the user to generate at least a 3D image of the room and physical dimensions of the room including elevation, the scanning means being capable of generating an augmented reality, scaled image of the scanned room including immovable objects and any preexisting movable objects associated with the at least one scanned room, the instructions being further operable to select one of the options of (i) allowing the server to serve at least one furnishing recommendation to the user's device based on the user's interior design preference data and demographic data, and (ii) allowing the user to make a first selection selected from one of (a) removing all preexisting movable objects to create an empty scanned room, (b) rearranging at least one of the preexisting movable objects, and (c) furnishing the empty scanned room based on a library of furnishing options, and the instructions including a generative AI program trained with at least the options selected by the user to refine future recommendations of the user.
2 . The system according to claim 1 , wherein the user demographic data includes data indicative of at least one of user age, gender, income, neighborhood, zip codes.
3 . The system according to claim 1 , wherein the movable objects within the floor plan include objects of furniture and the immovable objects and the immovable objects include at least one of windows, doors, walls, floors and ceilings, both the immovable and movable objects being associated with the scanned room.
4 . The system according to claim 1 , wherein the library of furnishing options is selectable by at least one of the user and the server.
5 . The system according to claim 1 , wherein the at least one user device includes means for permitting user addition and/or subtraction of furnishings to and/or from the at least one scanned room.
6 . A method comprising: storing on a server user interior design preference information and user demographic information; and scanning at least one room associated with a user device to generate at least a 3D image and physical dimensions of the room including elevation, the 3D image including movable and immovable objects and defining a floor plan, the server having access to the least one user device; and optionally selecting one of the options of (i) allowing the server to serve at least one furnishing, a recommended furniture layout having multiple furnishings for the at least one scanned room and (ii) at least one recommended article of furnishing for the at least one scanned room, wherein the option (i) and option (ii) recommendations are generated by an artificial intelligence (AI) model using the interior design preference data and user demographic data, selecting recommended furnishings for the furniture layout to form a furniture rendering, and training the AI model with at least the options selected by the user to refine future recommendations.
7 . The method of claim 6 , wherein the user demographic information data includes data indicative of at least one of user age, gender, income, neighborhood, zip codes.
8 . The method according to claim 6 , wherein the movable objects within the floor plan include objects of furniture and the immovable objects and the immovable objects include at least one of windows, doors, walls, floors and ceilings, both the immovable and movable objects being associated with the scanned room.
9 . The method according to claim 6 , further comprising providing a library of furnishing options generated by the AI model, and selecting between two options (i) a decorated room with recommended furnishings chosen by the AI model and (ii) individual pieces of furnishing recommended by the AI model but chose by the user.
10 . The method according to claim 6 , wherein the computer readable instructions are operable to permit user addition, subtraction and/or placement of furnishings from the 3D image of the scanned room.
11 . The method of claim 6 , further comprising displaying on the at least one user device a rendering of the scanned room with recommended and selected furnishing, and displaying a revised rendering of the scanned room as changes as to furnishings and locations are selected by the user based on server recommendations.
12 . The method of claim 6 , further comprising displaying on the user device initially selected furnishings and selecting alternative furnishings with the user device after the initially displayed furnishings are displayed.
13 . The method of claim 11 , further comprising: displaying on the user device an option menu to accept said first selection or said at least one furnishing selection; and uploading said accepted selection to said server.
14 . The method of claim 6 , further comprising: connecting the user to a vendor of said first selection or said at least one furnishing recommendation and completing a sale and/or delivery.
15 . The method of claim 14 , further comprising establishing an ecommerce link between said user device and said vendor.
16 . The method of claim 15 , wherein said link to said vendor includes communication with a salesperson associated with said vendor.
17 . The method of claim 15 , wherein said link comprises an interface allowing said user to order delivery of said first selection.
18 . The method of claim 11 , further comprising sharing said revised 3D image with one of a person, an electronic device, and an application.
19 . The method of claim 18 , wherein the electronic device is a printer.
20 . An interior design method comprising: collecting information about a user's interior design preferences; storing the user's interior design preferences on a server; scanning a room with a user scanning device to generate scanned room data file which includes a floor plan and a 3-D image of the room having measured dimensions of the room including elevation, all immovable and movable objects within the room; sending the scanned room data file to the server; and sending to the user's device from the server a first furniture layout for the scanned room, the first furniture layout including multiple movable articles of furniture, recommending articles of furniture for the furniture layout based on generative AI model trained at least in part with the user's interior design preferences, selecting recommended movable objects including articles of furniture to create a furniture rendering for the scanned room, optionally reselecting articles of furniture and optionally moving selected articles of furniture within the scanned room, and further training the AI model based on user selections.

Description

BACKGROUND OF THE INVENTION Field of the Invention The present invention pertains to the domain of software applications utilized in the fields of Interior decorating, design and architecture; Furnishing retailers; Art galleries and Museums; Luxury assets (such as yachts, planes, boats etc.) Real estate (such as all spaces, living, amenities, workspaces, showrooms, under Residential, Commercial, Industrial, Hospitality, Brokerage, Developments; as well as home insurance; and high-tech facilities and warehouses. More specifically, the invention relates to a software-based system and methodology that employs augmented reality (AR), artificial intelligence (AI), and machine learning (ML) for the enhancement of visualization, customization, and acquisition processes related to (furniture, lighting, decor, rugs, art, surface materials (such as wall materials, flooring materials, stone, glass, metal, woods, etc.), hardware, cabinetry, millwork, electrical, sound, acoustical equipment & materials, ISP (Internet Service Provider), security equipment (wires, boxes and routers), Heating & Cooling equipment (HVAC) and or any other materials needed to be specified for the design.) 1 Description of the Related Design Traditionally, designing a home or space has been an inefficient and often frustrating process for homeowners and or Owners. Unless they have professional training in interior design, most people struggle to visualize how different furnishings, fabrics, materials, and colors will come together in their space. Historically, homeowners would visit furniture stores, pick up tear sheets with product images and measurements, and maybe even take home small fabric swatches. Then, they would return home and attempt to imagine how these pieces would fit within their space. This process was incredibly limiting-relying on a small piece of fabric and a two-dimensional tear sheet makes it nearly impossible to accurately picture how the final design will look. In the field of interior design, professional designers typically bring samples of fabrics and other materials and rely on the imagination of the customer to imagine what walls, surfaces, furnishings, carpets and drapes would look like in a particular room or area. To make matters more complicated, homeowners would have to measure their space manually, using a tape measure to determine whether a piece of furniture would fit. However, the majority of people struggle with spatial visualization, making it easy to miscalculate or misunderstand proportions. This often results in frustration, costly mistakes, and frequent returns when furniture doesn't fit as expected. Beyond the challenge of visualization, the traditional process requires extensive research and shopping. Homeowners must visit multiple local furniture stores, browse countless websites, and sift through an overwhelming number of options to find pieces that match their style and budget. Even after all this effort, they still risk making choices that don't work together cohesively. Another traditional approach is hiring an interior designer. In this case, the designer would visit the homeowner's space, assess their needs, and guide them through the shopping process by introducing them to stores that match their style and budget. The designer would accompany them while shopping, helping them select furniture and materials. Once the homeowner has an idea of their preferred pieces, the designer would return to their home to manually measure the space. These measurements would then be entered into AutoCAD or another design software back at the designer's office. Using this information, the designer would create a few expert layouts, ensuring that the furniture is properly scaled and arranged for optimal functionality and aesthetics. From there, the designer would develop a rendering-a visual representation of how the space will look with the selected furniture, to scale, within the homeowner's actual space. This is often the first point in the process where the homeowner can truly see how everything will come together in a professional, cohesive way. At this stage, the homeowner and designer may go back and forth, refining the layout and adjusting based on feedback. Once the homeowner approves the final design, the designer assists with purchasing the furniture and coordinating delivery. While this process results in a professionally designed space, it is time-consuming, expensive, and requires multiple back-and-forth steps, making it inaccessible for many homeowners. A need exists for a better way for interior designers to work with clients to obtain their design goals and aspirations faster and more efficiently. SUMMARY OF THE INVENTION The invention includes a software platform for interactive augmented reality (AR) design. The platform integrates AR technology with artificial intelligence (AI) and machine learning (ML) to enhance user experience in virtual product placement, design recommendations, and tran