System and method for analyzing architecture of structure

Abstract

A system and method configured to determine aspects of a structure. The systems and methods include an XR architecture analysis device including one or more sensors configured to detect aspects of a structure. The XR architecture analysis device is configured to output a signal including data related to aspects of the structure. The control unit is in communication with the XR architecture analysis device. The control unit is configured to receive the signal and determine aspects of the structure based on the data.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to systems and methods for analyzing the architecture of a structure, such as a room within a residence or commercial building. Background Art

[0002] Various buildings include components that are inspected during and after construction. For example, residential and commercial buildings include rooms that are inspected to determine certain components within the walls, floors, ceilings, etc.

[0003] Certain hand tools can be used to measure objects, find studs within a structure, structural supports, etc. Given the cost of most construction projects, most methods for analyzing a room seek to minimize cost. A smartphone application can be used to use the smartphone's camera to help estimate room dimensions. As another example, a smartphone's magnetometer can be used to help locate wall studs. As another example, certain peripherals of a smartphone can be used to provide information about the subsurface location of building elements.

[0004] As another example, a light detection and ranging (LIDAR) system can be mounted to the top of a tripod and provide specific details of a room. However, LIDAR systems are relatively expensive, bulky, and may operate for a relatively long period of time. Summary of the invention

[0005] There is a need for a system and method for efficiently and effectively analyzing a structure, such as a room within a building. In view of this need, certain examples of the present disclosure provide a system configured to determine aspects of a structure. The system includes an architectural analysis device including one or more sensors configured to detect aspects of the structure. The architectural analysis device is configured to output a signal including data related to the aspects of the structure. A control unit communicates with the architectural analysis device. The control unit is configured to receive the signal and determine aspects of the structure based on the data.

[0006] The system may further comprise a user interface comprising a display. The control unit is configured to show aspects of the structure on the display.

[0007] The architecture analysis device may be separate and distinct from the control unit.Alternatively, the architecture analysis device may include the control unit.

[0008] In at least one example, the architecture analysis device is an XR device. The XR device is one of a mixed reality device, a virtual reality device, or an augmented reality device.

[0009] In at least one example, the control unit is further configured to generate a three-dimensional (3D) model of the structure based on the data.

[0010] In at least one example, the control unit is further configured to determine the position of one or more components of the structure based on the distance between the components detected by the architecture analysis device. For example, the one or more components include a column, and the component includes one or both of a switch or an outlet.

[0011] The one or more sensors may include an acoustic sensor such as a microphone array.

[0012] In at least one example, the control unit is further configured to identify a load-bearing wall based on the data.

[0013] The control unit may be an artificial intelligence or machine learning system.

[0014] The architecture analysis device may include headphones, glasses, eyepieces, a harness, a wand, a stand, and / or a mobile subsystem.

[0015] Certain examples of the present disclosure provide a method for determining aspects of a structure. The method includes: detecting aspects of a structure by an architecture analysis device including one or more sensors; outputting a signal including data related to the aspects of the structure by the architecture analysis device; receiving the signal by a control unit in communication with the architecture analysis device; and determining aspects of the structure by the control unit based on the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic block diagram of a system for analyzing a structure according to an example of the present disclosure is shown.

[0017] Figure 2 A simplified block diagram of an architectural analysis device according to an example of the present disclosure is shown.

[0018] Figure 3 A simplified top view of a structure according to an example of the present disclosure is shown.

[0019] Figure 4 A simplified top view of a structure according to an example of the present disclosure is shown.

[0020] Figure 5 A simplified front view of a wall within a structure according to an example of the present disclosure is shown. DETAILED DESCRIPTION

[0021] It will be readily understood that, in addition to the described exemplary embodiments, the components of the embodiments as generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following more detailed description of the exemplary embodiments as illustrated in the drawings is not intended to limit the scope of the claimed embodiments, but merely represents example embodiments.

[0022] Throughout this specification, references to "one embodiment" or "an embodiment" (etc.) mean that a particular component, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment. Thus, throughout this specification, the phrases "in one embodiment," "in an embodiment," etc., appearing in various places, do not necessarily all refer to the same embodiment.

[0023] In addition, the described components, structures or characteristics can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to give a thorough understanding of various embodiments. However, those skilled in the relevant art will recognize that various embodiments can be practiced without one or more of the specific details, or using other methods, parts, materials, etc. In other examples, well-known structures, materials or operations are not shown or described in detail to avoid confusion. The following description is intended to be used as an example only, and some example embodiments are simply shown.

[0024] Figure 1 A schematic block diagram of a system 100 for analyzing a structure 102 according to an example of the present disclosure is shown. In at least one example, the structure 102 is a room within a building, such as a residence or a commercial building. The structure 102 includes a floor 104, one or more walls 106, and a ceiling 108. An interior space 109 is defined between the floor 104, the walls 106, and the ceiling 108. Optionally, for example, the structure 102 may not include a ceiling. The structure 102 may or may not be enclosed.

[0025] The system 100 includes an architecture analysis device 110 that communicates with a control unit 112, for example, via one or more wired or wireless connections. The control unit 112 is coupled to a memory 124, for example, via one or more wired or wireless connections. The control unit 112 may be separate and distinct from the memory 124. Optionally, the control unit 112 includes the memory 124.

[0026] The control unit 112 also communicates with the user interface 114, for example, via one or more wired or wireless connections. The user interface 114 includes a display 116 and an input device 118. For example, the display 116 is an electronic monitor, a television, etc., and the input device 118 includes one or more of a keyboard, a mouse, a stylus, etc. In at least one example, the display 116 and the input device 118 are integrated as a touch screen interface. In at least one example, the user interface 114 is a computer workstation. As another example, the user interface 114 is a handheld device such as a smart phone, a smart tablet, etc.

[0027] As shown, the architecture analysis device 110 can be separate and distinct from the control unit 112 and the user interface 114. In at least one example, the architecture analysis device 110, the control unit 112, and the user interface 114 are within the interior space 109 of the structure 102. As another example, the control unit 112 and the user interface 114 can be outside of the interior space 109, such as in another room. In at least one other example, the architecture analysis device 110 includes the control unit 112 and the user interface 114. For example, a housing such as a workstation, a handheld device, a headset, a band, etc. can include the architecture analysis device 110, the control unit 112, and the user interface 114.

[0028] In at least one example, the architecture analysis device 110 is an XR device. The XR device can be a mixed reality device, a virtual reality device, or an augmented reality device. The XR device has a special perception of the surrounding environment and has one or more sensors configured to approximate the distance, angle, and measurement of points within the field of view. The XR device is also configured to record data and / or view objects within the structure 102.

[0029] In at least one example, the architecture analysis device 110 is an XR device that includes one or more sensors 120 and a viewer 122. The sensor 120 may include one or more of an acoustic sensor (e.g., one or more ultrasound detectors, one or more microphones, etc.), an optical sensor (e.g., a camera, an infrared detector, a LIDAR sensor, one or more lasers, etc.), a pressure sensor, etc. The viewer 122 may be separate and distinct from the sensor 120. The viewer 122 may be a video camera, an infrared camera, etc. Optionally, the viewer 122 may be the sensor 120.

[0030] The architecture analysis device 110 may be operated by an individual to detect various components of the structure 102. As an example, the architecture analysis device 110 may include headphones worn by an individual within the structure 102. Alternatively, the architecture analysis device 110 may be a handheld device. As another example, the architecture analysis device 110 may be a fixed system such as mounted on a stand, such as a tripod.

[0031] In operation, the architecture analysis device 110 is manipulated, moved, etc. to view various components within the structure 102, such as the wall 106, the floor 104, and / or the ceiling 108. The viewer 122 is configured to view and output image data of the various components. As an example, if the architecture analysis device 110 is viewing a wall 106 having a light switch 107 and a socket 111, one or more sensors 120 can measure the distance between the various components. The control unit 112 receives a signal including the distance data from the sensor 120. In response, the control unit 112 then determines (e.g., via derivation) which side of the column 113 in the wall 106 is located on the light switch 107 and / or the socket 111. For example, the memory 124 stores building specification data, which includes information about the position of various components relative to other components. The control unit 112 retrieves the building specification data from the memory 124. As an example, the building code may specify that switches and sockets are to be fixed to the column. Such information is stored in the building specification data in the memory 124. Some types of construction are "16 on center" or "24 on center" (related to inches between each stud and measured from the middle of the stud). Thus, when the architecture analysis device 110 acquires an image of the switch 107 and the receptacle 111 on the wall 106, the architecture analysis device 110 determines the location of the stud 113, for example, from the building code data in the memory 124.

[0032] In at least one example, the architecture analysis device 110 is an XR device that acquires images of various components of the structure 102. After the architecture analysis device 110 acquires images of various components within the structure 102, the control unit 112 identifies the components through the data stored in the memory 124 and the generated three-dimensional (3D) model of the structure 102. In this way, the control unit 112 can generate a virtual 3D indoor space model including one or more structures, such as the structure 102.

[0033] In response to generating the 3D model of the structure 102, the control unit 112 outputs a model signal to the user interface 114. The model signal includes data about the 3D model. The control unit 112 can then display the 3D model on the display 116 via the model signal. The model signal can also include information related to the distance between components, the position of the components, etc., which can also be displayed on the display in the form of graphics, text, etc.

[0034] In at least one example, multiple architectural analysis devices 110, such as multiple XR devices, may be used to provide information about the structure 102. Information from the architectural analysis devices 110 may be received by the control unit 112 and integrated to provide a unified view of the various components within the structure 102, which may then be shown on the display 116. For example, two different architectural analysis devices 110 may operate on opposite sides of any given wall. Information obtained from the different architectural analysis devices 110 may be received and analyzed by the control unit 112 to generate a 3D model with increased accuracy.

[0035] As described, the sensor 120 may include an acoustic sensor such as a microphone array. The microphone array may be operated to help locate components hidden in the floor 104, wall 106, or ceiling 108, such as pipes for the flow of air conditioning coolant, water, sewage, and drain water, by using directional sound positioning. As an example, a toilet may be flushed, and the microphone array may detect an audio signal to determine where the water is flowing within the wall. The control unit 112 receives such a signal from the microphone array, and the location of the pipes within the floor 104, wall 106, and / or ceiling 108 may then be determined. As another example, the air conditioner may be started, and the microphone array detects an audio signal of the location where the coolant line runs, which may then be determined by the control unit 112.

[0036] The 3D model generated by the control unit 112 may include information about well-known and shared building standards. In this way, the 3D model may be analyzed to identify how the structure may be built.

[0037] The control unit 112 may also identify load-bearing walls based on data stored in the memory 124. Such data may include material lengths, locations of walls, and / or components within the structure 102. The control unit 112 may also analyze the data stored in the memory 124 to identify stud spacing by placement of outlets, switches, or components that protrude joists and nail pops. In addition, the control unit 112 may analyze the data stored in the memory 124 to determine directions that floor or ceiling support beams may travel, and / or plumbing and electrical components within the floor 104, wall 106, and / or ceiling 108.

[0038] In at least one example, the 3D model of the structure 102 generated by the control unit 112 can be mapped with an image acquired by the viewer 122 (e.g., within an XR headset or an XR-enabled device) to provide a physical view with properties that can be shown in relation to the virtual 3D model. The control unit 112 can also provide markings (e.g., graphics, text, etc.) on the 3D model and / or image to provide information about the design of the structure 102.

[0039] In at least one example, the 3D model generated by the control unit 112 can be enhanced by one or more additional devices, such as a submersible camera / snake camera that can be pushed into a smaller location that the architectural analysis device 110 may not fit. In at least one example, the control unit 112 can generate and provide a video stream to a display of the architectural analysis device (e.g., a display within an XR headset) and / or the display 116 to show the in-wall location of pipes, wires, or other architectural details such as structural supports.

[0040] As described herein, examples of the present disclosure provide a system 100 configured to determine aspects of a structure 102. The system includes an architecture analysis device 110, which includes one or more sensors 120 configured to detect aspects of the structure 102. The architecture analysis device 110 is configured to output a signal including data related to the aspects of the structure 102. A control unit 112 communicates with the architecture analysis device 110. The control unit 112 is configured to receive the signal and determine the aspects of the structure 102 through analysis of the data. The aspects may include the size of the room (e.g., length, width, height), the size and shape of the floor 104, walls 106, and ceiling 108, the location of various components within a portion of the structure 102 (e.g., switch 107, outlet 111, column 113), etc.

[0041] As used herein, the terms "control unit," "central processing unit," "CPU," "computer," and the like may include any processor-based or microprocessor-based system, including systems using microcontrollers, reduced instruction set computers (RISC), application specific integrated circuits (ASICs), logic circuits, and any other circuits or processors, including hardware, software, or a combination thereof, capable of performing the functions described herein. These are exemplary only, and thus are not intended to limit the definition and / or meaning of such terms in any way. For example, as described herein, the control unit 112 may be or include one or more processors configured to control operations.

[0042] The control unit 112 is configured to execute instruction sets stored in one or more data storage units or elements (e.g., one or more memories) to process data. For example, the control unit 112 may include or be coupled to one or more memories. The data storage unit may also store data or other information as desired or required. The data storage unit may be in the form of an information source or a physical memory element within a processing machine.

[0043] The instruction set may include various commands that instruct the control unit 112 as a processing machine to perform specific operations of the methods and processes of various embodiments of the subject matter described herein. The instruction set may be in the form of a software program. The software may be in various forms such as system software or application software. In addition, the software may be in the form of a collection of separate programs, a subset of programs within a larger program, or a part of a program. The software may also include modular programming in the form of object-oriented programming. The processing machine may process input data in response to user commands, or in response to the results of previous processing, or in response to a request made by another processing machine.

[0044] The figures of the embodiments of this paper may show one or more control units or processing units such as control unit 112. It should be understood that the processing unit or control unit may represent a circuit, circuit system or part thereof, which may be implemented as hardware with associated instructions (e.g., software stored on a tangible and non-transient computer-readable storage medium such as a computer hard drive, ROM, RAM, etc.), which performs the operations described herein. The hardware may include a hard-wired state machine circuit system that performs the functions described herein. Alternatively, the hardware may include an electronic circuit that includes and / or is connected to one or more logic-based devices such as a microprocessor, a processor, a controller, etc. Alternatively, the control unit 112 may represent a processing circuit system such as one or more of a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a microprocessor, etc. The circuits in various embodiments may be configured to execute one or more algorithms to perform the functions described herein. Whether or not explicitly identified in a flowchart or method, one or more algorithms may include aspects of the embodiments disclosed herein.

[0045] As used herein, the terms "software" and "firmware" are interchangeable and include any computer program stored in a data storage unit (e.g., one or more memories) for execution by a computer, the one or more memories including RAM memory, ROM memory, EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory. The above data storage unit types are exemplary only, and are therefore not limited to the types of memories that can be used to store computer programs.

[0046] In at least one example, all or part of the systems and methods described herein may be or otherwise include an artificial intelligence (AI) or machine learning system that can automatically perform the operations of the methods also described herein. For example, the control unit 112 may be an artificial intelligence or machine learning system. For example, these types of systems may be trained and / or self-trained based on external information to repeatedly improve the information shown on the display 116. The control unit 112 may determine the positions of the components and components within the structure 102 via artificial intelligence and / or machine learning. Over time, these systems may be improved by matching records with increased accuracy and speed, thereby significantly reducing the likelihood of any potential errors. The AI ​​or machine learning systems described herein may include techniques implemented by adaptive predictive capabilities, and exhibit at least some degree of autonomous learning to automate and / or enhance pattern detection (e.g., identifying irregularities or regularities in data), customization (e.g., generating or modifying rules to optimize record matching), etc. Feedback from one or more previous analyses of samples and / or data may be used to train and retrain the system. Based on the feedback, the system may be trained by adjusting one or more parameters, weights, rules, criteria, etc. used in the analysis of the same or other samples. This process can be performed using generated data instead of training data, and can be repeated multiple times to repeatedly improve the relevance of the commands. The training of the record matching system minimizes false positives and / or false negatives by performing an iterative training algorithm in which the system is retrained using an updated data set and based on feedback examined prior to the most recent training of the system. This provides a robust analytical model that can better determine components, locations of components, distances between components, etc.

[0047] Figure 2 A simplified block diagram of an architecture analysis device according to an example of the present disclosure is shown. Headset 110a is an example of an architecture analysis device. Headset 110a is configured to be worn by an individual. In at least one example, headset 110a is an XR headset.

[0048] The glasses 110b are an example of an architecture analysis device. The glasses 110b are configured to be worn by an individual. In at least one example, the glasses 110b are XR glasses.

[0049] Eyepiece 110c is an example of an architectural analysis device. Eyepiece 110c is configured to be worn by an individual. In at least one example, eyepiece 110c is an XR eyepiece.

[0050] Band 110d is an example of an architectural analysis device. Band 110d is configured to be worn by an individual. In at least one example, band 110d is an XR band.

[0051] The wand 110e is an example of an architectural analysis device. The wand 110e is configured to be held and manipulated by an individual. In at least one example, the wand 110e is an XR wand.

[0052] The stand 110f is an example of an architectural analysis device. The stand 110f is configured to be placed on a structure and supported on a floor. The stand 110f can be, for example, a tripod. The stand 110f can include one or more actuators configured to automatically move a viewer, sensor, etc. In at least one example, the stand 110f is an XR stand.

[0053] The mobile subsystem 110g is an example of an architecture analysis device. The mobile subsystem 110g may include a conveying tool such as one or more wheels, tracks, etc., a navigation subsystem, etc. configured to allow the mobile subsystem 110g to automatically move throughout the structure. As described herein, the mobile subsystem 110g also includes sensors and viewers. In at least one example, the mobile subsystem 110g is a robot. In at least one example, the mobile subsystem 110g is an XR mobile subsystem.

[0054] In at least one example, the architecture analysis device includes one or more of earphones 110a, glasses 110b, eyepieces 110c, straps 110d, wands 110e, stands 110f, and / or mobile subsystems 110g.

[0055] Figure 2 An example of an architecture analysis device is shown. Figure 2 The examples shown in are non-limiting. Other types of architectural analysis devices may be used.

[0056] Figure 3 A simplified top view of a structure 102 according to an example of the present disclosure is shown. Figure 1 and Figure 2 , an individual 200 within the interior space 109 of the structure 102 has an architecture analysis device 110. For example, the individual 200 may wear the architecture analysis device 110, which may be an XR headset.

[0057] Individual 200 moves throughout enclosure 109, causing architecture analysis device 110 to acquire data about structure 102, such as through sensor 120 and viewer 122. In this manner, data acquired by architecture analysis device 110 is received by control unit 112, which then determines the size of structure 102 from the received data. By retrieving data about structure 102 stored in memory 124 (e.g., building code data, architectural data, etc.), control unit 112 can then determine the orientation of materials within various structures (e.g., floor 104, wall 106, and / or ceiling 108) to determine the location of load-bearing walls.

[0058] As an example, data stored in memory 124 may indicate that the maximum length of wooden materials in a horizontal layout is approximately 16 feet to 20 feet, depending on the width and depth of the wood. Based on this material knowledge, control unit 112 is able to determine that one or more of walls 106 are load bearing because, as indicated in the stored data, if beams or supports are required every 16 inches, the beams are not long enough to span a 40 foot room without extreme lengths of wooden materials or wider materials (such as steel). The standard distance between supports in floors, walls, and ceilings may be 16 inches, which is referred to as "16 on center." As another example, some buildings may use walls that are "24 on center."

[0059] Figure 4 A simplified top view of a structure 102 according to an example of the present disclosure is shown. Figure 1 and Figure 4 In at least one example, where structure 102 exhibits support beams 210 in ceiling 108 running from left to right (as detected by architectural analysis device 110 operated by individual 200), control unit 112 retrieves building code and / or architectural data within memory 124 and, therefore, determines that all four walls 106 are load-bearing because the left and right walls will support the ends of horizontal beams and floor support joists for the top and bottom areas of the ceiling.

[0060] Figure 5 A simplified front view of a wall 106 within a structure 102 is shown according to an example of the present disclosure. Figure 1 and Figure 5 , the architecture analysis device 110 obtains data indicating that the wall 106 includes electrical outlets 111 spaced every 6 feet above the floor line 105. Based on the data stored in the memory 124, the control unit 112 determines the presence of the stud 113 behind the wall 106. Based on the data stored in the memory 124, the control unit 112 also determines, for example based on the "center distance 16" or "center distance 24" rule (as stored in the memory 124) that in the absence of some other structural elements, a normal 40 foot by 16 foot size room as shown has the stud 113 located at the indicated location. One of the sensors 120 can be an infrared laser array that is used to detect defects in the surface of the wall 106 to detect locations where drywall can be joined together (edges nailed to studs in the wall), and / or provide other visual indications, such as a barely noticeable "nail bump", to identify stud locations.

[0061] In at least one example, the architecture analysis device 110 detects, via the one or more sensors 120, that the distance d1 from the first side of the structure to the first outlet 111a is 29 inches, and the distance d2 from the second side of the room to the final outlet 111n is 35 inches. Based on the data stored in the memory 124, the control unit 112 determines that the structure 102 uses a "16-center" column configuration, and is therefore able to determine the position of each of the columns 113.

[0062] Reference Figures 1 to 5 , the system 100 can be used to determine plumb, square, or level indications within the structure 102. For example, the sensors 120 can include optical sensors such as infrared laser arrays and gyroscopic sensors, which can help engineers understand sagging, tilting, and settling issues with a building that have developed over time or were introduced during previous construction. This information can be used to understand if floors need to be inspected for termites, rot, or incorrect floor deflection calculations (e.g., the wrong width beam or height beam was used for room size) and help identify changes that may be needed to correct such problems. In some locations, the tilt of the floor is acceptable within certain thresholds, where other locations may require correction if that portion of the building is being remodeled or constructed to pass a building inspection.

[0063] System 100 can be used to enhance wiring diagrams based on electrical outlet and switch placement and proximity to water sources. If within a certain distance of a water source, the electrical code can indicate the type of circuit to use for outlet 111. For example, outlets in a kitchen or bathroom are often part of a circuit that contains a GFI / GFCI circuit to prevent water from causing a short circuit. Such information can be used to highlight and / or outline the outlets and estimated wiring locations presented on the wall where the wires may be located using a color indication of the normal circuit associated with the GFI / GFCI circuit.

[0064] The system 100 may also be used to provide material calculation estimates based on the 3D model generated by the control unit 112. Sizing may be used to calculate cost estimates depending on the type of work being performed (e.g., area of ​​wall for painting or wallpapering, amount of drywall in a restoration job, and square feet of floor area for carpet or hardwood flooring). Sizing may also be used to calculate HVAC airflow parameters for air exchange requirements for air conditioning systems, which may be required during installation, replacement, and system verification if the installation is suspected to be oversized or undersized. The calculation takes into account the size of the room, and also takes into account the number of windows, type of windows, and thickness of the walls, which helps define the total weight of the unit, ductwork size, and possible area.

[0065] The system 100 can also be used to convert a 3D model into a blueprint. An existing house structure may not have blueprints. These blueprints are either not provided to the homeowner, or are lost or thrown away at some point in time. As described herein, the control unit 112 can generate a 3D model to help generate blueprints for modification by an architect or general contractor to provide information for a remodel, expansion, or restoration job.

[0066] As described herein, examples of the present disclosure provide systems and methods for generating a 3D model of a structure (e.g., an interior compartment model) having contextual clues obtained from visual indications and measurements to identify structural details. The control unit 112 can enhance the 3D model with details and metadata within the walls, floors, and ceilings. The 3D model can be used to provide architectural drawings and blueprints, material volume / area estimates, and the types of materials used to build the structure. The control unit 112 can analyze the building standards or specification data and the generated 3D model of the structure 102 to visually indicate how the structure 102 is most likely to be built, wired, and piped without causing destructive changes to the structure 102. The data stored in the memory 124 can include material information to identify the products used in the construction.

[0067] In addition, the present disclosure includes implementations according to the following clauses:

[0068] Clause 1. A system configured to determine aspects of a structure, the system comprising:

[0069] an architectural analysis device comprising one or more sensors configured to detect aspects of the structure, wherein the architectural analysis device is configured to output a signal comprising data related to aspects of the structure; and

[0070] A control unit is in communication with the architectural analysis device, wherein the control unit is configured to receive the signal and determine aspects of the structure based on the data.

[0071] Clause 2. The system of clause 1, further comprising a user interface comprising a display, wherein the control unit is configured to show aspects of the structure on the display.

[0072] Clause 3. The system of clause 1 or 2, wherein the architecture analysis device is separate and distinct from the control unit.

[0073] Clause 4. The system of any one of clauses 1 to 3, wherein the architecture analysis device comprises the control unit.

[0074] Clause 5. The system of any one of clauses 1 to 4, wherein the architecture analysis device is an XR device, and wherein the XR device is one of a mixed reality device, a virtual reality device, or an augmented reality device.

[0075] Clause 6. The system according to any one of clauses 1 to 5, wherein the control unit is further configured to generate a three-dimensional (3D) model of the structure based on the data.

[0076] Clause 7. The system of any one of clauses 1 to 6, wherein the control unit is further configured to determine a position of one or more components of the structure based on distances between components detected by the architectural analysis device.

[0077] Clause 8. The system of Clause 7, wherein the one or more members comprise a column, and wherein the component comprises one or both of a switch or a socket.

[0078] Clause 9. The system of any one of clauses 1 to 8, wherein the one or more sensors comprises a microphone array.

[0079] Clause 10. The system of any one of clauses 1 to 9, wherein the control unit is further configured to identify a load-bearing wall from the data.

[0080] Clause 11. A system according to any one of clauses 1 to 10, wherein the control unit is an artificial intelligence or machine learning system.

[0081] Clause 12. The system of any one of clauses 1 to 11, wherein the architecture analysis device comprises one or more earphones, glasses, eyepieces, belts, wands, stands, or mobile subsystems.

[0082] Clause 13. A method for determining aspects of a structure, the method comprising:

[0083] monitoring various aspects of the structure using an architectural analysis device including one or more sensors;

[0084] outputting, by the architectural analysis device, a signal comprising data relating to aspects of the structure;

[0085] receiving the signal by a control unit in communication with the architectural analysis device; and

[0086] Aspects of the structure are determined by the control unit based on the data.

[0087] Clause 14. The method of clause 13, further comprising displaying, by the control unit, aspects of the structure on a display of a user interface.

[0088] Clause 15. The method of clause 13 or 14, wherein the architecture analysis device is separate and distinct from the control unit.

[0089] Clause 16. The method of any one of clauses 13 to 15, wherein the architecture analysis device comprises the control unit.

[0090] Clause 17. The method of any one of clauses 13 to 16, wherein the architecture analysis device is an XR device, and wherein the XR device is one of a mixed reality device, a virtual reality device, or an augmented reality device.

[0091] Clause 18. The method according to any one of clauses 13 to 17, further comprising generating, by the control unit, a three-dimensional (3D) model of the structure based on the data.

[0092] Clause 19. The method of any of clauses 13 to 18, wherein the determining comprises determining a position of one or more components of the structure based on distances between components detected by the architectural analysis device.

[0093] Clause 20. The method of Clause 19, wherein the one or more members comprise a column, and wherein the component comprises one or both of a switch or a socket.

[0094] As described herein, examples of the present disclosure provide systems and methods for efficiently and effectively analyzing structures, such as rooms within a building.

[0095] Although various spatial and directional terms such as top, bottom, lower, middle, lateral, horizontal, vertical, front, etc. may be used to describe embodiments of the present disclosure, it should be understood that such terms are used only with respect to the orientations shown in the accompanying drawings. The orientation may be reversed, rotated, or otherwise changed so that an upper portion is a lower portion (and vice versa), horizontal becomes vertical, etc.

[0096] As used herein, a structure, limitation, or element "configured to" perform a task or operation is specifically structurally formed, constructed, or adapted in a manner corresponding to the task or operation. For purposes of clarity and avoidance of doubt, an object that is merely capable of being modified to perform a task or operation is not "configured to" perform a task or operation as used herein.

[0097] It should be understood that the above description is intended to illustrate rather than limit. For example, the above embodiments (and / or aspects thereof) can be used in combination with each other. In addition, without departing from the scope of the present disclosure, many modifications can be made to adapt specific situations or materials to the teachings of the various embodiments of the present disclosure. Although the types and sizes of the materials described herein are intended to limit the parameters of the various embodiments of the present disclosure, these embodiments are by no means restrictive, but exemplary embodiments. After reviewing the above description, many other embodiments will be obvious to those skilled in the art. Therefore, the scope of the various embodiments of the present disclosure should be determined with reference to the attached claims and the full scope of equivalents given by such claims. In the attached claims and the specific embodiments herein, the terms "including" and "in which" are used as the common English equivalents of the corresponding terms "comprising" and "wherein". In addition, the terms "first", "second" and "third" etc. are used only as labels and are not intended to impose numerical requirements on their objects. Furthermore, the appended claim limitations are not drafted in a means-plus-function format and are not intended to be interpreted based on 35 U.S.C. §112(f) unless and until such claim limitations expressly use the phrase "means for..." followed by a recitation of the function without further structure.

[0098] This written description uses examples to disclose various embodiments of the disclosure, including the best mode, and also to enable any person skilled in the art to practice the various embodiments of the disclosure, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the various embodiments of the disclosure is defined by the claims, and may include other examples that occur to those skilled in the art. If an example has structural elements that do not differ from the literal language of the claims, or if an example includes equivalent structural elements that do not differ substantially from the literal language of the claims, such other examples are intended to be within the scope of the claims.

Claims

1. A system configured to determine aspects of a structure, the system comprising: an architectural analysis device comprising one or more sensors configured to detect aspects of the structure, wherein the architectural analysis device is configured to output a signal comprising data related to aspects of the structure; and A control unit is in communication with the architectural analysis device, wherein the control unit is configured to receive the signal and determine aspects of the structure based on the data.

2. The system of claim 1, further comprising a user interface comprising a display, wherein: The control unit is configured to show aspects of the structure on the display.

3. The system according to claim 1, wherein: The architecture analysis device is separate and distinct from the control unit.

4. The system according to claim 1, wherein: The architecture analysis device includes the control unit.

5. The system according to claim 1, wherein: The architecture analysis device is an XR device, and wherein the XR device is one of a mixed reality device, a virtual reality device, or an augmented reality device.

6. The system according to claim 1, wherein: The control unit is further configured to generate a three-dimensional model of the structure based on the data.

7. The system according to claim 1, wherein: The control unit is further configured to determine a position of one or more components of the structure based on distances between components detected by the architectural analysis device.

8. The system according to claim 7, wherein: The one or more members include a column, and wherein the component includes one or both of a switch or a socket.

9. The system according to claim 1, wherein: The one or more sensors include a microphone array.

10. The system according to claim 1, wherein: The control unit is further configured to identify a load-bearing wall based on the data.

11. The system according to claim 1, wherein: The control unit is an artificial intelligence or machine learning system.

12. The system of claim 1, wherein: The architectural analysis device includes one or more headphones, glasses, eyepieces, belts, sticks, stands, or mobile subsystems.

13. A method for determining aspects of a structure, the method comprising: monitoring various aspects of the structure using an architectural analysis device including one or more sensors; outputting, by the architectural analysis device, a signal comprising data relating to aspects of the structure; receiving the signal by a control unit in communication with the architecture analysis device; as well as Aspects of the structure are determined by the control unit based on the data.

14. The method of claim 13, further comprising showing, by the control unit, aspects of the structure on a display of a user interface.

15. The method according to claim 13, wherein: The architecture analysis device is separate and distinct from the control unit.

16. The method according to claim 13, wherein: The architecture analysis device includes the control unit.

17. The method according to claim 13, wherein: The architecture analysis device is an XR device, and wherein the XR device is one of a mixed reality device, a virtual reality device, or an augmented reality device.

18. The method of claim 13, further comprising generating, by the control unit, a three-dimensional model of the structure based on the data.

19. The method according to claim 13, wherein: The determining includes determining a location of one or more components of the structure based on distances between components detected by the architectural analysis device.

20. The method according to claim 19, wherein: The one or more members include a column, and wherein the component includes one or both of a switch or a socket.

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