Positioning method, device, generating and display device, and proposal system for visual data of a building

Abstract

Embodiments of the present application provide a positioning method, device, generation and display device, and proposal system for visual data of a building, the positioning method comprising: obtaining position information related to a first position in need of modification in a target system of the building and first visual data of the building; determining a processing node associated with the position information based on a first artificial intelligence model; in the processing node, determining position reference information of a second position in the first visual data associated with the position information in the first visual data based on a second artificial intelligence model; the position reference information is reference information for positioning the first position in need of modification in the target system in the second position in the first visual data. Thus, the position of the position in need of modification in the target system of the building in the existing first visual data of the building can be accurately determined, so that the visual data of the target system including the position in need of modification can be accurately generated based on the position.

Description

Technical Field

[0001] This invention relates to the field of building management, and in particular to a method, apparatus, generation and display device, and proposal system for locating visual data of buildings. Background Technology

[0002] As buildings become increasingly intelligent and user demands grow, the types and number of configurable systems and the number of devices within those systems are also increasing, making building design data complex and voluminous.

[0003] In smart building proposals, the building design data is complex and voluminous, leading to low efficiency, high cost, and a high risk of errors in manually designing proposal materials. Furthermore, because some clients are unfamiliar with building design, they may find it difficult to clearly express their renovation needs, resulting in proposal materials that fail to meet the actual needs of users. This reduces client satisfaction with the proposal materials and affects the success rate of the proposal and the user experience.

[0004] To address the aforementioned issues, automated proposal technologies for building design have been proposed, such as: ① generating proposal materials based on text and fixed templates (e.g., PPT templates); ② using artificial intelligence models to automatically understand customer needs and generate proposal content.

[0005] It should be noted that the above description of the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of the present invention and facilitating understanding by those skilled in the art. It should not be assumed that the above technical solutions are known to those skilled in the art simply because they have been described in the background section of this invention. Summary of the Invention

[0006] The inventors discovered that, regarding the aforementioned prior art ①, namely the prior art that generates proposal materials based on text and fixed templates, although it achieves proposal automation, it cannot establish a connection between the generated proposal materials and the building's design data. Therefore, it cannot match the customer's needs with the location in the building's design data, which is not conducive to the customer's intuitive and quick understanding of the proposal content. As for the aforementioned prior art ②, namely the prior art that uses artificial intelligence models to automatically understand customer needs and generate proposal content, although it can generate relatively accurate proposal content, when faced with complex building design data, relying solely on the capabilities of the artificial intelligence model itself still cannot accurately match the locations that need to be modified in the customer's needs with the locations in the building's design data. This results in a large deviation between the locations in the generated design data and the locations that need to be modified in the customer's needs, thereby affecting the proposal success rate and user experience.

[0007] To address one or more of the aforementioned problems, embodiments of the present invention provide a method, apparatus, generation and display device, and proposal system for locating visual data of buildings. This system can accurately determine the location of the area to be modified in the target system of a building within the existing first visual data of the building. In other words, it achieves accurate location of the area to be modified within the first visual data of the building, thereby enabling accurate generation of visual data in the target system including the area to be modified based on that location.

[0008] According to a first aspect of the present invention, a method for locating visual data of a building is provided. The method includes: acquiring location information related to a first location in a target system of the building that needs to be modified, and first visual data of the building; determining a processing node associated with the location information based on a first artificial intelligence model; in the processing node, determining location reference information of a second location in the first visual data that is associated with the location information based on a second artificial intelligence model; the location reference information is reference information used to locate the second location of the first location in the target system that needs to be modified in the first visual data; the first artificial intelligence model is based at least on the association between the location information related to the first location in the target system that needs to be modified and the processing node in the target system; the second artificial intelligence model is based at least on the association between the location information related to the first location in the target system that needs to be modified and the location reference information of the second location in the first visual data.

[0009] According to a second aspect of the present invention, a positioning device for visual data of a building is provided. The positioning device includes: an acquisition module that acquires location information related to a first location in a target system of the building that needs to be modified, and first visual data of the building; a first determination module that determines a processing node associated with the location information based on a first artificial intelligence model; and a second determination module that, in the processing node, determines location reference information of a second location in the first visual data that is associated with the location information based on a second artificial intelligence model. The location reference information is reference information used to locate the second location of the first location in the first visual data that needs to be modified in the target system. The first artificial intelligence model is based at least on the association between the location information related to the first location in the target system that needs to be modified and the processing node in the target system. The second artificial intelligence model is based at least on the association between the location information related to the first location in the target system that needs to be modified and the location reference information of the second location in the first visual data.

[0010] According to a third aspect of the present invention, a device for generating and displaying visual data of a building is provided. The device includes: a memory storing a computer program; a processor that, when executing the computer program, implements the positioning method for visual data of a building as described in the first aspect of the present invention, obtains location reference information of a second location associated with location information in the first visual data, and generates second visual data based on the first visual data and the location reference information; and a display that displays the second visual data of the building.

[0011] According to a fourth aspect of the present invention, a proposal system for buildings is provided, the system including at least one of the positioning device for visual data of buildings as described in the second aspect of the present invention and the generation and display device for visual data of buildings as described in the third aspect of the present invention.

[0012] One of the beneficial effects of the embodiments of the present invention is that:

[0013] By using an artificial intelligence model, the location reference information of the second location associated with the location information of the first location that needs to be modified in the target system of the building can be determined in the first visual data of the building. This can accurately correspond the first location that needs to be modified with the location in the first visual data, that is, to achieve accurate positioning of the location that needs to be modified in the first visual data of the building. Based on this location, visual data of the target system including the location that needs to be modified can be accurately generated.

[0014] Furthermore, based on the aforementioned location reference information and the first visual data of the building, visual data that accurately matches the user's needs or the content of the proposal to the user can be generated, which helps the user to intuitively and quickly understand the content of the proposal, thereby improving the success rate of the proposal and the user experience.

[0015] In addition, based on the location information related to the first location that needs to be modified in the target system of the building, the processing nodes associated with the location information are determined, and the location reference information of the second location associated with the location information in the first visual data is determined only in the determined processing nodes. Thus, when the user's needs or the content of the proposal to the user changes, the data of other processing nodes in the processing flow can be reused, and only the data of the processing nodes corresponding to the updated user needs or the content of the proposal to the user needs needs to be modified, thereby improving the efficiency of generating proposals.

[0016] Furthermore, regarding the location method for visual data of a building in the first aspect described above, when the location information related to the first location that needs to be modified in the target system of the building includes the first location in the building, the step of determining the location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model includes: using the second artificial intelligence model to determine the location reference information of the first visual data associated with the first location based on the first location.

[0017] Therefore, the location reference information can be accurately determined based on the explicit first location in the location information. Since the first location is explicitly given, the determined location reference information is more accurate, and the visual data generated based on this location reference information is more in line with user needs.

[0018] Furthermore, if the location information related to the first location that needs to be modified in the target system of the building does not include the first location in the building, the step of determining the location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model includes: generating the location reference information associated with the first location in the first visual data based on the location information related to the first location that needs to be modified in the target system of the building and the building design standard information.

[0019] Therefore, even if the location information does not include a specific location, accurate location reference information can be generated based on the location information and architectural design standard information.

[0020] Furthermore, the location information related to the first location that needs to be modified in the target system of the building includes: location information related to at least one of the user's needs, the content of the proposal to the user, the updated user's needs, and the updated content of the proposal to the user.

[0021] Therefore, determining the location information related to the location that needs to be modified based on user needs or the content of the proposal to users can further improve the accuracy of the determined location information.

[0022] Furthermore, the method for locating visual data of buildings further includes associating at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user with the corresponding location reference information.

[0023] This allows for the association of user needs with corresponding locations in the visual data of buildings, improving the matching degree between user needs and the actual generated visual data of the proposals.

[0024] Further, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is associated with the corresponding location reference information, including: using a third artificial intelligence model to refine at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user to obtain the user's first requirements; decomposing the first requirements according to the system functions of the building to obtain second requirements corresponding to each system function of the target system; and extracting the second requirements hierarchically according to the location reference information to obtain multiple user sub-requirements that correspond to each system function and contain the corresponding location reference information.

[0025] This allows for the precise mapping of segmented user sub-requirements to specific locations within the building model, thereby facilitating the generation of accurate and actionable visual data.

[0026] Furthermore, the method for locating visual data of buildings further includes associating at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user with the processing node associated with the corresponding location information.

[0027] By associating user needs with specific processing nodes in the process flow, user needs can be processed at the associated processing nodes, while reusing other processing nodes in the process flow, thus improving processing efficiency.

[0028] Furthermore, the method for locating visual data of a building further includes: generating second visual data of the building that meets at least one of the following: the first visual data of the building, location reference information of a second location associated with the location information in the first visual data, and the location reference information of the second location in the first visual data.

[0029] This ensures that user needs are accurately mapped to specific locations in the building's visual data, improving efficiency in handling updated user requirements, avoiding conflicts and errors between system functions, and enhancing the efficiency and accuracy of visual data that meets user needs. Furthermore, it facilitates quick and intuitive user understanding of proposals, increasing their success rate.

[0030] Further, generating second visual data of the building that conforms to at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user includes: in each associated processing node, based on the first visual data of the building, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user associated with each processing node, and location reference information associated with at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user, respectively, generating third visual data of the system functions corresponding to each processing node; integrating the third visual data of each system function to obtain the second visual data of the building.

[0031] Therefore, generating corresponding visual data at each processing node and integrating them to obtain second visual data can improve the efficiency and accuracy of the generated second visual data. Furthermore, processing the corresponding processing tasks according to the nodes can cope with changes in the processing content, resulting in greater flexibility. Moreover, each processing node can adopt the most suitable artificial intelligence model or algorithm for its corresponding processing content. Different processing nodes can use different artificial intelligence models or algorithms, thus enabling the use of the most suitable model for different processing tasks, resulting in better processing quality and higher efficiency.

[0032] Furthermore, the method for locating visual data for buildings further includes: displaying the second visual data using a display device; obtaining user feedback information on the displayed second visual data; if the feedback information includes updated user requirements, generating and displaying updated second visual data based on the updated user requirements; or, obtaining updated proposal content to the user; generating and displaying updated second visual data based on the updated proposal content to the user.

[0033] Therefore, updating the second visual data according to user needs can improve the matching degree between the actual generated proposal visual data and user needs. Furthermore, displaying the second visual data makes it easier for users to quickly and intuitively understand the proposal, thereby improving the success rate of the proposal and the user experience.

[0034] Furthermore, the processing node includes a workflow processing node; and the method for locating visual data for buildings further includes: using a fourth artificial intelligence model to construct a first workflow based on at least one associated first processing node in the user's needs and the content of the proposal to the user.

[0035] Therefore, it is possible to locate user needs in the visual data of buildings based on a workflow, thereby improving data processing efficiency.

[0036] Furthermore, the method for locating visual data for buildings further includes: using a fourth artificial intelligence model to update the workflow architecture of the first workflow based on at least one of the updated user requirements and the updated proposal content to the user, to obtain a second workflow; updating the workflow architecture of the first workflow includes: deleting a first processing node in the first workflow, or adding a second processing node in the first workflow that is associated with at least one of the user requirements and the updated proposal content to the user; and linking the first processing nodes that have not been deleted, or linking the first processing nodes that have not been deleted with the newly added second processing nodes, according to a set rule.

[0037] Therefore, when user needs or the content of proposals to users are updated, the corresponding processing nodes in the workflow are updated, thereby improving the efficiency of workflow construction and data location.

[0038] Furthermore, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is generated based on at least one of the voice data from user interaction, the user-filled requirement data form, and the user's requirement record information.

[0039] Therefore, it is possible to conveniently obtain user needs or propose content to users through various methods.

[0040] Furthermore, the user requirements include at least one of the following: system information, equipment information, area information, and evaluation information of the building environment; the proposal content to the user includes at least one of the following: system information, equipment information, area information, and evaluation information of the building environment.

[0041] Therefore, it is possible to easily generate user requirements and proposals to users based on evaluation information of systems, equipment, etc. in the building.

[0042] Furthermore, the method for locating visual data of a building further includes: determining the second position in the first visual data based on the first visual data of the building and the position reference information of the second position associated with the position information of the first position in the target system that needs to be modified; and displaying the first visual data, the second position, and the position reference information.

[0043] This allows the display of first visual data, second position, and position reference information, making it easier for users to intuitively understand the location of their needs within the first visual data and further improving the user experience.

[0044] Furthermore, the first visual data of the building includes at least one of the following: parameter data, image data, video data, and proposal data of the building's multi-dimensional visualization model; or at least one of the parameter data, image data, video data, and proposal data of the building's multi-dimensional visualization model generated based on previous user needs or previous proposals to the user. For example, the multi-dimensional visualization model includes, but is not limited to, 2D models, 3D models, and 4D models.

[0045] This allows users to easily view first-person visual data in different data formats, thereby further improving the user experience.

[0046] Furthermore, the location reference information includes at least one of the following: location information, spatial information, regional information, time information, material information, color information, pipeline routing information, and layer information.

[0047] Therefore, a second location can be determined based on a variety of different data, thereby improving the accuracy of locating the location that needs to be modified in the visual data of the building.

[0048] Furthermore, regarding the device for generating and displaying visual data of the building in the third aspect mentioned above, the display also displays first visual data of the building, a second location associated with location information related to a first location in the target system that needs to be modified, and location reference information.

[0049] This allows users to easily obtain the first visual data of the building, the second location corresponding to the first location that needs to be modified in the target system, and location reference information, which helps to further improve the user experience.

[0050] Specific embodiments of the invention are disclosed in detail with reference to the following description and accompanying drawings, indicating how the principles of the invention can be employed. It should be understood that the embodiments of the invention are not therefore limited in scope. Within the spirit and scope of the appended claims, embodiments of the invention include many changes, modifications, and equivalents.

[0051] The feature information described and illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, combined with feature information in other embodiments, or substituted for feature information in other embodiments.

[0052] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, whole, step, or component, but does not exclude the presence or addition of one or more other features, wholes, steps, or components. Attached Figure Description

[0053] The above and other objects, features and advantages of embodiments of the present invention will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

[0054] Figure 1 This is a schematic diagram of a method for locating visual data of buildings according to an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of a step in associating location reference information according to an embodiment of the present invention;

[0056] Figure 3 This is a schematic diagram of one step in generating second visual data according to an embodiment of the present invention;

[0057] Figure 4 This is a flowchart of a method for locating visual data of buildings according to an embodiment of the present invention;

[0058] Figure 5 This is a schematic diagram of the flow of a method for locating visual data of a building according to an embodiment of the present invention;

[0059] Figure 6 This is a schematic diagram of a positioning device for visual data of buildings according to an embodiment of the present invention;

[0060] Figure 7 This is a schematic diagram of a device for generating and displaying visual data of a building according to an embodiment of the present invention;

[0061] Figure 8 This is a schematic diagram of a proposal system for buildings according to an embodiment of the present invention. Detailed Implementation

[0062] Referring to the accompanying drawings, the foregoing and other features of the invention will become apparent from the following description. Specific embodiments of the invention are specifically disclosed in the description and drawings, illustrating partial implementations in which the principles of the invention can be employed. It should be understood that the invention is not limited to the described embodiments, but includes all modifications and equivalents falling within the scope of the appended claims.

[0063] The following description, in conjunction with the accompanying drawings, describes the positioning method, apparatus, generation and display apparatus, and proposal system for visual data of buildings according to embodiments of the present invention.

[0064] First aspect of the embodiments

[0065] An embodiment of the first aspect of the present invention provides a method for locating visual data of buildings. Figure 1 This is a schematic diagram of a method for locating visual data of buildings according to an embodiment of the present invention. Figure 1As shown, the localization method 100 for visual data of buildings includes:

[0066] Step 101: Obtain location information related to the first location in the target system of the building that needs to be modified, as well as the first visual data of the building;

[0067] Step 102: Determine the processing nodes associated with the location information based on the first artificial intelligence model;

[0068] Step 103: In the processing node, the location reference information of the second location associated with the location information in the first visual data is determined based on the second artificial intelligence model.

[0069] Among them, the location reference information is the reference information used to locate the first location that needs to be modified in the target system and the second location in the first visual data; the first artificial intelligence model is based at least on the relationship between the location information related to the first location that needs to be modified in the target system and the processing node in the target system; the second artificial intelligence model is based at least on the relationship between the location information related to the first location that needs to be modified in the target system and the location reference information of the second location in the first visual data.

[0070] Therefore, by using an artificial intelligence model, the location reference information of the second location associated with the location information of the first location that needs to be modified in the target system of the building can be determined in the first visual data of the building. This can accurately correspond the first location that needs to be modified with the location in the first visual data, that is, to achieve accurate positioning of the location that needs to be modified in the first visual data of the building. Based on this location, visual data of the target system including the location that needs to be modified can be accurately generated.

[0071] Furthermore, based on the aforementioned location reference information and the first visual data of the building, visual data that accurately matches the user's needs or the content of the proposal to the user can be generated, which helps the user to intuitively and quickly understand the content of the proposal, thereby improving the success rate of the proposal and the user experience.

[0072] In addition, based on the location information related to the first location that needs to be modified in the target system of the building, the processing nodes associated with the location information are determined, and the location reference information of the second location associated with the location information in the first visual data is determined only in the determined processing nodes. Thus, when the user's needs or the content of the proposal to the user changes, the data of other processing nodes in the processing flow can be reused, and only the data of the processing nodes corresponding to the updated user needs or the content of the proposal to the user needs needs to be modified, thereby improving the efficiency of generating proposals.

[0073] In some embodiments, the building can be of various types, such as office buildings, shopping malls, factory workshops, schools, apartments, and ordinary residences. The embodiments of the present invention do not limit the type of building.

[0074] In some embodiments, a building may also be referred to as a building, or a building may include various types of buildings.

[0075] In some embodiments, the target system of a building is at least one of a plurality of systems in the building that requires modification (including overall modification or partial modification).

[0076] Systems within a building may include, for example, audio-visual systems, electrical systems, network systems, air conditioning systems, water systems, lighting systems, curtain systems, and HVAC systems. Each system within a building may contain multiple and / or various types of equipment. This embodiment of the invention does not limit the systems or the equipment within them.

[0077] In some embodiments, “modification” includes, but is not limited to, adding, removing, or replacing hardware such as systems and equipment in a building; installing, updating, or designing software in systems or equipment configured in a building; and designing and decorating the building space.

[0078] In some embodiments, the first location to be modified includes at least one of an actual location and a virtual location existing in the target system of the building. The actual location is, for example, a location configured in the actual target system of the building, and the virtual location is, for example, a location configured in the software of the target system. This application does not limit this.

[0079] In some embodiments, the location information related to the first location in the target system of the building that needs to be modified includes: location information related to at least one of user needs, proposal content to the user, updated user needs, and updated proposal content to the user. Therefore, determining the location information related to the location that needs modification based on user needs or proposal content to the user can further improve the accuracy of the determined location information.

[0080] In some embodiments, user requirements refer to the functional requirements document proposed by the party requesting the renovation (also known as the user or the client) for the renovation of the target system of the building. It is a decision-making basis document and can also be called the client / user requirements specification.

[0081] In some embodiments, user requirements may include at least one of the following: system information, equipment information, area information, and evaluation information of the building environment. System information may include, for example, information on the functional deficiencies and upgrade requirements of the building's existing HVAC system, power system, lighting system, etc. Equipment information may include, for example, equipment operating parameters (e.g., air conditioning energy efficiency indicators) and equipment layout (e.g., requirements for optimizing the location of distribution cabinets). Area information may include, for example, information on functional zoning adjustment plans for the building (e.g., converting office areas into smart meeting rooms). Evaluation information related to the building environment may include, for example, direct sensory evaluations of the spatial environment by users, including but not limited to evaluations of the building's thermal environment (e.g., excessive heat in summer / excessive cold in winter, uneven heating in localized areas), air quality (e.g., stuffiness due to insufficient ventilation, excessive CO2 concentration), lighting environment (e.g., dimness due to insufficient natural light, glare interference), and acoustic environment (e.g., excessive equipment noise, significant echoes in meeting rooms). When users cannot professionally point out the deficiencies and upgrade requirements of the building's existing systems, direct sensory evaluations of the spatial environment can provide more straightforward feedback on system information.

[0082] In some embodiments, the demanders / users for renovation include, but are not limited to, at least one of the following: owners of all or part of the building, users of all or part of the building, and owners or users of the systems in all or part of the building.

[0083] In some embodiments, the proposal content provided to the user refers to a renovation plan customized by a professional service provider (also known as Party B or the proposal provider) based on the user's needs, or a renovation plan independently developed by a patent service provider based on the existing condition of the user's building; this can also be referred to as Party B's renovation proposal. The proposal content provided to the user shall include at least one of the following: system information, equipment information, area information, and environmental evaluation information of the building. See the preceding text for details, which will not be repeated here.

[0084] In some embodiments, an updated user requirement refers to at least one user requirement obtained after the initial acquisition of user requirements. An updated user requirement may include, for example, a new requirement submitted by a user after the initial request, or an improvement request submitted by a user based on any previously generated visual data or the content of a proposal to the user. This application does not impose any limitations on this.

[0085] In some embodiments, the updated proposal content to the user refers to at least one proposal made after the initial proposal to the user. The updated proposal content to the user may include, for example, a proposal that is further updated based on any previous proposal content to the user. The proposal content to the user may be updated based on updated user needs or user feedback.

[0086] In some embodiments, the proposal content presented to the user can be generated based on the user's needs and a preset proposal template. The preset proposal template is selected from a preset proposal template library. For example, based on this preset proposal template library, user needs can be intelligently matched with a database of renovation solutions built based on historical cases to select the proposal template that best meets the user's needs. For example, if the user's needs only include the renovation and upgrade of the air conditioning system, then only the preset template for the air conditioning system will be output as the renovation suggestion from the professional service provider.

[0087] In some embodiments, the proposal template can be stored and exported in various formats, such as PPT, Word, Excel, etc., and the embodiments of the present invention do not limit this.

[0088] In some embodiments, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is generated based on at least one of the following: voice data from user interaction, requirement data filled in by the user, and requirement record information from the proposer. Therefore, user requirements or proposal content to the user can be conveniently obtained through multiple methods.

[0089] In some embodiments, the proposer refers to the party providing the intelligent transformation, such as a salesperson interacting with users in the market. The voice data used in user interactions may include at least one of the user's voice data and the proposer's voice data, obtained with the user's consent. The user-submitted request data may be in form, including but not limited to forms such as tables, electronic documents, or paper documents.

[0090] Similarly, this embodiment of the invention does not limit the data representation and storage method of the proposer's requirement record information. Furthermore, the proposer's requirement record information may include voice data from user interactions, the requirement data filled in by the user, or content summarized by the proposer based on their understanding of the user's background information, which is more conducive to understanding and processing by the artificial intelligence model.

[0091] In some embodiments, the first visual data of a building includes at least one of the following:

[0092] The building's multi-dimensional visualization model includes parameter data, image data, video data, proposal data, parameter data of the building's multi-dimensional visualization model generated based on previous user needs or previous proposal content to users, image data of the building generated based on previous user needs or previous proposal content to users, video data of the building generated based on previous user needs or previous proposal content to users, and proposal data of the building generated based on previous user needs or previous proposal content to users.

[0093] For example, multi-dimensional visualization models include, but are not limited to, 2D models, 3D models, 4D models, etc.

[0094] This allows users to easily view first-person visual data in different data formats, thereby further improving the user experience.

[0095] Furthermore, the data types contained in the second and third visual data described later are similar to those in the first visual data.

[0096] In addition, the first visual data is existing visual data, while the second and third visual data are visual data to be generated.

[0097] In some embodiments, in step 102, processing nodes associated with location information related to a first location that needs to be modified in the target system of the building are determined based on a first artificial intelligence model. The first artificial intelligence model is based at least on the association between the location information related to the first location that needs to be modified in the target system of the building and the processing nodes in the target system.

[0098] In some embodiments, processing nodes correspond one-to-one with target systems, and modifications and other processes for different target systems are executed in the processing nodes corresponding to those target systems.

[0099] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0100] Associate at least one of the following: user requirements, the content of the proposal to the user, the updated user requirements, and the updated content of the proposal to the user, with the processing node associated with the corresponding location information.

[0101] In this embodiment, the corresponding "location information" includes location information related to at least one of the following: user requirements, proposal content to the user, updated user requirements, and updated proposal content to the user, i.e., location information related to the first location that needs to be modified in the target system of the building.

[0102] By associating user needs with specific processing nodes in the process flow, user needs can be processed at the associated processing nodes, while reusing other processing nodes in the process flow, thus improving processing efficiency.

[0103] In some embodiments, processing nodes include workflow processing nodes or process nodes in the design program. Therefore, when there is a need to modify a first location in the target system of a building, only the relevant processing in the processing node corresponding to the target system needs to be changed, without changing other processing nodes in the workflow or other process nodes in the design program, thus improving the efficiency of generating workflows or design programs.

[0104] In some embodiments, in step 103, in the processing node associated with the location information related to the first location that needs to be modified in the target system of the building, the location reference information of the second location in the first visual data of the building, which is associated with the aforementioned location information, is determined based on the second artificial intelligence model. The second artificial intelligence model is based at least on the association between the location information related to the first location that needs to be modified in the target system of the building and the location reference information of the second location in the first visual data.

[0105] In some embodiments, the second position refers to a virtual position in the first visual data of the building, the relative position of the second position in the first visual data being the same as the relative position of the first position in the building, that is, the second position is the position of the first position mapped to the first visual data.

[0106] In some embodiments, location reference information of the second location is used to determine the second location in the first visual data of the building.

[0107] For example, the location reference information includes at least one of the following: location information, spatial information, regional information, time information, material information, color information, pipeline routing information, and layer information.

[0108] Therefore, a second location can be determined based on a variety of different data, thereby improving the accuracy of locating the location that needs to be modified in the visual data of the building.

[0109] In some embodiments, location information may include, for example, the specific coordinates of various areas, equipment, pipelines, etc., within a building. For instance, the location information of a meeting room may be determined based on a predetermined coordinate system, such as the coordinates (x = 10, y = 20, z = 0) of a representative point (e.g., the center point) of the meeting room. The origin of the coordinate system may include, but is not limited to, the geometric center of the building, the center of a functional area within the building (e.g., meeting rooms, offices), or the center of areas with frequent user activity (e.g., corridors, lobbies, etc.).

[0110] In some embodiments, different coordinate origins can be selected according to actual needs. For example, using the geometric center of the building as the coordinate origin is suitable for positioning the overall layout; using the center of a functional area within the building as the coordinate origin is suitable for positioning based on local needs; and using an area with frequent user activity as the coordinate origin is suitable for positioning to optimize user experience.

[0111] In some embodiments, spatial information may include, for example, the dimensions and shapes of various areas within a building. For instance, the dimensions of a meeting room are 10m × 5m × 3m.

[0112] In some embodiments, area information may include, for example, the functions and attributes of various areas within a building. For instance, a meeting room may function as a video conferencing space and have attributes such as soundproofing and good lighting.

[0113] In some embodiments, the time information may include, for example, time information related to the evolution of a building at different stages of time. This could include time information related to the gradual completion of the building from its initial bare state to the installation of plumbing, hard furnishings, and soft furnishings.

[0114] In some embodiments, material information may include, for example, the material properties of various areas within the building. For instance, the walls of a meeting room may be made of plasterboard, and the flooring may be made of carpet.

[0115] In some embodiments, color information may include, for example, the color attributes of various areas within a building. For instance, the walls of a meeting room may be white, and the floor may be gray.

[0116] In some embodiments, conduit routing information may include, for example, the conduit routes and connection points in various areas of the building. For instance, the electrical wiring in the conference room may run from (x=2, y=1, z=0.5) to (x=5, y=1, z=2.5).

[0117] In some embodiments, layer information may include, for example, the various areas within a building and the relative positions of systems and devices within those areas.

[0118] In some implementations, the location reference information determined in step 103 includes at least one of the location reference information corresponding to multiple spatial location regions in the pre-determined first visual data of the building. The location reference information corresponding to the multiple spatial location regions in the first visual data is pre-determined, for example, by a generative artificial intelligence model. For instance, the first visual data of the building is converted into a format readable by the generative artificial intelligence model (e.g., text formats such as XML or IFC), and combined with the knowledge base of the generative artificial intelligence model and building design standards, the first visual data of the building is divided into spatial location regions, and the location reference information corresponding to each subdivided spatial location region in the first visual data is determined.

[0119] For example, suppose there is a simple first-view data of an office building, which includes floors, areas, rooms, and equipment. The spatial locations are further refined from the floors, areas, rooms, and equipment. For instance, based on area and functional requirements, the office area can be further divided from a single area into eight smaller areas. Generative AI models can more accurately understand the building's structure and the location of equipment, thus more precisely mapping user needs to specific locations within the building in subsequent steps. In this embodiment, the pre-determined location reference information is text-based data describing the spatial locations of each floor, area, room, and equipment in the first-view data of the building, along with their specific locations.

[0120] In some embodiments, the spatial division of a building can be performed sequentially according to different levels of granularity. For example, the spatial division of a building can be initially performed according to its system functions, and then the space belonging to the system can be further divided according to the walls. For example, based on building design standards and users' personalized needs, the space belonging to the system can be element-matched to each wall.

[0121] The above method of dividing spatial locations based on the system functions and walls of buildings has the following advantages: (1) Directly linking user needs with the system: Dividing according to the system functions of the building (such as lighting, air conditioning, security, etc.) can directly map each user need to a specific system function, which helps ensure that the proposal can effectively support the functional requirements of each system. (2) Facilitating independent optimization of system functions: Each building system has its specific functional goals and technical requirements. By dividing according to the system functions of the building, it can be ensured that each system function corresponding to the user needs is optimized independently. (3) Improving the accuracy of spatial location division: Based on the division according to the system functions of the building, further refining the spatial location areas according to the walls can more accurately handle the design needs of each space, including the layout of systems such as lighting, air conditioning, and security. This helps the generative artificial intelligence model make more detailed decisions on spatial layout, and thus accurately map user needs to specific physical locations.

[0122] In some embodiments, the knowledge base of a generative artificial intelligence model is generated, for example, through the following steps:

[0123] Obtain historical proposal project data and architectural design standards; this proposal project data refers to data used to represent the correspondence between user needs in historical proposal projects and the system functions of the building, including historical user needs and the proposals ultimately accepted by users corresponding to those needs;

[0124] The acquired historical proposal project data and architectural design standards are converted into vectors readable by the generative AI model;

[0125] The above vectors are stored in a database as a knowledge base for generative AI.

[0126] In some embodiments, building design standards include at least one of the following: various national standards, regional standards, and industry standards related to buildings.

[0127] Therefore, location reference information can be determined based on various standards, thereby improving the accuracy and reference value of the generated location reference information.

[0128] Tables 1 to 3 below are some examples of building design standards provided by embodiments of the present invention. Table 1 shows the proportion of air-conditioned area to building area, Table 2 shows the estimated building area of ​​air-conditioned equipment rooms, and Table 3 shows the estimated cooling load index (W / m²) using the air-conditioned cooling load method. 2 (Air-conditioned area).

[0129] Table 1: Proportion of Air-Conditioned Area in Building Area

[0130] Building type Proportion(%) Building type Proportion(%) Tourist hotels and restaurants 70-80 Hospital 15-35 Office buildings and exhibition centers 65-80 department store 50-65 Theaters, cinemas, clubs 75-85 - -

[0131] Table 2: Estimated Building Area Indicators for Air Conditioning Rooms

[0132]

[0133] Table 3: Estimation of Cooling Index (W / m²) using Air Conditioning Cooling Load Method 2 (Air conditioning area)

[0134]

[0135] In some embodiments, depending on the content of the location information related to the first location that needs to be modified in the target system of the building, the location reference information of the second location in the first visual data associated with the location information related to the first location that needs to be modified in the target system of the building can be determined in different ways.

[0136] In some embodiments, where the location information related to the first location that needs to be modified in the target system of the building includes the first location in the building, step 103, namely determining the location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model, includes:

[0137] Using a second artificial intelligence model, positional reference information associated with the first position is determined from the first visual data based on the first position.

[0138] Therefore, the location reference information can be accurately determined based on the explicit first location in the location information. Since the first location is explicitly given, the determined location reference information is more accurate, and the visual data generated based on this location reference information is more in line with user needs.

[0139] In some embodiments, where the location information related to the first location that needs to be modified in the target system of the building does not include the first location in the building, step 103, determining location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model, includes:

[0140] Based on the location information related to the first location that needs to be modified in the target system of the building and the building design standard information, the second artificial intelligence model is used to generate location reference information associated with the first location in the first visual data.

[0141] Therefore, even if the location information does not include a specific location, accurate location reference information can be generated based on the location information and architectural design standard information.

[0142] The following is an example of determining location reference information based on location information related to the first location that needs to be modified in the target system of the building, as well as building design standard information.

[0143] First, calculate the cooling load based on the basic parameters of the conference room (e.g., area, personnel density, equipment heat generation, lighting power, building orientation, and exterior wall materials). For example, for a 50-square-meter conference room, by calculating the cooling load for personnel, equipment, lighting, solar radiation, and heat transfer from the exterior walls, the total cooling load is found to be 7.5 kW, with a cooling index of 150 W / m². 2 This step provides a basis for selecting air conditioning equipment.

[0144] When the specific location of the air conditioner is not clearly defined in the location information related to the first location in the target system of the building that needs to be modified, location reference information is generated based on building design standards. For example, according to building design standards, the air conditioner should be installed in a location with good air circulation to avoid direct airflow onto people. Considering the layout of the conference room (e.g., 10m long, 5m wide, 3m high), and determining that the air conditioner is installed on one wall of the conference room, 2.5m above the ground, the specific coordinates for installing the air conditioner can be determined as (2, 0, 2.5). This information can be used as location reference information. Simultaneously, the airflow direction of the air conditioner can be further determined to ensure that the airflow covers the entire conference room.

[0145] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0146] Associate at least one of the following: user requirements, proposal content to users, updated user requirements, and updated proposal content to users, with the corresponding location reference information.

[0147] In some embodiments, the “location reference information” associated with at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is the location reference information of the second location in the first visual data associated with the relevant location information (i.e., the location information related to the first location that needs to be modified in the target system of the building) in at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user.

[0148] This allows for the association of user needs with corresponding locations in the visual data of buildings, improving the matching degree between user needs and the actual generated visual data of the proposals.

[0149] Figure 2 This is a schematic diagram illustrating one step of the present invention involving association with location reference information. For example... Figure 2 As shown, at least one of the following is associated with corresponding location reference information: user requirements, proposal content to users, updated user requirements, and updated proposal content to users.

[0150] Step 201: Using the third artificial intelligence model, refine at least one of the user needs, the content of the proposal to the user, the updated user needs, and the updated content of the proposal to the user to obtain the user's first needs.

[0151] Step 202: Decompose the first requirement according to the system function of the building to obtain the second requirement corresponding to each system function of the target system;

[0152] Step 203: Extract the second requirement in layers based on the location reference information to obtain multiple user sub-requirements that correspond to the functions of each system and contain the corresponding location reference information.

[0153] This allows for the precise mapping of segmented user sub-requirements to specific locations within the building model, thereby facilitating the generation of accurate and actionable visual data.

[0154] In some embodiments, the third artificial intelligence model is, for example, a generative artificial intelligence model.

[0155] In some embodiments, in step 201, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is input into the third artificial intelligence model. Combined with the knowledge base of the generative artificial intelligence model, a first requirement is obtained after refining at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user.

[0156] In some embodiments, in step 202, the refined first requirement is further decomposed in the corresponding processing node according to the system function of the building to obtain the second requirement corresponding to each system function of the target system.

[0157] Through the "refinement" process in step 201 and the "decomposition" process in step 202, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is refined from a vague or high-level description into specific, actionable technical requirements. This process includes, for example, clarifying the specific object of the user requirements or the proposal content to the user (e.g., equipment type), determining the spatial location (e.g., room coordinates), quantifying technical parameters (e.g., power, color temperature), analyzing the relevance of the requirements (e.g., compatibility with existing systems), and generating executable sub-requirements (e.g., wiring, installation, debugging). The refined first requirement can be accurately mapped to the first visual data of the building, providing clear input for subsequent steps.

[0158] For example, suppose a user's requirement is that the customer wants to add a video conferencing system to their conference room, including cameras, microphones, displays, etc., and ensure that these devices have a reliable power supply and network connectivity. After refining and decomposing this user requirement through steps 201 and 202, the resulting second requirement includes the following system and related functional requirements. System requirements include, for example: for the audio / video system, responsible for the installation and operation of cameras, microphones, displays, etc.; for the power system, providing power to the video conferencing equipment; for the network system, ensuring network connectivity for the video conferencing equipment. Related functional requirements include, for example: for the camera, installed at the front of the conference room at a height of 2.5m, covering the entire conference room; for the microphone, installed in the center of the conference room at a height of 2m, ensuring clear sound capture; for the display, installed at the front of the conference room at a height of 1.5m for easy viewing; for the power supply, ensuring all devices have a reliable power supply, which may require additional sockets or extension cables; for the network connectivity, ensuring all devices can connect to the network, which may require additional network interfaces or the use of a wireless network.

[0159] In some embodiments, when user requirements are relatively vague, user requirements can be supplemented and expanded based on generative artificial intelligence models, based on at least one of historical proposal projects and architectural design standards.

[0160] Here's an example of supplementing and expanding user needs based on historical proposal projects: Data collection is used to obtain requirement data and design schemes from historical proposal projects similar to the user's needs. For example, video conferencing system design schemes from other office buildings can be collected. Then, generative AI is used to analyze these proposal projects, extracting common requirements and design patterns. For instance, analysis reveals that most office building video conferencing systems include cameras, microphones, and displays. Based on the analysis results, the client's potential needs can be expanded. For example, it can be suggested that the client add cameras, microphones, and displays to the meeting room, along with specific equipment selection and installation locations.

[0161] Examples of supplementing and expanding user needs based on architectural design standards are as follows: Using a generative artificial intelligence model, the client's routine needs can be inferred from architectural design benchmarks. For example, based on lighting standards, the lighting requirement for a conference room can be inferred to be 300 lumens / m². 2 Then, based on the reasoning results, supplement the client's routine needs, such as suggesting that the client install lighting fixtures that meet lighting standards in the conference room, and providing specific installation locations and brightness requirements.

[0162] In some embodiments, in step 203, based on the location reference information corresponding to each spatial location area in the predetermined first visual data, the second requirements corresponding to each system function of the target system determined in step 202 are extracted hierarchically to obtain multiple user sub-requirements corresponding to each system function, including the location reference information of the spatial location area corresponding to the target system to which the system function belongs in the first visual data, thereby completing the association between user requirements and location reference information in the first visual data of the building.

[0163] Therefore, obtaining user sub-requirements that include location reference information from the building's first visual data ensures that user requirements are accurately mapped to specific locations within the building's first visual data, thus guaranteeing the generation of accurate and executable visual data. Furthermore, by associating user requirements with location reference information (such as coordinates, regions, and device locations) from the building's first visual data, the specific implementation location of the user requirement within the building can be clearly defined (e.g., installing a light fixture at location (x=12, y=22, z=2.5) in office A), avoiding deviations between user requirements and the actual building layout. Therefore, this not only improves the accuracy of proposals but also supports rapid location and adjustment when user requirements are updated, thereby enhancing overall efficiency and customer satisfaction.

[0164] In some embodiments, in step 203, location reference information corresponding to each spatial location region in the predetermined first visual data is read by a generative artificial intelligence model, and the second requirement is mapped to the corresponding location reference information.

[0165] The following example illustrates the steps of a generative artificial intelligence model in reading location reference information. The generative artificial intelligence model reads location reference information through the following steps: (1) Data preprocessing: Convert the first visual data of the building into IFC format and clean the data; (2) Feature extraction: Extract the spatial layout of the meeting room (e.g., the size of the meeting room is 10m x 5m x 3m), the location of equipment (e.g., the location coordinates of the camera (x=5, y=1, z=2.5)) and the direction of pipelines (e.g., the direction of the power pipeline is from location coordinates (x=2, y=1, z=0.5) to location coordinates (x=5, y=1, z=2.5)). (3) Semantic understanding: Parse the text information in the first visual data of the building and identify the type and function of the camera; (4) Location parameter generation: Generate the location coordinates of the camera as (x=5, y=1, z=2.5) and the attribute information as "Type: HD camera, resolution: 1080p"; (5) Data verification: Check the consistency between the camera location and the power pipeline to ensure that the camera can be powered normally.

[0166] The following example illustrates the steps of a generative artificial intelligence model in mapping a second requirement to its corresponding location reference information. The generative artificial intelligence model establishes the mapping relationship between the second requirement and location reference information through the following steps: (1) Semantic matching: Utilizing the semantic understanding capability of the generative artificial intelligence model, analyze the similarity and correlation between the user's second requirement and existing parameters; for example, through semantic matching, associate the user requirement "install a camera in the conference room" with the location (x=10, y=20, z=0) and size (10m x 5m x 3m) of the conference room. (2) Rule definition: Based on architectural design standards and customer requirements, predefine matching rules to match the specific attributes of the user's second requirement with existing location reference information; for example, the camera should be installed at the front of the conference room at a height of 2.5m. (3) Location calculation: Based on the matching rules and matching results, calculate the specific location of the user's requirement in the building's first visual data. For example, calculate the camera's installation location as (x=12, y=22, z=2.5).

[0167] In some embodiments, the location of user needs in the first visual data of a building is achieved by dynamically adjusting the granularity.

[0168] For example, in the early stages of a project, a coarser, second-level granularity is used for requirement identification, such as treating the conference room as a single area. As the project progresses, the granularity is gradually refined; for example, the conference room is subdivided into sub-areas such as the front, back, left, and right sides for more precise requirement identification. Later, the granularity and accuracy of the identification can be adjusted based on customer feedback; for example, the installation position and angle of the cameras can be adjusted based on customer feedback regarding camera viewing angles.

[0169] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0170] Based on the first visual data of the building, and the location reference information of the second location associated with the location information of the first location that needs to be modified in the target system, determine the second location in the first visual data; display the first visual data, the second location, and the location reference information.

[0171] This allows the display of first visual data, second position, and position reference information, making it easier for users to intuitively understand the location of their needs within the first visual data and further improving the user experience.

[0172] In some embodiments, while or after displaying first visual data, a second location, and location reference information, the display device also displays one or more visual modules that can be operated by the user (e.g., click operation, touch operation, etc.). By operating the corresponding visual module, the user can trigger at least one of the following operations: confirming the second location; obtaining updated information about the second location. When the user operation triggers "obtain updated information about the second location," the user or proposer can be prompted to input the updated information about the second location through voice announcement, text, images, etc. Furthermore, the user or proposer can input the updated information about the second location through voice input, text input, file import, click operation, etc. Based on this updated information about the second location, the second location and location reference information can be updated, thereby correcting the second location and improving accuracy.

[0173] This allows users to quickly and intuitively determine whether the second position is correct, facilitating user confirmation or feedback, and further improving the user experience.

[0174] In some implementations, the method for locating visual data of buildings according to embodiments of the present invention further includes:

[0175] Based on the building's first visual data, the location reference information of the second location associated with the location information of the first location in the building's target system that needs to be modified, the second visual data of the building is generated to meet at least one of the following: user needs, proposal content to the user, updated user needs, and updated proposal content to the user.

[0176] For example, in the example above where location reference information is determined based on location information related to the first location that needs to be modified in the target system of the building and architectural design standard information, after determining the location reference information for the installation location of the air conditioning equipment (e.g., specific coordinates (2,0,2.5)), the data model corresponding to the air conditioning equipment is then precisely placed at a specified location in the first visual data of the building (e.g., the location at coordinates (2,0,2.5)) based on the determined location reference information, generating the second visual data of the building, and adjusting the direction of the air outlets to ensure that the airflow covers the entire conference room. Thus, the generated second visual data not only accurately reflects the location and function of the air conditioning equipment, but also conforms to architectural design standards and user needs.

[0177] This ensures that user needs are accurately mapped to specific locations in the building's visual data, improving efficiency in handling updated user requirements, avoiding conflicts and errors between system functions, and enhancing the efficiency and accuracy of visual data that meets user needs. Furthermore, it facilitates quick and intuitive user understanding of proposals, increasing their success rate.

[0178] Figure 3 This is a schematic diagram illustrating one step of generating second visual data according to an embodiment of the present invention. Figure 3 As shown, generating second visual data of a building that meets at least one of the following: user requirements, a proposal to the user, updated user requirements, and updated proposal to the user, includes:

[0179] Step 301: In each processing node associated with the location information related to the first location that needs to be modified in the target system of the building, based on the first visual data of the building, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user associated with each processing node, and location reference information associated with at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user, the third visual data of the system function corresponding to each processing node is generated respectively.

[0180] Step 302: Integrate the third visual data from each system function to obtain the second visual data of the building. This second visual data is a complete visual data of the building that meets user needs.

[0181] Therefore, generating corresponding visual data at each processing node and integrating them to obtain second visual data can improve the efficiency and accuracy of the generated second visual data. Furthermore, processing the corresponding processing tasks according to the nodes can cope with changes in the processing content, resulting in greater flexibility. Moreover, each processing node can adopt the most suitable artificial intelligence model or algorithm for its corresponding processing content. Different processing nodes can use different artificial intelligence models or algorithms, thus enabling the use of the most suitable model for different processing tasks, resulting in better processing quality and higher efficiency.

[0182] In some embodiments, in step 301 above, in each processing node associated with the location information related to the first location that needs to be modified in the target system of the building, according to each user sub-demand determined in step 203 above, the object required to satisfy each user sub-demand is analyzed by combining the generative artificial intelligence model, and the data model corresponding to the object is obtained from the pre-established data model knowledge base.

[0183] Then, after obtaining the data model corresponding to the object required to meet the user's sub-needs, the generative artificial intelligence model is used in conjunction with the location reference information contained in the user's sub-needs (see step 203 above) to determine the specific spatial arrangement of the data model corresponding to the object in the corresponding area.

[0184] Then, after determining the specific spatial arrangement of the data model of the objects required to meet the user's sub-requirements, based on the location reference information contained in the user's sub-requirements, the data model of the objects determined in the above steps, and the specific spatial arrangement of the data model of the objects determined in the above steps, the third visual data of the building containing the user's sub-requirements is generated on the basis of the first visual data of the building.

[0185] In some embodiments, during the process of generating third-vision data using a generative artificial intelligence model, the knowledge base of the generative artificial intelligence model, which is constructed based on historical proposal project data as described above, can be used to match key information in the customer's needs in the knowledge base. The generative artificial intelligence model generates proposal text based on the matching results and generates prompt words based on the proposal text. The prompt words are used to instruct the generative artificial intelligence model to generate third-vision data, which can improve the accuracy of the generated third-vision data and second-vision data.

[0186] In some embodiments, considering the different nature and content of user sub-requirements, the objects required to satisfy user sub-requirements in this invention include at least one of physical objects and abstract objects. Physical objects are, for example, tangible objects such as air conditioners. However, when user sub-requirements involve system functions, process optimization, or abstract concepts (e.g., improving user experience), the user sub-requirements correspond to abstract objects, not directly to specific physical objects. For cases where user sub-requirements do not correspond to abstract objects but not physical objects, the user sub-requirements can be satisfied by adjusting the quantity and spatial layout of existing systems and devices without adding new physical objects. If the physical objects corresponding to user sub-requirements have already been established, the attributes of the established physical objects (including but not limited to location, power, color, etc.) can be updated to satisfy the user sub-requirements.

[0187] In some embodiments, in step 301 above, the step of generating third visual data of the system function corresponding to each processing node in each processing node associated with the location information related to the first location to be modified in the target system of the building can be processed in parallel. This improves the efficiency of generating second visual data of the building.

[0188] In some embodiments, in step 302, when the third visual data is obtained based on the user's initial request or the content of the initial proposal to the user, the third visual data of each system function is integrated with the first visual data of the building to obtain the second visual data of the building.

[0189] When the third-view data is obtained based on the updated user requirements or the updated proposal content to the user, the third-view data of each system function is integrated with the second-view data of the building generated based on the previous user requirements or the previous proposal content to the user to obtain the updated second-view data of the building.

[0190] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0191] Obtain user feedback on the generated second visual data;

[0192] If the feedback includes updated user requirements, updated second visual data is generated based on those updated requirements.

[0193] Therefore, updating the second visual data based on user feedback can improve the matching degree between the actual generated proposal visual data and user needs, thereby further enhancing the user experience.

[0194] In some embodiments, user feedback includes, but is not limited to, adjustments to positions in the second visual data. User feedback may be collected based on at least one of the following: voice data from user interaction, a user-filled request data form, or user request record information. This application does not impose any limitations on this.

[0195] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0196] Get the updated proposal content to users;

[0197] Based on the updated proposal to users, generate updated second visual data.

[0198] Therefore, updating the second visual data based on the updated proposal content to the user can improve the matching degree between the actual generated proposal visual data and user needs, thereby further enhancing the user experience.

[0199] In some embodiments, during the generation of updated second visual data, the updated user requirements and the updated proposal content to the user are processed in a manner similar to steps 201 to 203 described above, generating updated user sub-requirements containing location reference information. Furthermore, in the corresponding processing node, for the updated user sub-requirements containing location reference information, processes similar to steps 301 and 302 described above are performed to redetermine the data model and spatial arrangement corresponding to the objects of the updated user sub-requirements, thereby generating updated third visual data of the building that includes the updated user sub-requirements. Then, the updated third visual data is integrated with the previously generated second visual data; for example, the portion of the previously generated second visual data corresponding to the updated third visual data is replaced with the updated third visual data, resulting in updated, complete visual data of the building that meets the updated user requirements.

[0200] Therefore, when there are updated user requirements or updated proposals to users, it is only necessary to generate the visual data corresponding to the updated user requirements or updated proposals to users, and integrate it with the previously generated second visual data to update the second visual data. This improves the efficiency and accuracy of updating the second visual data.

[0201] In some embodiments, before obtaining the final second visual data of the building, steps of data integration, verification, and adjustment are included to efficiently respond to changes in user needs.

[0202] In some embodiments, data integration refers to integrating location reference information of user needs with existing parameters in the building's first visual data to ensure coordination among all relevant systems of the building.

[0203] For example, assuming the user needs to install a camera in the conference room, the specific data integration steps include: (1) Data alignment: Align the camera's installation location (e.g., location coordinates x=5, y=1, z=2.5) with the coordinate system of the building's first visual data; (2) Spatial layout integration: Associate the camera's location with the spatial layout of the conference room and check for conflicts with existing equipment (e.g., lighting fixtures); (3) System function integration: Add a socket for the camera with location coordinates (x=4, y=1, z=0.5); add a network interface with location coordinates (x=3, y=1, z=0.5); (4) Attribute integration: Add the camera's power information (e.g., 50W) to the load calculation of the power system.

[0204] In some embodiments, the integrated data is in text formats such as XML and IFC, which can be directly converted into visual data using data conversion tools to facilitate intuitive and quick viewing by users.

[0205] In some embodiments, verification and adjustment refer to verifying the feasibility of user needs through technical feasibility verification, digital verification of user needs such as pipeline collision detection and structural load simulation based on the first visual data of the building, and / or generating modification suggestions such as reserved equipment interfaces and spatial layout through scalable design.

[0206] For example, assuming the user's requirement is to install a camera in the conference room, the specific verification and adjustment steps include: (1) Consistency check: verifying whether the camera's position coordinates (x=5, y=1, z=2.5) and function (viewpoint covering the entire conference room) meet the customer's requirements and industry standards; (2) Conflict detection: checking whether the camera conflicts with the lighting fixtures or air conditioning vents; (3) Function verification: verifying whether the power of the newly added socket meets the camera's requirements, and whether the bandwidth of the newly added network interface meets the camera's requirements; (4) Simulation and visualization: simulating the camera's viewpoint in the building's first-view data to ensure that it covers the entire conference room; (5) User feedback: showing the camera's position and function to the customer and obtaining user feedback; (6) Adjustment and optimization: if a conflict is found between the camera and the lighting fixtures, adjust the camera's position; if the power system load is insufficient, optimize the power system load distribution.

[0207] Based on technical feasibility verification and scalable design, user needs or parts of user needs that are unreasonable in design or technically impossible to achieve can be eliminated, thereby making the subsequently generated visual data more patentable and reasonable. At the same time, it can show users more possible modification suggestions, improve user experience and proposal success rate.

[0208] In some embodiments, the method for locating visual data of buildings according to the present invention further includes:

[0209] The generated second visual data is displayed using a display device.

[0210] The displayed second visual data includes the initial second visual data generated based on user needs and the proposal content to the user, as well as the updated second visual data based on updated user needs and the updated proposal content to the user.

[0211] This allows for the display of secondary visual data, enabling users to quickly and intuitively understand the proposal and facilitate confirmation. It also allows users to provide feedback, further enhancing the user experience. Therefore, even if building design data is complex and voluminous, and users are unfamiliar with building design or unable to express clear renovation needs, a visually appealing building design proposal can be presented to them for confirmation. Furthermore, by using a large language model combined with sub-processing nodes to refine user needs or proposals, it can more accurately understand and process user requirements, thereby generating visual data that meets those needs more accurately and efficiently. For example, user needs can be met by generating visual data in one or a few batches.

[0212] In some embodiments, the display device displays one or more visualization modules that can be operated by the user (e.g., click, touch, etc.) simultaneously or after displaying the generated second visual data. These visualization modules may be displayed on (overlapping with) the second visual data or outside of it (not overlapping). By operating the corresponding visualization module, the user can trigger at least one of the following operations: confirming the second visual data; obtaining updated user requirements; or obtaining updated proposal content to the user. When the user operation triggers "obtaining updated user requirements," the user can be prompted to input updated user requirements via voice announcement, text, images, etc. Furthermore, the user can input updated user requirements via voice input, text input, file import, etc.

[0213] This allows users to quickly and intuitively understand the proposal, facilitates user confirmation, or provides feedback, and further improves the user experience.

[0214] In some embodiments, when at least one of the updated user requirements and the updated proposal content to the user is obtained, the location method for visual data of buildings according to the present invention further includes the step of updating the workflow.

[0215] In some embodiments, the step of updating the workflow includes:

[0216] Using the fourth artificial intelligence model, the process architecture of the first workflow is updated based on at least one of the updated user needs and the updated proposal content to the user, to obtain the second workflow;

[0217] Updating the workflow architecture of the first workflow includes: deleting the first processing node in the first workflow, or adding a second processing node to the first workflow that is associated with at least one of the updated user requirements and the updated proposal content to the user; and

[0218] According to the set rules, the first processing node that has not been deleted is linked, or the first processing node that has not been deleted is linked with the newly added second processing node.

[0219] For example, suppose the user's original requirement is to design a lighting system and an air conditioning system for an office building. The existing workflow nodes include, for example, the following: (1) Lighting system node: handles the selection and installation of lighting equipment; (2) Air conditioning system node: handles the selection and installation of air conditioning equipment. Suppose the user's updated requirement includes adding a video conferencing system to the conference room. The following operations can be performed in the existing workflow nodes: (1) Modify the lighting system node: The new video conferencing system requires additional lighting support. Adjust the parameters of the lighting system node to increase the lighting requirements of the conference room. For example, increase the number of lights and the brightness requirements of the conference room. (2) Delete redundant nodes: If there are redundant nodes in the original workflow that are not related to the video conferencing system (such as outdated security system nodes), these nodes can be deleted to simplify the workflow. (3) Add a video conferencing system node: According to the new requirements of the customer, add a video conferencing system node to handle the selection and location distribution of equipment such as cameras, microphones, and displays.

[0220] Therefore, when user needs or the content of proposals to users are updated, the corresponding processing nodes in the workflow are updated, thereby improving the efficiency of workflow construction and data location.

[0221] The processes of user requirement decomposition and mapping, association of user requirements with location reference information, data integration, and visual data generation involved in the above embodiments of the present invention are all implemented in the corresponding processing nodes. Therefore, user requirements can be processed in the associated processing nodes, while reusing other processing nodes in the processing flow, thus improving processing efficiency.

[0222] Figure 4 This is a flowchart of a method for locating visual data of buildings according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the flow of a method for locating visual data of buildings according to an embodiment of the present invention. Figure 4 and Figure 5 As shown, the localization methods for visual data of buildings include:

[0223] Step 401: Obtain user needs or the content of the proposal to the user;

[0224] Step 402: Determine whether the user's request or the proposal to the user is the first time it has been made. If yes, proceed to step 403. If no, that is, if the user's request is an updated user request or the proposal to the user is an updated user proposal, proceed to step 409.

[0225] Step 403: Refine and decompose the user requirements or the proposals to the user to obtain the requirements corresponding to the target system.

[0226] For example, such as Figure 5 As shown, user needs or proposals to users are refined and broken down into multiple needs corresponding to air conditioning systems, lighting systems, and security systems. The execution of step 403 can be found in the embodiments related to steps 201 and 202 mentioned above, and will not be repeated here.

[0227] Step 404: In the processing nodes corresponding to each target system, the requirements of each target system are further refined to obtain multiple user sub-requirements corresponding to each target system.

[0228] For example, such as Figure 5 As shown, the requirements corresponding to the air conditioning system are further refined into multiple "primary requirements and corresponding location reference information" and "secondary requirements and corresponding location reference information" corresponding to the air conditioning system; the requirements corresponding to the lighting system are further refined into multiple "primary requirements and corresponding location reference information" corresponding to the air conditioning system; and the requirements corresponding to the lighting system are further refined into multiple "primary requirements and corresponding location reference information" corresponding to the air conditioning system. The execution of step 404 can be found in the embodiments related to the aforementioned step 203, and will not be repeated here.

[0229] Step 405: In the processing nodes corresponding to each target system, generate the third visual data corresponding to the target system according to the user sub-requirements of the target system obtained in step 404.

[0230] For example, such as Figure 5As shown, visual data of the air conditioning system in the building containing the corresponding user sub-requirements is generated in the processing node corresponding to the air conditioning system; visual data of the lighting system in the building containing the corresponding user sub-requirements is generated in the processing node corresponding to the lighting system; and visual data of the security system in the building containing the corresponding user sub-requirements is generated in the processing node corresponding to the security system. The execution of step 405 can be found in the embodiments related to the aforementioned step 301, and will not be repeated here.

[0231] Step 406: Integrate the third visual data corresponding to each target system to obtain second visual data of the building that meets the user's needs. The execution of step 406 can be found in the embodiments related to step 302 above, and will not be repeated here.

[0232] Step 407: Obtain user feedback information.

[0233] Step 408: Determine whether the feedback information includes the updated user requirements, or whether the updated proposal content to the user has been obtained. If yes, proceed to step 409; if no, proceed to step 410.

[0234] Step 409: Extract the updated part from the updated user requirements or the updated proposal to the user, determine the target system corresponding to the updated part, and return to step 404.

[0235] In step 404, user sub-requirements are regenerated in the processing node of the target system corresponding to the updated part. Then, in step 405, the third visual data corresponding to the target system is regenerated. In step 406, the regenerated third visual data corresponding to the target system is integrated with the second visual data of the building generated based on the previous user requirements or the previous proposal content to the user to obtain the updated second visual data.

[0236] Step 410: Output the second visual data of the building that meets the user's requirements.

[0237] Through the above embodiments, the present invention utilizes an artificial intelligence model to determine the location reference information of a second location associated with the location information of the first location that needs to be modified in the target system of the building in the first visual data of the building. This enables the first location that needs to be modified to be accurately matched with the location in the first visual data, that is, to achieve accurate positioning of the location that needs to be modified in the first visual data of the building, thereby enabling the accurate generation of visual data in the target system including the location that needs to be modified based on the location.

[0238] Furthermore, based on the aforementioned location reference information and the first visual data of the building, visual data that accurately matches the user's needs or the content of the proposal to the user can be generated, which helps the user to intuitively and quickly understand the content of the proposal, thereby improving the success rate of the proposal and the user experience.

[0239] In addition, based on the location information related to the first location that needs to be modified in the target system of the building, the processing nodes associated with the location information are determined, and the location reference information of the second location associated with the location information in the first visual data is determined only in the determined processing nodes. Thus, when the user's needs or the content of the proposal to the user changes, the data of other processing nodes in the processing flow can be reused, and only the data of the processing nodes corresponding to the updated user needs or the content of the proposal to the user needs needs to be modified, thereby improving the efficiency of generating proposals.

[0240] Second aspect of the embodiments

[0241] A second aspect of the present invention provides a positioning device for visual data of buildings. Figure 6 This is a schematic diagram of a positioning device for visual data of buildings according to an embodiment of the present invention. Figure 6 As shown, the positioning device 600 for visual data of buildings includes:

[0242] The acquisition module 601 acquires location information related to the first location in the target system of the building that needs to be modified, as well as the first visual data of the building.

[0243] The first determining module 602 determines the processing node associated with the location information based on the first artificial intelligence model;

[0244] The second determining module 603, in the processing node, determines the location reference information of the second location associated with the location information in the first visual data based on the second artificial intelligence model;

[0245] Location reference information is used to locate the first position that needs to be modified in the target system and the second position in the first visual data.

[0246] The first artificial intelligence model is based at least on the relationship between the location information related to the first location that needs to be modified in the target system and the processing nodes in the target system;

[0247] The second artificial intelligence model is based at least on the correlation between the location information related to the first location that needs to be modified in the target system and the location reference information of the second location in the first visual data.

[0248] The positioning device for visual data of buildings provided in this embodiment of the invention can be used to implement the positioning method for visual data of buildings described in the first aspect of the invention. Since the principle of the positioning device for visual data of buildings is similar to that of the positioning method for visual data of buildings, the implementation of the positioning device for visual data of buildings can refer to the implementation of the positioning method for visual data of buildings, and will not be repeated here.

[0249] A second aspect of the present invention also provides a device for generating and displaying visual data of a building. Figure 7 This is a schematic diagram of a device for generating and displaying visual data of a building according to an embodiment of the present invention. Figure 7 As shown, the building visual data generation and display device 700 includes:

[0250] Memory 701 stores computer programs;

[0251] Processor 702, when executing the computer program, implements any of the positioning methods for visual data of buildings according to the first embodiment of the present invention, obtains position reference information of a second location associated with position information in the first visual data, and generates second visual data based on the first visual data and the position reference information; and

[0252] Display 703 displays secondary visual data of the building.

[0253] In some embodiments, the display 703 also displays first visual data of the building, a second location associated with location information related to a first location in the target system that needs to be modified, and location reference information.

[0254] Therefore, this invention utilizes an artificial intelligence model to determine the location reference information of a second location associated with the location information of the first location that needs to be modified in the target system of the building in the first visual data of the building. This enables the first location that needs to be modified to be accurately matched with the location in the first visual data, that is, to achieve accurate positioning of the location that needs to be modified in the first visual data of the building, thereby enabling the accurate generation of visual data in the target system including the location that needs to be modified based on this location.

[0255] Furthermore, based on the aforementioned location reference information and the first visual data of the building, visual data that accurately matches the user's needs or the content of the proposal to the user can be generated, which helps the user to intuitively and quickly understand the content of the proposal, thereby improving the success rate of the proposal and the user experience.

[0256] In addition, based on the location information related to the first location that needs to be modified in the target system of the building, the processing nodes associated with the location information are determined, and the location reference information of the second location associated with the location information in the first visual data is determined only in the determined processing nodes. Thus, when the user's needs or the content of the proposal to the user changes, the data of other processing nodes in the processing flow can be reused, and only the data of the processing nodes corresponding to the updated user needs or the content of the proposal to the user needs needs to be modified, thereby improving the efficiency of generating proposals.

[0257] Third aspect of the embodiments

[0258] A third aspect of the present invention provides a proposal system for buildings. Figure 8 This is a schematic diagram of a proposal system for buildings according to an embodiment of the present invention. Figure 8 As shown, the proposal system 800 for buildings includes at least one of the positioning device 600 for visual data of buildings and the generation and display device 700 for visual data of buildings described in the second aspect of the present invention. A control device for responding to building demands is also included. In the embodiments of the present invention, the implementation of the functions of the proposal system for buildings can refer to the description of the relevant steps in the embodiments of the first and second aspects of the present invention, and will not be repeated here.

[0259] The proposal system 800 for buildings may also include Figure 8 For components not shown, please refer to relevant technologies.

[0260] Through the above embodiments, the present invention utilizes an artificial intelligence model to determine the location reference information of a second location associated with the location information of the first location that needs to be modified in the target system of the building in the first visual data of the building. This enables the first location that needs to be modified to be accurately matched with the location in the first visual data, that is, to achieve accurate positioning of the location that needs to be modified in the first visual data of the building, thereby enabling the accurate generation of visual data in the target system including the location that needs to be modified based on the location.

[0261] Furthermore, based on the aforementioned location reference information and the first visual data of the building, visual data that accurately matches the user's needs or the content of the proposal to the user can be generated, which helps the user to intuitively and quickly understand the content of the proposal, thereby improving the success rate of the proposal and the user experience.

[0262] In addition, based on the location information related to the first location that needs to be modified in the target system of the building, the processing nodes associated with the location information are determined, and the location reference information of the second location associated with the location information in the first visual data is determined only in the determined processing nodes. Thus, when the user's needs or the content of the proposal to the user changes, the data of other processing nodes in the processing flow can be reused, and only the data of the processing nodes corresponding to the updated user needs or the content of the proposal to the user needs needs to be modified, thereby improving the efficiency of generating proposals.

[0263] This invention also provides a computer-readable program, wherein when executed, the program causes a computer to perform any of the location methods for visual data of buildings described in the embodiments of the first aspect of this invention.

[0264] The present invention also provides a computer-readable storage medium storing a computer program that causes a computer to perform any of the location methods for visual data of buildings described in the embodiments of the first aspect of the present invention.

[0265] This invention also provides a computer program product, wherein when executed by a processor, the computer program product causes a computer to perform any of the location methods for visual data of buildings described in the first aspect of this invention.

[0266] The apparatus and methods described above in the embodiments of the present invention can be implemented in hardware or in combination with software. The present invention relates to a computer-readable program that, when executed by a logic component, enables the logic component to implement the aforementioned apparatus or constituent parts, or to implement the various methods or steps described above.

[0267] The embodiments of the present invention also relate to storage media for storing the above programs, such as hard disks, magnetic disks, optical disks, DVDs, flash memory, etc.

[0268] It should be noted that the limitations of each step involved in this invention are not considered as limiting the order of steps, provided that they do not affect the implementation of the specific solution. The steps listed first can be executed first, or they can be executed later, or they can even be executed simultaneously. As long as this solution can be implemented, they should be considered to fall within the protection scope of this invention.

[0269] The present invention has been described above with reference to specific embodiments. However, those skilled in the art should understand that these descriptions are exemplary and not intended to limit the scope of protection of the present invention. Those skilled in the art can make various modifications and variations to the present invention based on its spirit and principles, and these modifications and variations are also within the scope of the present invention.

Claims

1. A method for locating visual data of buildings, characterized in that, The method includes: Acquire location information related to the first location in the target system of the building that needs to be modified, as well as the first visual data of the building; The processing node associated with the location information is determined based on the first artificial intelligence model; In the processing node, location reference information of the second location associated with the location information in the first visual data is determined based on the second artificial intelligence model; The location reference information is reference information used to locate the second position of the first position that needs to be modified in the target system in the first visual data; The first artificial intelligence model is based at least on the relationship between location information related to the first location in the target system that needs to be modified and the processing nodes in the target system; The second artificial intelligence model is based at least on the correlation between the location information related to the first location that needs to be modified in the target system and the location reference information of the second location in the first visual data.

2. The method according to claim 1, characterized in that, When the location information related to the first location that needs to be modified in the target system of the building includes the first location in the building, the step of determining the location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model includes: Using the second artificial intelligence model, position reference information associated with the first position is determined in the first visual data based on the first position; If the location information related to the first location in the target system of the building that needs to be modified does not include the first location in the building, the step of determining the location reference information of the location associated with the location information in the first visual data based on the second artificial intelligence model includes: Based on the location information related to the first location that needs to be modified in the target system of the building and the building design standard information, the second artificial intelligence model is used to generate location reference information in the first visual data that is associated with the first location.

3. The method according to claim 1, characterized in that, The location information related to the first location that needs to be modified in the target system of the building includes: Location information related to at least one of the user requirements, the content of the proposal to the user, the updated user requirements, and the updated content of the proposal to the user.

4. The method according to claim 3, characterized in that, The method further includes: Associate at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user with the corresponding location reference information.

5. The method according to claim 4, characterized in that, Associating at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user with the corresponding location reference information includes: Using a third artificial intelligence model, at least one of the user needs, the proposal content to the user, the updated user needs, and the updated proposal content to the user is refined to obtain the user's first needs; The first requirement is decomposed according to the system function of the building to obtain the second requirement corresponding to each system function of the target system; The second requirement is extracted hierarchically based on the location reference information to obtain multiple user sub-requirements that correspond to the functions of each system and contain the corresponding location reference information.

6. The method according to claim 4, characterized in that, The method further includes: Associate at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user with the processing node associated with the corresponding location information.

7. The method according to claim 3, characterized in that, The method further includes: Based on the first visual data of the building and the location reference information of the second location associated with the location information in the first visual data, a second visual data of the building is generated that meets at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user.

8. The method according to claim 7, characterized in that, Generating second visual data of the building that conforms to at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user, including: In each associated processing node, based on the first visual data of the building, at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user associated with each processing node, and the location reference information associated with at least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user, third visual data of the system function corresponding to each processing node is generated respectively. The third visual data of each system function is integrated to obtain the second visual data of the building.

9. The method according to claim 7, characterized in that, The method further includes: The second visual data is displayed using a display device; Obtain user feedback on the displayed second visual data; if the feedback includes updated user requirements, generate and display updated second visual data based on the updated user requirements; or Obtain the updated proposal content to the user; generate and display the updated second visual data based on the updated proposal content to the user.

10. The method according to claim 3, characterized in that, The processing nodes include workflow processing nodes; The method further includes: Using the fourth artificial intelligence model, a first workflow is constructed based on user needs and at least one associated first processing node in the content of the proposal to the user.

11. The method according to claim 10, characterized in that, The method further includes: Using a fourth artificial intelligence model, the process architecture of the first workflow is updated based on at least one of the updated user requirements and the updated proposal content to the user, to obtain a second workflow. Updating the workflow architecture of the first workflow includes: deleting a first processing node in the first workflow, or adding a second processing node in the first workflow that is associated with at least one of the user requirements and the updated proposal content to the user; and According to the set rules, the first processing node that has not been deleted is linked, or the first processing node that has not been deleted is linked with the newly added second processing node.

12. The method according to claim 3, characterized in that, At least one of the user requirements, the proposal content to the user, the updated user requirements, and the updated proposal content to the user is generated based on at least one of the voice data from user interaction, the user-filled requirement data form, and the user's requirement record information.

13. The method according to claim 3, characterized in that, The user requirements include at least one of the following: system information, equipment information, area information, and evaluation information of the building environment; The proposal to the user includes at least one of the following: system information, equipment information, area information, and evaluation information of the building environment.

14. The method according to any one of claims 1 to 13, characterized in that, The method further includes: Based on the first visual data of the building and the location reference information of the second location associated with the location information of the first location in the first visual data that is related to the first location that needs to be modified in the target system, the second location in the first visual data is determined; Display the first visual data, the second position, and the position reference information.

15. The method according to any one of claims 1 to 13, characterized in that, The first visual data of the building includes at least one of the following: The parameter data, image data, video data, and proposal data of the multi-dimensional visualization model of the building; The building's multi-dimensional visualization model, generated based on previous user needs or previous proposals to users, includes at least one of the following: parameter data, image data, video data, and proposal data.

16. The method according to any one of claims 1 to 13, characterized in that, The location reference information includes at least one of the following: Location information, spatial information, regional information, time information, material information, color information, pipeline routing information, and layer information.

17. A positioning device for visual data of buildings, characterized in that, The device includes: The acquisition module acquires location information related to the first location in the target system of the building that needs to be modified, as well as the first visual data of the building. The first determining module determines the processing node associated with the location information based on the first artificial intelligence model; The second determining module, in the processing node, determines the location reference information of the second location associated with the location information in the first visual data based on the second artificial intelligence model; The location reference information is reference information used to locate the second position of the first position that needs to be modified in the target system in the first visual data; The first artificial intelligence model is based at least on the relationship between location information related to the first location in the target system that needs to be modified and the processing nodes in the target system; The second artificial intelligence model is based at least on the correlation between the location information related to the first location that needs to be modified in the target system and the location reference information of the second location in the first visual data.

18. A device for generating and displaying visual data of a building, characterized in that, The device includes: A memory that stores computer programs; A processor, which, when executing the computer program, implements the method of any one of claims 1 to 16, obtaining position reference information of a second position associated with the position information in first visual data, and generating second visual data based on the first visual data and the position reference information; and A display screen shows secondary visual data of the building.

19. The apparatus according to claim 18, characterized in that, The display also shows first visual data of the building, a second location associated with location information related to the first location that needs to be modified in the target system, and location reference information.

20. A proposal system for buildings, characterized in that, The system includes the apparatus of any one of claims 17 to 19.

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