Building house decoration intelligent design analysis system based on artificial intelligence

Abstract

The invention discloses a building house decoration intelligent design analysis system based on artificial intelligence, which belongs to the technical field of decoration design and comprises a platform end and a user end. The user side comprises an information module and an evaluation display module; the information module is used for performing information management on the user house, acquiring house information, a decoration design drawing and additional design data of the user house, and performing size supplementation on the decoration design drawing according to the house information and the additional design data; granting a sharing permission to the design evaluation module of the platform end; the evaluation display module is used for visually displaying the design evaluation data; the platform end comprises a design evaluation module; the design evaluation module is used for carrying out design evaluation, identifying user sides with sharing authority in real time, identifying corresponding decoration design drawings, additional design data and house information from the user sides, and carrying out application evaluation on the decoration design drawings to obtain design evaluation data of the decoration design drawings; and the evaluation display module is used for sending the design evaluation data to the user side.

Description

Technical Field

[0001] This invention belongs to the field of interior design technology, specifically an intelligent design and analysis system for building decoration based on artificial intelligence. Background Technology

[0002] In the field of building decoration, homeowners, as the end users and evaluators of interior design, often face numerous challenges in evaluating design schemes. A particularly prominent issue is the widespread lack of professional knowledge among users. Under traditional interior design evaluation models, homeowners typically rely on personal aesthetics, life experience, and fragmented information obtained from non-professional channels to form judgments about design schemes. This process is not only inefficient but also highly susceptible to subjectivity and bias due to a lack of professional knowledge. Specifically, when evaluating interior designs, homeowners often lack understanding of professional standards such as building structural safety codes, material performance parameters, and space utilization efficiency, making it difficult to comprehensively consider the scientific validity and rationality of the design scheme. This forces homeowners to rely solely on the designer's descriptions for evaluation, resulting in significant bias. This is especially true given that many interior designers are not architectural professionals, and the designers themselves often lack professional knowledge, leading to considerable uncertainty in interior design.

[0003] In order to solve the above problems, this invention provides an intelligent design and analysis system for building decoration based on artificial intelligence. Summary of the Invention

[0004] To address the problems of the above solutions, this invention provides an intelligent design and analysis system for building decoration and renovation based on artificial intelligence.

[0005] The objective of this invention can be achieved through the following technical solutions: An AI-based intelligent design and analysis system for building decoration and renovation includes a platform and a user terminal. Furthermore, there is a communication connection between the platform and each user terminal.

[0006] The user terminal includes an information module and an evaluation display module; The information module is used to manage user housing information, obtain housing information, decoration design drawings, and additional design data of user housing. The additional design data is design data provided by the decoration design party that is not part of the decoration design drawings. The module supplements the decoration design drawings with dimensions based on the housing information and additional design data. The module summarizes and stores the decoration design drawings, additional design data, and housing information. The module grants sharing permissions to the design evaluation module on the platform.

[0007] Furthermore, the dimensions of the renovation design drawings are supplemented based on the house information and additional design data, including: Identify dimensional data in housing information and additional design data, and identify the dimensional targets corresponding to the dimensional data; Identify the target dimensions in the interior design drawings and supplement the corresponding dimension data for each target dimension in the interior design drawings.

[0008] Furthermore, dynamic permission management is implemented for the granted shared permissions. Methods for dynamic permission management include: Get users' design evaluation requirements in real time, and determine whether to grant sharing permissions based on the design evaluation requirements; If it is determined that sharing permissions should not be granted, no corresponding action will be taken; When it is determined to grant sharing permissions, the sharing permissions are granted to the design evaluation module, and the access records of the stored data on the platform are identified in real time. Based on the access records, it is determined whether to revoke the sharing permissions granted to the design evaluation module.

[0009] Further, based on the access records, determine whether to revoke the shared permissions granted to the design evaluation module, including: When it is determined from the access records that the platform has accessed and shared the decoration design drawings, additional design data and house information, the sharing permission granted to the design evaluation module will be revoked. When access to non-shared data is detected in the access log, the shared permissions granted to the design evaluation module are revoked, and feedback is sent to the user.

[0010] The evaluation and display module is used to visualize the received design evaluation data.

[0011] Furthermore, the design evaluation data is visualized, including: Acquire life simulation animations from design evaluation data, identify anomaly markers in the life simulation animations, segment the life simulation animations based on the anomaly markers, and obtain anomaly display animations; then present the anomaly display animations and anomaly design units to the user; When a user needs to view the complete life simulation animation, the undivided life simulation animation will be displayed to the user.

[0012] The platform includes a design evaluation module; The design evaluation module is used to perform design evaluation, identify user terminals with sharing permissions in real time, identify the corresponding decoration design drawings, additional design data and house information from the user terminals, evaluate the application of the decoration design drawings, obtain the design evaluation data of the decoration design drawings, and send the design evaluation data to the evaluation display module of the user terminals.

[0013] Furthermore, an application evaluation of the decoration design drawings is conducted, including: Identify each design unit in the interior design drawings, obtain the intended use of the house from the house information, and generate a life simulation animation based on the intended use and the interior design drawings; Application evaluation is conducted based on life simulation animations to obtain abnormal design units. Abnormalities are marked on the life simulation animations based on the abnormal design units, and design evaluation data is formed based on each abnormal design unit and the life simulation animation.

[0014] Furthermore, application evaluation based on life simulation animations includes: The platform provider shall establish a design anomaly database, which shall be used to store various anomaly identification features and anomaly causes. An anomaly identification model is established based on the anomaly database. The expression for the anomaly identification model is: ; In the formula: (s) i U) is the input data, s i This represents the corresponding anomaly identification feature in the anomaly database, where i is the subscript, i = 1, 2, ..., n, and n is the number of anomaly identification features in the anomaly database; U represents the life simulation animation; s i →U indicates that the life simulation animation has corresponding anomaly recognition characteristics; the output data is the anomaly recognition value YU(s) i (U), the abnormal identification value is 1 or 0; Anomaly detection models are used to analyze life simulation animations to obtain anomaly detection values ​​for corresponding anomaly detection features. When the anomaly detection value is 0, no corresponding action is taken; When the anomaly identification value is 1, the anomaly cause corresponding to the anomaly identification feature is identified, and the anomaly design unit is determined based on the anomaly cause and the life simulation animation.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention provides an AI-based intelligent design and analysis system for building decoration and renovation, effectively overcoming the evaluation dilemma caused by homeowners' lack of professional knowledge in traditional decoration design assessment models. The system uses AI technology to intelligently evaluate decoration design drawings and presents design flaws intuitively to users through animation. This allows homeowners to obtain scientific and objective evaluation results without relying on fragmented information or one-sided descriptions from non-professional designers. The system not only eliminates the subjectivity and bias in evaluations caused by homeowners' lack of professional knowledge but also avoids design uncertainties caused by the insufficient capabilities of non-professional designers through intelligent analysis, significantly improving the efficiency and accuracy of decoration design assessments. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a block diagram illustrating the principle of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, an intelligent design and analysis system for building decoration based on artificial intelligence includes a platform and a user terminal. The platform and each user terminal are connected for communication; the user terminal is used by the users of each associated house.

[0020] The user terminal includes an information module and an evaluation display module; The information module is used for information management of user properties, acquiring property information, interior design drawings, and additional design data. Property information includes dimensions, pictures, structure, and intended use, such as rental, owner-occupancy, or pet ownership, thus specifying various possible uses. Additional design data includes other design data provided by the designer, such as furniture dimension drawings. The property information, additional design data, and interior design drawings are uploaded by the user. The module supplements the interior design drawings with dimensions based on the property information and additional design data. It summarizes and stores the current interior design drawings, additional design data, and property information. It also grants sharing permissions to the platform's design evaluation module, allowing it to access the stored interior design drawings, additional design data, and property information.

[0021] Size data and other information can be obtained from the interior design company, as they will conduct on-site measurements of the house before the design process, and will have the actual house size data.

[0022] The dimensions of the interior design drawings are supplemented based on the house information and additional design data. This means marking the corresponding dimensions on the interior design drawings, since it is difficult to directly obtain the corresponding dimension information from the current 3D interior design drawings. The dimensions of other furniture such as cabinets are also added to the interior design drawings. After implementation, the corresponding dimension data can be directly identified from the interior design drawings. If the interior design drawings have complete dimension data, then no supplementation is required.

[0023] For example, identify the dimensional data in the house information and additional design data, and identify the dimensional targets corresponding to the dimensional data, such as the dimensional targets of the house structure, wardrobe, TV cabinet, etc. Identify the various dimensional targets in the decoration design drawings, and supplement the corresponding dimensional data of each dimensional target in the decoration design drawings based on the dimensional data.

[0024] In one embodiment, the granting of sharing permissions is manually enabled and disabled by the user. Sharing permissions are granted when design evaluation is required, and are revoked after the evaluation is completed.

[0025] In one embodiment, because users often fail to revoke shared permissions in practical applications, posing a certain security risk, the management of shared permissions in this embodiment includes: Real-time acquisition of users' design evaluation needs, i.e., whether users need design evaluation of decoration design drawings; and determination of whether to grant sharing permissions based on design evaluation needs. If it is determined that sharing permissions should not be granted, no corresponding action will be taken; When it is determined to grant sharing permissions, the sharing permissions are granted to the design evaluation module. The access records of the stored data on the platform are identified in real time. The stored data includes not only decoration design drawings, additional design data and house information. Based on the access records, it is determined whether to revoke the sharing permissions granted to the design evaluation module.

[0026] In one embodiment, the system determines whether to revoke the sharing permission granted to the design evaluation module based on the access records. When the access records identify that the interior design drawings, additional design data, and house information have been accessed and shared, the sharing permission granted to the design evaluation module is revoked.

[0027] In one embodiment, if the access logs identify other accesses to irrelevant data on the platform, the shared permissions granted to the design evaluation module are revoked directly, and feedback is sent to the user.

[0028] Irrelevant data is determined based on the preset required data range and is marked as non-shared data.

[0029] The evaluation and display module is used to visualize the received design evaluation data.

[0030] The data can be displayed in a preset way. For example, for non-animated design evaluation data, a visual simulation can be created based on the data. For animated data, it can be displayed directly to the user, or the normal animation can be removed to facilitate the user's efficient understanding of the evaluation results.

[0031] The platform includes a design evaluation module; The design evaluation module is used to perform design evaluations, identify user terminals with sharing permissions in real time, identify corresponding decoration design drawings, additional design data, and house information from the corresponding user terminals, evaluate the application of the decoration design drawings, determine whether each design in the decoration design drawings is reasonable in subsequent use, and obtain corresponding design evaluation data; that is, this invention performs design evaluation from an application perspective, and for styles, aesthetics, etc., which have a great deal of individuality, users can evaluate according to their own preferences; the design evaluation data is sent to the evaluation display module of the corresponding user terminal.

[0032] In one embodiment, the interior design drawings are evaluated to obtain the intended use of the house information. Based on existing technology, the current interior design drawings are evaluated to determine whether they can meet the various intended uses, thereby identifying the unreasonable parts of the design and summarizing them to form design evaluation data.

[0033] In one embodiment, the application evaluation of the decoration design drawings includes: Identify the various design units in the interior design drawings and categorize them according to room type, such as master bedroom floor, hallway floor, living room floor, master bedroom wardrobe, secondary bedroom wardrobe, balcony wardrobe, and balcony laundry cabinet. Obtain the intended use of the house and generate a life simulation animation based on the intended use and the interior design drawings. That is, generate corresponding virtual characters based on the number of people, pets, etc., and simulate the activities of the virtual characters according to the intended use and the interior design drawings to form an animation, which is marked as a life simulation animation. Application evaluation is conducted based on life simulation animations to identify unreasonable design units, which are marked as abnormal design units. Based on the abnormal design units, the life simulation animations are further anomaly-marked, i.e., which simulated behaviors make the design unit an abnormal design unit. Design evaluation data is then generated based on each abnormal design unit and the life simulation animation.

[0034] In one embodiment, a life simulation animation is generated based on usage and interior design drawings. The platform pre-sets various character backgrounds, each representing a specific character's usage purpose. Based on these backgrounds, corresponding usage simulation data is set, such as simulations of washing clothes, cooking, and pet toileting. For example, a cat might jump, scratch the sofa, use the litter box, eat, groom itself, and sleep; a dog might run, fetch a toy, wag its tail, urinate, eat, and snuggle with its owner. Different usage simulation data are set based on various family situations, such as the presence or absence of pets and family composition. The platform can then match the most relevant usage simulation data to the user's actual situation. The life simulation animation is generated using the matched usage simulation data, character backgrounds, and interior design drawings. Specifically, this is achieved using existing technology.

[0035] An example of an AI-driven animation generation process: Scene Analysis and Planning: Space division: Divide the house model into functional areas (living room, bedroom, kitchen, etc.) and mark the entrance / exit locations.

[0036] Path network construction: A navigation mesh (NavMesh) is generated based on the layout of walls and furniture to ensure that the passable area for characters is reasonable.

[0037] Conflict detection: Predict potential collision points (such as narrow corridors or door frame heights) and mark them as high-risk areas.

[0038] Behavioral sequence generation: Match corresponding actions from the asset library based on the character's background; insert random behaviors (such as a child suddenly running away to play while eating) to increase realism.

[0039] Multi-agent collaboration: The Social Force Model is used to simulate multi-person interactions (such as the avoidance logic when family members use the living room at the same time).

[0040] Pet behavior interacts with human behavior (e.g., a dog follows its owner, a cat jumps onto the sofa when its owner is watching TV).

[0041] Physics simulation: When a character collides with furniture, physical feedback is triggered (such as hitting a table causing the item to fall).

[0042] An animation of cleaning is generated after the pet uses the toilet (such as the owner cleaning the litter box).

[0043] Emergency scenario triggering: Fire simulation: Smoke diffusion path → Escape route selection for personnel → Exit congestion analysis.

[0044] Water pipe burst: water flow direction → people's avoidance behavior → furniture damage assessment.

[0045] Real-time rendering engine: Engine selection: Unity or Unreal Engine, supporting high-fidelity rendering and physical calculations.

[0046] Optimization techniques: LOD (Level of Detail) management: Reduce precision for distant objects to improve performance.

[0047] Batch rendering: Merging objects with similar materials reduces draw calls.

[0048] Cloud rendering support: Process large-scale scenes via AWS Thinkbox or Azure Batch.

[0049] Multi-view output: Fixed viewpoint: Provides top view, side view, and first-person view for easy observation of movement.

[0050] Free Viewpoint: You can drag the mouse or the image to rotate the scene and view details in 360 degrees.

[0051] Interactive features: Pause / Rewind: Supports viewing animation frame by frame and analyzing behavior at specific moments.

[0052] Parameter adjustment: Modify parameters such as character speed and pet personality in real time to observe design changes.

[0053] VR Mode: Immersive experience through Oculus or HTC Vive devices.

[0054] In one embodiment, application evaluation based on life simulation animation can be conducted using existing evaluation methods, such as machine learning or deep learning algorithms. The platform provider establishes an intelligent evaluation model, which is then trained on a training set labeled with the life data of the corresponding families. The intelligent evaluation model, once successfully trained, analyzes the life simulation animation to obtain the corresponding abnormal design units.

[0055] In one embodiment, application evaluation based on life simulation animation includes: The platform will establish a design anomaly database to store various anomaly identification features, such as the following abnormal usage phenomena: the kitchen countertop is too far from the refrigerator and sink, causing repeated walking while cooking; the wet and dry areas of the bathroom are not separated, making the floor slippery and easy to fall on after use; the living room TV wall is too thick and takes up too much space; the bedroom wardrobe is not deep enough, making it difficult to hang clothes; the kitchen wall cabinets are too high, making it inconvenient to take items out and put them in. Anomaly identification features will be determined based on abnormal usage phenomena; that is, anomaly identification features will be set according to various abnormal usage phenomena caused by unreasonable design. An anomaly identification model is established based on an anomaly database. This model is used to identify real-life simulation animations and determine whether they possess corresponding anomaly identification features. The expression for the anomaly identification model is: ; In the formula: (s) i U) is the input data, s i This represents the corresponding anomaly identification feature in the anomaly database, where i is the subscript, i = 1, 2, ..., n, and n is the number of anomaly identification features in the anomaly database; U represents the life simulation animation; s i →U indicates that the life simulation animation has corresponding anomaly recognition characteristics; the output data is the anomaly recognition value YU(s) i (U), the anomaly identification value is 1 or 0; the training set is marked with corresponding historical data so that the anomaly identification model can identify whether there are corresponding anomaly identification features in life simulation animation; Anomaly detection models are used to analyze life simulation animations to obtain anomaly detection values ​​for corresponding anomaly detection features. When the anomaly detection value is 0, no corresponding action is taken; When the anomaly identification value is 1, the cause of the anomaly identification feature is determined based on the life simulation animation, and the anomaly design unit is determined. If multiple design units are affected, then multiple combinations of design units form an anomaly design unit, such as unreasonable spatial layout. The anomaly design unit can be determined based on the life simulation animation and the anomaly identification feature, or the anomaly cause of each anomaly identification feature in the anomaly library can be set in advance, and the anomaly design unit can be determined in the life simulation animation based on the anomaly cause.

[0056] The above formulas are all numerical calculations after removing dimensions. The formulas are obtained by software simulation based on a large amount of data and are closest to the real situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained by simulation based on a large amount of data.

[0057] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An intelligent design and analysis system for building decoration and renovation based on artificial intelligence, characterized in that, Including both the platform side and the user side; The user terminal includes an information module and an evaluation and display module; the platform terminal includes a design evaluation module. The information module is used to manage information about the user's house, and to obtain the house information, decoration design drawings and additional design data of the user's house. The additional design data is the design data that is not part of the decoration design drawings provided by the decoration design party. The dimensions of the renovation design drawings are supplemented based on the house information and additional design data; the renovation design drawings, additional design data, and house information are summarized and stored; and sharing permissions are granted to the design evaluation module on the platform. The evaluation and display module is used to visualize the received design evaluation data; The design evaluation module is used to perform design evaluation, identify user terminals with sharing permissions in real time, identify the corresponding decoration design drawings, additional design data and house information from the user terminals, evaluate the application of the decoration design drawings, obtain the design evaluation data of the decoration design drawings, and send the design evaluation data to the evaluation display module of the user terminals.

2. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 1, characterized in that, Based on the house information and additional design data, supplement the dimensions of the renovation design drawings, including: Identify dimensional data in housing information and additional design data, and identify the dimensional targets corresponding to the dimensional data; Identify the target dimensions in the interior design drawings and supplement the corresponding dimension data for each target dimension in the interior design drawings.

3. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 2, characterized in that, Dynamic permission management is implemented for granted shared permissions. Methods for dynamic permission management include: Get users' design evaluation requirements in real time, and determine whether to grant sharing permissions based on the design evaluation requirements; If it is determined that sharing permissions should not be granted, no corresponding action will be taken; When it is determined to grant sharing permissions, the sharing permissions are granted to the design evaluation module, and the access records of the stored data on the platform are identified in real time. Based on the access records, it is determined whether to revoke the sharing permissions granted to the design evaluation module.

4. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 3, characterized in that, Determine whether to revoke shared permissions granted to the design evaluation module based on access records, including: When it is determined from the access records that the platform has accessed and shared the decoration design drawings, additional design data and house information, the sharing permission granted to the design evaluation module will be revoked. When access to non-shared data is detected in the access log, the shared permissions granted to the design evaluation module are revoked, and feedback is sent to the user.

5. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 1, characterized in that, Visualize the design evaluation data, including: Acquire life simulation animations from design evaluation data, identify anomaly markers in the life simulation animations, segment the life simulation animations based on the anomaly markers, and obtain anomaly display animations; then present the anomaly display animations and anomaly design units to the user; When a user needs to view the complete life simulation animation, the undivided life simulation animation will be displayed to the user.

6. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 1, characterized in that, An evaluation of the application of the interior design drawings is conducted, including: Identify each design unit in the interior design drawings, obtain the intended use of the house from the house information, and generate a life simulation animation based on the intended use and the interior design drawings; Application evaluation is conducted based on life simulation animations to obtain abnormal design units. Abnormalities are marked on the life simulation animations based on the abnormal design units, and design evaluation data is formed based on each abnormal design unit and the life simulation animation.

7. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 6, characterized in that, Application evaluation based on life simulation animation, including: The platform provider shall establish a design anomaly database, which shall be used to store various anomaly identification features and anomaly causes. An anomaly identification model is established based on the anomaly database. The expression for the anomaly identification model is: ； In the formula: (s) i U) is the input data, s i This represents the corresponding anomaly identification feature in the anomaly database, where i is the subscript, i = 1, 2, ..., n, and n is the number of anomaly identification features in the anomaly database; U represents the life simulation animation; s i →U indicates that the life simulation animation has corresponding anomaly recognition characteristics; the output data is the anomaly recognition value YU(s) i (U), the abnormal identification value is 1 or 0; Anomaly detection models are used to analyze life simulation animations to obtain anomaly detection values ​​for corresponding anomaly detection features. When the anomaly detection value is 0, no corresponding action is taken; When the anomaly identification value is 1, the anomaly cause corresponding to the anomaly identification feature is identified, and the anomaly design unit is determined based on the anomaly cause and the life simulation animation.

8. The intelligent design and analysis system for building decoration and renovation based on artificial intelligence according to claim 1, characterized in that, The communication connection between the platform and each user terminal.

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