An AR-assisted building design monitoring management system and method

Abstract

The application discloses an AR-assisted building design monitoring management system and method, and relates to the technical field of building construction management.The system comprises an AR rendering module, which acquires real-time data in the building design process, and renders a building design model in an augmented reality device based on the real-time data; a progress tracking module, which tracks the building construction progress in real time, and uses a time series analysis model to predict the deviation of the progress at the next moment; an analysis and decision module, which establishes a construction quality and safety evaluation model based on the predicted deviation of the progress at the next moment, and through real-time data feedback and intelligent analysis algorithms; and a modification suggestion generation and decision support module, which generates modification suggestions based on the evaluation results.The application proposes that the AR technology superimposes the building design model on the construction site in real time, and can intuitively understand the design requirements and the construction progress, and through the integration of the progress deviation, quality feedback and safety data, the system can intelligently evaluate the current construction quality and safety, and reduce the risks in the construction.

Description

Technical Field

[0001] This invention relates to the field of building construction management technology, specifically to an AR-assisted building design monitoring and management system and method. Background Technology

[0002] As a traditional labor-intensive industry, the construction industry typically faces numerous challenges in design, construction, and schedule management, especially in large-scale construction projects. Managers need to coordinate information from multiple aspects, including design drawings, construction schedules, quality control, and safety risks. Traditional construction management methods rely heavily on manual recording and on-site inspections, which are inefficient and prone to errors and delays. AR technology, as an emerging technology, has been applied in many industries, particularly in construction. AR technology can combine virtual information with the real environment, providing real-time visual feedback and greatly improving the efficiency and accuracy of information transmission. Building Information Modeling (BIM) technology provides precise control over each stage of construction through digital building models. Combining BIM with AR can seamlessly connect the building design model with the actual situation on the construction site, presenting building information in real time.

[0003] However, although AR and BIM technologies have made some progress in the application of building management, there is still a lack of integrated solutions in terms of construction progress tracking, quality control, safety assessment, and intelligent decision support. Therefore, an AR-assisted building design monitoring and management system is proposed, which aims to provide intelligent decision support for building projects through real-time data collection and analysis, progress prediction, quality and safety assessment, and other functions, thereby improving building management efficiency and project execution quality. Summary of the Invention

[0004] To address the aforementioned technical problems, an AR-assisted building design monitoring and management system and method are provided. This technical solution resolves the problems described above.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] An AR-assisted building design monitoring and management system includes:

[0007] The AR rendering module is used to acquire real-time data during the architectural design process, render the architectural design model in the augmented reality device, and overlay the architectural design information onto the actual scene of the construction site.

[0008] The progress tracking module is used to track the construction progress in real time, compare the real-time progress with the planned progress, use a time series analysis model to predict the deviation of the progress at the next moment, and issue an early warning notification when the construction progress deviates from the plan, prompting the construction management personnel to make adjustments.

[0009] The analysis and decision-making module, based on the deviation of the predicted progress at the next moment, establishes a construction quality and safety assessment model through real-time data feedback and intelligent analysis algorithms to comprehensively assess the construction quality and safety.

[0010] Improvement suggestion generation and decision support module: Based on the assessment results of the construction quality and safety assessment model, it generates improvement suggestions.

[0011] Preferably, the AR rendering module specifically includes:

[0012] Real-time data acquisition unit: Based on sensors at the construction site, it collects real-time data during the architectural design process, including architectural design drawings and construction progress;

[0013] 3D architectural design model building unit: Based on architectural design drawings, a 3D model of the building is generated by combining BIM technology with AR.

[0014] Augmented Reality Scene Rendering Unit: Combines real-time collected environmental data with the 3D architectural design model, and uses AR rendering technology to overlay the architectural design model onto the actual scene of the construction site. The AR device overlays construction data in real time and updates the architectural model and design information in real time.

[0015] Preferably, the progress tracking module specifically includes:

[0016] Real-time progress vs. planned progress comparison unit: Input the original construction plan data, store the construction plan progress data in the database, compare the real-time collected construction progress data with the planned progress data, and obtain the progress deviation;

[0017] Construction progress deviation early warning unit: Based on the currently identified progress deviation, the system uses a time series analysis model to predict the progress deviation at the next moment, obtains historical data on progress deviation, sets a deviation threshold, sets the threshold based on the standard deviation, and sets a 2x coefficient to define the threshold. When the predicted progress deviation at the next moment exceeds the preset threshold, the system automatically issues an early warning notification.

[0018] Warning notification generation and transmission unit: When the deviation from the predicted progress at the next moment exceeds the set threshold, the system generates a warning notification, including the deviation content and suggested adjustment measures.

[0019] Preferably, the step of using a time series analysis model to predict the progress deviation at the next moment based on the currently identified progress deviation specifically includes:

[0020] The formula for the time series analysis model is as follows:

[0021] ;

[0022] In the formula, It is the predicted next moment. Schedule deviation, It is the mean. These are the coefficients of the autoregressive component. It is a historic moment Schedule deviation, It is the moving average coefficient. It is a historic moment Error term, It is the order of the autoregressive part. It is the order of the moving average component.

[0023] Preferably, the analysis and decision-making module specifically includes:

[0024] Quality and Safety Assessment Unit: Based on the predicted schedule deviations and combined with quality feedback data, a quality prediction model is established using a linear regression equation to predict potential quality problems in the current stage. The quality prediction model formula is as follows:

[0025] ;

[0026] In the formula, Indicates the current stage of the forecast. Quality rating It is the intercept term of the model. It is related to schedule deviation The relevant regression coefficients, It is related to historical quality data The relevant regression coefficients, It is an error term;

[0027] Construction safety assessment: Collect safety data from the construction site and combine it with progress data for safety analysis. Use decision tree algorithms to assess potential safety risks in the current construction process. Combine predicted progress deviations with historical data to determine whether progress delays will increase the risk of safety accidents.

[0028] Integrated Quality and Safety Assessment Unit: This unit integrates schedule deviation prediction data, construction quality data, and safety data to construct an integrated assessment model and obtain comprehensive construction quality and safety assessment results.

[0029] Preferably, the integration of schedule deviation prediction data, construction quality data, and safety data to construct a comprehensive evaluation model and obtain a comprehensive construction quality and safety evaluation result specifically includes:

[0030] Based on the weighted average formula, a comprehensive evaluation model is established using schedule deviation prediction data, construction quality data, and safety data as inputs, and construction quality and safety assessment results as outputs. The formula for the comprehensive evaluation model is as follows:

[0031] ;

[0032] In the formula, Based on the comprehensive assessment results of construction quality and safety, This represents the deviation from the projected progress at the current stage. This indicates the quality score for the current stage. This indicates the results of the construction safety assessment. The weighting coefficients for predicting schedule deviations, These are the weighting coefficients for the quality score. Weighting coefficients for construction safety assessment results.

[0033] Preferably, the improvement suggestion generation and decision support module specifically includes:

[0034] Improvement suggestion generation unit: Based on the quality and safety assessment results, schedule deviations and safety risk analysis, it generates targeted construction improvement suggestions, including construction schedule adjustments, quality control measures and safety risk prevention strategies;

[0035] Decision Support Unit: Based on improvement suggestions and the actual situation of the project, it provides decision support to help construction management personnel make adjustment decisions and presents the suggestions in the AR device so that they can be applied in real time on the construction site.

[0036] An AR-assisted building design monitoring and management method includes:

[0037] Step 1: Real-time data acquisition, collecting architectural design drawings, construction progress, quality feedback, and safety data through on-site sensors and equipment;

[0038] Step 2: Rendering the 3D architectural design model. Combining BIM technology and AR, a 3D architectural model is generated and rendered in real time to the construction site, overlaying design information with the actual scene.

[0039] Step 3: Progress tracking and forecasting, real-time comparison of construction progress with planned progress, use time series analysis to predict progress deviations, and generate deviation warning notifications;

[0040] Step 4: Quality and safety assessment. Based on predicted schedule deviations, real-time data, and historical information, intelligent algorithms are used to comprehensively assess construction quality and safety, generate corresponding improvement suggestions, and provide decision support.

[0041] Preferably, step two specifically includes:

[0042] Based on architectural design drawings and sensor data from the construction site, a three-dimensional architectural design model is constructed.

[0043] By combining BIM and AR technologies, AR devices can display 3D models in real time and overlay construction data, enabling seamless integration of design information and construction site data.

[0044] The building model is dynamically updated in an augmented reality scenario, and the construction progress and quality feedback are presented in real time.

[0045] Preferably, step three specifically includes: comparing the real-time progress with the planned progress, identifying the progress deviation, using a time series analysis model to predict the progress deviation at the next moment based on historical data, and setting an early warning threshold. When the predicted deviation exceeds the threshold, the system automatically issues an early warning notification, which includes the deviation content, suggested adjustment measures, and provides decision support.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] This invention proposes AR technology to overlay architectural design models onto the construction site in real time, helping construction workers to more intuitively understand design requirements and construction progress, reducing errors and rework, and improving construction accuracy and efficiency. The system can track construction progress in real time and compare it with the original plan. It predicts progress deviations through time series analysis models and issues warnings when progress is lagging, helping construction managers to adjust plans in a timely manner and avoid project delays. By integrating progress deviations, quality feedback, and safety data, the system can use intelligent algorithms to assess the current construction quality and safety, identify potential quality problems and safety hazards in advance, and reduce risks during construction. Attached Figure Description

[0048] Figure 1 This is a system framework diagram of the present invention;

[0049] Figure 2 This is a flowchart illustrating the steps of the present invention. Detailed Implementation

[0050] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0051] Reference Figure 1 As shown, an AR-assisted building design monitoring and management system includes:

[0052] The AR rendering module is used to acquire real-time data during the architectural design process, render the architectural design model in the augmented reality device, and overlay the architectural design information onto the actual scene of the construction site.

[0053] The progress tracking module is used to track the construction progress in real time, compare the real-time progress with the planned progress, use a time series analysis model to predict the deviation of the progress at the next moment, and issue an early warning notification when the construction progress deviates from the plan, prompting the construction management personnel to make adjustments.

[0054] The analysis and decision-making module, based on the deviation of the predicted progress at the next moment, establishes a construction quality and safety assessment model through real-time data feedback and intelligent analysis algorithms to comprehensively assess the construction quality and safety.

[0055] Improvement suggestion generation and decision support module: Based on the assessment results of the construction quality and safety assessment model, it generates improvement suggestions.

[0056] The AR rendering module specifically includes:

[0057] Real-time data acquisition unit: Based on sensors at the construction site, it collects real-time data during the architectural design process, including architectural design drawings and construction progress;

[0058] 3D architectural design model building unit: Based on architectural design drawings, a 3D model of the building is generated by combining BIM technology with AR.

[0059] Augmented Reality Scene Rendering Unit: Combines real-time collected environmental data with the 3D architectural design model, and uses AR rendering technology to overlay the architectural design model onto the actual scene of the construction site. The AR device overlays construction data in real time and updates the architectural model and design information in real time.

[0060] This module combines real-time data acquisition with augmented reality technology to overlay architectural design models onto the construction site, achieving seamless integration of architectural information with the actual scene. It utilizes AR technology to improve the visual management of the construction site and enhances the transmission and interactivity of design information.

[0061] The progress tracking module specifically includes:

[0062] Real-time progress vs. planned progress comparison unit: Input the original construction plan data, store the construction plan progress data in the database, compare the real-time collected construction progress data with the planned progress data, and obtain the progress deviation;

[0063] Construction progress deviation early warning unit: Based on the currently identified progress deviation, the system uses a time series analysis model to predict the progress deviation at the next moment, obtains historical data on progress deviation, sets a deviation threshold, sets the threshold based on the standard deviation, and sets a 2x coefficient to define the threshold. When the predicted progress deviation at the next moment exceeds the preset threshold, the system automatically issues an early warning notification.

[0064] Warning notification generation and transmission unit: When the deviation from the predicted progress at the next moment exceeds the set threshold, the system generates a warning notification, including the deviation content and suggested adjustment measures;

[0065] By comparing real-time progress with planned progress, time series analysis is used to predict construction progress deviations, and early warning notices are issued based on the deviations to prompt construction management personnel to make adjustments. The use of time series analysis models to predict future progress deviations enhances the foresight and responsiveness of construction management.

[0066] Based on the currently identified progress deviations, a time series analysis model is used to predict the specific progress deviations at the next time step, including:

[0067] The formula for the time series analysis model is as follows:

[0068] ;

[0069] In the formula, It is the predicted next moment. Schedule deviation, It is the mean. These are the coefficients of the autoregressive component. It is a historic moment Schedule deviation, It is the moving average coefficient. It is a historic moment Error term, It is the order of the autoregressive part. It is the order of the moving average component;

[0070] Using a time series analysis model, predictions are made based on historical progress data and the coefficients of the autoregressive component, providing more accurate deviation predictions. The prediction model and standard deviation threshold settings are introduced to monitor progress deviations in real time and provide early warnings.

[0071] The analysis and decision-making module specifically includes:

[0072] Quality and Safety Assessment Unit: Based on the predicted schedule deviations and combined with quality feedback data, a quality prediction model is established using a linear regression equation to predict potential quality problems in the current stage. The quality prediction model formula is as follows:

[0073] ;

[0074] In the formula, Indicates the current stage of the forecast. Quality rating It is the intercept term of the model. It is related to schedule deviation The relevant regression coefficients, It is related to historical quality data The relevant regression coefficients, It is an error term;

[0075] Construction safety assessment: Collect safety data from the construction site and combine it with progress data for safety analysis. Use decision tree algorithms to assess potential safety risks in the current construction process. Combine predicted progress deviations with historical data to determine whether progress delays will increase the risk of safety accidents.

[0076] Integrated Quality and Safety Assessment Unit: This unit integrates schedule deviation prediction data, construction quality data, and safety data to construct an integrated assessment model and obtain comprehensive construction quality and safety assessment results.

[0077] By combining predicted schedule deviations with real-time data, intelligent analysis algorithms are used to comprehensively evaluate construction quality and safety. This integrates a quality and safety assessment model and combines schedule deviations with quality feedback data to ensure real-time management of construction quality and safety.

[0078] By integrating schedule deviation prediction data, construction quality data, and safety data, a comprehensive evaluation model is constructed to obtain comprehensive construction quality and safety evaluation results, including:

[0079] Based on the weighted average formula, a comprehensive evaluation model is established using schedule deviation prediction data, construction quality data, and safety data as inputs, and construction quality and safety assessment results as outputs. The formula for the comprehensive evaluation model is as follows:

[0080] ;

[0081] In the formula, Based on the comprehensive assessment results of construction quality and safety, This represents the deviation from the projected progress at the current stage. This indicates the quality score for the current stage. This indicates the results of the construction safety assessment. The weighting coefficients for predicting schedule deviations, These are the weighting coefficients for the quality score. Weighting coefficients for construction safety assessment results;

[0082] By integrating schedule deviation, quality, and safety data through a weighted average model, a comprehensive construction quality and safety assessment result is generated. The weighted average method provides a full range of construction quality and safety assessments, improving the accuracy of decision support.

[0083] The improvement suggestion generation and decision support module specifically includes:

[0084] Improvement suggestion generation unit: Based on the quality and safety assessment results, schedule deviations and safety risk analysis, it generates targeted construction improvement suggestions, including construction schedule adjustments, quality control measures and safety risk prevention strategies;

[0085] Decision Support Unit: Based on improvement suggestions and the actual situation of the project, it provides decision support to help construction management personnel make adjustment decisions and presents the suggestions in AR devices so that they can be applied in real time on the construction site;

[0086] Based on the assessment results, specific construction improvement suggestions are generated and decision support is provided in combination with the actual situation of the project to help managers make timely adjustments. The innovation lies in the real-time generation of targeted construction improvement suggestions, which, combined with AR equipment display, can be directly applied to the construction site.

[0087] Reference Figure 2 As shown, an AR-assisted building design monitoring and management method includes:

[0088] Step 1: Real-time data acquisition, collecting architectural design drawings, construction progress, quality feedback, and safety data through on-site sensors and equipment;

[0089] Step 2: Rendering the 3D architectural design model. Combining BIM technology and AR, a 3D architectural model is generated and rendered in real time to the construction site, overlaying design information with the actual scene.

[0090] Step 3: Progress tracking and forecasting, real-time comparison of construction progress with planned progress, use time series analysis to predict progress deviations, and generate deviation warning notifications;

[0091] Step 4: Quality and safety assessment. Based on predicted schedule deviations, real-time data, and historical information, intelligent algorithms are used to comprehensively assess construction quality and safety, generate corresponding improvement suggestions, and provide decision support.

[0092] This method provides comprehensive construction monitoring and optimization decision support through steps such as real-time data acquisition, 3D model rendering, progress tracking and prediction, and quality and safety assessment. By combining AR with BIM, it comprehensively improves the visualization, precision and intelligent management of the construction process.

[0093] Step two specifically includes:

[0094] Based on architectural design drawings and sensor data from the construction site, a three-dimensional architectural design model is constructed.

[0095] By combining BIM and AR technologies, AR devices can display 3D models in real time and overlay construction data, enabling seamless integration of design information and construction site data.

[0096] The building model is dynamically updated in the augmented reality scene, and the construction progress and quality feedback are presented in real time.

[0097] Based on design drawings and on-site sensor data, a 3D building model is constructed and rendered to the construction site in real time. The building model and construction data are dynamically updated through AR devices, realizing real-time interaction between design and construction data and optimizing on-site management efficiency.

[0098] Step 3 specifically includes: comparing real-time progress with planned progress, identifying progress deviations, using a time series analysis model to predict the progress deviation at the next moment based on historical data, and setting an early warning threshold. When the predicted deviation exceeds the threshold, the system automatically issues an early warning notification, which includes the deviation details, suggested adjustment measures, and provides decision support.

[0099] By comparing real-time progress with planned progress, a time series analysis model is used to predict progress deviations and issue warnings when deviations exceed a threshold. The innovation lies in the accurate prediction and warning system of time series analysis, which enhances the ability to control and adjust construction progress.

[0100] In summary, the advantages of this invention are as follows:

[0101] AR technology overlays architectural design models onto the construction site in real time, helping construction workers to understand design requirements and construction progress more intuitively, reducing errors and rework, and improving the accuracy and efficiency of construction.

[0102] The system can track construction progress in real time and compare it with the original plan. It can predict progress deviations through time series analysis models and issue early warnings when progress is lagging, helping construction managers to adjust plans in a timely manner and avoid project delays.

[0103] By integrating schedule deviations, quality feedback, and safety data, the system can use intelligent algorithms to assess the current construction quality and safety, identify potential quality problems and safety hazards in advance, and reduce risks during construction.

[0104] Based on real-time and historical data, the system builds a comprehensive evaluation model to provide intelligent improvement suggestions, helping managers make accurate adjustment decisions and improve the scientific nature of project management and the accuracy of decision-making.

[0105] The improvement suggestion generation module feeds back the evaluation results and decision suggestions to the AR device in real time, enabling construction personnel to obtain targeted adjustment solutions directly on site, thereby quickly responding to on-site problems and reducing communication and decision-making time delays;

[0106] AR technology can visualize all design and construction information, allowing all parties involved in the project to share information on the same platform, improving team collaboration efficiency and information transparency, and promoting better communication and cooperation.

[0107] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. An AR assistance-based building design monitoring management system, characterized by, Comprise: AR rendering module for obtaining real-time data in the process of architectural design, rendering architectural design model in augmented reality device, and superimposing architectural design information on actual scene of construction site; Progress tracking module for tracking real-time construction progress, comparing real-time progress with planned progress, using time series analysis model to predict deviation of next time progress, and issuing warning notification when construction progress deviates from plan to prompt construction management personnel to adjust; Analysis and decision module for predicting deviation of next time progress based on real-time data feedback and intelligent analysis algorithm, establishing construction quality and safety evaluation model, and comprehensively evaluating construction quality and safety; Improvement suggestion generation and decision support module for generating improvement suggestions based on evaluation results of construction quality and safety evaluation model; The AR rendering module specifically comprises: Real-time data acquisition unit: based on sensors on construction site, collecting real-time data in the process of architectural design, including architectural design drawings and construction progress; Three-dimensional architectural design model construction unit: generating three-dimensional model of building by combining BIM technology with AR according to architectural design drawings; Augmented reality scene rendering unit: combining real-time collected environmental data with architectural design three-dimensional model, using AR rendering technology to superimpose architectural design model on actual scene of construction site, and real-time updating architectural model and design information by AR device; The progress tracking module specifically comprises: Real-time progress and planned progress comparison unit: inputting original construction plan data, storing construction plan progress data in database, comparing real-time collected construction progress data with plan progress data, and obtaining progress deviation; Construction progress deviation warning unit: based on identified deviation of current progress, using time series analysis model to predict deviation of next time progress, obtaining historical data of progress deviation, setting deviation threshold, setting threshold according to standard deviation, setting 2 times coefficient to define threshold, and automatically issuing warning notification when predicted deviation of next time progress exceeds preset threshold; Warning notification generation and delivery unit: generating warning notification including deviation content and suggested adjustment measures when predicted deviation of next time progress exceeds set threshold; The analysis and decision module specifically comprises: Quality and safety evaluation unit: using linear regression equation to establish quality prediction model based on predicted progress deviation and quality feedback data, and predicting possible quality problems in current stage, wherein, quality prediction model formula is: ； wherein, represents the predicted quality score for the current stage , is the intercept term of the model, is the regression coefficient associated with the progress bias , is the regression coefficient associated with the historical quality data , is the error term; Construction safety evaluation: collecting safety data on construction site, analyzing safety based on progress data, using decision tree algorithm to evaluate potential safety risks in current construction process, and judging whether progress lag will increase risk of safety accidents based on predicted progress deviation and historical data; Comprehensive quality and safety evaluation unit: integrating progress deviation prediction data, construction quality data and safety data, constructing comprehensive evaluation model, and obtaining comprehensive construction quality and safety evaluation results; The improvement suggestion generation and decision support module specifically comprises: The improvement suggestion generation unit generates targeted construction improvement suggestions, including construction schedule adjustment, quality control measures, and safety risk prevention strategies, based on the quality and safety assessment results, schedule deviation, and safety risk analysis. The decision support unit provides decision support based on the improvement suggestions and the actual project situation, helping construction managers make adjustment decisions, and presents the suggestions in the AR device for real-time application on the construction site.

2. The AR assistance-based building design monitoring management system according to claim 1, characterized by, The time series analysis model is used to predict the next time schedule deviation based on the current identified schedule deviation The time series analysis model formula is as follows: The progress deviation prediction data, construction quality data, and safety data are integrated to build a comprehensive evaluation model, and the comprehensive construction quality and safety evaluation results are obtained ； wherein is the predicted progress deviation at the next time point , is the mean, is the coefficient of the autoregressive part, is the progress deviation at the historical time point , is the moving average coefficient, is the error term at the historical time point , is the order of the autoregressive part, is the order of the moving average part.

3. The AR assistance-based building design monitoring management system according to claim 2, characterized by, Based on the weighted average formula, the progress deviation prediction data, construction quality data, and safety data are used as input, and the construction quality and safety evaluation results are used as output to establish a comprehensive evaluation model, where the comprehensive evaluation model formula is as follows: Step one: Real-time data collection, building design drawings, construction progress, quality feedback, and safety data are collected through on-site sensors and equipment ； In the formula, is the comprehensive construction quality and safety evaluation result, is the predicted progress deviation of the current stage, represents the quality score of the current stage, represents the construction safety evaluation result, is the weight coefficient of the predicted progress deviation, is the weight coefficient of the quality score, is the weight coefficient of the construction safety evaluation result.

4. The AR-assisted building design monitoring management method is suitable for the AR-assisted building design monitoring management system of claim 3, characterized in that, Step two: Three-dimensional building design model rendering, combined with BIM technology and AR, generates a three-dimensional building model and real-time rendering to the construction site, superimposing design information and actual scene Step three: Schedule tracking and prediction, real-time comparison of construction progress and planned progress, using time series analysis to predict schedule deviation, and generating deviation warning notifications Step four: Quality and safety assessment, based on predicted schedule deviation, real-time data, and historical information, comprehensive assessment of construction quality and safety through intelligent algorithms, generating corresponding improvement suggestions and providing decision support Step two specifically includes: Based on the building design drawings and sensor data from the construction site, a three-dimensional building design model is constructed 5. The AR assistance-based building design monitoring management method according to claim 4, characterized by, Using BIM technology and AR technology, real-time display of three-dimensional models through AR devices and superimposition of construction data enables seamless integration of design information and construction site data The three-dimensional model is dynamically updated in the augmented reality scene, and the construction progress and quality feedback during the construction process are presented in real time. Step three specifically includes: comparing real-time progress with planned progress, identifying schedule deviation, using a time series analysis model to predict the next time schedule deviation based on historical data, and setting a warning threshold. When the predicted deviation exceeds the threshold, the system automatically sends a warning notification containing the deviation content, suggested adjustment measures, and provides decision support. ​ 6. The AR assistance-based building design monitoring management method according to claim 5, characterized by, ​

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