A construction monitoring method and system based on intelligent AI

Abstract

This invention relates to the field of building construction management technology, specifically to a building construction monitoring method and system based on intelligent AI, comprising: an upload module for uploading building structure information and setting a collection path for images of exterior wall insulation material installation based on the building structure information; and a collection module for receiving the collection path for exterior wall insulation material safety images set in the upload module and collecting images of exterior wall insulation material installation based on the collection path. This invention uses an AGV (Automated Guided Vehicle) equipped with a camera to collect real-time image data of the installation status of exterior wall insulation materials. Through image data processing and detection of the proportion of insulation material installation, the progress of exterior wall insulation material installation is monitored. Furthermore, based on the similarity calculation of the collected images, a valuable assessment of the installation quality of the exterior wall insulation is conducted, assisting building construction site management users in better controlling the stable progress of exterior wall insulation material installation projects.

Description

Technical Field

[0001] This invention relates to the field of construction engineering management technology, specifically to a construction monitoring method and system based on intelligent AI. Background Art

[0002] There are various types of dry-hanging insulation materials for exterior walls. Organic materials, such as polyurethane boards, offer excellent insulation and waterproofing; inorganic materials, like rock wool boards, provide superior fire resistance. Composite exterior wall cladding panels combine decoration and insulation functions. These materials are designed to meet different building needs, providing efficient insulation for exterior walls and improving building energy efficiency and overall performance.

[0003] Patent application No. 201210042507.4 discloses a building construction monitoring system, comprising: a sensor unit deployed on the target monitoring floor, consisting of several temperature sensors and several strain sensors, for measuring the temperature load and strain of the building structure; a vertical displacement measurement unit deployed on the target monitoring floor, for measuring the overall vertical displacement of the building structure; several acquisition units deployed on the target monitoring floor, connected to the sensor unit and the vertical displacement measurement unit, for acquiring the measurement data of the sensor unit and the vertical displacement measurement unit; a host computer for outputting the measurement data acquired by the acquisition units; the acquisition units are divided into multiple acquisition substations; in each acquisition substation, the acquisition unit closest to the host computer serves as the acquisition master station, and the remaining acquisition units serve as acquisition substations; the acquisition master station is connected to the host computer, for acquiring the measurement data of the sensor unit and the vertical displacement measurement unit and outputting the acquired measurement data to the host computer; the acquisition substations are used to acquire the measurement data of the sensor unit and the vertical displacement measurement unit and output the acquired measurement data to the host computer through the acquisition master station.

[0004] The application aims to address the following issues: "Due to limitations in building scale and construction period, the monitoring cycle for super high-rise building construction has been relatively short in the past, with only local components being monitored. The number of monitoring points is relatively small, the data lacks completeness, and is not representative. Manual, periodic offline monitoring is used, but its monitoring content and efficiency cannot meet the needs of real-time online continuous monitoring. It is impossible to obtain timely and comprehensive response information during the structural construction process, resulting in low monitoring efficiency and an inability to provide timely and comprehensive guidance for the construction of super high-rise buildings."

[0005] However, in the case of exterior wall insulation material installation during building construction, due to the influence of building height, ground-based supervisors cannot conduct a comprehensive and accurate inspection of the installed insulation materials, and the installation quality of exterior wall insulation materials cannot be effectively monitored and supervised.

[0006] To address this, a construction monitoring method and system based on intelligent AI is proposed. Summary of the Invention

[0007] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a construction monitoring method and system based on intelligent AI, which solves the technical problems mentioned in the background.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] Firstly, a construction monitoring system based on intelligent AI includes:

[0010] The upload module is used to upload building structure information and set the acquisition path for the installation images of the exterior wall insulation materials based on the building structure information; the acquisition module is used to receive the acquisition path for the installation images of the exterior wall insulation materials set in the upload module and acquire the installation images of the exterior wall insulation materials based on the acquisition path; the segmentation module is used to receive the installation images of the exterior wall insulation materials acquired in the acquisition module and segment the installation images of the exterior wall insulation materials to obtain the images of the exterior wall area.

[0011] The segmentation module includes sub-modules, including:

[0012] The storage unit is used to receive and store the building exterior wall area image obtained by the segmentation process in the segmentation module.

[0013] The logic of the segmentation module in segmenting and obtaining images of the building's exterior wall area from the installation image of the building's exterior wall insulation material is as follows:

[0014] ;

[0015] In the formula: P(A) is the determination value for whether pixel A belongs to the building exterior wall area image; H is the gray value of pixel A; (a1,b1) is the gray value range of the building exterior wall; (a2,b2) is the gray value range of the building exterior wall insulation material.

[0016] Based on the above formula, all pixels in the image of building exterior wall insulation material installation are calculated, and pixels with a judgment value of 0 are segmented in the image of building exterior wall insulation material installation.

[0017] Next, the distance between adjacent pixels in all pixels in the segmented image is identified, and pixels with a non-zero distance between adjacent pixels are used as the discard targets, and the discard operation is performed in the segmented image.

[0018] Among them, the pixel proximity interval is in pixels. The image of the building exterior wall insulation material installation after segmentation and discarding is recorded as the building exterior wall area image.

[0019] The monitoring module is used to traverse images of the building's exterior wall area and measure the proportion of thermal insulation material installation in the images. The evaluation module is used to obtain the traversal results of the building's exterior wall area images from the monitoring module, pick up images of all building exterior wall areas fully covered by thermal insulation materials, and evaluate the installation quality of the building's exterior wall thermal insulation materials based on the picked images. The output module is used to receive the measured proportion of thermal insulation material installation in the images of the building's exterior wall area from the monitoring module and the evaluation results of the installation quality of the building's exterior wall thermal insulation materials from the evaluation module, and feed the proportion of thermal insulation material installation and the evaluation results back to the user on the system side.

[0020] Furthermore, the building structure information uploaded in the upload module includes: the boundary coordinates of the road area surrounding the building structure and the building structure specifications.

[0021] After the building structure information is uploaded, it is synchronously connected to the adjacent road area boundary coordinates of the building structure to construct a two-dimensional graphic representing the road area around the building structure, which is denoted as the image acquisition area. Based on the building structure specifications, a three-dimensional model of the building structure is constructed. The image acquisition area and the three-dimensional model of the building structure are placed in the same three-dimensional space, so that the image acquisition area is placed on the bottom surface of the three-dimensional model of the building structure, and the bottom surface of the three-dimensional model of the building structure is within the image acquisition area.

[0022] Furthermore, the upload module has sub-modules at its lower level, including:

[0023] AGV modules are used to carry the acquisition module and move it within the image acquisition area;

[0024] The editing unit is used to edit the acquisition path of the installation image of the external wall insulation material, load the edited acquisition path into the AGV module, and control the AGV module to move based on the acquisition path;

[0025] The AGV module integrates an AGV vehicle, an automatic obstacle avoidance system, and a data acquisition module. The data acquisition module is a high-definition camera. The automatic obstacle avoidance system can be any one of a lidar obstacle avoidance system, an ultrasonic obstacle avoidance system, a visual obstacle avoidance system, or an infrared obstacle avoidance system. When the editing unit runs and edits the data acquisition path of the external wall insulation material installation image, the system user selects several position coordinates in the image acquisition area. The position coordinates are connected to form the acquisition path. The system user further selects several points in the acquisition path and marks the direction and angle of each selected point. When the AGV module carrying the data acquisition module moves along the acquisition path, it coordinates the carried data acquisition module based on the direction and angle marked at the point each time it reaches the point selected by the system user, so that the camera end of the data acquisition module is aligned with the surface of the building's external wall.

[0026] Furthermore, the AGV module carrying the acquisition module performs the operation of acquiring images of the installation of building exterior wall insulation materials at least once a day;

[0027] When storing images of the building's exterior wall area, the storage unit distinguishes and stores them according to the acquisition date of the images of the building's exterior wall insulation material installation.

[0028] When the monitoring module performs the measurement operation on the proportion of thermal insulation material installation in the image of the building's exterior wall area, it performs the measurement based on (a1,b1) and (a2,b2), and the measurement result is expressed as a percentage.

[0029] Furthermore, the monitoring module updates synchronously with the images of the building's exterior wall area stored in the storage unit.

[0030] After measuring the percentage of thermal insulation material installed in the image of the building's exterior wall area, the monitoring module generates a trend chart showing the change in the percentage of thermal insulation material installed, based on the measurement date. This trend chart is then stored synchronously in the storage unit.

[0031] Furthermore, the images of the building's exterior wall area captured by the evaluation module are sorted according to the acquisition date of the images of the building's exterior wall insulation material installation, and then an evaluation of the installation quality of the building's exterior wall insulation material is performed:

[0032] ;

[0033] In the formula: SIMM is the similarity between two images of the exterior wall area of ​​a building; B is the total number of color intervals; H1(b) and H2(b) are the number of pixels in the two images of the exterior wall area of ​​a building that fall into the b-th color interval.

[0034] Using any two images of the exterior wall area of ​​a building as the target for similarity calculation, the calculation operation is performed, and then the minimum value of the calculation result and the two images of the exterior wall area corresponding to the minimum value are obtained to evaluate the installation quality of the building exterior wall insulation material.

[0035] ;

[0036] Where: Q is the performance value of the installation quality of building exterior wall insulation materials; SIMM min This represents the minimum value of the similarity calculation result; The time interval defined by the date corresponding to the image source of the building exterior wall insulation material installation image, which points to the minimum value of the building exterior wall area;

[0037] Among them, the larger the Q value of the installation quality performance of the building exterior wall insulation material, the better the installation quality of the building exterior wall insulation material, and vice versa.

[0038] Furthermore, during the operation of the output module, the mobile computer device held by the system user is used as the transmission target. The insulation material installation ratio and evaluation results are transmitted to the computer device via a wireless network, and the system user reads the insulation material installation ratio and evaluation results on the mobile computer.

[0039] The output module also includes a trend chart showing the change in the proportion of insulation material installation.

[0040] Furthermore, the upload module is wirelessly connected to an AGV module and an editing unit, and is also wirelessly connected to a data acquisition module and a segmentation module. The segmentation module is internally connected to a storage unit via a wireless network, and is also wirelessly connected to a monitoring module and an evaluation module. The evaluation module is wirelessly connected to an output module.

[0041] Secondly, a construction monitoring method based on intelligent AI includes the following steps:

[0042] The acquisition path for the installation images of the external wall insulation material is set according to the building structure information. The AGV equipment equipped with a camera moves according to the acquisition path and acquires images of the external wall insulation material installation during the movement.

[0043] The installation images of exterior wall insulation materials are segmented to obtain exterior wall area images, which are then stored. The proportion of exterior wall insulation materials installed is then measured based on the stored exterior wall area images.

[0044] A trend chart showing the change in the percentage of exterior wall insulation materials installed is generated based on historical measurement results.

[0045] Traverse the images of the exterior wall area, pick out the exterior wall area image with full coverage of the insulation material, and evaluate the overall installation quality of the building's exterior wall insulation material based on the picked exterior wall area image;

[0046] Output of the percentage of building exterior wall insulation materials installed and the results of the installation quality assessment.

[0047] Compared with known public technologies, the technical solution provided by this invention has the following beneficial effects:

[0048] This invention provides a building construction monitoring method and system based on intelligent AI. During execution, the method and system use an AGV (Automated Guided Vehicle) equipped with a camera to collect real-time image data on the installation status of thermal insulation materials on building exterior walls. By processing the image data and detecting the installation ratio of thermal insulation materials, the progress of the thermal insulation material installation is monitored. Simultaneously, based on the similarity calculation of the collected images, a valuable assessment of the installation quality of the thermal insulation materials is further performed, assisting building construction site management users in better controlling the stable progress of the building exterior wall thermal insulation material installation project. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0050] Figure 1 This is a structural diagram of a building construction monitoring system based on intelligent AI;

[0051] Figure 2 This is a flowchart illustrating a construction monitoring method based on intelligent AI. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0053] The present invention will be further described below with reference to embodiments.

[0054] Example 1:

[0055] This embodiment presents a building construction monitoring system based on intelligent AI, such as... Figure 1 As shown, it includes:

[0056] The upload module is used to upload building structure information and set the acquisition path for images of the installation of external wall insulation materials based on the building structure information;

[0057] The building structure information uploaded in the upload module includes: the boundary coordinates of the road area surrounding the building structure and the building structure specifications.

[0058] After the building structure information is uploaded, the module synchronously connects adjacent road area boundary coordinates to construct a two-dimensional graphic representing the road area around the building structure, which is denoted as the image acquisition area. Based on the building structure specifications, a three-dimensional model of the building structure is constructed. The image acquisition area and the three-dimensional model of the building structure are placed in the same three-dimensional space, with the image acquisition area placed on the bottom surface of the three-dimensional model of the building structure, and the bottom surface of the three-dimensional model of the building structure is within the image acquisition area.

[0059] The upload module has sub-modules, including:

[0060] AGV modules are used to carry the acquisition module and move it within the image acquisition area;

[0061] The editing unit is used to edit the acquisition path of the installation image of the external wall insulation material, load the edited acquisition path into the AGV module, and control the AGV module to move based on the acquisition path;

[0062] The AGV module integrates an AGV vehicle, an automatic obstacle avoidance system, and a data acquisition module. The data acquisition module is a high-definition camera. The automatic obstacle avoidance system can be any one of a lidar obstacle avoidance system, an ultrasonic obstacle avoidance system, a visual obstacle avoidance system, or an infrared obstacle avoidance system. When the editing unit runs and edits the data acquisition path of the external wall insulation material installation image, the system user selects several position coordinates in the image acquisition area. The position coordinates are connected to each other to form the acquisition path. The system user further selects several points in the acquisition path and marks the direction and angle of each selected point. When the AGV module carrying the data acquisition module moves along the acquisition path, each time it reaches a point selected by the system user, it coordinates the carried data acquisition module based on the direction and angle marked at that point so that the camera end of the data acquisition module is opposite to the surface of the building's external wall.

[0063] The acquisition module is used to receive the acquisition path of the external wall insulation material installation image set in the upload module, and acquire the building external wall insulation material installation image based on the acquisition path;

[0064] The segmentation module is used to receive images of the building exterior wall insulation material installation acquired by the acquisition module, and to segment and obtain images of the building exterior wall area from the images of the building exterior wall insulation material installation.

[0065] The segmentation module contains sub-modules, including:

[0066] The storage unit is used to receive and store the building exterior wall area image obtained by the segmentation process in the segmentation module.

[0067] The logic of the segmentation module in segmenting and obtaining images of the building's exterior wall area from the images of the building's exterior wall insulation material installation is as follows:

[0068] ;

[0069] In the formula: P(A) is the determination value for whether pixel A belongs to the building exterior wall area image; H is the gray value of pixel A; (a1,b1) is the gray value range of the building exterior wall; (a2,b2) is the gray value range of the building exterior wall insulation material.

[0070] Based on the above formula, all pixels in the image of building exterior wall insulation material installation are calculated, and pixels with a judgment value of 0 are segmented in the image of building exterior wall insulation material installation.

[0071] Next, the distance between adjacent pixels in all pixels in the segmented image is identified, and pixels with a non-zero distance between adjacent pixels are used as the discard targets, and the discard operation is performed in the segmented image.

[0072] Among them, the pixel proximity interval is in pixels. The image of the building exterior wall insulation material installation after segmentation and discarding is recorded as the building exterior wall area image.

[0073] The above logical formula provides a specified effective segmentation logic for the segmentation of the building exterior wall area image in the segmentation module;

[0074] The AGV module, carrying the acquisition module, performs the operation of acquiring images of the installation of building exterior wall insulation materials at least once a day.

[0075] When storing images of the building's exterior wall area, the storage unit distinguishes and stores them according to the acquisition date of the images of the building's exterior wall insulation material installation.

[0076] When the monitoring module performs the measurement operation on the installation ratio of thermal insulation material in the image of the building's exterior wall area, it performs the measurement based on (a1,b1) and (a2,b2), and the measurement result is expressed as a percentage.

[0077] The monitoring module updates synchronously with the images of the building's exterior walls stored in the storage unit.

[0078] After measuring the percentage of thermal insulation material installed in the image of the building's exterior wall area, the monitoring module generates a trend chart showing the change in the percentage of thermal insulation material installed, based on the measurement date. This trend chart is then stored synchronously in the storage unit.

[0079] The monitoring module is used to traverse images of the building's exterior wall area and measure the percentage of thermal insulation material installed in the images.

[0080] The evaluation module is used to obtain the image traversal results of the building exterior wall area in the monitoring module, pick up the images of the building exterior wall area fully covered by all insulation materials, and evaluate the installation quality of the building exterior wall insulation materials based on the picked images;

[0081] The evaluation module sorts the images of the building's exterior wall area according to the acquisition date of the images of the building's exterior wall insulation material installation, and then performs an evaluation of the quality of the building's exterior wall insulation material installation.

[0082] ;

[0083] In the formula: SIMM is the similarity between two images of the exterior wall area of ​​a building; B is the total number of color intervals; H1(b) and H2(b) are the number of pixels in the two images of the exterior wall area of ​​a building that fall into the b-th color interval.

[0084] Using any two images of the exterior wall area of ​​a building as the target for similarity calculation, the calculation operation is performed, and then the minimum value of the calculation result and the two images of the exterior wall area corresponding to the minimum value are obtained to evaluate the installation quality of the building exterior wall insulation material.

[0085] ;

[0086] Where: Q is the performance value of the installation quality of building exterior wall insulation materials; SIMM min This represents the minimum value of the similarity calculation result; The time interval defined by the date corresponding to the image source of the building exterior wall insulation material installation image, which points to the minimum value of the building exterior wall area;

[0087] Among them, the larger the Q value of the installation quality performance of the building exterior wall insulation material, the better the installation quality of the building exterior wall insulation material, and vice versa.

[0088] The installation quality of building exterior wall insulation materials is digitally identified through the above logical formula, enabling on-site construction managers to more quickly assess the installation status of these materials.

[0089] The output module is used to receive the proportion of thermal insulation material installation in the building exterior wall area image measured by the monitoring module and the evaluation results of the building exterior wall thermal insulation material installation quality in the evaluation module, and to feed back the proportion of thermal insulation material installation and evaluation results to the system user.

[0090] The upload module has AGV modules and editing units connected to it via a wireless network. The upload module also has acquisition and segmentation modules connected to it via a wireless network. The segmentation module has storage units connected to it via a wireless network. The segmentation module also has monitoring and evaluation modules connected to it via a wireless network. The evaluation module also has an output module connected to it via a wireless network.

[0091] In this embodiment, the upload module uploads building structure information and sets the acquisition path for the installation images of the exterior wall insulation material based on the building structure information. The AGV module synchronously carries the acquisition module and moves within the image acquisition area. The editing unit edits the acquisition path for the installation images of the exterior wall insulation material in real time, loads the edited acquisition path into the AGV module, and controls the AGV module to move based on the acquisition path. The acquisition module further receives the acquisition path for the installation images of the exterior wall insulation material set in the upload module and acquires the installation images of the building's exterior wall insulation material based on the acquisition path. The segmentation module runs subsequently to receive the installation images of the building's exterior wall insulation material acquired by the acquisition module and segments and obtains the exterior wall insulation material from the installation images. The storage unit synchronously receives the building exterior wall area images obtained from the segmentation processing in the segmentation module, stores the building exterior wall area images, and then the monitoring module traverses the building exterior wall area images to measure the proportion of thermal insulation material installation in the building exterior wall area images. Finally, the evaluation module obtains the building exterior wall area image traversal results from the monitoring module, picks up all building exterior wall area images with full coverage of thermal insulation material, evaluates the installation quality of building exterior wall thermal insulation material based on the picked images, and outputs the measurement of the proportion of thermal insulation material installation in the building exterior wall area images from the monitoring module and the evaluation results of the building exterior wall thermal insulation material installation quality from the evaluation module. The thermal insulation material installation proportion and evaluation results are then fed back to the system user.

[0092] Through the system operation in the above embodiments, real-time artificial intelligence monitoring services are provided for the installation of building exterior wall insulation materials, effectively assisting on-site management personnel of building projects to supervise the installation of building exterior wall insulation materials more quickly and comprehensively.

[0093] like Figure 1 As shown, during the output module operation phase, the mobile computer device held by the system user is used as the transmission target. The insulation material installation ratio and evaluation results are transmitted to the computer device through the wireless network. The system user reads the insulation material installation ratio and evaluation results on the mobile computer.

[0094] The output module also includes a trend chart showing the change in the proportion of insulation material installation.

[0095] The above settings further define the operating logic and output content of the output module.

[0096] Example 2:

[0097] At the implementation level, based on Example 1, this example refers to... Figure 2 A further detailed description of the construction monitoring system based on intelligent AI in Example 1 is provided below:

[0098] A construction monitoring method based on intelligent AI includes the following steps:

[0099] The acquisition path for the installation images of the external wall insulation material is set according to the building structure information. The AGV equipment equipped with a camera moves according to the acquisition path and acquires images of the external wall insulation material installation during the movement.

[0100] The installation images of exterior wall insulation materials are segmented to obtain exterior wall area images, which are then stored. The proportion of exterior wall insulation materials installed is then measured based on the stored exterior wall area images.

[0101] A trend chart showing the change in the percentage of exterior wall insulation materials installed is generated based on historical measurement results.

[0102] Traverse the images of the exterior wall area, pick out the exterior wall area image with full coverage of the insulation material, and evaluate the overall installation quality of the building's exterior wall insulation material based on the picked exterior wall area image;

[0103] Output of the percentage of building exterior wall insulation materials installed and the results of the installation quality assessment.

[0104] In summary, during the execution of the methods and systems described in the above embodiments, the AGV equipped with a camera collects real-time image data of the installation status of thermal insulation materials on the building's exterior walls. By processing the image data and detecting the installation ratio of thermal insulation materials, the progress of the exterior wall thermal insulation material installation is monitored. Furthermore, based on the similarity calculation of the collected images, a valuable assessment of the installation quality of the exterior wall insulation is conducted, assisting building construction site management users in better controlling the stable progress of the building's exterior wall thermal insulation material installation project.

[0105] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A construction monitoring system based on intelligent AI, characterized in that, include: The upload module is used to upload building structure information and set the acquisition path for images of the installation of external wall insulation materials based on the building structure information; The acquisition module is used to receive the acquisition path of the external wall insulation material installation image set in the upload module, and acquire the building external wall insulation material installation image based on the acquisition path; The segmentation module is used to receive images of the building exterior wall insulation material installation acquired by the acquisition module, and to segment and obtain images of the building exterior wall area from the images of the building exterior wall insulation material installation. The monitoring module is used to traverse images of the building's exterior wall area and measure the percentage of thermal insulation material installed in the images. The evaluation module is used to obtain the image traversal results of the building exterior wall area in the monitoring module, pick up the images of the building exterior wall area fully covered by all insulation materials, and evaluate the installation quality of the building exterior wall insulation materials based on the picked images; The output module is used to receive the proportion of thermal insulation material installation in the building exterior wall area image measured by the monitoring module and the evaluation results of the building exterior wall thermal insulation material installation quality in the evaluation module, and to feed back the proportion of thermal insulation material installation and evaluation results to the system user.

2. The construction monitoring system based on intelligent AI according to claim 1, characterized in that, The building structure information uploaded in the upload module includes: the boundary coordinates of the road area surrounding the building structure and the building structure specifications. After the building structure information is uploaded, it is synchronously connected to the adjacent road area boundary coordinates of the building structure to construct a two-dimensional graphic representing the road area around the building structure, which is denoted as the image acquisition area. Based on the building structure specifications, a three-dimensional model of the building structure is constructed. The image acquisition area and the three-dimensional model of the building structure are placed in the same three-dimensional space, so that the image acquisition area is placed on the bottom surface of the three-dimensional model of the building structure, and the bottom surface of the three-dimensional model of the building structure is within the image acquisition area.

3. The construction monitoring system based on intelligent AI according to claim 2, characterized in that, The upload module has sub-modules, including: AGV modules are used to carry the acquisition module and move it within the image acquisition area; The editing unit is used to edit the acquisition path of the installation image of the external wall insulation material, load the edited acquisition path into the AGV module, and control the AGV module to move based on the acquisition path; The AGV module integrates an AGV vehicle, an automatic obstacle avoidance system, and a data acquisition module. The data acquisition module is a high-definition camera. The automatic obstacle avoidance system can be any one of a lidar obstacle avoidance system, an ultrasonic obstacle avoidance system, a visual obstacle avoidance system, or an infrared obstacle avoidance system. When the editing unit runs and edits the data acquisition path of the external wall insulation material installation image, the system user selects several position coordinates in the image acquisition area. The position coordinates are connected to each other to form the acquisition path. The system user further selects several points in the acquisition path and marks the direction and angle of each selected point. When the AGV module carrying the data acquisition module moves along the acquisition path, each time it reaches a point selected by the system user, it coordinates the carried data acquisition module based on the direction and angle marked at that point so that the camera end of the data acquisition module is opposite to the surface of the building's external wall. The segmentation module includes sub-modules, including: The storage unit is used to receive and store the building exterior wall area images obtained from the segmentation process in the segmentation module.

4. The construction monitoring system based on intelligent AI according to claim 1, characterized in that, The logic of the segmentation module in segmenting and obtaining images of the building's exterior wall area from the installation image of the building's exterior wall insulation material is as follows: ； In the formula: P(A) is the determination value for whether pixel A belongs to the building exterior wall area image; H is the gray value of pixel A; (a1,b1) is the gray value range of the building exterior wall; (a2,b2) is the gray value range of the building exterior wall insulation material. Based on the above formula, all pixels in the image of building exterior wall insulation material installation are calculated, and pixels with a judgment value of 0 are segmented in the image of building exterior wall insulation material installation. Next, the distance between adjacent pixels in all pixels of the segmented image is identified, and pixels with a non-zero distance between adjacent pixels are used as the discard targets, and the discard operation is performed in the segmented image. Among them, the pixel-close interval distance is in pixels. The image of the building exterior wall insulation material installation after segmentation and discarding is recorded as the building exterior wall area image.

5. A construction monitoring system based on intelligent AI according to claim 3, characterized in that, The AGV module, carrying the acquisition module, performs the operation of acquiring images of the installation of building exterior wall insulation materials at least once a day. When storing images of the building's exterior wall area, the storage unit distinguishes and stores them according to the acquisition date of the images of the building's exterior wall insulation material installation. When the monitoring module performs the measurement operation on the proportion of thermal insulation material installation in the image of the building's exterior wall area, it performs the measurement based on (a1,b1) and (a2,b2), and the measurement result is expressed as a percentage.

6. A construction monitoring system based on intelligent AI according to claim 4, characterized in that, The monitoring module updates synchronously with the images of the building's exterior wall area stored in the storage unit. After measuring the percentage of thermal insulation material installed in the image of the building's exterior wall area, the monitoring module generates a trend chart showing the change in the percentage of thermal insulation material installed, based on the measurement date. This trend chart is then stored synchronously in the storage unit.

7. A construction monitoring system based on intelligent AI according to claim 1, characterized in that, The evaluation module sorts the images of the building's exterior wall area according to the acquisition date of the images of the building's exterior wall insulation material installation, and then performs an evaluation of the quality of the building's exterior wall insulation material installation. ； In the formula: SIMM is the similarity between two images of the exterior wall area of ​​a building; B is the total number of color intervals; H1(b) and H2(b) are the number of pixels in the two images of the exterior wall area of ​​a building that fall into the b-th color interval. Using any two images of the exterior wall area of ​​a building as the target for similarity calculation, the calculation operation is performed, and then the minimum value of the calculation result and the two images of the exterior wall area corresponding to the minimum value are obtained to evaluate the installation quality of the building exterior wall insulation material. ； Where: Q is the performance value of the installation quality of building exterior wall insulation materials; SIMM min This represents the minimum value of the similarity calculation result; The time interval defined by the date corresponding to the image source of the building exterior wall insulation material installation image, which points to the minimum value of the building exterior wall area; Among them, the larger the Q value of the installation quality performance of the building exterior wall insulation material, the better the installation quality of the building exterior wall insulation material, and vice versa.

8. A construction monitoring system based on intelligent AI according to claim 1, characterized in that, During the operation of the output module, the mobile computer device held by the system user is used as the transmission target. The insulation material installation ratio and evaluation results are transmitted to the computer device through a wireless network. The system user reads the insulation material installation ratio and evaluation results on the mobile computer. The output module also includes a trend chart showing the change in the proportion of thermal insulation material installation.

9. A construction monitoring system based on intelligent AI according to claim 1, characterized in that, The upload module is connected to an AGV module and an editing unit via a wireless network. The upload module is also connected to a data acquisition module and a segmentation module via a wireless network. The segmentation module is internally connected to a storage unit via a wireless network. The segmentation module is also connected to a monitoring module and an evaluation module via a wireless network. The evaluation module is connected to an output module via a wireless network.

10. A construction monitoring method based on intelligent AI, wherein the method is an implementation method of the construction monitoring system based on intelligent AI as described in any one of claims 1-9, characterized in that, Includes the following steps: The acquisition path for the installation images of the external wall insulation material is set according to the building structure information. The AGV equipment equipped with a camera moves according to the acquisition path and acquires images of the external wall insulation material installation during the movement. The installation images of exterior wall insulation materials are segmented to obtain exterior wall area images, which are then stored. The proportion of exterior wall insulation materials installed is then measured based on the stored exterior wall area images. A trend chart showing the change in the percentage of exterior wall insulation materials installed is generated based on historical measurement results. Traverse the images of the exterior wall area, pick out the exterior wall area image with full coverage of the insulation material, and evaluate the overall installation quality of the building's exterior wall insulation material based on the picked exterior wall area image; Output of the percentage of building exterior wall insulation materials installed and the results of the installation quality assessment.

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