Building monitoring and management method, equipment, medium and product in urban physical examination

Abstract

The invention relates to the technical field of building management, in particular to a building monitoring and management method and device in urban physical examination, a medium and a product. The method comprises the steps of obtaining a BIM model and an internal image of a target building and a region image of a building region where the target building is located; performing potential safety hazard checking on the target building based on the BIM model, the internal image and the area image to obtain a potential hazard checking result of the target building; performing physical examination on the building area based on the BIM model and the area image to obtain an area evaluation result of the building area; and generating a rectification suggestion list based on the hidden danger checking result and the area evaluation result, and sending the rectification suggestion list to terminal equipment of a manager of the building area. According to the invention, the building monitoring and management efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of building management technology, and in particular to a method, equipment, medium and product for building monitoring and management in urban physical examinations. Background Art

[0002] With the acceleration of urbanization and the dramatic increase in the number of buildings, building management has become increasingly important. As crucial places for people to work and live, the safety, functionality, and sustainability of buildings are directly related to the safety of life, property, and quality of life. Building management not only enables the timely identification and elimination of potential safety hazards, ensuring the safety of people and property, but also ensures the proper use and maintenance of buildings, extending their service life and improving the efficient use of urban space.

[0003] However, existing building management methods present numerous technical challenges. Traditional manual inspections rely on staff experience and subjective judgment, resulting in low efficiency, high costs, and a high risk of missed inspections and misjudgments, making it difficult to conduct comprehensive and accurate safety hazard inspections and assessments of buildings. Furthermore, traditional methods lack effective data integration and analysis for the overall planning and management of building areas. These methods fail to comprehensively consider the relationships between buildings and their coordination with the surrounding environment, making it difficult to scientifically evaluate and optimize the management of building areas. This results in inefficient building monitoring and management during urban health checks. Summary of the Invention

[0004] In order to solve the problem of low efficiency in building monitoring and management in the existing technology, the present application provides a method, equipment, medium and product for building monitoring and management in urban physical examination.

[0005] In the first aspect, the present application provides a method for monitoring and managing buildings in urban physical examinations, which adopts the following technical solutions: A method for monitoring and managing buildings in urban physical examinations, comprising: Obtaining a BIM model, interior images, and area images of the target building; Performing a safety hazard inspection on the target building based on the BIM model, the internal image, and the regional image to obtain a safety hazard inspection result for the target building; Performing a physical examination on the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area; A rectification suggestion list is generated based on the hidden danger inspection result and the area evaluation result, and the rectification suggestion list is sent to a terminal device of a manager of the building area.

[0006] By adopting the above technical solution, the BIM model, internal images and regional images of the target building are obtained, multi-source data fusion is realized, and safety hazard inspections are carried out based on these data. The precise spatial information and image recognition technology of the BIM model can be used to quickly and accurately locate structural and fire hazards. When inspecting the building area, the BIM model and regional images are combined to comprehensively evaluate aspects such as building spacing, greening, volume and public facilities. Finally, a list of rectification suggestions is generated based on the hazard inspection and regional evaluation results and sent to management personnel, realizing full-process intelligent management from data collection, analysis and evaluation to decision support, effectively improving the efficiency and accuracy of building monitoring management, reducing safety risks, and optimizing the overall environment of the building area.

[0007] In a preferred example, the present application may be further configured as follows: the hidden danger inspection results include structural hidden danger inspection results and fire hidden danger inspection results; The performing safety hazard inspection on the target building based on the BIM model, the internal image, and the regional image to obtain a safety hazard inspection result of the target building includes: Identify whether the target building has structural hidden dangers based on the internal image and the regional image, and obtain a structural hidden danger inspection result; Identify whether the target building has fire hazards based on the internal image, and obtain fire hazard investigation results; When the structural hidden danger inspection result or the fire hidden danger inspection result indicates the existence of hidden dangers, the hidden danger type, hidden danger level and hidden danger area are marked on the BIM model.

[0008] By adopting the above technical solution, using internal images and regional images, combined with advanced image recognition algorithms and deep learning models, hidden dangers in the target building structure, such as cracks, material peeling and tilt, can be identified from multiple angles. Fire hazards such as fire protection facilities and passages can then be specifically identified based on internal images to ensure that hidden dangers are detected comprehensively without blind spots. Finally, the identified hidden dangers will be marked on the BIM model, and the powerful three-dimensional visualization and information integration capabilities of the BIM model will be used to intuitively present the type, level and area of ​​hidden dangers, making it easier for managers to quickly locate and understand the hidden danger situation.

[0009] In a preferred example, the present application may be further configured as follows: the structural hidden dangers include: crack hidden dangers, material peeling hidden dangers and tilt hidden dangers; The identifying whether the target building has structural hidden dangers based on the internal image and the regional image, and obtaining a structural hidden danger investigation result, includes: Inputting the internal image and the regional image into a hidden danger identification model, the hidden danger identification model outputting an identification result of whether the target building has the hidden danger of cracks and the hidden danger of material peeling; determining a tilt angle of the target building based on the regional image, and determining that the target building has the tilt risk when the tilt angle exceeds a standard tilt angle; When the target building has any structural hidden danger, the hidden danger level of the structural hidden danger is determined.

[0010] By adopting the above technical solutions, the hidden danger identification model can efficiently and accurately detect crack hazards and material peeling hazards, greatly improving the efficiency and accuracy of hidden danger identification; the inclination angle of the target building is determined based on the regional image, and with the help of image processing and geometric calculation technology, a scientific quantitative judgment of the building tilt hazard is achieved; when a structural hidden danger is found, the hidden danger level is determined according to the preset assessment standards, so that the hidden danger risk can be quantified and graded.

[0011] In a preferred example, the present application may be further configured as follows: when the target building has any structural hidden danger, determining the hidden danger level of the structural hidden danger includes: When the hidden danger identification model outputs that the crack hidden danger exists, determining the crack length and the maximum crack width based on the crack area output by the hidden danger identification model, and determining the hidden danger level of the crack hidden danger based on the crack length and the maximum crack width; When the hidden danger identification model outputs that the material spalling hidden danger exists, determining the material spalling area based on the material spalling region output by the hidden danger identification model, and determining the hidden danger level of the material spalling hidden danger based on the material spalling area; When the target building has the tilt risk, the risk level of the tilt risk is determined based on the tilt angle.

[0012] By adopting the above technical solution, when determining the structural hazard level, for crack hazards, the crack area is accurately delineated based on the hazard identification model, the crack length and maximum width are quantified, and by comparing with the established standards, the crack risk is scientifically graded, and the degree of crack hazard is intuitively presented; for material spalling hazards, the spalling area data output by the model is used to calculate the spalling area, to achieve a quantitative assessment of the hazard and accurately define the hazard level; and for tilt hazards, the hazard level is determined according to the standard based on the accurately measured tilt angle.

[0013] In a preferred example, the present application may be further configured as follows: the identifying whether the target building has a fire hazard based on the internal image and obtaining a fire hazard inspection result includes: Determine the building type of the target building and retrieve the fire protection regulations corresponding to the building type; identifying, based on the internal image, the location and type of firefighting facilities within the target building, as well as fire passage congestion conditions, wherein the fire passage congestion conditions include locked conditions and debris accumulation conditions; The facility location, facility type and congestion of the fire-fighting facilities are compared with the fire-fighting regulations to determine the fire hazard inspection results. The fire hazard inspection results include the determination result of whether there are fire hazards, and the hazard level and hazard area of ​​the fire hazards when it is determined that the fire hazards exist.

[0014] By adopting the above technical solution, the corresponding fire protection regulations are retrieved according to the target building type, providing accurate standards for fire hazard determination and ensuring that there is a law to follow for investigation; then, through analysis of internal images, image recognition technology is used to accurately locate fire protection facilities, identify facility types, and comprehensively detect congestion such as locked fire passages and piled up debris, so as to achieve comprehensive collection of fire hazard information; finally, the collected fire protection facilities are compared with the passage conditions and fire protection regulations, which can not only quickly determine whether there are fire hazards, but also scientifically divide the hazard levels and locate the hazard areas.

[0015] In a preferred example, the present application may be further configured as follows: performing a physical examination on the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area includes: Obtaining sunlight information for the area where the building area is located, determining the actual building distance and building height information between the target building and the front building based on the BIM model, calculating a standard building distance based on the sunlight information and the building height information, and comparing the actual building distance with the standard building distance to determine a sunlight evaluation result for the target building; Summarizing the sunlight evaluation results of all buildings in the building area to generate a building spacing evaluation result for the building area; determining a greening condition of the building area based on the area image and the BIM model, and generating a greening evaluation result of the building area based on the greening condition; identifying the public facilities situation of the building area based on the area image, and generating a public facilities evaluation result of the building area based on the public facilities situation; The regional evaluation result of the building area is generated by integrating the building distance evaluation result, the greening evaluation result, the volume evaluation result and the public facilities evaluation result.

[0016] By adopting the above technical solution and integrating BIM models with regional image data, we first scientifically calculate and compare the standard and actual building spacing based on sunlight information and BIM model data to accurately obtain the sunlight evaluation results of the target building, and then summarize and generate an evaluation that comprehensively reflects the regional building spacing situation; then, with the help of data fusion and image recognition technology, we extract greening and public facilities information from regional images and BIM models, and form objective greening and public facilities evaluation results respectively; finally, we comprehensively evaluate various dimensions to construct a complete building area evaluation system, which realizes quantitative evaluation and systematic diagnosis of various aspects such as sunlight conditions, spatial planning, environmental quality and public service facilities in the building area.

[0017] In a preferred example, the present application may be further configured as follows: generating a list of rectification suggestions based on the hidden danger investigation results and the regional evaluation results includes: Determining a plurality of first items to be improved based on the hidden danger inspection results, prioritizing the plurality of first items to be improved based on the hidden danger level of each building hidden danger in the hidden danger inspection results, and generating a first list of the plurality of first items to be improved in descending order of priority; Determining a plurality of second items to be improved and priorities of the plurality of second items to be improved based on the regional evaluation results, and generating a second list of the plurality of second items to be improved in descending order of priority; The first list and the second list are integrated as an improvement suggestion list, wherein the priority of any first item to be improved in the improvement suggestion list is higher than the priority of any second item to be improved.

[0018] By adopting the above technical solution, building safety hazards are accurately located based on the results of hidden danger inspections, and the first project to be improved is given priority according to the level of hidden dangers, forming a logically clear and focused hidden danger rectification sequence to ensure that high-risk hidden dangers are dealt with first and building safety is guaranteed; then, based on the regional evaluation results, the second project to be improved that affects regional quality is sorted out and reasonably ranked to indicate the direction for regional optimization; finally, the two lists are integrated to clarify that the safety hazard rectification project has a higher priority than the regional optimization project, which not only highlights the management principle of safety first, but also takes into account the overall improvement of the region.

[0019] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: one or more processors; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the building monitoring and management method in urban physical examination as described in any one of the first aspects.

[0020] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program thereon. When the computer program is executed in a computer, the computer is caused to execute the building monitoring and management method in urban physical examination as described in any one of the first aspects.

[0021] In a fourth aspect, the present application provides a computer program product that adopts the following technical solution: A computer program product includes a computer program. When the computer program is executed by a processor, it implements the building monitoring and management method in urban physical examination as described in any one of the first aspects.

[0022] In summary, this application has the following beneficial technical effects: This application achieves multi-source data fusion by acquiring the BIM model, internal images and regional images of the target building, and conducts safety hazard inspections based on these data. By utilizing the precise spatial information and image recognition technology of the BIM model, it can quickly and accurately locate structural and fire hazards. When inspecting the building area, the BIM model and regional images are combined to comprehensively evaluate aspects such as building spacing, greening, volume and public facilities. Finally, a list of rectification suggestions is generated based on the hazard inspection and regional evaluation results and sent to management personnel, realizing full-process intelligent management from data collection, analysis and evaluation to decision support, effectively improving the efficiency and accuracy of building monitoring management, reducing safety risks, and optimizing the overall environment of the building area. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a method for monitoring and managing buildings in a city physical examination provided by an embodiment of the present application; Figure 2 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following is combined with Figure 1 -Attached Figure 2 This application is described in further detail.

[0025] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed, but as long as they are within the scope of the claims of the present application, they are protected by the patent law.

[0026] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0028] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0029] The present application embodiment provides a method for monitoring and managing buildings in a city physical examination, such as Figure 1 As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S104, wherein: S101: Acquire a BIM model, an interior image, and an area image of the building area where the target building is located.

[0030] Specifically, the target building is any building within the construction area, which can be a park, residential area, school, etc. By connecting with the architectural design unit or construction unit, the BIM model of the target building can be retrieved from the project file library saved by it. BIM modeling software can also be used to reconstruct the BIM model of the target building based on the architectural design drawings and construction materials.

[0031] For internal images of target buildings, multiple high-definition cameras can be deployed inside the building, with timed or triggered capture mechanisms set up to continuously capture images of the building's interior. For areas where fixed cameras are not feasible, professionals can be assigned to carry portable image acquisition equipment (such as high-definition cameras or panoramic cameras) to manually capture images along predetermined routes and within specified shooting specifications, ensuring that the captured images fully cover every area of ​​the building.

[0032] For regional images of building areas, a drone equipped with a high-resolution camera can be used to fly over the target building area along a predetermined route to obtain regional images including the target building and the surrounding environment. Satellite remote sensing images, aerial maps, etc. of the area can also be obtained from the local geographic information system (GIS) or relevant departments as regional image data sources, and image cropping and preprocessing can be performed according to actual needs. This is not limited in this embodiment.

[0033] S102: Conduct a safety hazard inspection on the target building based on the BIM model, the internal image, and the regional image to obtain a safety hazard inspection result for the target building.

[0034] Specifically, the hazard inspection results include structural hazard inspection results and fire hazard inspection results. Structural hazard types include crack hazards, material peeling hazards, and tilt hazards. Crack hazards and material peeling hazards can be identified using pre-trained hazard recognition models. Tilt hazards can be identified by calculating the target building's tilt angle using regional images. This tilt angle is then compared with the standard tilt angle to determine whether the target building has a tilt risk.

[0035] When the target building has structural hazards or fire hazards, the hazard area and hazard level are determined. The hazard inspection results include the hazard type, hazard area and hazard level of each safety hazard identified.

[0036] S103: Perform a physical inspection of the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area.

[0037] Specifically, the physical examination of a building area includes multiple dimensions, including: building spacing evaluation results, green space evaluation results, volume evaluation results, green space evaluation results, and public facilities evaluation results. Each evaluation result can be presented as a score, and the scores of each evaluation result are weighted and summed. The result of this weighted sum is used as the overall evaluation of the building area, namely the regional evaluation result. The weight of each dimension can be flexibly set based on actual experience and is not limited in this embodiment.

[0038] S104: Generate a list of rectification suggestions based on the hidden danger inspection results and the regional evaluation results, and send the list of rectification suggestions to the terminal devices of the managers of the building areas.

[0039] Specifically, the results of the hidden danger inspection were sorted out, and various existing building hidden dangers were converted into specific first-level improvement items. Based on the regional evaluation results, existing problems in building spacing, green space, volume, public facilities, etc. within the building area were converted into second-level improvement items.

[0040] When the number of first improvement items is greater than one, the first improvement items are sorted based on their hazard levels to obtain a first list. When the number of second improvement items is greater than one, the second improvement items are sorted based on their corresponding dimension scores to obtain a second list. Because building safety hazards are directly related to the safety of life and property, in the integrated improvement suggestion list, the priority of any first improvement item is set higher than the priority of any second improvement item. That is, the integration places the second list after the first list, resulting in a completed integrated rectification suggestion list.

[0041] This embodiment achieves multi-source data fusion by acquiring the BIM model, internal images, and regional images of the target building, and conducts safety hazard inspections based on these data. By utilizing the precise spatial information and image recognition technology of the BIM model, it can quickly and accurately locate structural and fire hazards. When inspecting the building area, the BIM model and regional images are combined to comprehensively assess aspects such as building spacing, greening, volume, and public facilities. Finally, a list of rectification suggestions is generated based on the hazard inspection and regional evaluation results and sent to management personnel, realizing intelligent management of the entire process from data collection, analysis and evaluation to decision support, effectively improving the efficiency and accuracy of building monitoring and management, reducing safety risks, and optimizing the overall environment of the building area.

[0042] In a possible implementation of the embodiment of the present application, the hidden danger inspection result includes a structural hidden danger inspection result and a fire hidden danger inspection result; Based on the BIM model, internal images, and regional images, the target building is inspected for potential safety hazards, and the inspection results for the target building are obtained, including: Identify whether the target building has structural hazards based on internal images and regional images, and obtain structural hazard inspection results; Identify whether the target building has fire hazards based on internal images and obtain fire hazard inspection results; When the structural hazard inspection results or fire hazard inspection results indicate the existence of hazards, the hazard type, hazard level and hazard area shall be marked on the BIM model.

[0043] In this embodiment, images of the target building's interior and region are fed into a pre-trained hidden danger identification model. The model then outputs a determination of whether cracks or material peeling are present on the target building's interior or exterior walls. If cracks or material peeling are detected, the model also outputs a designated hidden danger area where cracks or material peeling are present. The hidden danger level is further determined based on features such as the size and shape of the hidden danger area. Larger cracks indicate a higher hidden danger level, while larger areas of material peeling indicate a higher hidden danger level.

[0044] For potential tilt hazards, the tilt angle of the target building is determined based on the regional image. If the tilt angle exceeds the standard tilt angle, the target building is considered to have a tilt hazard. The hazard level is further determined based on the tilt angle, with the larger the tilt angle, the higher the hazard level.

[0045] This embodiment uses internal images and regional images, combined with advanced image recognition algorithms and deep learning models, to identify hidden dangers in the target building structure from multiple angles, such as cracks, material peeling and tilting. It then specifically identifies fire hazards such as fire protection facilities and passages based on the internal images, ensuring that the hidden dangers are detected comprehensively without blind spots. Finally, the identified hidden dangers are marked on the BIM model, and the powerful three-dimensional visualization and information integration capabilities of the BIM model are used to intuitively present the type, level and area of ​​the hidden dangers, making it easier for managers to quickly locate and understand the hidden danger situation.

[0046] In a possible implementation of the embodiment of the present application, the structural hidden dangers include: crack hidden dangers, material peeling hidden dangers, and tilt hidden dangers; Based on internal and regional images, the target building is identified for structural hazards and the structural hazard inspection results are obtained, including: The internal image and the regional image are input into the hidden danger identification model, and the hidden danger identification model outputs the identification result of whether the target building has crack hidden dangers and material peeling hidden dangers; Determine the tilt angle of the target building based on the regional image. If the tilt angle exceeds the standard tilt angle, it is determined that the target building has a tilt risk. When the target building has any structural hidden danger, determine the hidden danger level of the structural hidden danger.

[0047] In this embodiment, the hidden danger identification model can be a deep learning model such as a convolutional neural network, which is trained using a large amount of image data labeled with structural hidden dangers. The trained hidden danger identification model analyzes internal images and regional images, and outputs an identification result of whether the target building has crack hidden dangers and material peeling hidden dangers.

[0048] For the regional image, feature points of the target building's facade are extracted from the regional image. Corresponding feature points are then extracted from the 2D projection image generated by the BIM model. A feature matching algorithm is then applied to these points. The homography matrix between the image plane and the BIM plane is calculated using the matched feature points in the regional image and the 2D projection image. This matrix is ​​then decomposed to obtain the rotation parameters of the target building. From these rotation parameters, the rotation angle about the vertical axis is extracted as the target building's tilt angle.

[0049] This embodiment utilizes a hidden danger identification model to efficiently and accurately detect crack hidden dangers and material peeling hidden dangers, greatly improving the efficiency and accuracy of hidden danger identification; determines the inclination angle of the target building based on the regional image, and uses image processing and geometric calculation technology to achieve scientific quantitative judgment of the building inclination hidden danger; when a structural hidden danger is discovered, the hidden danger level is determined according to preset assessment standards, so that the hidden danger risk can be quantified and graded.

[0050] In one possible implementation of the embodiment of the present application, when a target building has any structural hidden danger, determining the hidden danger level of the structural hidden danger includes: When the hidden danger identification model outputs that there is a crack hidden danger, the crack length and the maximum crack width are determined based on the crack area output by the hidden danger identification model, and the hidden danger level of the crack hidden danger is determined based on the crack length and the maximum crack width; When the hazard identification model outputs a material spalling hazard, the material spalling area is determined based on the material spalling region output by the hazard identification model, and the hazard level of the material spalling hazard is determined based on the material spalling area; When the target building has a tilt risk, the hazard level of the tilt risk is determined based on the tilt angle.

[0051] In this embodiment, when the hidden danger identification model outputs a crack hidden danger, the pixel coordinates of the crack area are obtained from the model output. The pixels in the crack area are processed, and a pixel chain code tracking algorithm is used to sequentially record the pixel coordinates along the crack's direction. The Euclidean distance between adjacent pixels is calculated to accumulate the crack length (in pixels). Within the crack area, the pixel widths at each location perpendicular to the crack's direction are counted, and the maximum value is taken as the maximum crack width (in pixels). The pixel values ​​of the crack length and maximum width are converted to actual length and width dimensions (e.g., millimeters or centimeters) based on the image acquisition device parameters (such as resolution and focal length) and the distance information at the time of capture.

[0052] Then, based on pre-established crack hazard classification standards, the actual crack length and maximum width are compared with the standard values ​​to determine the crack hazard level. For example, if the crack length is less than a certain threshold and the maximum width is also less than the corresponding threshold, it is a low-level hazard; if the crack length or maximum width exceeds a certain range, it is a medium-level hazard; if the crack length and maximum width both far exceed the standard values, it is a high-level hazard.

[0053] When the hazard identification model outputs a material spalling hazard, pixel information of the spalling area is extracted from the model output. The pixels in the spalling area are counted and then converted to an actual area (e.g., square meters or square centimeters) based on the image scale (determined by the acquisition device parameters and the shooting distance). Based on pre-defined hazard classification standards, the calculated spalling area is compared with the area range for each pre-defined hazard level to determine the hazard level.

[0054] When it is determined that the target building has a potential tilt hazard, the tilt angle is matched with the angle range corresponding to each pre-divided potential hazard level to determine the potential hazard level corresponding to the target building.

[0055] When determining the structural hazard level, this embodiment, for crack hazards, quantifies the crack length and maximum width based on the crack area accurately delineated by the hazard identification model. By comparing with the established standards, the crack risk is scientifically graded and the degree of crack hazard is intuitively presented. For material spalling hazards, the spalling area data output by the model is used to calculate the spalling area, achieve a quantitative assessment of the hazard, and accurately define the hazard level. For tilt hazards, the hazard level is determined according to the standard based on the accurately measured tilt angle.

[0056] One possible implementation of the embodiment of the present application is to identify whether a target building has fire hazards based on internal images and obtain fire hazard inspection results, including: Determine the building type of the target building and retrieve the fire protection regulations corresponding to the building type; Identify the location and type of firefighting facilities within the target building based on internal images, as well as fire passage congestion, including whether they are locked or have debris piled up. The location, type and congestion of fire passages of fire-fighting facilities are compared with fire-fighting regulations to determine the results of fire hazard inspection. The results of fire hazard inspection include the determination of whether there are fire hazards, and the hazard level and hazard area of ​​fire hazards when it is determined that there are fire hazards.

[0057] In this embodiment, the building design document is retrieved to determine the building type, such as residential, commercial, hospital, etc. Based on the determined building type, the building fire protection code is obtained from a local database or a cloud server, including fire protection facility configuration standards and fire escape requirements.

[0058] A recognition model for firefighting facilities can be pre-trained. The model receives interior images as input and identifies the location and type of firefighting facilities within them. The recognition results for each interior image of the target building are then annotated on the BIM model. Firefighting regulations can include the type and quantity of firefighting facilities required on each floor, as well as a pre-set layout of firefighting facilities on the BIM model.

[0059] When the fire protection regulations specify the types and quantities of fire protection facilities to be installed on each floor, the actual layout of the fire protection facilities is determined on the marked BIM model (decomposed into the actual layout of each floor, including the number and type of fire protection facilities actually installed on each floor). The actual layout is compared with the fire protection regulations to check whether the actual layout of each floor is compliant. When the type or quantity of fire protection facilities on a certain floor does not comply with the corresponding fire protection regulations, the floor is judged to be non-compliant.

[0060] When the fire protection regulations are for a preset fire protection facility layout, based on the BIM model with the type and location of the fire protection facilities marked, for each fire protection facility in the preset fire protection facility layout, the preset location and preset type of the preset fire protection facility are determined, the actual fire protection facility closest to the preset location is queried, and it is determined whether the type of the actual fire protection facility meets the preset type. If so, the distance from the preset location to the actual fire protection facility is calculated, and the distance is compared with the preset offset threshold. If the distance does not exceed the preset offset threshold, the actual fire protection facility at the preset location is determined to be compliant, and the actual fire protection facility is marked as matched. When determining the next preset fire protection facility in the preset fire protection facility layout, the nearest actual fire protection facility that is not marked as matched is queried. When there is an actual fire protection facility on any layer that does not meet the type requirements, or the distance exceeds the preset offset threshold, or there is no actual fire protection facility to match, the fire protection facilities on that layer are determined to be non-compliant.

[0061] The congestion of the fire passage can be determined by identifying the door image of the fire passage. A recognition model is pre-trained to identify the open or closed status of the door and whether the lock is locked. When the door is identified as closed, the lock features on the door are further identified. When both the door closing and the lock locked features are identified at the same time, the corresponding fire passage door is determined to be locked; when the door is identified as open, the corresponding fire passage door is determined to be open; when the door is identified as closed and the lock is unlocked, the corresponding fire passage door is determined to be closed and unlocked.

[0062] After determining the locking status of the fire escape on each floor, compare the locking status with the fire regulations to identify floors that do not comply with fire regulations and record the floors with non-compliant locking status.

[0063] To address debris accumulation, we collected a large amount of image data containing passage areas, including both unobstructed and blocked scenes. These images were annotated, categorizing passage areas as either unobstructed or blocked. Congested images were also labeled with a congestion level, with higher levels indicating more severe congestion. A classification model was then trained based on these annotated images. Fire passage images from internal images were fed into the trained classification model, which then output a clear or blocked determination, along with the level of congestion.

[0064] Furthermore, when there are floors in the target building whose fire-fighting facilities do not comply with fire-fighting regulations, the proportion of the number of floors whose fire-fighting facilities do not comply with fire-fighting regulations to the total number of floors is counted, and the proportion is matched with the correspondence between the pre-divided proportion range and the hazard level to determine the hazard level of the fire-fighting facilities violations of the target building, and the hazard area is the specific floor that does not comply with fire-fighting regulations.

[0065] For the locking situation, the floors whose locking situation does not comply with the fire protection regulations are counted, and the ratio of the number of floors whose locking situation does not comply with the fire protection regulations to the total floors is counted. The ratio is matched with the correspondence between the pre-divided locking situation ratio range and the hazard level, and the hazard level of the locking situation violation of the target building is determined. The hazard area is the specific floor that does not comply with the locking situation regulations.

[0066] For the accumulation of debris, the model outputs that the floors where the fire escape passages are blocked are hidden danger areas, and the highest level of the blocked fire escape passages in the target building is the hidden danger level of the debris accumulation.

[0067] This embodiment retrieves the corresponding fire protection regulations based on the target building type, providing accurate standards for fire hazard determination and ensuring that there is a legal basis for investigation. Then, through analysis of internal images, image recognition technology is used to accurately locate fire protection facilities, identify facility types, and comprehensively detect congestion such as locked fire passages and piled up debris, thereby achieving comprehensive collection of fire hazard information. Finally, the collected fire protection facilities and passage conditions are compared with fire protection regulations, which can not only quickly determine whether there are fire hazards, but also scientifically classify hazard levels and locate hazard areas.

[0068] A possible implementation of the embodiment of the present application is to perform a physical examination of the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area, including: Obtain sunlight information for the area where the building is located, determine the actual distance between the target building and the building in front, and the building height information based on the BIM model, calculate the standard distance between buildings based on the sunlight information and building height information, and compare the actual distance between buildings with the standard distance between buildings to determine the sunlight evaluation result for the target building; Summarize the sunlight evaluation results of all buildings in the building area and generate the building spacing evaluation results of the building area; Determine the greening situation of the building area based on the regional image and BIM model, and generate greening evaluation results of the building area based on the greening situation; Determine the volume of the building area based on the BIM model, and generate a volume evaluation result for the building area based on the volume; Identify the public facilities situation in the building area based on the regional image, and generate a public facilities evaluation result for the building area based on the public facilities situation; The building spacing evaluation results, greening evaluation results, volume evaluation results and public facilities evaluation results are integrated to generate regional evaluation results for the building area.

[0069] In this embodiment, sunlight information includes the solar altitude angle h at noon on the winter solstice. Building height information includes the front building eave height H and the first-floor window height H1 of the target building. The sunlight spacing (i.e., the standard building spacing) is calculated as: D = (H - H1) / tan(h). If the actual building spacing is not less than the standard building spacing, the target building's sunlight exposure meets the standard. The sunlight evaluation results for all buildings within the building area are summarized, and buildings that do not meet the standard are screened out as the building spacing evaluation result for the building area.

[0070] Image processing techniques, such as vegetation analysis or image segmentation, are used to analyze regional images, identify green areas within the building area, and calculate the area of ​​the green areas and the total building area as the green coverage rate. A vegetation classification model can also be pre-trained to identify existing vegetation types within the building area and compare the vegetation types with the vegetation richness specification (the minimum number of types specified). If the number of existing vegetation types is not less than the vegetation richness specification, and the green coverage rate is not less than the green coverage rate specification, the greening evaluation result is determined to be greening compliance. If the number of existing vegetation types is less than the vegetation richness specification, or the green coverage rate is less than the green coverage rate specification, the greening evaluation result is determined to be greening non-compliance, and the non-compliant green coverage rate and / or vegetation type is designated as a greening non-compliance type.

[0071] Image recognition technology is used to analyze regional images and identify various public facilities within the building area, such as parking lots, fitness facilities, public restrooms, and waste disposal facilities. Facilities are then classified according to their function and type. The number of each type of public facility is counted and their locations are accurately marked on the BIM model. Comparing the actual layout of public facilities with the planned layout in the BIM model verifies whether they comply with planning requirements. Facility types that do not meet planning requirements are classified as non-compliant.

[0072] This embodiment integrates BIM models with regional image data. First, based on sunlight information and BIM model data, scientific calculations are performed and the standard and actual building spacing are compared to accurately obtain the sunlight evaluation results of the target building. The results are then summarized to generate an evaluation that comprehensively reflects the regional building spacing conditions. Then, with the help of data fusion and image recognition technology, greening and public facilities information is extracted from the regional image and BIM model to form objective greening and public facilities evaluation results respectively. Finally, comprehensive evaluations of various dimensions are combined to construct a complete building area evaluation system, which realizes quantitative evaluation and systematic diagnosis of various aspects such as sunlight conditions, spatial planning, environmental quality and public service facilities in the building area.

[0073] One possible implementation of the embodiment of the present application generates a list of rectification suggestions based on the hidden danger investigation results and regional assessment results, including: Determining a number of first improvement items based on the hidden danger inspection results, prioritizing the number of first improvement items based on the hidden danger level of each building hidden danger in the hidden danger inspection results, and generating a first list of the number of first improvement items in descending order of priority; Determining a plurality of second items to be improved and priorities of the plurality of second items to be improved based on the regional evaluation results, and generating a second list of the plurality of second items to be improved in descending order of priority; The first list and the second list are integrated as an improvement suggestion list, wherein the priority of any first item to be improved in the improvement suggestion list is higher than the priority of any second item to be improved.

[0074] In this embodiment, each item identified as a potential hazard in the hidden danger inspection results is considered the first item for improvement. For the regional assessment results, noncompliant items are considered the second item for improvement. If several first or second items for improvement have the same hazard level, the items with the same level can be randomly sorted, though this embodiment does not limit this. For buildings with noncompliant building spacing, reflective devices can be installed to increase daylighting.

[0075] This embodiment accurately locates building safety hazards based on the hidden danger inspection results, assigns priority to the first improvement project according to the hazard level, and forms a logically clear and focused hidden danger rectification sequence to ensure that high-risk hazards are dealt with first and guarantee building safety; then, based on the regional evaluation results, the second improvement projects that affect regional quality are sorted out and reasonably ranked to indicate the direction for regional optimization; finally, the two lists are integrated to clarify that the safety hazard rectification projects have a higher priority than the regional optimization projects, which not only highlights the management principle of safety first, but also takes into account the overall improvement of the region.

[0076] An electronic device is provided in an embodiment of the present application, such as Figure 2 As shown, Figure 2 The electronic device 200 shown includes a processor 201 and a memory 203. The processor 201 and the memory 203 are connected, for example, via a bus 202. Optionally, the electronic device 200 may further include a transceiver 204. It should be noted that in actual applications, the number of transceivers 204 is not limited to one, and the structure of the electronic device 200 does not constitute a limitation on the embodiments of the present application.

[0077] Processor 201 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 201 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0078] The bus 202 may include a path for transmitting information between the above components. The bus 202 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 202 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but it does not mean that there is only one bus or one type of bus.

[0079] The memory 203 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0080] The memory 203 is used to store the application code for executing the solution of the present application, and is controlled by the processor 201. The processor 201 is used to execute the application code stored in the memory 203 to implement the content shown in the embodiment of the building monitoring and management method in the above-mentioned urban physical examination.

[0081] Figure 2 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0082] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the contents shown in the embodiment of the building monitoring and management method in the aforementioned urban physical examination.

[0083] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0084] An embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the contents shown in the embodiment of the building monitoring and management method in the aforementioned urban physical examination are implemented.

[0085] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for monitoring and managing buildings in urban physical examination, characterized in that: include: Obtaining a BIM model, interior images, and area images of the target building; Performing a safety hazard inspection on the target building based on the BIM model, the internal image, and the regional image to obtain a safety hazard inspection result for the target building; Performing a physical examination on the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area; A rectification suggestion list is generated based on the hidden danger inspection result and the area evaluation result, and the rectification suggestion list is sent to a terminal device of a manager of the building area.

2. The building monitoring and management method in urban physical examination according to claim 1 is characterized in that: The hidden danger inspection results include structural hidden danger inspection results and fire hidden danger inspection results; The performing safety hazard inspection on the target building based on the BIM model, the internal image, and the regional image to obtain a safety hazard inspection result of the target building includes: Identify whether the target building has structural hidden dangers based on the internal image and the regional image, and obtain a structural hidden danger inspection result; Identify whether the target building has fire hazards based on the internal image, and obtain fire hazard investigation results; When the structural hidden danger inspection result or the fire hidden danger inspection result indicates the existence of hidden dangers, the hidden danger type, hidden danger level and hidden danger area are marked on the BIM model.

3. The building monitoring and management method in urban physical examination according to claim 2 is characterized in that: The types of structural hazards include: crack hazards, material peeling hazards and tilt hazards; The identifying whether the target building has structural hidden dangers based on the internal image and the regional image, and obtaining a structural hidden danger investigation result, includes: Inputting the internal image and the regional image into a hidden danger identification model, the hidden danger identification model outputting an identification result of whether the target building has the hidden danger of cracks and the hidden danger of material peeling; determining a tilt angle of the target building based on the regional image, and determining that the target building has the tilt risk when the tilt angle exceeds a standard tilt angle; When the target building has any structural hidden danger, the hidden danger level of the structural hidden danger is determined.

4. The building monitoring and management method in urban physical examination according to claim 3 is characterized in that: When the target building has any structural hidden danger, determining the hidden danger level of the structural hidden danger includes: When the hidden danger identification model outputs that the crack hidden danger exists, determining the crack length and the maximum crack width based on the crack area output by the hidden danger identification model, and determining the hidden danger level of the crack hidden danger based on the crack length and the maximum crack width; When the hidden danger identification model outputs that the material spalling hidden danger exists, determining the material spalling area based on the material spalling region output by the hidden danger identification model, and determining the hidden danger level of the material spalling hidden danger based on the material spalling area; When the target building has the tilt risk, the risk level of the tilt risk is determined based on the tilt angle.

5. The building monitoring and management method in urban physical examination according to claim 2 is characterized in that: The identifying whether the target building has a fire hazard based on the internal image and obtaining a fire hazard investigation result includes: Determine the building type of the target building and retrieve the fire protection regulations corresponding to the building type; identifying, based on the internal image, the location and type of firefighting facilities within the target building, as well as fire passage congestion conditions, wherein the fire passage congestion conditions include locked conditions and debris accumulation conditions; The facility location, facility type and congestion of the fire-fighting facilities are compared with the fire-fighting regulations to determine the fire hazard inspection results. The fire hazard inspection results include the determination result of whether there are fire hazards, and the hazard level and hazard area of ​​the fire hazards when it is determined that the fire hazards exist.

6. The building monitoring and management method in urban physical examination according to claim 1 is characterized in that: The performing a physical examination on the building area based on the BIM model and the regional image to obtain a regional evaluation result of the building area includes: Obtaining sunlight information for the area where the building area is located, determining the actual building distance and building height information between the target building and the front building based on the BIM model, calculating a standard building distance based on the sunlight information and the building height information, and comparing the actual building distance with the standard building distance to determine a sunlight evaluation result for the target building; Summarizing the sunlight evaluation results of all buildings in the building area to generate a building spacing evaluation result for the building area; determining a greening condition of the building area based on the area image and the BIM model, and generating a greening evaluation result of the building area based on the greening condition; identifying the public facilities situation of the building area based on the area image, and generating a public facilities evaluation result of the building area based on the public facilities situation; The regional evaluation result of the building area is generated by integrating the building distance evaluation result, the greening evaluation result, the volume evaluation result and the public facilities evaluation result.

7. The building monitoring and management method in urban physical examination according to claim 1 is characterized in that: The generating of a list of rectification suggestions based on the hidden danger investigation results and the regional evaluation results includes: Determining a plurality of first items to be improved based on the hidden danger inspection results, prioritizing the plurality of first items to be improved based on the hidden danger level of each building hidden danger in the hidden danger inspection results, and generating a first list of the plurality of first items to be improved in descending order of priority; Determining a plurality of second items to be improved and priorities of the plurality of second items to be improved based on the regional evaluation results, and generating a second list of the plurality of second items to be improved in descending order of priority; The first list and the second list are integrated as an improvement suggestion list, wherein the priority of any first item to be improved in the improvement suggestion list is higher than the priority of any second item to be improved.

8. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the building monitoring and management method in urban physical examination according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the building monitoring and management method in urban physical examination according to any one of claims 1 to 7.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of the building monitoring and management method in urban physical examination according to any one of claims 1 to 7.

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