Method and system for automatically mapping BIM (Building Information Modeling) model and Iot (Internet of Things) equipment based on graphic engine

Abstract

The invention relates to the technical field of BIM model and Iot device mapping, in particular to a BIM model and Iot device automatic mapping method and system based on a graphic engine, and the mapping method comprises the steps: marking an Iot device identifier and an Iot device size for a two-dimensional CAD drawing; and creating a three-dimensional BIM model according to the CAD drawing. And importing the CAD drawing and the three-dimensional BIM model into a graphic engine. And converting the Iot device and the Iot device identifier corresponding to the single-layer two-dimensional CAD drawing into a three-dimensional BIM graphic element. And selecting Iot equipment which needs to be mapped. And carrying out space matching operation based on the selected Iot equipment. The Iot equipment identification mapping method solves the problems that an Iot equipment identification mapping method at the present stage is complex in operation, low in efficiency, high in cost, low in precision, difficult in secondary updating and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of mapping technology between BIM models and Iot devices. Specifically, it relates to an automatic mapping method and system for BIM models and Iot devices based on a graphics engine. Background Art

[0002] In the process of BIM intelligent operation and maintenance applications, it is necessary to precisely control and monitor each Iot device in a building. For example, it is necessary to remotely control the opening and closing of various lighting fixtures, air conditioners, etc., and to monitor and collect the real-time status of various temperature and humidity sensors and each valve. To achieve this goal, the most important thing is to perform device identification mapping operations on these Iot devices, that is: on-site verification personnel verify and check each device point and draw two-dimensional CAD drawings with device identifications, then three-dimensional modeling personnel perform refined modeling and processing according to the drawings, and developers complete the automatic mapping of device identifications and models on relevant graphics engines. Finally, a one-to-one correspondence is established between each on-site Iot device and the operation and maintenance model, so as to achieve the effect of precise control.

[0003] Currently, most commonly used device identification mapping operations are mainly divided into two types. The first is to complete the mapping manually, that is: manually bind the device identifications on the two-dimensional CAD drawings one by one in the three-dimensional BIM model, and then relevant developers perform data retrieval on the model and identifications to complete the mapping. The disadvantages of this mapping method are relatively obvious. When the number of devices is large, it will consume a lot of manpower, and manual operations are prone to errors and are very difficult to troubleshoot.

[0004] The second is to extract data from the two-dimensional CAD drawings and establish two databases, namely a relevant device identification database and a corresponding three-dimensional model component ID database, and then find the correspondence of fields such as device identifications and device unique IDs for association, so as to achieve the mapping effect. Although this method improves the accuracy of mapping, it increases the programming investment cost of creating the database, and also requires a lot of manpower and financial resources for the later maintenance of the database.

[0005] In summary, the commonly used Iot device identification mapping methods at the present stage generally have problems such as low accuracy, cumbersome operation process, low efficiency, and difficulty in updating secondary device identifications.

[0006] In view of this, this application is specifically proposed. Summary of the Invention

[0007] The first object of the present invention is to provide a method for automatically mapping a BIM model and IoT devices based on a graphics engine, which makes the entire IoT device identification mapping process more intelligent and convenient, effectively solves a series of problems such as complex operation, low efficiency, high input cost, low accuracy, and difficulty in secondary device identification update in the current common IoT device identification mapping methods, and is of great significance for the progress of the current IoT device identification mapping field, providing a reliable and efficient solution for the industry.

[0008] The second object of the present invention is to provide a system for automatically mapping a BIM model and IoT devices based on a graphics engine, which makes the entire IoT device identification mapping process more intelligent and convenient, effectively solves a series of problems such as complex operation, low efficiency, high input cost, low accuracy, and difficulty in secondary device identification update in the current common IoT device identification mapping methods, and is of great significance for the progress of the current IoT device identification mapping field, providing a reliable and efficient solution for the industry.

[0009] The embodiments of the present invention are implemented as follows:

[0010] A method for automatically mapping a BIM model and IoT devices based on a graphics engine, which includes the following steps:

[0011] S1. Mark the IoT devices in the two-dimensional CAD drawing, and the marking content includes: IoT device identification and IoT device size. Split the two-dimensional CAD drawing by floor to obtain single-layer two-dimensional CAD drawings.

[0012] S2. Create a three-dimensional BIM model according to the single-layer two-dimensional CAD drawing and determine the floor attribution of the three-dimensional BIM model.

[0013] S3. Import the single-layer two-dimensional CAD drawing and the three-dimensional BIM model into the graphics engine.

[0014] S4. Perform data parsing on the imported single-layer two-dimensional CAD drawing and three-dimensional BIM model in the graphics engine. Determine according to the single-layer two-dimensional CAD drawing: the two-dimensional coordinates of the IoT device, the size of the IoT device, the floor attribution of the IoT device, the two-dimensional coordinates of the IoT device identification, and the two-dimensional coordinates of the size annotation text of the IoT device. Determine according to the three-dimensional BIM model: the three-dimensional coordinates of the IoT device model, the type of the IoT device, and the floor attribution of the IoT device model.

[0015] S5. Convert the Iot devices and Iot device identifiers corresponding to the single-layer 2D CAD drawings into 3D BIM graphic elements, obtaining the 3D graphic elements of Iot devices and the 3D graphic elements of Iot device identifiers. Convert the corresponding 2D coordinates of Iot devices and the 2D coordinates of Iot device identifiers into 3D coordinates, obtaining the 3D converted coordinates of Iot devices and the 3D converted coordinates of Iot device identifiers.

[0016] S6. Select the Iot devices that need to be mapped.

[0017] S7. Perform spatial matching operations based on the selected Iot devices, including: S71. Create a virtual coordinate with the center being the 3D coordinates of the Iot device model obtained from the 3D BIM model in S4. Then, mark the 3D graphic elements of Iot devices in S5 in the virtual coordinate according to the 3D converted coordinates of Iot devices, and mark the 3D graphic elements of Iot device identifiers in S5 in the virtual coordinate according to the 3D converted coordinates of Iot device identifiers. S72. Define the center of the virtual coordinate as: A, define the 3D graphic elements of Iot devices as: B1, B2 ······ Bn, and define the 3D graphic elements of Iot device identifiers as: C1, C2 ······ Cn. S73. Calculate the 3D spatial Euclidean distances between A and each point of B1, B2 ······ Bn respectively, obtaining n groups of first distance values: D11, D12 ······ D1n. Determine the minimum value among the n groups of first distance values, denoted as D1min, and determine the 3D graphic element of the Iot device corresponding to D1min, denoted as Bmin. S74. Calculate the 3D spatial Euclidean distances between Bmin and each point of C1, C2 ······ Cn respectively, obtaining n groups of second distance values: D21, D22 ······ D2n. Determine the minimum value among the n groups of second distance values, denoted as D2min, and determine the 3D graphic element of the Iot device identifier corresponding to D2min, denoted as Cmin. S75. Establish a mapping relationship among the Iot device in the 3D BIM model corresponding to A, the Iot device in the single-layer 2D CAD drawing corresponding to Bmin, and the Iot device identifier in the single-layer 2D CAD drawing corresponding to Cmin.

[0018] Furthermore, it also includes performing size matching operations based on the Iot devices selected in S6, including:

[0019] S81. Determine the projected area of the Iot device on the xy plane according to the 3D BIM model in S4.

[0020] S82. Determine the 2D area of the Iot device according to the single-layer 2D CAD drawing in S4.

[0021] S83. If the difference between the projected area and the two-dimensional area is within the error range, it is determined that the Iot device corresponding to the 3D BIM model in S81 and the Iot device corresponding to the single-layer two-dimensional CAD drawing in S82 belong to the same device, and a mapping relationship is established.

[0022] Further, in S82, the two-dimensional area is obtained by annotating the text according to the size of the Iot device in the single-layer two-dimensional CAD drawing.

[0023] Further, in S6, the Iot devices are classified according to the device type. When selecting the Iot devices that need to be mapped, they are selected according to the device type of the Iot devices.

[0024] Further, in S1, the Iot device in the two-dimensional CAD drawing, the Iot device identifier corresponding to the Iot device, and the Iot device size annotation text for recording the size of the Iot device are all on different layers.

[0025] Further, the calculation formula for the three-dimensional space Euclidean distance is: d = sqrt((x1 - x2)^2 + (y1 - y2)^2 + (z1 - z2)^2).

[0026] A BIM model and Iot device automatic mapping system based on a graphics engine, which includes: a memory and a processor.

[0027] The memory stores a computer program, and the computer program is set to execute the above-mentioned BIM model and Iot device automatic mapping method based on the graphics engine when running.

[0028] The processor is set to execute the above-mentioned BIM model and Iot device automatic mapping method based on the graphics engine through the computer program.

[0029] The beneficial effects of the technical solution of the embodiment of the present invention include:

[0030] The automatic mapping method for the BIM model and Iot device based on the graphics engine provided by the embodiment of the present invention is automatically completed, greatly reducing the workload in the device identifier mapping stage and greatly improving the work efficiency. Thanks to this, in the subsequent update of the device identifier, only the content that needs to be updated needs to be modified on the two-dimensional CAD drawing, and then the above method steps are executed again, and the updated content will overwrite the original content to complete the update. This method makes the device identifier update more intelligent and convenient.

[0031] In addition, all device identifiers are bound one by one by this method, breaking the dilemma of easy errors in manual operations, ensuring the correct rate of device identifier mapping, and laying a solid foundation for subsequent device operation and maintenance applications.

[0032] Through the creative means of this application, the originally time-consuming and laborious mapping process with cumbersome operations becomes more intelligent and efficient. Moreover, by directly uploading CAD 2D drawings and BIM 3D models through the graphics engine, data parsing is carried out and the Iot device identification mapping is automatically completed. This is of great significance for the progress of the current device mapping field, provides a reliable and convenient solution for the industry, is expected to reduce the device mapping cost, improve the management level, and has made remarkable progress in digitization and intelligence, bringing new possibilities and prospects to the device mapping field.

[0033] Generally speaking, both the method and system for automatic mapping of BIM models and Iot devices based on the graphics engine provided by the embodiments of the present invention can make the entire Iot device identification mapping process more intelligent and convenient, effectively solve a series of problems such as complex operations, low efficiency, high input costs, low accuracy, and difficulty in secondary device identification update in the current common Iot device identification mapping methods, and are of great significance for the progress of the Iot device identification mapping field at the present stage, providing a reliable and efficient solution for the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, so they should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0035] Figure 1 It is the overall flowchart of the method for automatic mapping of BIM models and Iot devices based on the graphics engine provided by the embodiments of the present invention;

[0036] Figure 2 It is the overall flowchart of the spatial matching operation in the method for automatic mapping of BIM models and Iot devices based on the graphics engine provided by the embodiments of the present invention;

[0037] Figure 3 It is the overall flowchart of the size matching operation in the method for automatic mapping of BIM models and Iot devices based on the graphics engine provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0039] Accordingly, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0040] Please refer to Figure 1 , this embodiment provides a method for automatically mapping a BIM model and IoT devices based on a graphics engine, including the following steps:

[0041] S1. Label the IoT devices in the 2D CAD drawing. The labeling content includes: IoT device identifier and IoT device size. Split the 2D CAD drawing by floor to obtain single - floor 2D CAD drawings. The 2D CAD drawing contains 2D graphics of IoT devices. The IoT device identifier is an identifier for classifying IoT devices according to a preset classification method to represent the specific type of the IoT device, and the IoT device size is recorded in the IoT device size annotation text. The IoT device identifier and the IoT device size annotation text are only labeled near the corresponding 2D graphics of the IoT devices. Each split CAD drawing corresponds to the content of only one floor.

[0042] S2. Create a 3D BIM model according to the single - floor 2D CAD drawing and determine the floor attribution of the 3D BIM model. The floor to which the 3D BIM model belongs is determined by the floor corresponding to the single - floor 2D CAD drawing it is based on, and one 3D BIM model corresponds to one floor.

[0043] S3. Import the single - floor 2D CAD drawing and the 3D BIM model into the graphics engine.

[0044] S4. Perform data parsing on the single - floor 2D CAD drawing and the 3D BIM model imported into the graphics engine. Determine from the single - floor 2D CAD drawing: the 2D coordinates of the IoT device, the IoT device size (the size of the IoT device recorded in the IoT device size annotation text), the floor attribution of the IoT device, the 2D coordinates of the IoT device identifier (the coordinate data of the IoT device identifier in the single - floor 2D CAD drawing), and the 2D coordinates of the IoT device size annotation text (the coordinate data of the IoT device size annotation text in the single - floor 2D CAD drawing); and determine from the 3D BIM model: the 3D coordinates of the IoT device model, the IoT device type, and the floor attribution of the IoT device model.

[0045] S5. Convert the Iot devices and Iot device identifiers corresponding to the single-layer 2D CAD drawings into 3D BIM graphic elements to obtain 3D Iot device graphic elements and 3D Iot device identifier graphic elements. Convert the corresponding 2D coordinates of the Iot devices and the 2D coordinates of the Iot device identifiers into 3D coordinates to obtain 3D converted coordinates of the Iot devices and 3D converted coordinates of the Iot device identifiers. When determining the 3D coordinates, including but not limited to: determining the 3D converted coordinates according to the floor attribution relationship.

[0046] S6. Select the Iot devices that need to be mapped.

[0047] S7. Perform a spatial matching operation based on the selected Iot devices. Please combine Figure 2 , and the spatial matching operation includes:

[0048] S71. Create a new virtual coordinate (3D). The center of the virtual coordinate is the 3D coordinate of the Iot device model obtained from the 3D BIM model in S4. Then, mark the 3D Iot device graphic elements in S5 in the virtual coordinate according to the 3D converted coordinates of the Iot devices, and mark the 3D Iot device identifier graphic elements in S5 in the virtual coordinate according to the 3D converted coordinates of the Iot device identifiers.

[0049] S72. Define the center of the virtual coordinate as: A, define the 3D Iot device graphic elements as: B1, B2 ······ Bn, and define the 3D Iot device identifier graphic elements as: C1, C2 ······ Cn.

[0050] S73. Calculate the 3D spatial Euclidean distances between point A and points B1, B2 ······ Bn respectively to obtain n groups of first distance values: D11, D12 ······ D1n. Determine the minimum value among the n groups of first distance values, denoted as D1min, and determine the 3D Iot device graphic element corresponding to D1min, denoted as Bmin.

[0051] S74. Calculate the 3D spatial Euclidean distances between Bmin and points C1, C2 ······ Cn respectively to obtain n groups of second distance values: D21, D22 ······ D2n. Determine the minimum value among the n groups of second distance values, denoted as D2min, and determine the 3D Iot device identifier graphic element corresponding to D2min, denoted as Cmin.

[0052] S75. Establish a mapping relationship among the Iot devices in the 3D BIM model corresponding to A, the Iot devices in the single-layer 2D CAD drawing corresponding to Bmin, and the Iot device identifiers in the single-layer 2D CAD drawing corresponding to Cmin.

[0053] Through the above design, the corresponding relationship between the 2D drawings and 3D models of IoT devices can be accurately confirmed, thus realizing automatic mapping.

[0054] The automated mapping process greatly reduces the workload in the device identification mapping stage, significantly improving work efficiency. Thanks to this, for subsequent device identification updates, only the content that needs to be updated needs to be modified on the 2D CAD drawings, and then the above method steps are executed again. The updated content will overwrite the original content to complete the update. This method makes device identification updates more intelligent and convenient.

[0055] In addition, all device identifications are bound one by one by this method, breaking the dilemma of error-prone manual operations, ensuring the accuracy rate of device identification mapping, and laying a solid foundation for subsequent device operation and maintenance applications.

[0056] Through the creative means of this application, the originally time-consuming, laborious, and cumbersome mapping process becomes more intelligent and efficient. By directly uploading 2D CAD drawings and BIM 3D models through the graphics engine, data parsing is performed and IoT device identification mapping is automatically completed. This is of great significance for the progress of the current device mapping field, provides a reliable and convenient solution for the industry, is expected to reduce device mapping costs, improve management levels, and has made remarkable progress in terms of digitization and intelligence, bringing new possibilities and prospects to the device mapping field.

[0057] Optionally, the calculation formula for the Euclidean distance in three-dimensional space is: d = sqrt((x1 - x2)^2 + (y1 - y2)^2 + (z1 - z2)^2).

[0058] Please refer to Figure 3 , in this embodiment, the automatic mapping method of the BIM model and IoT devices based on the graphics engine further includes performing a size matching operation on the IoT devices selected based on S6. The size matching operation specifically includes the following steps:

[0059] S81. Determine the projected area of the IoT device on the xy plane according to the 3D BIM model in S4.

[0060] S82. Determine the 2D area of the IoT device according to the single-layer 2D CAD drawing in S4.

[0061] S83. If the difference between the projected area in S81 and the 2D area in S82 is within the error range, it is determined that the IoT device corresponding to the 3D BIM model in S81 and the IoT device corresponding to the single-layer 2D CAD drawing in S82 belong to the same device, and a mapping relationship is established.

[0062] Through the above design, the automatic verification of the mapping process can be realized, and the accuracy of automatic mapping can be further improved.

[0063] Optionally, in S82, the two-dimensional area is obtained by annotating the text according to the size of the Iot device in the single-layer two-dimensional CAD drawing.

[0064] Optionally, in S6, the Iot devices are classified according to the device type. When selecting the Iot devices that need to be mapped, select them according to the device type of the Iot devices. With such a design, the mapping efficiency can be effectively improved.

[0065] Further optionally, in S1, the Iot devices in the two-dimensional CAD drawing, the Iot device identifiers corresponding to the Iot devices, and the Iot device size annotation text for recording the size of the Iot devices are all located on different layers. With such a design, the relative independence and integrity of each part of the content can be effectively improved, and the mutual interference between different data can be reduced.

[0066] This embodiment also provides a BIM model and Iot device automatic mapping system based on a graphics engine for specifically implementing the above-mentioned BIM model and Iot device automatic mapping method based on a graphics engine. The system includes: a memory and a processor.

[0067] The memory stores a computer program, and the computer program is set to execute the above-mentioned BIM model and Iot device automatic mapping method when running.

[0068] The processor is set to execute the above-mentioned BIM model and Iot device automatic mapping method through the computer program.

[0069] In summary, both the BIM model and Iot device automatic mapping method and system provided by the embodiments of the present invention make the entire Iot device identifier mapping process more intelligent and convenient, effectively solving a series of problems such as complex operation, low efficiency, high input cost, low accuracy, and difficulty in updating secondary device identifiers in the current common Iot device identifier mapping methods. It is of great significance for the progress of the Iot device identifier mapping field at the present stage and provides a reliable and efficient solution for the industry.

[0070] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An automatic mapping method for BIM models and IoT devices based on a graphics engine, characterized in that, It includes the following steps: S1. Label the Iot devices in the 2D CAD drawing. The labeling content includes: Iot device identifier and Iot device size; Split the 2D CAD drawing by floor to obtain single - floor 2D CAD drawings; S2. Create a 3D BIM model based on the single - floor 2D CAD drawing and determine the floor attribution of the 3D BIM model; S3. Import the single - floor 2D CAD drawing and the 3D BIM model into the graphics engine; S4. Perform data parsing on the single - floor 2D CAD drawing and the 3D BIM model imported into the graphics engine; Determine from the single - floor 2D CAD drawing: Iot device 2D coordinates, Iot device size, Iot device floor attribution, Iot device identifier 2D coordinates, and Iot device size annotation text 2D coordinates; Determine from the 3D BIM model: Iot device model 3D coordinates, Iot device type, and Iot device model floor attribution; S5. Convert the Iot devices and Iot device identifiers corresponding to the single - floor 2D CAD drawing into 3D BIM graphic elements to obtain Iot device 3D graphic elements and Iot device identifier 3D graphic elements; Convert the corresponding Iot device 2D coordinates and Iot device identifier 2D coordinates into 3D coordinates to obtain Iot device 3D conversion coordinates and Iot device identifier 3D conversion coordinates; S6. Select the Iot devices that need to be mapped; S7. Perform spatial matching operations based on the selected IoT device, including: S71. Create a virtual coordinate. The center of the virtual coordinate is the three-dimensional coordinate of the IoT device model obtained from the three-dimensional BIM model in S4. Then, label the three-dimensional graphic elements of the IoT device in S5 in the virtual coordinate according to the three-dimensional transformation coordinates of the IoT device, and label the three-dimensional graphic elements of the IoT device identifier in S5 in the virtual coordinate according to the three-dimensional transformation coordinates of the IoT device identifier; S72. Define the center of the virtual coordinate as: A, define the three-dimensional graphic elements of the IoT device as: B1, B2 ······ Bn respectively, and define the three-dimensional graphic elements of the IoT device identifier as: C1, C2 ······ Cn respectively; S73. Calculate the three-dimensional spatial Euclidean distances between A and each of B1, B2 ······ Bn points respectively, to obtain n groups of first distance values: D11, D12 ······ D1n. Determine the minimum value among the n groups of the first distance values, denoted as D1min, and determine the three-dimensional graphic element of the IoT device corresponding to D1min, denoted as Bmin; S74. Calculate the three-dimensional spatial Euclidean distances between Bmin and each of C1, C2 ······ Cn points respectively, to obtain n groups of second distance values: D21, D22 ······ D2n. Determine the minimum value among the n groups of the second distance values, denoted as D2min, and determine the three-dimensional graphic element of the IoT device identifier corresponding to D2min, denoted as Cmin; S75. Establish a mapping relationship among the IoT device in the three-dimensional BIM model corresponding to A, the IoT device in the single-layer two-dimensional CAD drawing corresponding to Bmin, and the IoT device identifier in the single-layer two-dimensional CAD drawing corresponding to Cmin.

2. The automatic mapping method of the BIM model and Iot device based on the graphics engine according to claim 1, wherein It also includes performing size matching operations based on the IoT device selected in S6, including: S81. Determine the projected area of the IoT device on the xy plane according to the three-dimensional BIM model in S4; S82. Determine the two-dimensional area of the IoT device according to the single-layer two-dimensional CAD drawing in S4; S83. If the difference between the projected area and the two-dimensional area is within the error range, then determine that the IoT device corresponding to the three-dimensional BIM model in S81 and the IoT device corresponding to the single-layer two-dimensional CAD drawing in S82 belong to the same device, and establish a mapping relationship.

3. The automatic mapping method of the BIM model and Iot device based on the graphics engine according to claim 2, characterized in that, In S82, the two-dimensional area is obtained according to the size annotation text of the IoT device in the single-layer two-dimensional CAD drawing.

4. The automatic mapping method of the BIM model and Iot device based on the graphics engine according to claim 1, wherein In S6, classify the IoT devices by device type. When selecting the IoT devices that need to be mapped, select them according to the device type of the IoT devices.

5. The automatic mapping method of the BIM model and Iot device based on a graphics engine according to claim 1, wherein In S1, the IoT device in the two-dimensional CAD drawing, the IoT device identifier corresponding to this IoT device, and the IoT device size annotation text for recording the size of this IoT device are all on different layers.

6. The automatic mapping method of the BIM model and Iot device based on the graphics engine according to claim 1, characterized in that, The calculation formula for the Euclidean distance in three-dimensional space is: d = sqrt((x1 - x2)^2 + (y1 - y2)^2 + (z1 - z2)^2).

7. A BIM model and Iot device automatic mapping system based on a graphics engine, characterized in that, Including: A memory and a processor. The memory stores a computer program, and the computer program is set to execute the automatic mapping method of the BIM model based on the graphics engine and the Iot device according to any one of claims 1 to 6 when running; The processor is set to execute the automatic mapping method of the BIM model based on the graphics engine and the Iot device according to any one of claims 1 to 6 through the computer program.

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