BIM-based construction environment monitoring method, device, equipment and medium

Abstract

Embodiments of the present application disclose a BIM-based construction environment monitoring method, device, equipment and medium. The method comprises: constructing a BIM environment monitoring model, the BIM environment monitoring model comprising a plurality of virtual monitoring points; acquiring real-time monitoring data uploaded by a plurality of intelligent sensor devices respectively; performing spatial matching on the real-time monitoring data and the virtual monitoring points according to the device identifiers, sensor coordinates in the real-time monitoring data and the device identifiers, monitoring point coordinates of the virtual monitoring points, to determine a target virtual monitoring point corresponding to each real-time monitoring data; for each virtual monitoring point, performing risk early warning processing on the corresponding sensor value through a risk monitoring rule of the target virtual monitoring point to obtain risk early warning information of the virtual monitoring point; and displaying the BIM environment monitoring model carrying the risk early warning information through a BIM visualization platform. The embodiments can realize visual early warning monitoring of construction environment risks.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to BIM-based construction environment monitoring methods, devices, equipment and media. Background Technology

[0002] In traditional construction processes, environmental parameters at construction sites (such as soil stability, noise levels, air quality, and groundwater quality) usually rely on manual inspections or discrete testing, which suffers from problems such as data lag, incomplete coverage, and slow response, making it difficult to achieve real-time, continuous, and accurate monitoring of the construction environment.

[0003] Therefore, there is an urgent need for a dynamic monitoring method for the construction environment to achieve real-time early warning of environmental risks. Summary of the Invention

[0004] This application provides a BIM-based construction environment monitoring method, device, equipment, and medium, which can realize visualized early warning monitoring of construction environment risks through BIM.

[0005] In a first aspect, embodiments of this application provide a BIM-based construction environment monitoring method, which includes: constructing a BIM environment monitoring model corresponding to the target construction site, wherein the BIM environment monitoring model includes multiple virtual monitoring points, and each virtual monitoring point is respectively bound to a corresponding equipment identifier, monitoring point coordinates and risk monitoring rules;

[0006] Acquire real-time monitoring data uploaded by multiple smart sensor devices, wherein the real-time monitoring data includes device identification, sensor values, and sensor coordinates;

[0007] Based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, spatial matching is performed on the real-time monitoring data and the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data;

[0008] For each virtual monitoring point, the risk warning processing of the corresponding sensor values ​​is performed according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point;

[0009] The BIM environmental monitoring model carrying the aforementioned risk warning information is displayed through a BIM visualization platform.

[0010] In some embodiments, the step of spatially matching the real-time monitoring data and the virtual monitoring points based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, to determine the target virtual monitoring point corresponding to each of the real-time monitoring data, includes:

[0011] For each of the real-time monitoring data, the virtual monitoring points containing the corresponding device identifiers in the multiple virtual monitoring points are determined as the set monitoring points of the real-time monitoring data;

[0012] For each of the real-time monitoring data, determine the coordinate error between the sensor coordinates of the real-time monitoring data and the coordinates of the monitoring point of the set monitoring point;

[0013] If the coordinate error is less than or equal to the preset error range, the corresponding set monitoring point will be determined as the target virtual monitoring point.

[0014] In some embodiments, after determining the coordinate error between the sensor coordinates of the real-time monitoring data and the coordinates of the monitoring point at the set monitoring point, the method further includes:

[0015] If the coordinate error is greater than the preset error range, a sensor position offset reminder message corresponding to the set monitoring point is generated;

[0016] The BIM environment monitoring model carrying the sensor position offset reminder information is displayed through the BIM visualization platform.

[0017] In some embodiments, the risk monitoring rules include multiple threshold ranges corresponding to different risk levels. The step of performing risk warning processing on the corresponding sensor values ​​using the risk monitoring rules for the target virtual monitoring point to obtain risk warning information for the virtual monitoring point includes:

[0018] Determine the target threshold range in which the sensor value falls;

[0019] The risk warning information is determined based on the risk level corresponding to the target threshold range.

[0020] In some embodiments, after determining the risk warning information based on the risk level corresponding to the target threshold range, the method further includes:

[0021] When the risk warning information is a Level 1 warning information, a text message is sent to the terminal of the preset responsible person.

[0022] When the risk warning information is a level 2 warning information, the warning information is pushed to the target application in the preset responsible person's terminal, and on-site sound and light alarms are triggered in the smart sensor device corresponding to the target construction site.

[0023] When the risk warning information is a level three warning information, relevant work suspension reminder information and work order rectification information are generated, and the relevant work suspension reminder information and work order rectification information are sent to the terminal of the preset responsible person.

[0024] In some embodiments, the BIM environmental monitoring model includes multiple environmentally sensitive areas, each of which is bound to at least one virtual monitoring point. Displaying the BIM environmental monitoring model carrying the risk warning information through a BIM visualization platform includes:

[0025] Based on the preset correspondence between virtual monitoring points and visualization rules, and the risk warning information, the visualization warning information corresponding to each virtual monitoring point is determined.

[0026] An IFC model is generated based on the visualized early warning information and the BIM environmental monitoring model.

[0027] The IFC model is sent to the BIM visualization platform so that the BIM environment monitoring model carrying the visualized early warning information can be displayed through the BIM visualization platform.

[0028] In some embodiments, the virtual monitoring points include soil moisture content monitoring points, soil displacement monitoring points, noise value monitoring points, and water quality monitoring points;

[0029] The visual early warning information corresponding to the soil moisture content monitoring points is a heat map indicating the moisture content; the visual early warning information corresponding to the soil displacement monitoring points is an animated arrow indicating the direction and magnitude of soil settlement; the visual early warning information corresponding to the noise value monitoring points is a bar chart indicating the noise value; and the visual early warning information corresponding to the water quality monitoring points is a curve indicating the COD of the water.

[0030] In some embodiments, the risk monitoring rule includes a risk trend prediction network model, and the step of performing risk warning processing on the corresponding sensor values ​​through the risk monitoring rule of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point includes:

[0031] Acquire meteorological data, construction progress, and equipment operating status within a preset time period;

[0032] The sensor values, meteorological data, construction progress, and equipment operating status are input into the risk trend prediction network model corresponding to the virtual monitoring point to perform risk prediction and obtain risk warning information after a preset time.

[0033] Secondly, embodiments of this application also provide a BIM-based construction environment monitoring device, which includes:

[0034] The processing unit constructs a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points, and each virtual monitoring point is bound to a corresponding device identifier, monitoring point coordinates, and risk monitoring rules.

[0035] The transceiver unit is used to acquire real-time monitoring data uploaded by multiple smart sensor devices, including device identifiers, sensor values, and sensor coordinates.

[0036] The processing unit is further configured to perform spatial matching of the real-time monitoring data and the virtual monitoring points based on the device identifiers, sensor coordinates, and device identifiers and monitoring point coordinates of each of the real-time monitoring data, to determine the target virtual monitoring point corresponding to each of the real-time monitoring data; for each virtual monitoring point, to perform risk warning processing on the corresponding sensor values ​​according to the risk monitoring rules of the target virtual monitoring point, to obtain the risk warning information of the virtual monitoring point; and to display the BIM environment monitoring model carrying the risk warning information through the BIM visualization platform.

[0037] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0038] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the above-described method.

[0039] This application provides a BIM-based construction environment monitoring method, device, equipment, and medium. The method includes: constructing a BIM environment monitoring model corresponding to a target construction site, the BIM environment monitoring model including multiple virtual monitoring points, each virtual monitoring point being bound to a corresponding device identifier, monitoring point coordinates, and risk monitoring rules; acquiring real-time monitoring data uploaded by multiple intelligent sensor devices, the real-time monitoring data including device identifiers, sensor values, and sensor coordinates; spatially matching the real-time monitoring data and the virtual monitoring points based on the device identifiers, sensor coordinates, and device identifiers and monitoring point coordinates of each virtual monitoring point to determine a target virtual monitoring point corresponding to each set of real-time monitoring data; for each virtual monitoring point, performing risk warning processing on the corresponding sensor values ​​according to the risk monitoring rules of the target virtual monitoring point to obtain risk warning information for the virtual monitoring point; and displaying the BIM environment monitoring model carrying the risk warning information through a BIM visualization platform. This embodiment of the application sets up intelligent sensor devices in the target construction site and automatically acquires real-time monitoring data of the target construction site through each intelligent sensor device. It also intelligently displays the risk warning information corresponding to the real-time monitoring data through a BIM visualization platform. It can be seen that this embodiment can realize the visualization and early warning monitoring of environmental risks through BIM, so as to monitor the construction environment in real time, continuously and accurately. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 A flowchart illustrating the BIM-based construction environment monitoring method provided in this application embodiment;

[0042] Figure 2 A schematic diagram of a sub-process of the BIM-based construction environment monitoring method provided in the embodiments of this application;

[0043] Figure 3 A schematic diagram of a sub-process of the BIM-based construction environment monitoring method provided in the embodiments of this application;

[0044] Figure 4 A schematic diagram of a sub-process of the BIM-based construction environment monitoring method provided in the embodiments of this application;

[0045] Figure 5 A schematic diagram of a sub-process of the BIM-based construction environment monitoring method provided in the embodiments of this application;

[0046] Figure 6 A schematic block diagram of a BIM-based construction environment monitoring device provided in the embodiments of this application;

[0047] Figure 7 A schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0050] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0051] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0052] This application provides a method, apparatus, equipment, and medium for monitoring the construction environment based on Building Information Modeling (BIM).

[0053] The execution entity of the BIM-based construction environment monitoring method can be the BIM-based construction environment monitoring device provided in the embodiments of this application, or a computer device that integrates the BIM-based construction environment monitoring device. The BIM-based construction environment monitoring device can be implemented in hardware or software, and the computer device can be a terminal or a server. The server can be a local server or a cloud server.

[0054] With the development of BIM technology, its 3D visualization and information integration capabilities have provided new means for construction management. However, existing BIM applications are mostly concentrated on design collaboration, detailed design, and construction simulation, with less emphasis on deeply integrating environmental monitoring data for dynamic early warning and decision support. Meanwhile, although Internet of Things (IoT) sensors (smart sensor devices) have been used on some construction sites, the lack of a linkage and visualization mapping mechanism with BIM models has led to a serious "data silo" phenomenon.

[0055] In addition, 5G networks have the characteristics of high bandwidth, low latency and wide connectivity, which provide a foundation for the real-time transmission of massive amounts of sensor data, but their systematic application in construction environment monitoring is still in the exploratory stage.

[0056] The BIM-based construction environment monitoring method provided in this application deeply integrates BIM models, 5G networks, and intelligent sensing devices to achieve visualized early warning and closed-loop management of environmental risks.

[0057] Figure 1 This is a flowchart illustrating the BIM-based construction environment monitoring method provided in this application. Figure 1 As shown, the method includes the following steps S110-S150.

[0058] S110. Construct a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points, and each virtual monitoring point is bound to a corresponding equipment identifier, monitoring point coordinates, and risk monitoring rules.

[0059] In this embodiment, the BIM environmental monitoring model includes multiple environmentally sensitive areas, and each environmentally sensitive area is bound to at least one virtual monitoring point.

[0060] Specifically, Revit (a modeling software) and Civil 3D (a modeling software) are used to create a BIM design model corresponding to the target construction site. This BIM design model includes professional information such as topography, geology, high-risk work areas, buildings, structures, and underground electromechanical pipelines. Then, multiple environmentally sensitive areas are embedded in the BIM design model corresponding to the target construction site. These environmentally sensitive areas include the area around the foundation pit, pipeline corridor areas, areas adjacent to buildings (such as within 5 meters of existing buildings), drainage areas (such as around drainage outlets, rainwater wells, and septic tanks), high-noise work areas, and spraying and welding work areas. Each environmentally sensitive area is bound to at least one virtual monitoring point. Each virtual monitoring point is bound to a corresponding equipment identifier, monitoring point coordinates, and risk monitoring rules, so that each environmentally sensitive area forms a dedicated BIM sub-model for environmental monitoring with spatial positioning capabilities.

[0061] Furthermore, each virtual monitoring point is assigned a unique code. For example, SJ-01, ZS-01, SZ-03, and KQ-04 represent virtual monitoring points for soil, noise, water quality, and air quality, respectively. Based on the survey report, the project's overall construction plan, and the project's point re-measurement data, the coordinates of the monitoring points and the BIM environmental monitoring model are all based on the Geodetic 2000 coordinate system to ensure coordinate consistency. This ensures the accurate establishment of virtual monitoring points in the BIM environmental monitoring model, aligning the virtual monitoring points with their real geographic coordinates and ensuring precise spatial matching.

[0062] Each of the virtual monitoring points is bound to a corresponding device identifier (such as a device type identifier or BIM component element ID), monitoring point coordinates, and risk monitoring rules (including early warning thresholds and / or risk trend prediction network models). In addition, in some embodiments, each of the virtual monitoring points is also bound to the installation method (including installation depth / height) and monitoring frequency of the corresponding smart sensor device. The installation method of the smart sensor device is used to guide on-site personnel in installing the sensor, and the monitoring frequency is used to update the risk warning information based on the corresponding monitoring frequency.

[0063] S120. Acquire real-time monitoring data uploaded by multiple smart sensor devices, wherein the real-time monitoring data includes device identifier, sensor value, and sensor coordinates.

[0064] Specifically, the smart sensor devices provided in this application all have 5G network communication capabilities. Taking the cloud server as the implementing entity of this application as an example, the smart sensor devices send real-time monitoring data to the cloud server through the 5G network.

[0065] The included smart sensor devices include smart soil analyzers, noise analyzers, groundwater quality analyzers, and air quality analyzers. The deployment and installation of these smart sensor devices, along with the 5G communication network, are described below:

[0066] Intelligent soil testing instrument:

[0067] The monitoring parameters (i.e., the corresponding sensor values) include: moisture content, pH, conductivity, temperature, and displacement (tilt sensor).

[0068] Installation methods include: insertion type and embedded type, with a depth of 0.5~3m;

[0069] Communication method: 5G+NB-IoT dual-mode.

[0070] Noise detector:

[0071] Monitoring parameters include: A-weighted sound level (dBA), frequency distribution, and peak value;

[0072] Installation methods include: pole mounting, 1.5m high, avoiding obstructions;

[0073] Communication method: 5G direct connection.

[0074] Groundwater quality testing instrument:

[0075] The monitoring parameters include: pH value, turbidity, chemical oxygen demand (COD), ammonia nitrogen concentration, and heavy metal (lead, cadmium, zinc) content;

[0076] Installation methods include: submersible or well-fixed, located below the groundwater level;

[0077] Communication method: 5G + LoRa;

[0078] Air quality detector:

[0079] The monitoring parameters include: PM2.5 (fine particulate matter), PM10 (inhalable particulate matter), CO (carbon monoxide), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), TVOC (total volatile organic compounds), temperature, and humidity;

[0080] Installation methods include: pole mounting, 1.5m high, avoiding obstructions;

[0081] Communication method: 5G direct connection.

[0082] 5G industrial-grade customer premises equipment (CPE) is deployed on construction sites to connect various sensor terminals; it supports ultra-reliable low-latency communication mode to ensure data transmission latency (e.g., <50ms); and it is equipped with an edge computing gateway to achieve local data preprocessing and reduce cloud load.

[0083] In this embodiment, different smart sensor devices can be set to different acquisition frequencies, and the acquisition frequency can be intelligently adjusted according to the current weather and / or construction progress.

[0084] For example, under normal conditions: data is collected every 30 seconds; during rainy days or high-risk operations: data is automatically collected every 5 seconds.

[0085] In addition to device identification (device ID), sensor values, and sensor coordinates (GPS coordinates), real-time monitoring data also includes time watermarks and signal strength.

[0086] The process of data transmission from smart sensor devices to the cloud server is as follows: sensor → 5G CPE → 5G base station → core network → cloud server. After the cloud server obtains the real-time monitoring data, it writes the real-time monitoring data into the real-time database.

[0087] S130. Based on the device identifier, sensor coordinates and device identifier and monitoring point coordinates of each of the real-time monitoring data, spatial matching is performed on the real-time monitoring data and the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data.

[0088] Specifically, please refer to Figure 2 Step S130 includes:

[0089] S1301. For each of the real-time monitoring data, the virtual monitoring points containing the corresponding device identifiers in the multiple virtual monitoring points are determined as the set monitoring points of the real-time monitoring data.

[0090] S1302. For each of the real-time monitoring data, determine the coordinate error between the sensor coordinates of the real-time monitoring data and the coordinates of the monitoring point of the set monitoring point;

[0091] S1303. If the coordinate error is less than or equal to the preset error range, the corresponding set monitoring point is determined as the target virtual monitoring point.

[0092] Due to the special nature of the construction site, the sensors may be moved during the construction process, causing the sensors to not correspond to the pre-set virtual monitoring points. In order to ensure the accuracy of the position, after obtaining the real-time monitoring data, this embodiment not only finds the set monitoring point for each real-time monitoring data according to the corresponding device identifier, but also further verifies the coordinate error between the actual coordinates of the current sensor and the pre-set coordinates based on the sensor coordinates. If the error is too large, the corresponding set monitoring point will be determined as the target virtual monitoring point.

[0093] Furthermore, if the coordinate error is greater than the preset error range, a sensor position offset reminder message corresponding to the set monitoring point is generated; the BIM environment monitoring model carrying the sensor position offset reminder message is displayed through the BIM visualization platform.

[0094] The cloud server provided in this embodiment offers a BIM data interface program. This program enables the management, storage, parsing, and provision of BIM models used in the project (such as Industry Foundation Classes (IFC) files). Specifically, it reads the coordinates of monitoring points in the IFC model, spatially matches real-time data with BIM points, and establishes a mapping table between sensor IDs (device identifiers of intelligent sensor devices) and BIM component element IDs (device identifiers bound to virtual monitoring points).

[0095] S140. For each virtual monitoring point, risk warning processing is performed on the corresponding sensor values ​​according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point.

[0096] In some embodiments, the risk monitoring rules include multiple threshold ranges corresponding to different risk levels. For example, Figure 3 As shown, step S140 includes:

[0097] a1401. Determine the target threshold range in which the sensor value falls;

[0098] a1402. Determine the risk warning information based on the risk level corresponding to the target threshold range.

[0099] In this embodiment, different risk monitoring rules are bound to different virtual monitoring points. After the target virtual monitoring point corresponding to each real-time monitoring data is determined, the cloud server provides risk warnings to the sensor values ​​based on the risk monitoring rules bound to the corresponding virtual monitoring point.

[0100] As can be seen, this embodiment can provide real-time risk warnings based on real-time monitoring data uploaded by intelligent sensor devices.

[0101] Furthermore, after determining the risk warning information based on the risk level corresponding to the target threshold range, the method further includes:

[0102] When the risk warning information is a Level 1 warning information, a text message is sent to the terminal of the preset responsible person.

[0103] When the risk warning information is a level 2 warning information, the warning information is pushed to the target application in the preset responsible person's terminal, and on-site sound and light alarms are triggered in the smart sensor device corresponding to the target construction site.

[0104] When the risk warning information is a level three warning information, relevant work suspension reminder information and work order rectification information are generated, and the relevant work suspension reminder information and work order rectification information are sent to the terminal of the preset responsible person.

[0105] Specifically, if the Level 1 warning information indicates that the parameters are slightly exceeded, the system needs to record and notify the responsible person via SMS; if the Level 2 warning information indicates that the parameters are continuously exceeded or the trend is worsening, the system needs to push the information through the APP, use on-site audible and visual alarms, and generate a pending work order; if the Level 3 warning information indicates that the parameters are severely exceeded or there is a sudden abnormality, the system needs to automatically suspend related operations, trigger the emergency plan, and report to the supervision and safety supervision departments.

[0106] In other embodiments, the risk monitoring rules include a risk trend prediction network model, such as... Figure 4As shown, step S140 includes:

[0107] b1401. Obtain meteorological data, construction progress, and equipment operating status within a preset time period;

[0108] b1402. Input the sensor values, meteorological data, construction progress, and equipment operating status into the risk trend prediction network model corresponding to the virtual monitoring point to perform risk prediction and obtain risk warning information after a preset time.

[0109] In this embodiment, different risk trend prediction network models are bound to different virtual monitoring points. Different types of risk trend prediction network models are trained based on corresponding types of historical environmental data. For example, the noise risk trend prediction network model is trained based on historical noise data and related data (meteorological data, construction progress, and operating status of noise equipment).

[0110] For example, environmental data from the past 7 days can be extracted to train an LSTM neural network model to predict trends over the next 24 hours. Input variables include meteorological data (rainfall, temperature), construction progress, and equipment operating status. The model predicts the path of soil moisture increase after rain, the noise propagation range during large machinery operations, and outputs a "risk heat map" to simulate groundwater pollution diffusion and pre-mark high-risk areas.

[0111] As can be seen, this embodiment can predict risks over a future period of time based on real-time monitoring data uploaded by intelligent sensor devices.

[0112] In some embodiments, the risk monitoring rules include multiple threshold intervals corresponding to different risk levels and a risk trend prediction network model. Step S140 includes: determining the target threshold interval where the sensor value is located; determining the current risk warning information by assigning the risk level corresponding to the target threshold interval; acquiring meteorological data, construction progress, and equipment operating status within a preset time period; inputting the sensor value, the meteorological data, the construction progress, and the equipment operating status into the risk trend prediction network model corresponding to the virtual monitoring point for risk prediction, and obtaining risk warning information after a preset time period.

[0113] As can be seen, this embodiment can not only provide real-time risk warnings based on real-time monitoring data uploaded by intelligent sensor devices, but also predict risks over a future period of time.

[0114] S150. Display the BIM environment monitoring model carrying the risk warning information through the BIM visualization platform.

[0115] Specifically, in some embodiments, such as Figure 5As shown, step S150 includes:

[0116] S1501. Based on the preset correspondence between virtual monitoring points and visualization rules, and the risk warning information, determine the visualization warning information corresponding to each virtual monitoring point.

[0117] S1502. Generate an IFC model based on the visualized early warning information and the BIM environmental monitoring model;

[0118] S1503. Send the IFC model to the BIM visualization platform so that the BIM environment monitoring model carrying the visualized early warning information can be displayed through the BIM visualization platform.

[0119] The visualization rules specify the display type and location of the visual early warning information for the corresponding virtual monitoring points. Specifically, the visual early warning information for soil moisture monitoring points is a heat map indicating the moisture content; the visual early warning information for soil displacement monitoring points is an animated arrow indicating the direction and magnitude of soil settlement; the visual early warning information for noise monitoring points is a bar chart indicating the noise value; and the visual early warning information for water quality monitoring points is a curve indicating COD (Chemical Oxygen Demand). Furthermore, the warning status is displayed: a pop-up alarm window indicates the responsible person and the processing deadline.

[0120] Furthermore, the BIM-based construction environment monitoring method provided in this application enables closed-loop management and automatic report generation. The closed-loop management path is as follows:

[0121] Detect anomalies → Trigger an alert → Push a work order → Handle on-site → Upload evidence → Review and close → Archive in the ledger;

[0122] It automatically generates daily "Construction Environment Monitoring Daily Report" and "Special Monitoring Report" to statistically analyze events exceeding standards, compares the average values ​​of each region with the early warning response timeliness analysis, and supports exporting to PDF and Excel formats for internal management or regulatory department review.

[0123] Specifically, it automatically generates an electronic ledger of all early warning events (including risk warning information) according to a preset cycle (such as every day), and supports exporting PDF format "Daily Construction Environment Report" and "Special Monitoring Report" to achieve closed-loop management.

[0124] In some embodiments, the BIM-based construction environment monitoring method provided in this application also supports multi-source environmental data fusion and feature extraction to conduct an overall environmental assessment of the target construction site.

[0125] Specifically, after acquiring real-time monitoring data uploaded by multiple smart sensor devices, the real-time monitoring data is normalized. The weights of each smart sensor device are dynamically determined based on a preset multi-source data fusion weight calculation formula. Based on a preset fusion environment parameter calculation formula and the weights of each smart sensor device, the multiple real-time monitoring data are fused to obtain the current overall environmental assessment parameters.

[0126] This overall environmental assessment parameter allows users to intuitively understand the current overall environmental status of the target construction site.

[0127] The above formula for calculating the weight of multi-source data fusion is: ;

[0128] in, Let i be the weight of the i-th smart sensor device. RSSI is the standard deviation of historical data for the i-th smart sensor device, used to reflect data volatility. i RSSI is the signal strength when the i-th smart sensor device acquires real-time monitoring data. max Let be the maximum signal strength of the i-th smart sensor device. This is a preset smoothing constant used to avoid division by zero errors.

[0129] The formulas for calculating the above-mentioned fusion environment parameters are as follows: ;

[0130] Where n is the number of smart sensor devices. Overall environmental assessment parameters This represents the normalized real-time monitoring data of the i-th smart sensor device.

[0131] In summary, this embodiment of the application sets up intelligent sensor devices in the target construction site and automatically acquires real-time monitoring data of the target construction site through each intelligent sensor device. Furthermore, it intelligently displays the risk warning information corresponding to the real-time monitoring data and finally dynamically displays the BIM environmental monitoring model carrying the risk warning information through the BIM visualization platform. It can be seen that this embodiment can realize the visualized early warning monitoring of environmental risks through BIM, so as to monitor the construction environment in a real-time, continuous and accurate manner.

[0132] Figure 6 This is a schematic block diagram of a BIM-based construction environment monitoring device provided in an embodiment of this application. Figure 6As shown, corresponding to the above-described BIM-based construction environment monitoring method, this application also provides a BIM-based construction environment monitoring device 600. This BIM-based construction environment monitoring device 600 includes a unit for executing the above-described BIM-based construction environment monitoring method, and can be configured in a terminal or server. Specifically, please refer to... Figure 6 The BIM-based construction environment monitoring device 600 includes a transceiver unit 601 and a processing unit 602, wherein:

[0133] Processing unit 602 constructs a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points, and each virtual monitoring point is bound to a corresponding device identifier, monitoring point coordinates, and risk monitoring rules.

[0134] The transceiver unit 601 is used to acquire real-time monitoring data uploaded by multiple smart sensor devices, the real-time monitoring data including device identifiers, sensor values ​​and sensor coordinates;

[0135] The processing unit 602 is further configured to perform spatial matching of the real-time monitoring data and the virtual monitoring points based on the device identifiers, sensor coordinates, and device identifiers and monitoring point coordinates of each virtual monitoring point in the real-time monitoring data, to determine the target virtual monitoring point corresponding to each real-time monitoring data; for each virtual monitoring point, to perform risk warning processing on the corresponding sensor values ​​according to the risk monitoring rules of the target virtual monitoring point, to obtain the risk warning information of the virtual monitoring point; and to display the BIM environment monitoring model carrying the risk warning information through the BIM visualization platform.

[0136] In some embodiments, when the processing unit 602 performs the step of spatially matching the real-time monitoring data and the virtual monitoring points based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data, it is specifically used for:

[0137] For each of the real-time monitoring data, the virtual monitoring points containing the corresponding device identifiers among the multiple virtual monitoring points are determined as the set monitoring points of the real-time monitoring data; for each of the real-time monitoring data, the coordinate error between the sensor coordinates of the real-time monitoring data and the monitoring point coordinates of the set monitoring points is determined; if the coordinate error is less than or equal to a preset error range, the corresponding set monitoring point is determined as the target virtual monitoring point.

[0138] In some embodiments, the risk monitoring rules include multiple threshold ranges corresponding to different risk levels. When the processing unit 602 executes the step of performing risk warning processing on the corresponding sensor values ​​using the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point, it is specifically used for:

[0139] Determine the target threshold range in which the sensor value falls; determine the risk warning information based on the risk level corresponding to the target threshold range.

[0140] In some embodiments, after the processing unit 602 performs the step of determining the risk warning information based on the risk level corresponding to the target threshold range, the transceiver unit 601 is further configured to:

[0141] When the risk warning information is a Level 1 warning, a text message is sent to the terminal of the preset responsible person; when the risk warning information is a Level 2 warning, the warning information is pushed to the target application in the terminal of the preset responsible person, and an on-site audible and visual alarm is triggered on the smart sensor device corresponding to the target construction site; when the risk warning information is a Level 3 warning, relevant work suspension reminder information and work order rectification information are generated, and the relevant work suspension reminder information and work order rectification information are sent to the terminal of the preset responsible person.

[0142] In some embodiments, when the processing unit 602 performs the step of displaying the BIM environment monitoring model carrying the risk warning information through the BIM visualization platform, it is specifically used for:

[0143] Based on the preset correspondence between virtual monitoring points and visualization rules, and the risk warning information, the visualization warning information corresponding to each virtual monitoring point is determined.

[0144] An IFC model is generated based on the visualized early warning information and the BIM environmental monitoring model.

[0145] The IFC model is sent to the BIM visualization platform through the transceiver unit 601, so that the BIM environment monitoring model carrying the visualized early warning information can be displayed through the BIM visualization platform.

[0146] In some embodiments, the virtual monitoring points include soil moisture content monitoring points, soil displacement monitoring points, noise value monitoring points, and water quality monitoring points;

[0147] The visual early warning information corresponding to the soil moisture content monitoring points is a heat map indicating the moisture content; the visual early warning information corresponding to the soil displacement monitoring points is an animated arrow indicating the direction and magnitude of soil settlement; the visual early warning information corresponding to the noise value monitoring points is a bar chart indicating the noise value; and the visual early warning information corresponding to the water quality monitoring points is a curve indicating the COD of the water.

[0148] In some embodiments, the risk monitoring rule includes a risk trend prediction network model. When the processing unit 602 executes the step of performing risk warning processing on the corresponding sensor values ​​using the risk monitoring rule for the target virtual monitoring point to obtain the risk warning information for the virtual monitoring point, it is specifically used for:

[0149] Acquire meteorological data, construction progress, and equipment operating status within a preset time period; input the sensor values, meteorological data, construction progress, and equipment operating status into the risk trend prediction network model corresponding to the virtual monitoring point to perform risk prediction and obtain risk warning information after a preset time period.

[0150] In summary, this embodiment of the application sets up intelligent sensor devices in the target construction site and automatically acquires real-time monitoring data of the target construction site through each intelligent sensor device. Furthermore, it intelligently displays the risk warning information corresponding to the real-time monitoring data and finally dynamically displays the BIM environmental monitoring model carrying the risk warning information through the BIM visualization platform. It can be seen that this embodiment can realize the visualized early warning monitoring of environmental risks through BIM, so as to monitor the construction environment in a real-time, continuous and accurate manner.

[0151] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned BIM-based construction environment monitoring device and its various units can be found in the corresponding descriptions in the aforementioned method embodiments. For the sake of convenience and brevity, these details will not be repeated here.

[0152] The aforementioned BIM-based construction environment monitoring device can be implemented as a computer program, which can be used in, for example... Figure 7 It runs on the computer device shown.

[0153] Please see Figure 7 , Figure 7 This is a schematic block diagram of a computer device 700 provided in an embodiment of this application. The computer device 700 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0154] See Figure 7 The computer device 700 includes a processor 702, a memory, and a network interface 705 connected via a system bus 701. The memory may include a non-volatile storage medium 703 and internal memory 704.

[0155] The non-volatile storage medium 703 may store an operating system 7031 and a computer program 7032. The computer program 7032 includes program instructions that, when executed, cause the processor 702 to perform a BIM-based construction environment monitoring method.

[0156] The processor 702 provides computing and control capabilities to support the operation of the entire computer device 700.

[0157] The internal memory 704 provides an environment for the operation of the computer program 7032 in the non-volatile storage medium 703. When the computer program 7032 is executed by the processor 702, the processor 702 can execute a BIM-based construction environment monitoring method.

[0158] This network interface 705 is used for network communication with other devices. Those skilled in the art will understand that... Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 700 to which the present application is applied. The specific computer device 700 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0159] The processor 702 is used to run a computer program 7032 stored in the memory to perform the following steps:

[0160] Construct a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points. Each virtual monitoring point is bound to a corresponding equipment identifier, monitoring point coordinates, and risk monitoring rules.

[0161] Acquire real-time monitoring data uploaded by multiple smart sensor devices, wherein the real-time monitoring data includes device identification, sensor values, and sensor coordinates;

[0162] Based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, spatial matching is performed on the real-time monitoring data and the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data;

[0163] For each virtual monitoring point, the risk warning processing of the corresponding sensor values ​​is performed according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point;

[0164] The BIM environmental monitoring model carrying the aforementioned risk warning information is displayed through a BIM visualization platform.

[0165] It should be understood that in the embodiments of this application, the processor 702 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0166] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0167] Therefore, this application also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the following steps:

[0168] Construct a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points. Each virtual monitoring point is bound to a corresponding equipment identifier, monitoring point coordinates, and risk monitoring rules.

[0169] Acquire real-time monitoring data uploaded by multiple smart sensor devices, wherein the real-time monitoring data includes device identification, sensor values, and sensor coordinates;

[0170] Based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, spatial matching is performed on the real-time monitoring data and the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data;

[0171] For each virtual monitoring point, the risk warning processing of the corresponding sensor values ​​is performed according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point;

[0172] The BIM environmental monitoring model carrying the aforementioned risk warning information is displayed through a BIM visualization platform.

[0173] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0174] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0175] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0176] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0177] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0178] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A BIM-based construction environment monitoring method, characterized in that, include: Construct a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points. Each virtual monitoring point is bound to a corresponding equipment identifier, monitoring point coordinates, and risk monitoring rules. Acquire real-time monitoring data uploaded by multiple smart sensor devices, wherein the real-time monitoring data includes device identification, sensor values, and sensor coordinates; Based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, spatial matching is performed on the real-time monitoring data and the virtual monitoring points to determine the target virtual monitoring point corresponding to each of the real-time monitoring data; For each virtual monitoring point, the risk warning processing of the corresponding sensor values ​​is performed according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point; The BIM environmental monitoring model carrying the aforementioned risk warning information is displayed through a BIM visualization platform; The risk monitoring rules include multiple threshold ranges corresponding to different risk levels and a risk trend prediction network model. The risk monitoring rules for the target virtual monitoring points are used to perform risk warning processing on the corresponding sensor values ​​to obtain risk warning information for the virtual monitoring points, including: Determine the target threshold range where the sensor value is located; determine the current risk warning information by assigning the risk level corresponding to the target threshold range; acquire meteorological data, construction progress, and equipment operating status within a preset time period; input the sensor value, meteorological data, construction progress, and equipment operating status into the risk trend prediction network model corresponding to the virtual monitoring point to perform risk prediction and obtain risk warning information after a preset time period; After acquiring real-time monitoring data uploaded by multiple smart sensor devices, the method further includes: The real-time monitoring data are normalized, and the weights of each smart sensor device are dynamically determined based on the preset multi-source data fusion weight calculation formula. Based on the preset calculation formula for fusion environment parameters, and the weights corresponding to each of the smart sensor devices, multiple real-time monitoring data are fused to obtain the current overall environmental assessment parameters. The formula for calculating the weight of the multi-source data fusion is as follows: ; in, Let i be the weight of the i-th smart sensor device. Let be the standard deviation of the historical data of the i-th smart sensor device; RSSI i RSSI is the signal strength when the i-th smart sensor device acquires real-time monitoring data. max Let be the maximum signal strength of the i-th smart sensor device. This is a preset smoothing constant.

2. The method according to claim 1, characterized in that, The step of spatially matching the real-time monitoring data and the virtual monitoring points based on the device identifiers, sensor coordinates, and device identifiers and monitoring point coordinates of each of the real-time monitoring data to determine the target virtual monitoring point corresponding to each of the real-time monitoring data includes: For each of the real-time monitoring data, the virtual monitoring points containing the corresponding device identifiers in the multiple virtual monitoring points are determined as the set monitoring points of the real-time monitoring data; For each of the real-time monitoring data, determine the coordinate error between the sensor coordinates of the real-time monitoring data and the coordinates of the monitoring point of the set monitoring point; If the coordinate error is less than or equal to the preset error range, the corresponding set monitoring point will be determined as the target virtual monitoring point.

3. The method according to claim 1, characterized in that, After determining the current risk warning information by identifying the risk level corresponding to the target threshold range, the method further includes: When the risk warning information is a Level 1 warning information, a text message is sent to the terminal of the preset responsible person. When the risk warning information is a level 2 warning information, the warning information is pushed to the target application in the preset responsible person's terminal, and on-site sound and light alarms are triggered in the smart sensor device corresponding to the target construction site. When the risk warning information is a level three warning information, relevant work suspension reminder information and work order rectification information are generated, and the relevant work suspension reminder information and work order rectification information are sent to the terminal of the preset responsible person.

4. The method according to claim 1, characterized in that, The step of displaying the BIM environment monitoring model carrying the risk warning information through the BIM visualization platform includes: Based on the preset correspondence between virtual monitoring points and visualization rules, and the risk warning information, the visualization warning information corresponding to each virtual monitoring point is determined. An IFC model is generated based on the visualized early warning information and the BIM environmental monitoring model. The IFC model is sent to the BIM visualization platform so that the BIM environment monitoring model carrying the visualized early warning information can be displayed through the BIM visualization platform.

5. The method according to claim 4, characterized in that, The virtual monitoring points include soil moisture content monitoring points, soil displacement monitoring points, noise value monitoring points, and water quality monitoring points; The visual early warning information corresponding to the soil moisture content monitoring points is a heat map indicating the moisture content; the visual early warning information corresponding to the soil displacement monitoring points is an animated arrow indicating the direction and magnitude of soil settlement; the visual early warning information corresponding to the noise value monitoring points is a bar chart indicating the noise value; and the visual early warning information corresponding to the water quality monitoring points is a curve indicating the COD of the water.

6. A BIM-based construction environment monitoring device, characterized in that, include: The processing unit constructs a BIM environmental monitoring model corresponding to the target construction site. The BIM environmental monitoring model includes multiple virtual monitoring points, and each virtual monitoring point is bound to a corresponding device identifier, monitoring point coordinates, and risk monitoring rules. The transceiver unit is used to acquire real-time monitoring data uploaded by multiple smart sensor devices, including device identifiers, sensor values, and sensor coordinates. The processing unit is further configured to perform spatial matching on the real-time monitoring data and the virtual monitoring points based on the device identifier, sensor coordinates in each of the real-time monitoring data and the device identifier and monitoring point coordinates of each of the virtual monitoring points, and determine the target virtual monitoring point corresponding to each of the real-time monitoring data. For each virtual monitoring point, the risk warning processing of the corresponding sensor values ​​is performed according to the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point; The BIM environmental monitoring model carrying the aforementioned risk warning information is displayed through a BIM visualization platform; The risk monitoring rules include multiple threshold ranges corresponding to different risk levels and a risk trend prediction network model. When the processing unit executes the step of performing risk warning processing on the corresponding sensor values ​​using the risk monitoring rules of the target virtual monitoring point to obtain the risk warning information of the virtual monitoring point, it is specifically used for: Determine the target threshold range where the sensor value is located; determine the current risk warning information by assigning the risk level corresponding to the target threshold range; acquire meteorological data, construction progress, and equipment operating status within a preset time period; input the sensor value, meteorological data, construction progress, and equipment operating status into the risk trend prediction network model corresponding to the virtual monitoring point to perform risk prediction and obtain risk warning information after a preset time period; After the step of acquiring real-time monitoring data uploaded by multiple smart sensor devices, the processing unit is further configured to: The real-time monitoring data are normalized, and the weights of each smart sensor device are dynamically determined based on the preset multi-source data fusion weight calculation formula. Based on the preset calculation formula for fusion environment parameters, and the weights corresponding to each of the smart sensor devices, multiple real-time monitoring data are fused to obtain the current overall environmental assessment parameters. The formula for calculating the weight of the multi-source data fusion is as follows: ; in, Let i be the weight of the i-th smart sensor device. Let $\begin{b}{i}$ be the standard deviation of the historical data of the $i$-th smart sensor device. RSSI i RSSI is the signal strength when the i-th smart sensor device acquires real-time monitoring data. max Let be the maximum signal strength of the i-th smart sensor device. This is a preset smoothing constant.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the BIM-based construction environment monitoring method as described in any one of claims 1-5.

8. A storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, cause the processor to perform the BIM-based construction environment monitoring method as described in any one of claims 1-5.

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