A building engineering quality real-time monitoring method, system and device based on BIM and the Internet of Things and a storage medium

Abstract

This invention discloses a method, system, device, and storage medium for real-time monitoring of building engineering quality based on BIM and the Internet of Things (IoT). The monitoring method includes the following steps: S1: Constructing an enhanced BIM model integrating a quality monitoring rule base; S2: Deploying an IoT sensor network and collecting data; S3: Real-time data-driven updates and intelligent analysis of the enhanced BIM model; S4: Issuing a 3D visualization warning and identifying problems when monitoring data is abnormal or risks are predicted; S5: Generating an intelligent handling process and closed-loop collaboration. This invention establishes a closed-loop collaborative process for initiating, assigning, handling, and accepting quality problems based on a unified 3D scene, achieving automated and intelligent monitoring and early warning of key quality control points, nipping quality problems in the bud, and significantly reducing rework costs.

Description

Technical Field

[0001] This invention belongs to the field of building construction technology, specifically relating to a method, system, equipment, and storage medium for real-time monitoring of building engineering quality based on BIM and the Internet of Things. Background Technology

[0002] Currently, quality monitoring in construction projects mainly relies on on-site inspections by supervisors, visual observation, manual measurements, and paper records. This method has significant drawbacks:

[0003] 1. Delay: Quality problems are often only discovered after they occur, making it impossible to provide early warnings during the process and resulting in high rectification costs.

[0004] 2. Subjectivity: It relies on personal experience, the judgment criteria are not uniform, and it is easy to overlook something.

[0005] 3. Discreteness: The inspection data is isolated and discontinuous, making it difficult to form a quality archive that is traceable throughout the entire process.

[0006] 4. Inefficiency: Organizing massive amounts of paper records is time-consuming, information transmission is slow, and collaborative processing efficiency is low.

[0007] While some attempts have been made to use BIM for construction simulation or IoT for environmental monitoring, these technologies are often applied in isolation.

[0008] Simple BIM applications: mostly static models, lacking dynamic connection with the real-time construction status, are records and simulations of the "past" or "future," rather than management of the "present."

[0009] Simple IoT applications: Sensors generate massive amounts of discrete data, which can only form charts or simple alarms. They lack precise correlation with engineering entities, construction processes, and acceptance standards in three-dimensional space, resulting in vague problem localization and weak guidance.

[0010] Therefore, there is an urgent need for an innovative solution that can deeply couple real-time physical data with information models to realize the transformation of quality monitoring from "passive inspection" to "proactive prevention" and from "result verification" to "intelligent process control". Summary of the Invention

[0011] To address the shortcomings of existing technologies, this invention provides a method, system, device, and storage medium for real-time monitoring of building engineering quality based on BIM and the Internet of Things.

[0012] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0013] The first objective of this invention is to provide a method for real-time monitoring of building engineering quality based on BIM and the Internet of Things, comprising the following steps:

[0014] S1: Construct an enhanced BIM model that integrates a quality monitoring rule base;

[0015] S2: Deploy an IoT sensor network and collect data;

[0016] S3: Real-time data-driven enhanced BIM model updates and intelligent analysis;

[0017] S4: When monitoring data is abnormal or risks are predicted, a 3D visualization warning and problem location will be issued;

[0018] S5: Generate intelligent handling processes and closed-loop collaboration.

[0019] Preferably, in step S1, the quality monitoring rule base includes at least one of monitoring parameters, threshold standards, spatial coordinates of monitoring points, associated sensor types, detection frequencies, and associated acceptance specification clauses.

[0020] The monitoring parameters include at least one of the following: temperature, humidity, displacement, and stress.

[0021] Preferably, step S2 is as follows: based on the spatial coordinates of the monitoring points and the sensor type defined in the enhanced BIM model, IoT sensors are deployed at the corresponding locations of the physical structure on the construction site, and all IoT sensors upload real-time monitoring data to the cloud or local server via a wireless network.

[0022] The IoT sensors include at least one of the following: temperature sensor, humidity sensor, strain sensor, displacement sensor, tilt sensor, pressure sensor, camera, and intelligent measuring tool.

[0023] Preferably, step S3 specifically includes the following steps:

[0024] S31. The system receives IoT sensor data streams and matches and binds them with the sensor IDs and the unique codes of monitoring points in the enhanced BIM model.

[0025] S32. Map real-time data to the corresponding components of the enhanced BIM model and dynamically update their status attributes;

[0026] The system's built-in intelligent analysis engine compares real-time data with thresholds in the quality monitoring rule base and uses time series analysis and trend prediction algorithms to determine whether the current state exceeds the standard and predict the probability of exceeding the standard at a certain time in the future.

[0027] Preferably, step S4 specifically includes the following steps:

[0028] S41. When monitoring data is abnormal or a risk is predicted, the system highlights and flashes the abnormal component in the 3D BIM scene and displays its health status intuitively with a color gradient.

[0029] S42. Clicking on the abnormal component will bring up a details panel, displaying real-time data, historical curves, exceedance situations, related regulatory clauses, and possible cause analysis and suggestions.

[0030] Preferably, step S5 specifically includes the following steps:

[0031] S51. The system automatically generates a quality rectification notice containing the problem location, description, and screenshots, and pushes it to the terminals of the responsible party and the supervisor through the workflow engine;

[0032] S52. Receive and review rectification feedback data from the terminal: During the handling process, rectification personnel upload rectification process images and review data through the terminal;

[0033] S53. Update the status attributes of the corresponding components in the enhanced BIM model to complete the closed loop: The supervising engineer conducts acceptance on-site or remotely based on the real-time transmitted data, and the acceptance results are synchronously updated to the enhanced BIM model to form a traceable closed loop record.

[0034] The second objective of this invention is to provide a system for real-time monitoring of building engineering quality based on BIM and the Internet of Things, comprising:

[0035] An enhanced BIM modeling and management module is used to build enhanced BIM models that integrate a quality monitoring rule base.

[0036] The IoT access and data fusion module is used to deploy an IoT sensor network according to model guidance and collect real-time data;

[0037] The intelligent analysis and early warning engine includes a rule comparison unit and a prediction algorithm unit, which are used to compare real-time data with threshold standards in real time; and / or, based on time series data, use prediction algorithms to calculate the probability of data exceeding the standard in a specific future period.

[0038] A 3D visualization monitoring and interaction platform is used to mark components with abnormal status or risks in the 3D view of the enhanced BIM model by highlighting, color changes or animation effects.

[0039] A collaborative workflow engine is used to initiate and track closed-loop collaborative processing flows;

[0040] The quality knowledge base and traceability archive module is used to store quality monitoring rules and traceability archive content.

[0041] Preferably, the collaborative workflow engine includes a mobile terminal APP for use by supervisors and construction personnel. The mobile terminal APP supports receiving early warnings, viewing 3D models, uploading on-site multimedia data, and electronic signatures.

[0042] The enhanced BIM modeling and management module also uses machine learning to optimize threshold standards or prediction algorithm parameters in the quality monitoring rule base based on historical monitoring data and handling results.

[0043] A third objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the aforementioned method for real-time monitoring of building engineering quality based on BIM and the Internet of Things.

[0044] The fourth objective of this invention is to provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for real-time monitoring of building engineering quality based on BIM and the Internet of Things.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. Real-time and preventative: Shifting from post-event inspection to process monitoring and risk warning, nipping quality problems in the bud and significantly reducing rework costs.

[0047] 2. Objectivity and accuracy: Based on sensor data and standard provisions, the judgment is more accurate by reducing the influence of subjective human factors.

[0048] 3. Intuitive and collaborative: 3D visualization positioning makes problem descriptions unambiguous, and the online closed-loop process greatly improves the collaborative efficiency of the supervision and construction parties, with complete and traceable records.

[0049] 4. Knowledge Accumulation and Value Extension: The resulting digital quality archives can serve as part of the digital delivery upon completion, providing a valuable data foundation for subsequent operation and maintenance, and enhancing the added value of supervision services. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the system architecture for a method of real-time monitoring of building engineering quality based on BIM and the Internet of Things according to the present invention.

[0051] Figure 2 This is a flowchart of a method for real-time monitoring of building engineering quality based on BIM and the Internet of Things according to the present invention;

[0052] Figure 3 This is a schematic diagram of the enhanced BIM model construction process in this invention;

[0053] Figure 4This is a schematic diagram illustrating the mapping relationship between IoT data and BIM models in this invention;

[0054] Figure 5 This is a schematic diagram illustrating the working principle of the intelligent analysis and early warning engine in this invention;

[0055] Figure 6 This is a schematic diagram of the early warning display interface of the three-dimensional visualization platform in this invention;

[0056] Figure 7 This is a schematic diagram of the application interface of the collaborative workflow engine in this invention on a mobile terminal;

[0057] Figure 8 This is a partial schematic diagram of the BIM model for monitoring the curing of large-volume concrete in Embodiment 1 of the present invention. Detailed Implementation

[0058] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0059] Example 1: Monitoring and maintenance of large-volume concrete pier caps for municipal bridges ( Figures 1 to 8 ).

[0060] Background: The main pier foundation of a cross-river bridge is massive, and controlling the heat of hydration of the concrete is crucial to its quality. Traditional methods rely on manual, timed temperature measurements, which are labor-intensive and produce discontinuous data.

[0061] S1. Modeling: In the bridge BIM model, select the abutment component and insert monitoring rules: the monitoring parameters are internal temperature, surface temperature, and ambient temperature and humidity; the thresholds are: internal and external temperature difference ≤25℃, cooling rate ≤2℃ / day; the monitoring points are arranged in a three-dimensional matrix; the sensor type is a digital temperature sensor.

[0062] S2. Deployment: When binding the reinforcement of the foundation, pre-embed a chain of temperature sensors according to the model coordinates and connect it to the data acquisition instrument.

[0063] S3-S4 Monitoring: After pouring, the system displays a real-time three-dimensional temperature cloud map of the foundation. 40 hours after pouring, the system analysis found that the temperature at a certain point inside was rising too rapidly, predicting that the temperature difference between the inside and outside would exceed 22℃ (near the threshold) after 12 hours. Subsequently, a yellow warning was triggered at that location in the model.

[0064] S5. Action: The system automatically sends an early warning to the construction unit and supervising engineer, suggesting "check the cooling water flow rate at this location." After on-site adjustments by the construction personnel, the temperature curve flattens, and the warning is lifted. Data from the entire process is automatically recorded.

[0065] Example 2: Monitoring the installation accuracy of steel structures in building engineering.

[0066] Background: The installation of the core tube steel structure of high-rise buildings requires extremely high precision in terms of verticality and axial deviation.

[0067] S1 Modeling: In the structural BIM model, install the installation accuracy rules for each steel column: the monitoring parameters are the top three-dimensional coordinates (X, Y, Z) and the inclination; the threshold is set according to the acceptance specifications.

[0068] S2 Deployment: Install a wireless transmission smart prism or a BeiDou / GNSS receiver on the top of each steel column.

[0069] S3-S4 Monitoring: During installation, an automated total station or GNSS base station on-site measures the coordinates of each column top in real time and transmits the data back. The system displays the deviation vector (represented by colored line segments) between the actual position and the design position of each steel column in the BIM model in real time. The system issues an early warning when the deviation of a steel column approaches 80% of the allowable value.

[0070] S5 Handling: The supervising engineer views the 3D deviation diagram on a tablet computer, accurately directs the correction, and after the data is verified to be qualified, the system marks the component as "installation acceptance passed".

[0071] Comparative Example: Traditional Supervision Methods vs. This Invention

[0072] Taking concrete strength testing as an example:

[0073] Traditional method:

[0074] Data collection: Supervisors place test blocks at designated locations on-site, send them to a standard curing room and cure them under the same conditions, and then send them to the laboratory for pressing to obtain a strength report. The process takes more than 28 days, and the representativeness and authenticity of the test blocks are questionable.

[0075] Analysis and early warning: When a report of non-compliance with strength requirements is returned, the physical structure has already undergone multiple construction processes, making the handling extremely passive.

[0076] Collaborative handling: Sending reports via phone and email is inefficient and makes it difficult to trace responsibility.

[0077] Application of this invention:

[0078] Data acquisition: IoT wireless stress sensors and temperature and humidity sensors are embedded in key beam and slab components to monitor the strain development of concrete and the curing environment in real time.

[0079] Analysis and Early Warning: The system dynamically predicts the current strength based on real-time temperature and strain data using the maturity method or a strength prediction model based on big data. When the predicted strength development curve is lower than the standard curve, an early warning is issued stating, "The concrete strength growth may not meet the standard; it is recommended to check the mix proportions or strengthen the insulation."

[0080] Collaborative Response: Early warnings are directly pushed along with data curves, allowing construction units to immediately verify and take remedial measures (such as extending insulation), while supervisors can remotely monitor the effectiveness of remedial actions. All data, along with early warnings and response actions, are archived.

[0081] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for real-time monitoring of building engineering quality based on BIM and the Internet of Things, characterized in that, Includes the following steps: S1: Construct an enhanced BIM model that integrates a quality monitoring rule base; S2: Deploy an IoT sensor network and collect data; S3: Real-time data-driven enhanced BIM model updates and intelligent analysis; S4: When monitoring data is abnormal or risks are predicted, a 3D visualization warning and problem location will be issued; S5: Generate intelligent handling processes and closed-loop collaboration.

2. The method for real-time monitoring of building engineering quality based on BIM and IoT as described in claim 1, characterized in that, In step S1, the quality monitoring rule base includes at least one of the following: monitoring parameters, threshold standards, spatial coordinates of monitoring points, associated sensor types, detection frequencies, and associated acceptance specification clauses. The monitoring parameters include at least one of the following: temperature, humidity, displacement, and stress.

3. The method for real-time monitoring of building engineering quality based on BIM and IoT as described in claim 2, characterized in that, The specific steps of step S2 are as follows: Based on the spatial coordinates of the monitoring points and the sensor type defined in the enhanced BIM model, deploy IoT sensors at the corresponding locations of the physical structure on the construction site. All IoT sensors upload real-time monitoring data to the cloud or local server via wireless network. The IoT sensors include at least one of the following: temperature sensor, humidity sensor, strain sensor, displacement sensor, tilt sensor, pressure sensor, camera, and intelligent measuring tool.

4. The method for real-time monitoring of building engineering quality based on BIM and IoT as described in claim 3, characterized in that, The specific steps of step S3 are as follows: S31. The system receives IoT sensor data streams and matches and binds them with the sensor IDs and the unique codes of monitoring points in the enhanced BIM model. S32. Map real-time data to the corresponding components of the enhanced BIM model and dynamically update their status attributes; The system's built-in intelligent analysis engine compares real-time data with thresholds in the quality monitoring rule base and uses time series analysis and trend prediction algorithms to determine whether the current state exceeds the standard and predict the probability of exceeding the standard at a certain time in the future.

5. The method for real-time monitoring of building engineering quality based on BIM and IoT according to claim 4, characterized in that, The specific steps of step S4 are as follows: S41. When monitoring data is abnormal or a risk is predicted, the system highlights and flashes the abnormal component in the 3D BIM scene and displays its health status intuitively with a color gradient. S42. Clicking on the abnormal component will bring up a details panel, displaying real-time data, historical curves, exceedance situations, related regulatory clauses, and possible cause analysis and suggestions.

6. The method for real-time monitoring of building engineering quality based on BIM and IoT as described in claim 5, characterized in that, The specific steps of step S5 are as follows: S51. The system automatically generates a quality rectification notice containing the problem location, description, and screenshots, and pushes it to the terminals of the responsible party and the supervisor through the workflow engine; S52. Receive and review rectification feedback data from the terminal: During the handling process, rectification personnel upload rectification process images and review data through the terminal; S53. Update the status attributes of the corresponding components in the enhanced BIM model to complete the closed loop: The supervising engineer conducts acceptance on-site or remotely based on the real-time transmitted data, and the acceptance results are synchronously updated to the enhanced BIM model to form a traceable closed loop record.

7. A system for implementing the real-time monitoring method for building engineering quality based on BIM and the Internet of Things as described in any one of claims 1-6, characterized in that, include: An enhanced BIM modeling and management module is used to build enhanced BIM models that integrate a quality monitoring rule base. The IoT access and data fusion module is used to deploy an IoT sensor network according to model guidance and collect real-time data; The intelligent analysis and early warning engine includes a rule comparison unit and a prediction algorithm unit, which are used to compare real-time data with threshold standards in real time; and / or, based on time series data, use prediction algorithms to calculate the probability of data exceeding the standard in a specific future period. A 3D visualization monitoring and interaction platform is used to mark components with abnormal status or risks in the 3D view of the enhanced BIM model by highlighting, color changes or animation effects. A collaborative workflow engine is used to initiate and track closed-loop collaborative processing flows; The quality knowledge base and traceability archive module is used to store quality monitoring rules and traceability archive content.

8. The system according to claim 7, characterized in that, The collaborative workflow engine includes a mobile terminal APP for use by supervisors and construction personnel. The mobile terminal APP supports receiving early warnings, viewing 3D models, uploading on-site multimedia data, and electronic signatures. The enhanced BIM modeling and management module also uses machine learning to optimize threshold standards or prediction algorithm parameters in the quality monitoring rule base based on historical monitoring data and handling results.

9. An electronic 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 program, it implements the method as described in any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 / 6.

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