Building performance monitoring system based on BIM and Internet of Things technology

Abstract

The invention discloses a building performance monitoring system based on BIM and Internet of Things technology, and relates to the field of building performance monitoring, comprising: a BIM model construction and integration module creating and integrating a building BIM model; the Internet of Things sensor deployment module deploys a sensor; the data acquisition and transmission module acquires and transmits data; the data processing and analyzing module processes and analyzes the data; the building performance evaluation and early warning module performs evaluation and early warning; and the user interaction and visualization module realizes interaction and visualization. And each module has corresponding technologies, such as IFC format integration and low-power consumption sensor, so that the performance is improved. The building performance can be effectively monitored, the BIM model is integrated, comprehensive monitoring, intelligent analysis, accurate evaluation and early warning are achieved, interaction visualization is convenient and fast, safe and comfortable operation of the building is guaranteed, and management and maintenance are convenient.

Description

Technical Field

[0001] The present invention relates to the technical field of building performance detection, and in particular to a building performance monitoring system based on BIM and Internet of Things technologies. Background Art

[0002] With the acceleration of urbanization, the scale and complexity of buildings are increasing. Monitoring and management of building performance has become the key to ensuring the safety, comfort and efficient operation of buildings. Traditional building monitoring methods face many challenges in dealing with the diverse needs of modern buildings.

[0003] In terms of building information management, traditional two-dimensional drawings are difficult to fully and intuitively present the complex information of the building, including the building structure, equipment system, spatial relationship, etc. The large amount of data generated during the building design and construction process is scattered in various links and documents, and there is a lack of effective integration mechanism, which leads to poor information flow and difficulty in collaboration between different professionals. For example, in a building renovation project, it may be difficult for structural engineers to accurately obtain the layout information of the original equipment of the building, which affects the accuracy of the design plan.

[0004] For building performance monitoring, existing methods often rely on manual regular inspections and local, isolated sensor monitoring. Manual inspections are not only inefficient, but also prone to missed detections and misjudgments. Local sensor monitoring can only obtain limited data and cannot fully reflect the overall performance of the building. For example, by only monitoring the temperature at a few fixed points, it is impossible to accurately grasp the temperature field distribution inside the building, which may cause comfort issues in certain areas to be ignored.

[0005] In terms of data processing and analysis, the data obtained by traditional monitoring methods are mostly discrete and unintegrated, lacking effective analysis methods to explore the relationship and potential value between data. Different types of data (such as structural data, energy consumption data, and environmental data) are often independent of each other, making it difficult to comprehensively evaluate building performance. For example, it is impossible to accurately analyze whether abnormal energy consumption is caused by equipment failure, usage habits, or building envelope problems.

[0006] In addition, when performance problems occur in buildings, the existing early warning mechanism is not timely and accurate enough. It is difficult for managers to obtain comprehensive building performance information in a timely manner, and they cannot quickly locate problems and take effective measures. At the same time, there is a lack of effective information exchange channels with building users, so users cannot understand the performance status of the building and cannot provide feedback on problems in a timely manner.

[0007] Against the backdrop of the rapid development of the Internet of Things and information technology, the construction industry urgently needs a system that can integrate building information modeling (BIM) and Internet of Things technology to achieve comprehensive, real-time, accurate monitoring and efficient management of building performance, in order to improve the safety, comfort and sustainability of buildings. Summary of the invention

[0008] The present invention proposes a building performance monitoring system based on BIM and Internet of Things technology to solve the problems mentioned in the above-mentioned prior art.

[0009] In order to achieve the above object, the present invention adopts the following technical solution: a building performance monitoring system based on BIM and Internet of Things technology, comprising: The BIM model construction and integration module is used to create a building information model (BIM), which accurately covers the building's geometric structure, material properties, and spatial layout information. Through professional BIM modeling software, import architectural design drawings (including CAD drawings) and related documents to perform three-dimensional modeling of each building component. In the modeling process, according to building specifications and design requirements, accurately set the parameters of each component, such as the size and strength grade of beams and columns, the thickness and insulation performance of walls. At the same time, integrate sub-models of different disciplines (such as architecture, structure, water supply and drainage, and electricity) into a complete BIM model to achieve unified data management and interaction, and ensure the consistency and relevance of information from various disciplines.

[0010] The IoT sensor deployment module deploys various types of IoT sensors in key parts of the building according to the needs of building performance monitoring. Sensor types include but are not limited to temperature sensors, humidity sensors, pressure sensors, strain sensors, displacement sensors, and energy consumption sensors. When deploying temperature sensors, they are arranged in layers at different locations and heights indoors and outdoors according to the orientation, functional zoning, and heat transfer characteristics of the building to ensure that temperature field information can be accurately obtained. Humidity sensors are deployed in combination with moisture-prone areas in the building (such as basements and toilet areas) and humidity-sensitive functional spaces (such as computer rooms and archives). For strain and displacement sensors, they are installed in key stress-bearing parts of the structure (such as the nodes of beams and columns, and the middle of large-span structures) to monitor the deformation of the structure in real time. The sensor is connected to the data acquisition terminal through wired (such as RS485, Ethernet) or wireless (such as Zigbee, LoRa, Bluetooth) communication methods to ensure the stability and timeliness of data transmission.

[0011] The data acquisition and transmission module is responsible for collecting data obtained by IoT sensors and transmitting it to the data processing center. The module is equipped with a high-performance data acquisition terminal with multi-channel data acquisition capabilities, which can simultaneously receive data from different types of sensors. The acquisition terminal performs preliminary preprocessing on the sensor data, including signal amplification and filtering operations to improve data quality. During the data transmission process, a reliable communication protocol is adopted. For wired transmission, the TCP / IP protocol is followed; for wireless transmission, the corresponding wireless protocol stack is adopted according to the communication mode of the sensor. At the same time, in order to prevent data loss, a data caching mechanism and an error retransmission mechanism are set to ensure that the data is transmitted to the data processing center completely and accurately.

[0012] The data processing and analysis module processes and analyzes the collected data in the data processing center. First, the received data is format converted and normalized to conform to the unified data format standard. Then, the data analysis algorithm is used to analyze the data in real time. For energy consumption data, the time series analysis method is used to analyze the changing trend, peak and valley values ​​of energy consumption to identify abnormal energy consumption. For data related to structural safety (such as strain and displacement), the finite element analysis method is combined with the structural information in the BIM model to calculate the internal force and stress distribution of the structure and evaluate the safety of the structure. In addition, machine learning algorithms (such as cluster analysis and anomaly detection algorithms) are used to mine various types of data to discover potential patterns and anomalies in the data, providing a basis for building performance evaluation. In structural analysis, according to Hooke's law and stress-strain relationship, for linear elastic materials, the normal stress calculation formula in one-dimensional case is: ,in, is the normal stress, is the elastic modulus of the material, is the linear strain. In two-dimensional and three-dimensional cases, the stress-strain relationship is expressed in matrix form. For plane stress problems:

[0013] in, is the Poisson's ratio, is the shear modulus, It is shear strain. In actual building performance monitoring based on BIM and the Internet of Things, the stress of the structure is calculated through these formulas in combination with the strain data collected by the sensor, and then compared with the allowable stress of the material to evaluate the structural safety.

[0014] In building energy consumption monitoring, by establishing an ARMA model for historical energy consumption data, future energy consumption trends can be predicted and abnormal energy consumption changes can be identified. The specific formula is designed as follows: For time series data , the ARMA (p,q) model can be expressed as:

[0016] Where c is a constant term, p is the autoregressive order, is the autoregressive coefficient, q is the moving average order, is the moving average coefficient, is a white noise sequence.

[0017] The building performance assessment and early warning module evaluates building performance based on the results of data processing and analysis, and issues early warnings when abnormal situations occur. According to the pre-set building performance indicator system, a quantitative assessment is conducted on the thermal comfort, energy efficiency, and structural safety performance of the building. For example, based on indoor temperature and humidity data and the human thermal comfort model, assess whether the indoor thermal comfort meets the requirements; combine energy consumption data and building function types to assess whether the energy efficiency meets the standards. When the monitored data exceeds the normal threshold range, different levels of early warning information are sent to management personnel and maintenance personnel through SMS, email, and APP push according to the severity of the abnormality. At the same time, the abnormal location and related data are intuitively displayed in the BIM model, which is convenient for quick location and problem solving; In the building performance evaluation and early warning module, the thermal comfort, energy efficiency, structural safety performance and other aspects of the building are quantitatively evaluated according to the pre-set building performance index system. When evaluating thermal comfort, in addition to considering temperature and humidity factors, factors such as air velocity and radiation temperature are also considered comprehensively, and advanced thermal comfort evaluation models such as the Fanger thermal comfort equation are used to improve the accuracy of the evaluation. This equation is used to quantitatively evaluate indoor thermal comfort, which is an important basis for judging whether the building's thermal performance meets the standards. The specific design formula is as follows:

[0018] Among them, PMW represents the predicted average voting value, f represents the above complex functional relationship, M is the metabolic rate of the human body, W is the mechanical work done by the human body, and p a is the partial pressure of water vapor in air, t a is the indoor air temperature.

[0019] The user interaction and visualization module provides users with an interactive interface and visualization display functions. Through the web page or mobile APP, users can log in to the system to view building performance data, evaluation reports and warning information. In terms of visualization, the BIM model is combined with monitoring data to display the building performance status in a three-dimensional visualization. Users can view sensor data at different locations in the BIM model, and intuitively understand the distribution of building performance through color mapping and data annotation. At the same time, users are supported to operate the BIM model, such as rotating, zooming, and cutting, so as to observe the building and analyze data from different angles. Users can also set system parameters, adjust warning thresholds, and query historical data through the interactive interface.

[0020] Furthermore, when integrating different professional sub-models, the BIM model construction and integration module uses an intermediate file format (such as IFC format) for data exchange and integration to ensure lossless transmission and accurate fusion of information between sub-models.

[0021] Furthermore, the sensors in the IoT sensor deployment module adopt a low-power design and a built-in power management module, which can automatically adjust the power consumption mode according to the working status of the sensor, thereby extending the service life of the sensor and reducing maintenance costs.

[0022] Furthermore, when the data processing and analysis module uses a machine learning algorithm for anomaly detection, it adopts a deep autoencoder algorithm to construct a feature representation of the data by learning from normal data, and calculates the reconstruction error of the new data. When the reconstruction error exceeds a set threshold, it is determined to be abnormal data, thereby improving the accuracy of anomaly detection.

[0023] Furthermore, when evaluating the thermal comfort of a building, the building performance evaluation and early warning module not only considers temperature and humidity factors, but also comprehensively considers air velocity and radiation temperature factors, and adopts the advanced thermal comfort evaluation model of Fanger thermal comfort equation to improve the accuracy of the evaluation.

[0024] Furthermore, the user interaction and visualization module adopts virtual reality (VR) and augmented reality (AR) technologies in the mobile APP. Users can immersively view building performance data by wearing VR devices, or use AR technology to obtain real-time monitoring data and performance evaluation information of corresponding locations when viewing buildings on site, thereby enhancing user experience and the convenience of data interaction.

[0025] Furthermore, a building performance monitoring method based on BIM and Internet of Things technology includes the following steps: BIM model construction and integration steps, create and integrate the BIM model of the building, covering various professional information, to ensure the accuracy and consistency of the model.

[0026] The steps for deploying IoT sensors are to deploy a variety of sensors at key locations according to the building performance monitoring requirements and connect them to the collection terminal.

[0027] In the data collection and transmission step, sensor data is collected, pre-processed, and then transmitted to the data processing center through a reliable protocol.

[0028] Data processing and analysis steps: processing and analyzing the received data, including format conversion and algorithm analysis.

[0029] The building performance assessment and early warning steps evaluate the building performance based on the analysis results and issue early warnings when abnormalities occur.

[0030] The user interaction and visualization step provides users with an interactive interface and a visual display of building performance data.

[0031] Furthermore, in the BIM model construction and integration steps, a parametric modeling method is used for complex building components, and the component model is automatically generated by setting key parameters to improve modeling efficiency and model modifiability.

[0032] Furthermore, in the IoT sensor deployment step, the wireless communication frequency band of the sensor is adaptively adjusted according to the electromagnetic interference situation in the building environment, and the frequency band with the least interference is selected to ensure the reliability of data transmission.

[0033] Furthermore, in the data processing and analysis steps, when processing a large amount of data, distributed computing technology is used to split the data into multiple computing nodes for parallel processing to increase the processing speed.

[0034] Furthermore, in the building performance assessment and early warning step, trend analysis is regularly performed on the building performance assessment results to predict the changing trend of building performance, and corresponding measures are taken in advance for optimization and maintenance.

[0035] Furthermore, in the user interaction and visualization step, users are supported to customize the layout and display content of the visualization interface, and relevant data is displayed in a focused manner according to user needs, thereby improving user convenience.

[0036] Compared with the prior art, the present invention has the following beneficial effects: First, in terms of information integration, through the BIM model construction and integration module, the professional information of the building is integrated into a three-dimensional model, which facilitates the collaboration of different professionals and improves work efficiency and design and construction quality. For example, collision problems during construction can be avoided.

[0037] In terms of monitoring, the rational deployment of IoT sensors combined with data collection and transmission modules enables comprehensive and real-time monitoring of building performance. Whether it is structural safety, indoor environment or energy consumption, data can be accurately obtained and potential problems can be discovered in a timely manner, such as detecting small structural deformations or abnormal increases in energy consumption in advance.

[0038] The data processing and analysis module uses advanced algorithms to mine the relationship between data. Through comprehensive analysis of multiple data, the root cause of building performance problems can be accurately found, such as whether it is equipment failure or design defects that cause energy consumption problems, providing a basis for optimization.

[0039] The building performance assessment and early warning module can accurately assess building performance and issue early warnings in case of abnormalities. Early warnings at different levels allow managers to respond quickly and reduce losses. At the same time, the visualization and user interaction modules facilitate users to view and understand building performance data, enhance user experience, and allow users to feedback problems to promote continuous improvement of building performance. This series of functions ensures the safe, comfortable and efficient operation of the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic block diagram of a building performance monitoring system based on BIM and Internet of Things technology proposed in the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise" and "counterclockwise" indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0043] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0044] Reference Figure 1 :A building performance monitoring system based on BIM and Internet of Things technology, including: The BIM model construction and integration module is used to create a building information model (BIM), which accurately covers the building's geometric structure, material properties, and spatial layout information. Through professional BIM modeling software, import architectural design drawings (including CAD drawings) and related documents to perform three-dimensional modeling of each building component. In the modeling process, according to building specifications and design requirements, accurately set the parameters of each component, such as the size and strength grade of beams and columns, the thickness and insulation performance of walls. At the same time, integrate sub-models of different disciplines (such as architecture, structure, water supply and drainage, and electricity) into a complete BIM model to achieve unified data management and interaction, and ensure the consistency and relevance of information from various disciplines.

[0045] The IoT sensor deployment module deploys various types of IoT sensors in key parts of the building according to the needs of building performance monitoring. Sensor types include but are not limited to temperature sensors, humidity sensors, pressure sensors, strain sensors, displacement sensors, and energy consumption sensors. When deploying temperature sensors, they are arranged in layers at different locations and heights indoors and outdoors according to the orientation, functional zoning, and heat transfer characteristics of the building to ensure that temperature field information can be accurately obtained. Humidity sensors are deployed in combination with moisture-prone areas in the building (such as basements and toilet areas) and humidity-sensitive functional spaces (such as computer rooms and archives). For strain and displacement sensors, they are installed in key stress-bearing parts of the structure (such as the nodes of beams and columns, and the middle of large-span structures) to monitor the deformation of the structure in real time. The sensor is connected to the data acquisition terminal through wired (such as RS485, Ethernet) or wireless (such as Zigbee, LoRa, Bluetooth) communication methods to ensure the stability and timeliness of data transmission.

[0046] The data acquisition and transmission module is responsible for collecting data obtained by IoT sensors and transmitting it to the data processing center. The module is equipped with a high-performance data acquisition terminal with multi-channel data acquisition capabilities, which can simultaneously receive data from different types of sensors. The acquisition terminal performs preliminary preprocessing on the sensor data, including signal amplification and filtering operations to improve data quality. During the data transmission process, a reliable communication protocol is adopted. For wired transmission, the TCP / IP protocol is followed; for wireless transmission, the corresponding wireless protocol stack is adopted according to the communication mode of the sensor. At the same time, in order to prevent data loss, a data caching mechanism and an error retransmission mechanism are set to ensure that the data is transmitted to the data processing center completely and accurately.

[0047] The data processing and analysis module processes and analyzes the collected data in the data processing center. First, the received data is format converted and normalized to conform to the unified data format standard. Then, the data analysis algorithm is used to analyze the data in real time. For energy consumption data, the time series analysis method is used to analyze the changing trend, peak and valley values ​​of energy consumption to identify abnormal energy consumption. For data related to structural safety (such as strain and displacement), the finite element analysis method is combined with the structural information in the BIM model to calculate the internal force and stress distribution of the structure and evaluate the safety of the structure. In addition, machine learning algorithms (such as cluster analysis and anomaly detection algorithms) are used to mine various types of data to discover potential patterns and anomalies in the data, providing a basis for building performance evaluation. In structural analysis, according to Hooke's law and stress-strain relationship, for linear elastic materials, the normal stress calculation formula in one-dimensional case is: ,in, is the normal stress, is the elastic modulus of the material, is the linear strain. In two-dimensional and three-dimensional cases, the stress-strain relationship is expressed in matrix form. For plane stress problems:

[0048] in, is the Poisson's ratio, is the shear modulus, It is shear strain. In actual building performance monitoring based on BIM and the Internet of Things, the stress of the structure is calculated through these formulas in combination with the strain data collected by the sensor, and then compared with the allowable stress of the material to evaluate the structural safety.

[0049] In building energy consumption monitoring, by establishing an ARMA model for historical energy consumption data, future energy consumption trends can be predicted and abnormal energy consumption changes can be identified. The specific formula is designed as follows: For time series data , the ARMA (p,q) model can be expressed as:

[0050] Where c is a constant term, p is the autoregressive order, is the autoregressive coefficient, q is the moving average order, is the moving average coefficient, is a white noise sequence.

[0051] The building performance assessment and early warning module evaluates building performance based on the results of data processing and analysis, and issues early warnings when abnormal situations occur. According to the pre-set building performance indicator system, a quantitative assessment is conducted on the thermal comfort, energy efficiency, and structural safety performance of the building. For example, based on indoor temperature and humidity data and the human thermal comfort model, assess whether the indoor thermal comfort meets the requirements; combine energy consumption data and building function types to assess whether the energy efficiency meets the standards. When the monitored data exceeds the normal threshold range, different levels of early warning information are sent to management personnel and maintenance personnel through SMS, email, and APP push according to the severity of the abnormality. At the same time, the abnormal location and related data are intuitively displayed in the BIM model, which is convenient for quick location and problem solving; In the building performance evaluation and early warning module, the thermal comfort, energy efficiency, structural safety performance and other aspects of the building are quantitatively evaluated according to the pre-set building performance index system. When evaluating thermal comfort, in addition to considering temperature and humidity factors, factors such as air velocity and radiation temperature are also considered comprehensively, and advanced thermal comfort evaluation models such as the Fanger thermal comfort equation are used to improve the accuracy of the evaluation. This equation is used to quantitatively evaluate indoor thermal comfort, which is an important basis for judging whether the building's thermal performance meets the standards. The specific design formula is as follows:

[0052] Among them, PMW represents the predicted average voting value, f represents the above complex functional relationship, M is the metabolic rate of the human body, W is the mechanical work done by the human body, and p a is the partial pressure of water vapor in air, t a is the indoor air temperature.

[0053] The user interaction and visualization module provides users with an interactive interface and visualization display functions. Through the web page or mobile APP, users can log in to the system to view building performance data, evaluation reports and warning information. In terms of visualization, the BIM model is combined with monitoring data to display the building performance status in a three-dimensional visualization. Users can view sensor data at different locations in the BIM model, and intuitively understand the distribution of building performance through color mapping and data annotation. At the same time, users are supported to operate the BIM model, such as rotating, zooming, and cutting, so as to observe the building and analyze data from different angles. Users can also set system parameters, adjust warning thresholds, and query historical data through the interactive interface.

[0054] In the present invention, when integrating different professional sub-models, the BIM model construction and integration module adopts an intermediate file format (such as IFC format) for data exchange and integration, ensuring lossless transmission and accurate fusion of information between the sub-models.

[0055] In the present invention, the sensor in the IoT sensor deployment module adopts a low-power design and a built-in power management module, which can automatically adjust the power consumption mode according to the working state of the sensor, thereby extending the service life of the sensor and reducing maintenance costs.

[0056] In the present invention, when the data processing and analysis module uses a machine learning algorithm for anomaly detection, a deep autoencoder algorithm is used to construct a feature representation of the data by learning normal data, and reconstruction error calculation is performed on new data. When the reconstruction error exceeds a set threshold, it is determined to be abnormal data, thereby improving the accuracy of anomaly detection.

[0057] In the present invention, when evaluating the thermal comfort of a building, the building performance evaluation and early warning module not only considers the temperature and humidity factors, but also comprehensively considers the air velocity and radiation temperature factors, and adopts the advanced thermal comfort evaluation model of the Fanger thermal comfort equation to improve the accuracy of the evaluation.

[0058] In the present invention, the user interaction and visualization module adopts virtual reality (VR) and augmented reality (AR) technologies in the mobile APP. Users can immersively view building performance data by wearing VR devices, or use AR technology to obtain monitoring data and performance evaluation information of corresponding locations in real time when viewing buildings on site, thereby enhancing user experience and the convenience of data interaction.

[0059] In the present invention, a building performance monitoring method based on BIM and Internet of Things technology comprises the following steps: BIM model construction and integration steps, create and integrate the BIM model of the building, covering various professional information, to ensure the accuracy and consistency of the model.

[0060] The steps for deploying IoT sensors are to deploy a variety of sensors at key locations according to the building performance monitoring requirements and connect them to the collection terminal.

[0061] In the data collection and transmission step, sensor data is collected, pre-processed, and then transmitted to the data processing center through a reliable protocol.

[0062] Data processing and analysis steps: processing and analyzing the received data, including format conversion and algorithm analysis.

[0063] The building performance assessment and early warning steps evaluate the building performance based on the analysis results and issue early warnings when abnormalities occur.

[0064] The user interaction and visualization step provides users with an interactive interface and a visual display of building performance data.

[0065] In the present invention, in the BIM model construction and integration steps, a parametric modeling method is adopted for complex building components, and the component model is automatically generated by setting key parameters, thereby improving the modeling efficiency and the modifiability of the model.

[0066] In the present invention, in the IoT sensor deployment step, the wireless communication frequency band of the sensor is adaptively adjusted according to the electromagnetic interference situation in the building environment, and the frequency band with the least interference is selected to ensure the reliability of data transmission.

[0067] In the data processing and analysis steps of the present invention, considering that a large amount of data will be generated during the building performance monitoring process, the timely processing of this data is crucial for quickly obtaining building performance information. When a large amount of data needs to be processed, we use advanced distributed computing technology to improve processing efficiency. Specifically, the system will reasonably divide the data into multiple parts based on a specific algorithm, and these parts will be distributed to multiple computing nodes. Each computing node has independent computing capabilities, and they can process the allocated data fragments at the same time. For example, for different types of data such as structural safety monitoring data, energy consumption data, and environmental data, they can be segmented according to factors such as their data source, data format, or the building area to which the data corresponds. In the segmentation process, the correlation and independence between the data will be fully considered to ensure that the inherent logical relationship of the data will not be lost during parallel processing. Through this distributed computing technology, each computing node works in parallel, which greatly shortens the time required for data processing, thereby improving the speed of the entire data processing, so that the system can quickly provide accurate and timely data support for subsequent building performance evaluation and early warning steps.

[0068] In the building performance evaluation and early warning steps of the present invention, in order to ensure that the building is always in a good operating state, we have designed a mechanism for regularly performing trend analysis on the building performance evaluation results. This trend analysis is based on the long-term accumulated building performance evaluation data. The system will conduct in-depth analysis of the building performance evaluation results in previous time periods at predetermined time intervals, such as weekly, monthly or quarterly. During the analysis process, a variety of data analysis methods and mathematical models will be used to conduct trend studies on different performance indicators of the building, such as thermal comfort, energy efficiency, structural safety performance, etc. Taking energy efficiency as an example, the system will observe its changes in different seasons and different usage scenarios, analyze whether there is a trend of gradual increase or decrease, and whether this trend exceeds the normal fluctuation range. For structural safety performance, attention will be paid to the changing trends of stress and strain data in key parts of the structure to determine whether there are potential structural safety hazards. Through this comprehensive and detailed trend analysis, the system can accurately predict the changing trends of building performance. Based on these prediction results, managers can formulate corresponding measures in advance and carry out timely optimization and maintenance for possible performance degradation problems, such as abnormal increase in energy consumption or increased structural safety risks, so as to avoid further deterioration of the problem and ensure the stable operation of the building and the safety and comfort of users.

[0069] In the user interaction and visualization steps of the present invention, the personalized needs of different users for the display of building performance data are fully considered. The system is designed to support users to customize the layout and display content of the visualization interface, so as to improve the convenience of user use. Users can flexibly adjust the visualization interface according to their roles and focus. For example, for building managers, they may pay more attention to the overall performance profile of the building, abnormal alarm information, and energy consumption data comparison of each area. Then they can place these data modules in a prominent position on the visualization interface and adjust their size and display form to quickly obtain key information. For maintenance personnel, they may need more detailed equipment operation data and structural safety data, so these related data display areas can be enlarged and highlighted, while hiding some information that is not very important to them. For ordinary users, such as residents in the building, they may mainly care about indoor thermal comfort and environmental quality data. The system allows them to display these data on the interface in a concise and clear manner, such as through charts or simple numerical displays. Through this user-defined function, whether accessing the system through the web or mobile APP, users can easily focus on displaying relevant data according to their needs, thereby obtaining the required information more efficiently, improving the convenience and friendliness of the entire system during user use.

[0070] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A building performance monitoring system based on BIM and Internet of Things technology, characterized in that: include: BIM model construction and integration module is used to create the building information model BIM. Through BIM modeling software, architectural design drawings and related documents are imported to perform 3D modeling of each building component, and sub-models of different disciplines are integrated into a complete BIM model; IoT sensor deployment module: deploy various types of IoT sensors at key parts of the building according to the building performance monitoring requirements. When deploying temperature sensors, they are arranged in layers at different locations and heights indoors and outdoors according to the building's orientation, functional zoning, and heat transfer characteristics. The data acquisition and transmission module is responsible for collecting data obtained by IoT sensors and transmitting them to the data processing center, equipped with a data acquisition terminal to perform preliminary preprocessing on the sensor data; The data processing and analysis module processes and analyzes the collected data in the data processing center, converts the format of the received data and normalizes it. For energy consumption data, it uses time series analysis methods to analyze the changing trend, peak and valley values ​​of energy consumption and identify abnormal energy consumption. For data related to structural safety, the finite element analysis method is combined with the structural information in the BIM model to calculate the internal force and stress distribution of the structure, and the machine learning algorithms of cluster analysis and anomaly detection are used to mine various types of data; The building performance evaluation and early warning module evaluates the building performance based on the results of data processing and analysis, and issues early warnings when abnormal situations occur. When the monitored data exceeds the normal threshold range, different levels of early warning information are issued according to the severity of the abnormality, and the abnormal location and related data are displayed in the BIM model; The user interaction and visualization module provides users with an interactive interface and visualization functions, combines the BIM model with monitoring data, and displays the building performance status through three-dimensional visualization.

2. The building performance monitoring system based on BIM and Internet of Things technology according to claim 1 is characterized in that: The BIM model construction and integration module uses the intermediate file IFC format for data exchange and integration when integrating different professional sub-models.

3. The building performance monitoring system based on BIM and Internet of Things technology according to claim 1 is characterized in that: The sensors in the IoT sensor deployment module adopt a low-power design and a built-in power management module, which automatically adjusts the power consumption mode according to the working status of the sensor to extend the service life of the sensor.

4. The building performance monitoring system based on BIM and Internet of Things technology according to claim 1 is characterized in that: When the data processing and analysis module uses a machine learning algorithm for anomaly detection, it adopts a deep autoencoder algorithm to construct a feature representation of the data by learning normal data, calculate the reconstruction error of the new data, and determine it as abnormal data when the reconstruction error exceeds a set threshold.

5. The building performance monitoring system based on BIM and Internet of Things technology according to claim 1 is characterized in that: When evaluating the thermal comfort of a building, the building performance evaluation and early warning module not only considers temperature and humidity factors, but also comprehensively considers air velocity and radiation temperature factors, and adopts the advanced thermal comfort evaluation model of Fanger thermal comfort equation.

6. The building performance monitoring system based on BIM and Internet of Things technology according to claim 1 is characterized in that: The user interaction and visualization module adopts virtual reality and augmented reality technologies in the mobile APP. Users can immersively view building performance data by wearing VR devices, or use AR technology to obtain real-time monitoring data and performance evaluation information of corresponding locations when viewing buildings on site.

7. The building performance monitoring system based on BIM and Internet of Things technology according to any one of claims 1 to 6, characterized in that: The execution procedure of the system includes the following steps: BIM model construction and integration steps, creating and integrating the BIM model of the building, covering various professional information; IoT sensor deployment steps: deploy multiple sensors at key locations according to building performance monitoring requirements and connect them to collection terminals; Data collection and transmission steps, collect sensor data, and transmit it to the data processing center through a reliable protocol after preprocessing; Data processing and analysis steps: processing and analyzing received data, including format conversion and algorithm analysis; Building performance assessment and early warning steps: assess building performance based on analysis results and issue early warnings when abnormalities occur; The user interaction and visualization step provides users with an interactive interface and a visual display of building performance data.

8. The building performance monitoring system based on BIM and Internet of Things technology according to claim 7 is characterized in that: In the BIM model construction and integration steps, parametric modeling methods are used for complex building components to automatically generate component models by setting key parameters; In the IoT sensor deployment step, the wireless communication frequency band of the sensor is adaptively adjusted according to the electromagnetic interference in the building environment, and the frequency band with the least interference is selected; In the data processing and analysis steps, when processing large amounts of data, distributed computing technology is used to split the data into multiple computing nodes for parallel processing; In the building performance assessment and early warning step, the trend analysis of building performance assessment results is regularly conducted to predict the changing trend of building performance; In the user interaction and visualization step, users are supported to customize the layout and display content of the visualization interface, and relevant data is displayed in a focused manner according to user needs.

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