Building green construction whole process management method and system based on BIM technology

Abstract

The invention relates to the technical field of building management, and discloses a building green construction whole process management method and system based on a BIM technology, and the method comprises the following steps: data collection and integration: collecting multi-dimensional data of energy consumption, environment and equipment state of a building construction site through an arranged Internet of Things sensor network, data preprocessing and transmission are carried out through edge calculation; identification management is carried out on the building materials and equipment through RFID or two-dimensional codes; energy efficiency analysis and evaluation: performing real-time analysis on the energy efficiency and carbon emission of each construction link based on the collected data, and displaying the distribution condition of the energy efficiency and the carbon emission through a BIM model; and intelligent decision support and optimization: utilizing a machine learning algorithm to predict energy consumption and material consumption. Efficient resource allocation is realized through real-time monitoring and intelligent optimization; meanwhile, based on the BIM model and seamless data sharing in the operation and maintenance stage, the system realizes green management of the whole life cycle of the building, and supports sustainable development of the building industry.

Description

Technical Field

[0001] The present invention relates to the technical field of building management, and in particular to a whole-process management method and system for green construction of buildings based on BIM technology. Background Art

[0002] As global energy consumption and environmental pollution become increasingly serious, green construction and sustainable management in the construction industry have received widespread attention. High energy consumption and large amounts of carbon emissions during construction have become the main environmental burden of the construction industry, and promoting green management in the construction process has become a key direction for the development of the industry. At present, construction management technology based on building information modeling (BIM) has achieved the digitization and informatization of the construction process to a certain extent. The visualization of BIM models can help construction teams better coordinate and manage construction progress. However, existing technologies still have limitations in the comprehensive management of green construction, and it is difficult to improve construction energy efficiency and management response speed while meeting green construction standards.

[0003] Existing BIM technology applications are mainly concentrated in the construction design and progress management levels, helping construction teams to perform collision detection, resource allocation and construction coordination through three-dimensional models and data integration; most of these systems rely on manual data input and management, and lack real-time data collection and dynamic feedback capabilities; in addition, in terms of construction energy efficiency and carbon emission management, traditional BIM systems cannot provide accurate data support and analysis, and it is difficult to achieve real-time energy efficiency evaluation and carbon emission monitoring of the construction process. Although some green building evaluation standards provide a guiding framework for green construction, there is a lack of effective intelligent tools to dynamically optimize resource utilization and process selection. Therefore, it is difficult to ensure energy consumption control and continuous reduction of carbon emissions in actual applications. Summary of the invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a whole-process management method and system for green construction of buildings based on BIM technology, which solves the problems of energy efficiency improvement, carbon emission control and resource optimization in the construction process of buildings in the existing technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A whole-process management method for green construction of buildings based on BIM technology, comprising the following steps:

[0006] Data collection and integration: Collect multi-dimensional data on energy consumption, environment, and equipment status at the construction site through the deployed IoT sensor network, and perform data preprocessing and transmission through edge computing; identify and manage construction materials and equipment through RFID or QR codes;

[0007] Energy efficiency analysis and evaluation: Based on the collected data, the energy efficiency and carbon emissions of each construction link are analyzed in real time, and the distribution of energy efficiency and carbon emissions is displayed through the BIM model;

[0008] Intelligent decision support and optimization: Use machine learning algorithms to predict energy and material consumption, and use optimization algorithms to generate resource allocation and process selection solutions in the green construction process;

[0009] Visual monitoring and dynamic feedback: Display information on energy consumption and carbon emissions in the BIM model, and provide intelligent early warning and feedback mechanisms to ensure the realization of green goals during the construction process;

[0010] Post-operation and maintenance data sharing and feedback: Store and share energy efficiency and carbon emission data of the construction process in the cloud, and integrate the data with the operation and maintenance BIM model to achieve green management of the entire life cycle of the building.

[0011] Preferably, the data collection and integration step includes the following sub-steps:

[0012] Collect real-time data from the construction site through IoT sensors, including power consumption, temperature and humidity, air quality, and equipment status;

[0013] Use edge computing nodes at the data collection end to pre-process the data, including data cleaning, denoising, and compression;

[0014] Real-time synchronization between sensor data and BIM models is achieved through MQTT protocol and WebSocket protocol.

[0015] Preferably, the energy efficiency analysis and evaluation step includes:

[0016] The energy consumption per unit building area (EUI) is used as the energy efficiency evaluation indicator. The calculation formula of EUI is:

[0017]

[0018] Among them, E i represents the energy consumption of the ith link in the construction process, and A represents the building area;

[0019] The carbon emissions of each construction link are calculated based on the carbon emission factor library, and the carbon emission distribution is updated in real time in the BIM model.

[0020] Preferably, the energy efficiency analysis and evaluation step further includes:

[0021] Anomaly detection of energy consumption data during construction based on anomaly detection algorithms;

[0022] Identify energy-saving opportunities during construction through time series analysis and predictive algorithms, and generate energy-saving recommendations based on predicted energy consumption and carbon emission data.

[0023] Preferably, the intelligent decision support and optimization step includes the following sub-steps:

[0024] Use random forest or XGBoost algorithms to build energy consumption prediction models, with environmental parameters, construction progress, material type, and equipment power as input variables;

[0025] Based on a multi-objective optimization algorithm, with energy consumption, carbon emissions and costs as optimization targets, resource allocation and process selection suggestions are generated during the construction process.

[0026] Preferably, the multi-objective optimization algorithm is a genetic algorithm or a particle swarm algorithm, with minimization of energy consumption, minimization of carbon emissions and minimization of costs as optimization objective functions.

[0027] Preferably, the visual monitoring and dynamic feedback steps include:

[0028] The energy consumption, carbon emissions and construction progress data of the construction site are displayed in three-dimensional visualization in the BIM model;

[0029] Through the intelligent early warning system, when energy consumption or carbon emissions exceed the preset threshold, an alarm is automatically triggered and optimization adjustment suggestions are generated.

[0030] Preferably, the dynamic feedback mechanism includes:

[0031] Real-time detection of energy consumption and carbon emission data, and automatic feedback to the optimization module;

[0032] Adjust resource allocation and process selection during the construction process based on real-time feedback to ensure the dynamic realization of green construction goals.

[0033] Preferably, the later operation and maintenance data sharing and feedback steps include:

[0034] Build a data sharing platform in the cloud to store and manage data on energy efficiency, carbon emissions, and material consumption during the construction phase;

[0035] The energy efficiency data of the construction phase is integrated into the operation and maintenance BIM model through the data interface, providing historical data support for the green management of buildings in the operation and maintenance phase.

[0036] The whole process management system of green construction based on BIM technology includes: data collection and integration module, which is used to collect multi-dimensional data of the construction site and pre-process and standardize the data through edge computing nodes;

[0037] Energy efficiency analysis and evaluation module, which is used to evaluate the energy efficiency and carbon emissions of each construction link and update the analysis results to the BIM model in real time;

[0038] Intelligent decision support and optimization module, used to generate optimization suggestions for resource allocation and process selection based on collected data;

[0039] Visual monitoring and dynamic feedback module, used to display energy efficiency, carbon emissions and construction progress in the BIM model, and trigger warnings when data exceeds the standard;

[0040] The post-operation and maintenance data sharing and feedback module is used to connect the green management data of the construction phase during the operation and maintenance phase to achieve green management of the entire life cycle of the building.

[0041] The present invention provides a whole-process management method and system for green construction of buildings based on BIM technology. It has the following beneficial effects:

[0042] 1. The present invention realizes real-time monitoring of construction energy efficiency and carbon emissions through data collection and integration, energy efficiency analysis and evaluation modules. With the help of energy consumption indicators per unit building area and carbon emission factor library, the system can dynamically evaluate the energy efficiency performance of different construction stages, identify high energy consumption and high carbon emission links, and provide energy-saving suggestions in a timely manner. Compared with traditional methods, the system has significantly improved construction energy efficiency and significantly reduced carbon emissions, fully realizing the goal of green construction management.

[0043] 2. The present invention utilizes machine learning and multi-objective optimization algorithms in the intelligent decision support and optimization module to provide optimization solutions for resource allocation and process selection during the construction process. Through real-time monitoring and feedback mechanism of resource usage, the system can dynamically adjust resource allocation according to the progress of construction, thereby significantly improving resource utilization efficiency. At the same time, the intelligent early warning and feedback functions of the system greatly shorten the management response time, greatly improving the efficiency and accuracy of construction management.

[0044] 3. The present invention can seamlessly integrate the data of the construction phase into the building operation and maintenance phase through the later operation and maintenance data sharing and feedback module, and realize the long-term tracking and management of energy efficiency and carbon emission data. The cloud data sharing platform stores the energy efficiency and carbon emission data of the construction phase and integrates them with the operation and maintenance BIM model, providing historical data support and decision-making basis for the green management of the building throughout its life cycle. The system not only realizes green management in the construction phase, but also continues the green management benefits in the operation and maintenance phase, effectively supporting the sustainable development of the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of the method of the present invention;

[0046] Figure 2 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the specification 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.

[0048] Please see attached Figure 1 - Attachment Figure 2 The embodiment of the present invention provides a whole-process management method and system for green construction of buildings based on BIM technology, aiming to realize green management of the construction process. By combining building information model (BIM), Internet of Things (IoT), machine learning, data analysis and optimization algorithms, the system of the present invention can monitor the energy consumption and carbon emissions of the construction site in real time, provide intelligent decision support, and dynamically optimize the construction process through visual feedback and early warning mechanisms, ultimately realizing green management of the entire life cycle of the building.

[0049] 1. System architecture and principles

[0050] The core architecture of the system of the present invention includes the following five modules: data collection and integration module, energy efficiency analysis and evaluation module, intelligent decision support and optimization module, visual monitoring and dynamic feedback module, and post-operation and maintenance data sharing and feedback module. Through modular design, the system performs multi-dimensional data collection and analysis at various stages of construction, and realizes dynamic optimization of construction management in a data-driven manner.

[0051] Data collection and integration module: responsible for collecting real-time data on the construction site, including information on energy consumption, environmental status, equipment operation status, and material consumption. This module uses IoT device sensors and RFID tags to collect multi-dimensional data, and pre-processes the data through edge computing nodes to ensure real-time, accuracy, and low latency.

[0052] Energy efficiency analysis and evaluation module: Based on the collected construction data, the energy efficiency and carbon emissions of each construction link are evaluated in real time, the key indicators of energy consumption per unit building area (EUI) and carbon emissions are calculated, and abnormal points of energy consumption and carbon emissions are identified.

[0053] Intelligent decision support and optimization module: Use machine learning algorithms to predict future energy and material consumption, and generate optimal solutions for resource allocation and process selection through multi-objective optimization algorithms, ensuring that the construction process achieves optimal resource allocation while meeting green standards.

[0054] Visual monitoring and dynamic feedback module: The BIM model displays the data on energy efficiency, carbon emissions, and construction progress of the construction site in real time. Through the visual feedback mechanism and intelligent early warning system, resource allocation and process selection are dynamically adjusted to achieve optimization of the green construction process.

[0055] Post-operation and maintenance data sharing and feedback module: Build a cloud-based data sharing platform to store energy efficiency and carbon emission data during the construction phase, and integrate this data with the operation and maintenance BIM model to support the green management of buildings during the operation and maintenance phase, forming a green management closed loop for the entire life cycle of the building.

[0056] 2. Technical content and implementation details

[0057] 1. Data acquisition and integration module

[0058] The data acquisition and integration module mainly realizes the real-time acquisition, preprocessing and integration of multi-source data at the construction site, providing high-quality data support for the energy efficiency analysis and optimization of the system.

[0059] 1.1 IoT sensor network: Various sensors are deployed at the construction site, including power sensors, temperature and humidity sensors, air quality sensors, and equipment status sensors, to collect real-time energy consumption, environment, and equipment data.

[0060] For example, power consumption during construction can be monitored through power sensors, and the energy consumption of each construction link can be calculated. Temperature, humidity and air quality sensors can be used to monitor the construction environment in real time to ensure the timeliness of environmental data.

[0061] 1.2 RFID and QR code identification: Attach RFID or QR code tags to key materials and equipment to achieve full life cycle management of materials and equipment.

[0062] Each time the RFID or QR code is scanned, the material usage time and quantity information is recorded, and the usage status information of materials and equipment is provided to support subsequent material consumption and resource allocation analysis.

[0063] 1.3 Edge computing and data transmission: Introduce edge computing nodes at the data collection end to perform data preprocessing, including data cleaning, denoising and compression, to improve data transmission efficiency and accuracy.

[0064] Using the MQTT protocol and WebSocket protocol, the cleaned data is transmitted to the cloud database in real time, and the data is standardized through the ETL tool to meet the reading requirements of the BIM system.

[0065] 2. Energy efficiency analysis and evaluation module

[0066] The energy efficiency analysis and evaluation module conducts real-time analysis and evaluation of the energy efficiency and carbon emissions of each construction link based on construction data, providing a quantitative basis for green construction management.

[0067] 2.1 Energy efficiency assessment: Use the energy consumption per unit building area (EUI) indicator to evaluate the energy efficiency level of the construction process.

[0068] The EUI calculation formula is:

[0069]

[0070] Among them, E i It represents the energy consumption of the ith link in the construction process, and A represents the building area. The EUI value can reflect the efficiency of resource consumption in the construction process.

[0071] 2.2 Carbon emission assessment: Build a carbon emission factor library that covers the carbon emission coefficients of different materials and equipment. Calculate the carbon emissions during the construction process based on the material consumption and equipment usage time.

[0072] The formula for calculating carbon emissions is:

[0073] CO 2,i =Q i ×C i

[0074] Among them, Q i is the amount of material used, C i is the corresponding carbon emission coefficient.

[0075] 2.3 Anomaly detection and energy-saving analysis: Based on historical data, the machine learning isolation forest algorithm is used to build an anomaly detection model to identify construction links with abnormal energy consumption. Through time series analysis, energy-saving opportunities are identified and energy-saving suggestions are put forward.

[0076] 3. Intelligent decision support and optimization module

[0077] The intelligent decision support and optimization module uses machine learning and multi-objective optimization algorithms to provide intelligent optimization suggestions for resource allocation and process selection during the construction process.

[0078] 3.1 Energy consumption prediction model: Based on historical construction data and real-time on-site data, the energy consumption performance of each construction stage is predicted using random forest or XGBoost algorithms. Input variables include environmental parameters, construction progress, material type, and equipment power.

[0079] 3.2 Material consumption prediction model: Use LSTM neural network to predict the future demand for materials, optimize material procurement plan based on construction progress and current inventory, and ensure rational material supply.

[0080] 3.3 Multi-objective optimization: A multi-objective optimization model of minimizing energy consumption, carbon emissions and costs is constructed, and the genetic algorithm NSGA-II is used to optimize the construction resource allocation.

[0081] The objective function is defined as follows:

[0082] minf(x)=w1·EUI(x)+w2·CO2(x)+w3·Cost(x)

[0083] Among them, w1, w2, and w3 are weights, which respectively represent the importance of energy consumption, carbon emissions, and cost in the optimization objectives.

[0084] 3.4 Process selection optimization: Use the deep reinforcement learning DQN algorithm to optimize the selection of construction processes, adjust the process according to construction feedback, and achieve process optimization based on minimizing energy consumption and carbon emissions.

[0085] 4. Visual monitoring and dynamic feedback module

[0086] The visual monitoring and dynamic feedback module displays energy efficiency, carbon emissions and construction progress status in real time through the BIM platform, and provides an early warning and feedback mechanism.

[0087] 4.1 Data visualization: In the BIM model, energy efficiency, carbon emissions and construction progress data are displayed through 3D visualization technology. The energy efficiency indicators and carbon emission data of each construction area are updated in real time in the BIM model, making it easier for managers to understand resource usage.

[0088] 4.2 Trend chart display: Trend charts are integrated in the BIM interface, including energy consumption change curves, carbon emission accumulation and material consumption charts, to compare the energy efficiency performance of different construction stages through the timeline.

[0089] 4.3 Intelligent early warning system: Set early warning thresholds for energy consumption and carbon emissions. When real-time data exceeds the threshold, the system triggers an alarm, generates optimization suggestions, and prompts managers to adjust resource allocation and process selection in a timely manner.

[0090] 4.4 Dynamic feedback mechanism: Real-time monitoring of energy consumption and carbon emission data, feedback of exceeding standards to the optimization module, dynamic adjustment of construction strategies, and ensuring that the construction process always meets green construction standards.

[0091] 5. Post-operation and maintenance data sharing and feedback module

[0092] The post-operation and maintenance data sharing and feedback module builds a data sharing platform to achieve data connection between the construction and operation and maintenance stages, and supports green management of the entire life cycle of the building.

[0093] 5.1 Cloud data sharing platform: stores energy efficiency, carbon emissions and material consumption data during the construction process, and provides historical data support for green management during the operation and maintenance phase.

[0094] 5.2 Operation and maintenance BIM model integration: Import the energy efficiency benchmark and carbon emission records of the construction phase into the operation and maintenance BIM model to achieve energy efficiency monitoring and carbon emission management throughout the life cycle of the building.

[0095] 5.3 Data feedback mechanism: Feedback the data from the operation and maintenance phase to the design and construction teams to provide data support for the green design and construction strategies of future building projects.

[0096] Example 1: Green Construction Management of Residential Buildings

[0097] Project: 10-storey residential building construction project

[0098] Process parameters: construction area 5000 square meters, construction period 200 days

[0099] step

[0100] Data collection and integration:

[0101] Temperature and humidity sensors, air quality sensors and power sensors are deployed, with a sampling frequency of 5 minutes per time.

[0102] Use RFID to tag all building materials and major construction equipment to achieve real-time material tracking.

[0103] Data is cleaned and compressed through edge computing nodes, transmitted to the central database using the MQTT protocol, and integrated into the BIM model through ETL tools.

[0104] Energy efficiency analysis and evaluation:

[0105] The construction energy efficiency was evaluated based on energy consumption per unit building area (EU I). The calculation results showed that the initial stages with higher energy consumption were the foundation excavation stage and the concrete pouring stage.

[0106] Use the carbon emission factor library to calculate the carbon emissions of different materials and display them in the BIM model.

[0107] Intelligent decision support and optimization:

[0108] The future energy consumption was predicted by random forest algorithm, and in the basic stage, it was suggested to reduce nighttime construction to reduce energy consumption.

[0109] Use a multi-objective optimization algorithm to optimize concrete transportation and steel consumption with energy consumption, carbon emissions and cost as targets.

[0110] Visual monitoring and dynamic feedback:

[0111] Energy efficiency, carbon emissions and construction progress are displayed in real time in the BIM model. Early warnings are automatically triggered during construction peaks to remind managers to optimize energy use.

[0112] Adjust construction progress based on feedback to reduce energy consumption and carbon emissions during peak periods.

[0113] Post-operation and maintenance data sharing and feedback:

[0114] Import energy efficiency data from the construction phase into the operation and maintenance BIM model to support energy efficiency management and maintenance strategy optimization in the future operation and maintenance phase.

[0115] Example 2: Green Construction Management of Commercial Complex

[0116] Project: Commercial complex building project

[0117] Process parameters: construction area 20,000 square meters, construction period 400 days

[0118] step

[0119] Data collection and integration:

[0120] Air quality sensors, equipment status sensors and power sensors are deployed, with a sampling frequency of 10 minutes per time.

[0121] RFID tags are configured for major equipment (such as cranes, concrete pumps, etc.) to track the frequency of use and status of the equipment.

[0122] Data is standardized through edge computing nodes, and the WebSocket protocol is used to synchronize data with the BIM model.

[0123] Energy efficiency analysis and evaluation:

[0124] Construction energy efficiency was assessed using EUI and total carbon emissions. Initial analysis results showed that steel and cement consumption were the main sources of carbon emissions.

[0125] Focus on monitoring high energy consumption links during construction and display energy efficiency trend charts in the BIM model.

[0126] Intelligent decision support and optimization:

[0127] The LSTM prediction model is used to predict the material consumption at each construction stage, and the material inventory and transportation plan are optimized in combination with the multi-objective optimization algorithm.

[0128] During the optimization process, reduce steel usage, adjust equipment usage strategies, and reduce equipment operating time.

[0129] Visual monitoring and dynamic feedback:

[0130] The BIM model displays the energy consumption, carbon emissions and construction progress of the construction site in real time, and allows managers to understand the overall construction status through three-dimensional display.

[0131] Based on the feedback from the early warning system, adjust the process flow and resource allocation during high energy consumption stages.

[0132] Post-operation and maintenance data sharing and feedback:

[0133] Share construction energy efficiency and carbon emission data on the cloud platform to provide basic data for green management during the building operation phase.

[0134] Example 3: Green Construction Management of High-Rise Office Buildings

[0135] Project: 20-story office building construction project

[0136] Process parameters: construction area 10,000 square meters, construction period 300 days

[0137] step

[0138] Data collection and integration:

[0139] Use temperature and humidity sensors, air quality sensors, and RFID tags to achieve environmental monitoring and material tracking at the construction site.

[0140] The edge computing node collects and cleans data every 5 minutes and transmits it to the central database via the WebSocket protocol.

[0141] After standardized processing, the data is integrated into the BIM model to achieve real-time updating of construction data.

[0142] Energy efficiency analysis and evaluation:

[0143] Carbon emissions from each construction phase were evaluated based on the energy efficiency index EUI and the carbon emission factor library. The results showed that carbon emissions from formwork construction and concrete construction were relatively high.

[0144] Analyze carbon emission trends, identify equipment with abnormal energy consumption through anomaly detection algorithms, and improve construction efficiency.

[0145] Intelligent decision support and optimization:

[0146] The random forest algorithm is used to predict future energy demand, and the frequency of use of construction equipment is adjusted through a multi-objective optimization model to reduce energy consumption.

[0147] Dynamically optimize steel transportation and usage plans to minimize costs by reducing material waste.

[0148] Visual monitoring and dynamic feedback:

[0149] The BIM model displays the energy consumption, carbon emissions and progress of the construction site, and presents the efficiency of resource use during the construction process through trend charts.

[0150] When the system detects that energy consumption exceeds the standard, it automatically generates adjustment suggestions and triggers an early warning for managers.

[0151] Post-operation and maintenance data sharing and feedback:

[0152] Import the energy efficiency data of the construction phase into the operation and maintenance BIM model to achieve energy efficiency optimization and equipment maintenance strategy adjustment in the future operation and maintenance phase.

[0153] Comparative Example

[0154] The following is a comparative example corresponding to the above-mentioned embodiment, showing the situation of traditional green construction management without using the inventive system.

[0155] Comparative Example 1: Green Construction Management of Traditional Residential Buildings

[0156] Project: 10-storey residential building construction project

[0157] Method: Manually record construction data and energy consumption information, without real-time data feedback mechanism

[0158] step

[0159] Data collection: Material usage and energy consumption data are recorded manually on a regular basis, which lacks real-time performance and the data lags behind the construction progress.

[0160] Energy efficiency analysis: Total energy consumption is calculated based on historical data. It is impossible to conduct phased energy efficiency evaluation and there is no real-time carbon emission monitoring.

[0161] Decision support: Construction strategies mainly rely on the experience of managers and lack data-based intelligent decision support.

[0162] Visual monitoring: It is impossible to display real-time data in the BIM model, and managers rely on manual reports, which is inefficient.

[0163] Operation and maintenance data: Construction data is scattered, making it impossible to achieve effective energy efficiency management and data sharing during the operation and maintenance stage.

[0164] Comparative Example 2: Green Construction Management of Traditional Commercial Complexes

[0165] Project: Commercial complex building project

[0166] Method: Construction management through traditional monitoring system, without BIM real-time integration

[0167] step

[0168] Data collection: Manually collect construction site data and use traditional sensors to monitor environmental data, with low data synchronization frequency.

[0169] Energy efficiency analysis: Regular manual calculation of total energy consumption makes it impossible to analyze the energy efficiency performance of each stage in real time.

[0170] Decision support: Relying on manual judgment on material usage and equipment arrangement makes it difficult to optimize resource allocation.

[0171] Visual monitoring: Monitoring is limited to traditional two-dimensional data display and fails to achieve three-dimensional visualization in combination with BIM models.

[0172] Operation and maintenance data: Construction data lacks standardization, and it is difficult to obtain accurate historical energy efficiency data during the operation and maintenance stage.

[0173] Comparative Example 3: Green Construction Management of Traditional High-Rise Office Buildings

[0174] Project: 20-story office building construction project

[0175] Method: Using traditional construction management system for green management

[0176] step

[0177] Data collection: Manually record equipment energy consumption and material consumption, resulting in low data collection efficiency and poor timeliness.

[0178] Energy efficiency analysis: Manual analysis of energy efficiency based on historical data cannot track energy efficiency changes during the construction process in real time.

[0179] Decision support: Decisions are based on construction experience, lack of intelligent optimization strategies, and unoptimized use of equipment and materials.

[0180] Visual monitoring: Traditional management systems cannot achieve real-time visual display of BIM models, and managers lack on-site intuitive monitoring.

[0181] Operation and maintenance data: Construction data is not managed in a unified manner and is difficult to share during the operation and maintenance phase.

[0182] Comparative experiment

[0183] In order to evaluate the effect of the present invention, Example 1 and Comparative Example 1 were selected for comparative experiments to compare the differences in construction energy efficiency, carbon emissions and management efficiency when using the management system and the traditional method.

[0184] Experimental conditions

[0185] Project: 10-storey residential building construction project

[0186] Implementation period: 200 days

[0187] Evaluation indicators: total energy consumption (kWh), total carbon emissions (tons), resource utilization efficiency (%), management response time (hours)

[0188] Experimental data table:

[0189]

[0190] According to the data table, energy consumption is reduced: Example 1 saves about 11.1% of energy consumption compared with Comparative Example 1, thanks to real-time energy efficiency analysis and intelligent optimization; carbon emissions are reduced: the carbon emissions of Example 1 are reduced by 16.7% compared with Comparative Example 1, mainly because the system reduces the use of high-carbon materials and the duration of high-energy consumption links during the construction process; resource utilization efficiency is improved: the method of the present invention achieves 92% resource utilization efficiency, thanks to the optimized configuration of the intelligent decision support module; management response speed is improved: in Example 1, since the system has real-time monitoring and dynamic feedback functions, the management response time is shortened to 1 hour, while Comparative Example 1 requires manual analysis and the response time is as long as 12 hours. Therefore, compared with traditional methods, the "full-process management method and system for green construction of buildings based on BIM technology" of the present invention significantly improves the energy efficiency, carbon emission management and resource utilization efficiency of the construction process, and at the same time has a significant improvement in the management response speed, which verifies the significant advantages of the invention in green construction management.

[0191] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The whole process management method of green construction based on BIM technology is characterized by: The following steps are involved: Data collection and integration: Collect multi-dimensional data on energy consumption, environment, and equipment status at the construction site through the deployed IoT sensor network, and perform data preprocessing and transmission through edge computing; identify and manage construction materials and equipment through RFID or QR codes; Energy efficiency analysis and evaluation: Based on the collected data, the energy efficiency and carbon emissions of each construction link are analyzed in real time, and the distribution of energy efficiency and carbon emissions is displayed through the BIM model; Intelligent decision support and optimization: Use machine learning algorithms to predict energy and material consumption, and use optimization algorithms to generate resource allocation and process selection solutions in the green construction process; Visual monitoring and dynamic feedback: Display information on energy consumption and carbon emissions in the BIM model, and provide intelligent early warning and feedback mechanisms to ensure the realization of green goals during the construction process; Post-operation and maintenance data sharing and feedback: Store and share energy efficiency and carbon emission data of the construction process in the cloud, and integrate the data with the operation and maintenance BIM model to achieve green management of the entire life cycle of the building.

2. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The data collection and integration step includes the following sub-steps: Collect real-time data from the construction site through IoT sensors, including power consumption, temperature and humidity, air quality, and equipment status; Use edge computing nodes at the data collection end to pre-process the data, including data cleaning, denoising, and compression; Real-time synchronization between sensor data and BIM models is achieved through MQTT protocol and WebSocket protocol.

3. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The energy efficiency analysis and evaluation steps include: The energy consumption per unit building area (EUI) is used as the energy efficiency evaluation indicator. The calculation formula of EUI is: Among them, E i represents the energy consumption of the ith link in the construction process, and A represents the building area; The carbon emissions of each construction link are calculated based on the carbon emission factor library, and the carbon emission distribution is updated in real time in the BIM model.

4. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The energy efficiency analysis and assessment steps also include: Anomaly detection of energy consumption data during construction based on anomaly detection algorithms; Identify energy-saving opportunities during construction through time series analysis and predictive algorithms, and generate energy-saving recommendations based on predicted energy consumption and carbon emission data.

5. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The intelligent decision support and optimization step includes the following sub-steps: Use random forest or XGBoost algorithms to build energy consumption prediction models, with environmental parameters, construction progress, material type, and equipment power as input variables; Based on a multi-objective optimization algorithm, with energy consumption, carbon emissions and costs as optimization targets, resource allocation and process selection suggestions are generated during the construction process.

6. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The multi-objective optimization algorithm is a genetic algorithm or a particle swarm algorithm, with minimization of energy consumption, minimization of carbon emissions and minimization of costs as optimization objective functions.

7. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: Visual monitoring and dynamic feedback steps include: The energy consumption, carbon emissions and construction progress data of the construction site are displayed in three-dimensional visualization in the BIM model; Through the intelligent early warning system, when energy consumption or carbon emissions exceed the preset threshold, an alarm is automatically triggered and optimization adjustment suggestions are generated.

8. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: Dynamic feedback mechanisms include: Real-time detection of energy consumption and carbon emission data, and automatic feedback to the optimization module; Adjust resource allocation and process selection during the construction process based on real-time feedback to ensure the dynamic realization of green construction goals.

9. The whole process management method of building green construction based on BIM technology according to claim 1 is characterized in that: The subsequent operation and maintenance data sharing and feedback steps include: Build a data sharing platform in the cloud to store and manage data on energy efficiency, carbon emissions, and material consumption during the construction phase; The energy efficiency data of the construction phase is integrated into the operation and maintenance BIM model through the data interface, providing historical data support for the green management of buildings in the operation and maintenance phase.

10. A whole-process management system for green construction based on BIM technology, according to the whole-process management method for green construction based on BIM technology according to any one of claims 1 to 9, characterized in that: include: Data collection and integration module, which is used to collect multi-dimensional data from the construction site and pre-process and standardize the data through edge computing nodes; Energy efficiency analysis and evaluation module, which is used to evaluate the energy efficiency and carbon emissions of each construction link and update the analysis results to the BIM model in real time; Intelligent decision support and optimization module, used to generate optimization suggestions for resource allocation and process selection based on collected data; Visual monitoring and dynamic feedback module, used to display energy efficiency, carbon emissions and construction progress in the BIM model, and trigger warnings when data exceeds the standard; The post-operation and maintenance data sharing and feedback module is used to connect the green management data of the construction phase during the operation and maintenance phase to achieve green management of the entire life cycle of the building.

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