Green construction informatization management method and system, terminal and medium

Abstract

The invention provides a green construction informatization management method and system, a terminal and a medium, and relates to the technical field of constructional engineering informatization. According to the green construction informatization management method and system, the terminal and the medium, a construction environment monitoring initial model, a resource consumption evaluation initial model and a construction behavior analysis initial model are constructed at a cloud end, and the construction environment monitoring model, the resource consumption evaluation model and the construction behavior analysis model are obtained through parameter optimization. According to the environment-friendly construction informatization management method and system, the terminal and the medium, data processing and analysis are carried out on the edge computing device, dependence on the cloud is reduced, the real-time performance and reliability of data processing are improved, the data circulation and analysis efficiency is remarkably improved through a multi-level cache queue and a parallel processing mechanism, and the environment-friendly construction informatization management method and system, the terminal and the medium are suitable for being popularized and applied. Therefore, the overall efficiency of green construction management is enhanced.

Description

Technical Field

[0001] This invention relates to the field of information technology in building engineering, specifically to a green construction information management method, system, terminal, and medium. Background Technology

[0002] With rapid socio-economic development and accelerated urbanization, the construction industry faces challenges such as resource consumption and environmental pollution while driving economic growth. Green construction, as a sustainable development concept, aims to maximize resource conservation and minimize negative environmental impacts through scientific management and technological advancements.

[0003] However, in actual construction processes, the implementation of green construction is often constrained by outdated management methods, poor information transmission, and insufficient data integration capabilities. Existing construction management models rely heavily on manual recording and traditional information technology tools, making it difficult to achieve real-time monitoring, dynamic analysis, and efficient collaboration throughout the entire construction process.

[0004] Furthermore, existing technologies lack flexibility and intelligent support when dealing with complex construction scenarios, leading to resource waste, low construction efficiency, and difficulty in effectively controlling environmental impact. Therefore, there is an urgent need for a technological solution that can integrate all elements of green construction and achieve information-based management to improve the scientific and refined level of construction management and provide strong support for the sustainable development of the construction industry. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a green construction information management method, system, terminal, and medium, which solves the problems existing in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a green construction information management method, comprising... Initial models for construction environment monitoring, resource consumption assessment, and construction behavior analysis are constructed in the cloud, and the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are obtained through parameter optimization. The construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are deployed to local edge computing devices; At the edge computing device: Real-time collection of environmental data, resource usage data, and construction worker behavior data from the construction site; The environmental data is input into the construction environment monitoring model to conduct an environmental status assessment and generate an environmental status assessment result. The resource usage data is input into the resource consumption assessment model to perform resource utilization efficiency analysis and generate resource utilization efficiency analysis results. The construction workers' behavior data is input into the construction behavior analysis model for behavior compliance detection, and behavior compliance detection results are generated. A green construction evaluation report is generated by comprehensively scoring the environmental status assessment results, resource utilization efficiency analysis results, and behavioral compliance test results. Among them, environmental data, resource usage data, construction worker behavior data, and the output results of each model are all stored and scheduled using a multi-level cache queue.

[0007] Preferably, the input data of the initial model for construction environment monitoring includes temperature, humidity, noise and dust concentration data, and the output is an environmental status assessment result; the input data of the initial model for resource consumption assessment includes electricity consumption, water consumption and material consumption data, and the output is a resource utilization efficiency analysis result; the input data of the initial model for construction behavior analysis includes construction personnel action data, and the output is a behavior compliance detection result.

[0008] Preferably, the multi-level cache queue includes a first-level cache, a second-level cache, and a third-level cache; the first-level cache is used to temporarily store the latest collected data, the second-level cache is used to store the data after preliminary processing, and the third-level cache is used to store historical data for a long time.

[0009] Preferably, the environmental state assessment process includes data preprocessing, feature extraction, and model inference; the data preprocessing includes denoising and normalization operations, the feature extraction uses principal component analysis algorithm, and the model inference is based on deep learning algorithm.

[0010] Preferably, the resource utilization efficiency analysis process includes resource consumption pattern recognition and regression analysis; the regression analysis uses a linear regression algorithm, and the output is a resource utilization efficiency score.

[0011] Preferably, a green construction information management system includes a data acquisition module, a data processing module, a model deployment module, and a report generation module; The data acquisition module is used to acquire environmental data, resource usage data, and construction worker behavior data from the sensor network and management system. The data processing module is used for preprocessing, feature extraction, and storage scheduling of the collected data; The model deployment module is used to deploy the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model trained in the cloud to edge computing devices; The report generation module is used to generate a green construction evaluation report based on the model output results.

[0012] Preferably, the data acquisition module acquires data through temperature and humidity sensors, noise sensors, dust sensors, electricity meters, water meters, material management systems, cameras, and wearable devices.

[0013] Preferably, a green construction information management terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.

[0014] A green construction information management medium, on which a computer program is stored, which, when executed by a processor, implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.

[0015] This invention provides a method, system, terminal, and medium for green construction information management. It has the following beneficial effects: This invention reduces reliance on the cloud by performing data processing and analysis on edge computing devices, thereby improving the real-time performance and reliability of data processing. The green construction information management method, system, terminal, and media provided by this invention significantly improve data flow and analysis efficiency through multi-level caching queues and parallel processing mechanisms, thus enhancing the overall effectiveness of green construction management. The green construction information management method, system, terminal, and media provided by this invention, combined with environmental monitoring, resource assessment, and behavior analysis technologies, realize intelligent management of the entire green construction process and are applicable to various complex construction scenarios. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: This invention provides a method, system, terminal, and medium for green construction information management. In practical application scenarios, this invention aims to achieve comprehensive monitoring and analysis of the construction site environment, resource consumption, and personnel behavior through the collaborative work of edge computing devices and the cloud, thereby generating a scientific and reasonable green construction evaluation report and providing intelligent support for green construction management.

[0018] First, initial models for construction environment monitoring, resource consumption assessment, and construction behavior analysis are built in the cloud, and their parameters are optimized to obtain the final models. The cloud serves as the core platform for model training, responsible for collecting historical data and inputting it into the initial models for training. For example, the initial model for construction environment monitoring receives input data including environmental parameters such as temperature, humidity, noise, and dust concentration at the construction site, and outputs environmental status assessment results. This model employs a deep learning algorithm, with the specific mathematical formula: Y_env = f(X_env; θ_env), where X_env is the environmental data vector, θ_env is the model parameter, and f represents a nonlinear mapping function. θ_env is optimized using gradient descent to ensure the model accurately predicts environmental status. Similarly, the initial models for resource consumption assessment and construction behavior analysis are trained on resource usage data and construction worker behavior data, respectively, with mathematical expressions Y_res = g(X_res; θ_res) and Y_beh = h(X_beh; θ_beh), where g and h are the mapping functions of their respective models, and θ_res and θ_beh are the corresponding model parameters. After multiple rounds of iterative optimization, these models were deployed to local edge computing devices for real-time processing at the construction site.

[0019] At the edge computing devices, real-time collection of environmental data, resource usage data, and worker behavior data from the construction site forms the foundation for the entire system's operation. Edge computing devices acquire various types of data through sensor networks. For example, environmental data is collected by temperature and humidity sensors, noise sensors, and dust sensors; resource usage data is extracted from electricity meters, water meters, and material management systems; and worker behavior data is recorded through cameras and wearable devices. All data is timestamped and stored in a multi-level cache queue. The multi-level cache queue has three levels: the first level temporarily stores the most recently collected data, the second level stores data that has undergone preliminary processing, and the third level stores historical data long-term. This design ensures efficient data flow and scheduling, preventing system performance degradation due to excessive data volume.

[0020] In edge computing devices, environmental data is input into a construction environment monitoring model for environmental status assessment. The environmental status assessment process includes three stages: data preprocessing, feature extraction, and model inference. The data preprocessing stage denoises and normalizes the raw data to improve data quality. The feature extraction stage uses Principal Component Analysis (PCA) to extract key features from the environmental data; the mathematical formula is Z=AX, where A is the projection matrix, X is the input data matrix, and Z is the dimensionality-reduced feature vector. Finally, the model inference stage inputs the extracted features into the construction environment monitoring model to generate the environmental status assessment results. For example, when the dust concentration exceeds a set threshold, the system will issue a warning signal to remind construction personnel to take appropriate measures.

[0021] Meanwhile, resource usage data is input into a resource consumption assessment model for resource utilization efficiency analysis. The resource utilization efficiency analysis process is similar to environmental status assessment, but its focus is on identifying and optimizing resource consumption patterns. For example, by analyzing electricity meter data, peak electricity consumption periods can be identified, and adjustments to construction plans can be suggested to reduce energy consumption. The resource consumption assessment model uses a regression analysis algorithm, with the mathematical formula E_res=β_0+β_1·X_res1+β_2·X_res2+...+β_n·X_resn, where E_res is the resource utilization efficiency score, X_res1 to X_resn are the resource usage data for each item, and β_0 to β_n are the regression coefficients. By continuously updating the regression coefficients, the model can more accurately reflect the resource utilization status.

[0022] Construction worker behavior data is input into a construction behavior analysis model for compliance detection. The compliance detection process includes two steps: behavior recognition and rule matching. The behavior recognition stage uses computer vision technology to analyze video data and extract the movement features of construction workers. The rule matching stage compares the extracted movement features with preset behavioral standards to determine compliance. For example, when a construction worker is detected not wearing a safety helmet, the system immediately generates a violation record and notifies management. The construction behavior analysis model uses a Support Vector Machine (SVM) algorithm, with the mathematical formula f(x) = sign(w·x + b), where w is the weight vector, b is the bias term, x is the input feature vector, and sign is the sign function. By optimizing w and b, the model can accurately identify various behavioral patterns.

[0023] After completing environmental status assessment, resource utilization efficiency analysis, and behavioral compliance testing, the system performs a comprehensive scoring based on the output results of each model, generating a green construction evaluation report. The comprehensive score uses a weighted average method, with the mathematical formula S = w_env·S_env + w_res·S_res + w_beh·S_beh, where S is the comprehensive score, S_env, S_res, and S_beh are the environmental status assessment score, resource utilization efficiency score, and behavioral compliance score, respectively, and w_env, w_res, and w_beh are the corresponding weighting coefficients. The weighting coefficients need to be adjusted according to the actual construction scenario; for example, in high-pollution-risk areas, the value of w_env should be appropriately increased. The final green construction evaluation report includes each score and corresponding improvement suggestions, providing a basis for construction management decisions.

[0024] Furthermore, this invention also provides a green construction information management system, comprising the following modules: a data acquisition module, a data processing module, a model deployment module, and a report generation module. The data acquisition module is responsible for acquiring raw data from sensor networks and management systems; the data processing module is responsible for preprocessing, feature extraction, and storage scheduling of the data; the model deployment module is responsible for deploying cloud-trained models to edge computing devices; and the report generation module is responsible for generating green construction evaluation reports based on the model output results. The modules interact with each other via high-speed communication interfaces to ensure efficient system operation.

[0025] In practical applications, this invention is suitable for various complex construction scenarios. For example, in large construction sites, the system can promptly identify and resolve dust pollution problems through real-time monitoring of environmental data; optimize energy and material allocation through analysis of resource usage data; and improve construction safety and standardization by monitoring the behavior of construction workers. Furthermore, the system can be integrated with existing construction management systems to form a complete information management platform, further enhancing the level of intelligence in construction management.

[0026] In summary, this invention reduces reliance on the cloud and improves the real-time performance and reliability of data processing by performing data processing and analysis on edge computing devices; it significantly improves data flow and analysis efficiency through multi-level caching queues and parallel processing mechanisms; and it achieves intelligent management of the entire green construction process by combining environmental monitoring, resource assessment, and behavioral analysis technologies. These features give this invention broad application prospects and significant practical value.

[0027] Example 2: This invention provides a green construction information management method, including... Initial models for construction environment monitoring, resource consumption assessment, and construction behavior analysis are constructed in the cloud, and the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are obtained through parameter optimization. The construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are deployed to local edge computing devices; At the edge computing device: Real-time collection of environmental data, resource usage data, and construction worker behavior data from the construction site; The environmental data is input into the construction environment monitoring model to conduct an environmental status assessment and generate an environmental status assessment result. The resource usage data is input into the resource consumption assessment model to perform resource utilization efficiency analysis and generate resource utilization efficiency analysis results. The construction workers' behavior data is input into the construction behavior analysis model for behavior compliance detection, and behavior compliance detection results are generated. A green construction evaluation report is generated by comprehensively scoring the environmental status assessment results, resource utilization efficiency analysis results, and behavioral compliance test results. Among them, environmental data, resource usage data, construction worker behavior data, and the output results of each model are all stored and scheduled using a multi-level cache queue.

[0028] The input data for the initial model of construction environment monitoring includes temperature, humidity, noise, and dust concentration data, and the output is the environmental status assessment result; the input data for the initial model of resource consumption assessment includes electricity consumption, water consumption, and material consumption data, and the output is the resource utilization efficiency analysis result; the input data for the initial model of construction behavior analysis includes construction personnel action data, and the output is the behavior compliance detection result.

[0029] The multi-level cache queue includes a first-level cache, a second-level cache, and a third-level cache; the first-level cache is used to temporarily store the latest collected data, the second-level cache is used to store data that has undergone preliminary processing, and the third-level cache is used to store historical data for a long period of time.

[0030] The environmental state assessment process includes data preprocessing, feature extraction, and model inference; the data preprocessing includes denoising and normalization operations; the feature extraction uses principal component analysis algorithm; and the model inference is based on deep learning algorithm.

[0031] The resource utilization efficiency analysis process includes resource consumption pattern identification and regression analysis; the regression analysis uses a linear regression algorithm, and the output is a resource utilization efficiency score.

[0032] A green construction information management system includes a data acquisition module, a data processing module, a model deployment module, and a report generation module; The data acquisition module is used to acquire environmental data, resource usage data, and construction worker behavior data from the sensor network and management system. The data processing module is used for preprocessing, feature extraction, and storage scheduling of the collected data; The model deployment module is used to deploy the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model trained in the cloud to edge computing devices; The report generation module is used to generate a green construction evaluation report based on the model output results.

[0033] The data acquisition module obtains data through temperature and humidity sensors, noise sensors, dust sensors, electricity meters, water meters, a material management system, cameras, and wearable devices.

[0034] A green construction information management terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.

[0035] A green construction information management medium, on which a computer program is stored, which, when executed by a processor, implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A green construction information management method, characterized in that, include Initial models for construction environment monitoring, resource consumption assessment, and construction behavior analysis are constructed in the cloud, and the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are obtained through parameter optimization. The construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model are deployed to local edge computing devices; At the edge computing device: Real-time collection of environmental data, resource usage data, and construction worker behavior data from the construction site; The environmental data is input into the construction environment monitoring model to conduct an environmental status assessment and generate an environmental status assessment result. The resource usage data is input into the resource consumption assessment model to perform resource utilization efficiency analysis and generate resource utilization efficiency analysis results. The construction workers' behavior data is input into the construction behavior analysis model for behavior compliance detection, and behavior compliance detection results are generated. A green construction evaluation report is generated by comprehensively scoring the environmental status assessment results, resource utilization efficiency analysis results, and behavioral compliance test results. Among them, environmental data, resource usage data, construction worker behavior data, and the output results of each model are all stored and scheduled using a multi-level cache queue.

2. The green construction information management method according to claim 1, characterized in that: The input data for the initial model of construction environment monitoring includes temperature, humidity, noise, and dust concentration data, and the output is the environmental status assessment result; the input data for the initial model of resource consumption assessment includes electricity consumption, water consumption, and material consumption data, and the output is the resource utilization efficiency analysis result; the input data for the initial model of construction behavior analysis includes construction personnel action data, and the output is the behavior compliance detection result.

3. The green construction information management method according to claim 1, characterized in that: The multi-level cache queue includes a first-level cache, a second-level cache, and a third-level cache; the first-level cache is used to temporarily store the latest collected data, the second-level cache is used to store data that has undergone preliminary processing, and the third-level cache is used to store historical data for a long period of time.

4. The green construction information management method according to claim 1, characterized in that: The environmental state assessment process includes data preprocessing, feature extraction, and model inference; the data preprocessing includes denoising and normalization operations; the feature extraction uses principal component analysis algorithm; and the model inference is based on deep learning algorithm.

5. The green construction information management method according to claim 1, characterized in that: The resource utilization efficiency analysis process includes resource consumption pattern identification and regression analysis; the regression analysis uses a linear regression algorithm, and the output is a resource utilization efficiency score.

6. A green construction information management system, characterized in that, It includes a data acquisition module, a data processing module, a model deployment module, and a report generation module; The data acquisition module is used to acquire environmental data, resource usage data, and construction worker behavior data from the sensor network and management system. The data processing module is used for preprocessing, feature extraction, and storage scheduling of the collected data; The model deployment module is used to deploy the construction environment monitoring model, resource consumption assessment model, and construction behavior analysis model trained in the cloud to edge computing devices; The report generation module is used to generate a green construction evaluation report based on the model output results.

7. The green construction information management system according to claim 6, characterized in that: The data acquisition module obtains data through temperature and humidity sensors, noise sensors, dust sensors, electricity meters, water meters, a material management system, cameras, and wearable devices.

8. A green construction information management terminal, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the program, it implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.

9. A green construction information management medium, on which a computer program is stored, characterized in that, When executed by a processor, the program implements the method of any one of claims 1 to 5, or runs the system of claim 6 or 7.