Rapid decision-making platform and method for low-carbon construction technical scheme of constructional engineering

Abstract

The invention discloses a building engineering low-carbon construction technical scheme rapid decision platform and method, and the platform comprises a collection device, a cloud device and a terminal device, the collection device is in data interaction with the cloud device, and is used for collecting basic information of a project and various data of a construction site and transmitting the data to the cloud device; the cloud equipment performs data interaction with the terminal equipment, performs data preprocessing on the construction site data acquired by the acquisition equipment, gives an optimal low-carbon technical scheme in combination with a database and basic information of a project, and transmits the optimal low-carbon technical scheme to the terminal equipment; and the terminal equipment is used for checking the technical scheme evaluation result and generating a decision report. The intelligent low-carbon construction scheme decision-making platform is provided by comprehensively integrating multiple technologies such as data acquisition, technical evaluation, decision-making analysis and dynamic optimization, and low-carbon and green development of the building industry is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of building engineering, and in particular to a rapid decision-making platform and a decision-making method for a low-carbon construction technology solution for a building engineering. Background Art

[0002] As the global climate change problem becomes increasingly serious, environmental protection and sustainable development have become important issues that need to be urgently addressed in all walks of life, especially in the construction industry. The construction industry is not only one of the main sources of global carbon emissions, but also the resource consumption, energy consumption and waste emissions during the construction process have seriously affected the quality of the environment. According to relevant data from the international construction industry, carbon emissions from the construction industry account for more than 30% of the global total emissions, among which carbon emissions during the construction phase are particularly prominent. Therefore, promoting the low-carbon transformation in the construction process has become an inevitable choice for the global construction industry to cope with climate change and achieve green development.

[0003] The research and application of low-carbon building technology mainly focuses on reducing carbon emissions in the construction process, saving energy and reducing consumption, rationally using resources, and adopting environmentally friendly materials. However, the promotion and application of low-carbon building construction technology currently faces multiple challenges, which are mainly reflected in the following aspects:

[0004] Complexity in selecting low-carbon technical solutions: There are many types of low-carbon technical solutions involved in the construction process of building projects, including energy-saving building materials, energy-saving construction equipment, clean energy applications, waste recycling and treatment technologies, etc. The applicability and effectiveness of these technical solutions are affected by many factors such as the construction environment, project scale, budget, and time schedule. How to quickly and accurately select low-carbon technical solutions that are suitable for the characteristics of the project has become a difficult problem in construction management.

[0005] Lack of effective decision support tools: Currently, most construction projects still rely on manual experience or traditional evaluation methods to select low-carbon technology solutions. These methods usually lack data support, are difficult to respond quickly to dynamic changes in projects, and may lead to misjudgments or omissions in complex environments. In addition, most existing low-carbon technology decision-making tools fail to consider the multi-dimensional needs of the entire construction process, lack comprehensive technical, economic and environmental evaluation capabilities, and are difficult to make comprehensive and accurate decisions.

[0006] Low-carbon construction technology has poor dynamic adaptability: Construction projects are often accompanied by dynamic adjustments to factors such as resource supply, construction progress, and environmental changes. Once a traditional low-carbon technology solution is determined, it lacks a flexible adjustment mechanism. Once a sudden change occurs during the construction process (such as an extension of the construction period, resource shortages, etc.), the originally selected low-carbon technology solution may no longer meet the new needs, resulting in waste of resources or reduced carbon emission reduction effects.

[0007] Difficulty in evaluating low-carbon technologies: The implementation effect of low-carbon technologies is not only affected by the technology itself, but also closely related to the specific conditions of the construction project. How to scientifically and accurately evaluate the effects of various low-carbon technologies in actual construction is an urgent problem to be solved. Existing evaluation tools usually lack the ability to accurately match and personalize optimization for different project characteristics.

[0008] Lack of uniformity in policies, regulations and industry standards: Although many countries and regions have put forward clear policy goals and regulatory requirements for the low-carbonization of the construction industry, the relevant policies lack uniformity in implementation and there are large differences in industry standards, resulting in considerable challenges in the promotion and application of low-carbon technologies. Construction companies often face uncertainty and regulatory challenges when choosing low-carbon technology solutions.

[0009] Therefore, how to provide an efficient, scientific and intelligent decision-making platform for construction projects to help construction managers quickly select appropriate low-carbon technology solutions in a complex and changing construction environment is a problem that needs to be solved in this field. Summary of the invention

[0010] In view of the above-mentioned technical problems existing in the implementation of existing low-carbon construction technology solutions for construction projects, the purpose of the present invention is to provide a rapid decision-making platform for low-carbon construction technology solutions for construction projects. The platform integrates advanced technologies such as big data analysis, artificial intelligence, and cloud computing. Through comprehensive data collection, analysis, optimization and decision-making support, it can help construction managers quickly and efficiently select the low-carbon technology solution that best suits project needs, thereby achieving carbon emission reduction, resource optimization and energy efficiency improvement during the construction process. On this basis, a rapid decision-making method for low-carbon construction technology solutions for construction projects based on the rapid decision-making platform is also provided, which effectively overcomes the problems existing in the prior art.

[0011] In order to achieve the above-mentioned purpose, the present invention provides a rapid decision-making platform for low-carbon construction technology solutions for construction projects, including a collection device, a cloud device and a terminal device. The collection device interacts with the cloud device data to collect basic project information and various data on the construction site and transmits them to the cloud device. The cloud device interacts with the terminal device data. The cloud device preprocesses the construction site data collected by the collection device and gives the optimal low-carbon technology solution in combination with the database and the basic information of the project and transmits it to the terminal device. The terminal device is used to view the technical solution evaluation results and generate a decision report.

[0012] Further, the acquisition device includes a first acquisition component, a second acquisition component, a third acquisition component, a fourth acquisition component and a fifth acquisition component;

[0013] The first collection component is used to input basic information of the engineering project on the platform, the second collection component is used to collect energy consumption data, the third collection component is used to collect carbon emission data, the fourth collection component is used to collect material usage data, and the fifth collection component is used to collect construction progress data.

[0014] Furthermore, the cloud device includes a data acquisition module, a data preprocessing module, a database module, a decision analysis module, a decision support and optimization module, and a human-computer interaction module;

[0015] The data acquisition module interacts with the data preprocessing module, and the data acquisition module acquires data from on-site sensors and monitoring equipment in real time, and transmits the data to the data preprocessing module for preprocessing the collected data; the database module is used to store information on a variety of low-carbon technology solutions, and the decision analysis module interacts with the data preprocessing module and the database module respectively. The platform uses the low-carbon technology database of the database module, and combines the basic information of the project and the data processed by the data preprocessing module to match different low-carbon technology solutions and conduct a comprehensive evaluation. The decision support and optimization module interacts with the decision analysis module, and is used to automatically recommend the most suitable low-carbon technology solution for the project based on the output of the decision analysis module, and provide dynamic optimization suggestions. The human-computer interaction module is used to provide an intuitive operation interface for project managers, and graphically display the evaluation results, optimization suggestions and implementation steps of various technical solutions.

[0016] Furthermore, the data preprocessing module includes a denoising unit, a cleaning unit and a data standardization and formatting unit. The denoising unit interacts with the data acquisition module to denoise the collected data. The cleaning unit interacts with the denoising unit to check the consistency of the denoised data, eliminate abnormal data and fill in missing values. The data standardization and formatting unit interacts with the cleaning unit to standardize and format the cleaned data.

[0017] Furthermore, the database module includes a processing unit, a classification and sorting unit and a storage unit. The processing unit is used to clean and standardize the collected low-carbon technology information. The classification and sorting unit interacts with the processing unit data, and the data processed by the processing unit can be classified and dimensionally sorted as required. The storage unit interacts with the classification and sorting unit data, and the data sorted by the classification and sorting unit is structured and stored.

[0018] Furthermore, the database module also includes a dynamic update unit, which uses an incremental update mechanism to ensure the real-time and accuracy of the data through the real-time received data stream.

[0019] Furthermore, the database module also includes an expansion unit, which allows adding new data tables, fields and indexes according to needs by adopting an extensible architecture design.

[0020] Furthermore, the decision analysis module includes a screening unit, an evaluation unit and a ranking unit. The screening unit is used to screen applicable technical solutions based on project requirements. The evaluation unit interacts with the screening unit data and uses a multi-dimensional weight method to comprehensively evaluate the solutions screened by the screening unit. The ranking unit interacts with the evaluation unit data and ranks the comprehensive scores calculated by the evaluation unit.

[0021] Furthermore, the decision support and optimization module includes a scoring screening unit and an optimization unit. The scoring screening unit is used to screen the scheme scores output by the decision analysis module. The optimization unit interacts with the scoring screening unit data, and the optimization unit provides dynamic optimization suggestions based on real-time monitoring data.

[0022] In order to achieve the above object, the present invention provides a method for quickly making decisions on low-carbon construction technology solutions for building projects, the method comprising the following steps:

[0023] Step 1: Enter the basic information of the project on the platform;

[0024] Step 2: Collect various data on the construction site through collection equipment, including but not limited to energy consumption data, carbon emissions, construction progress, and resource usage;

[0025] Step 3: Transmit various data of the construction site collected by the collection equipment to the cloud server through the transmission medium;

[0026] Step 4: The cloud server performs denoising, cleaning, standardization and formatting on the data collected in step 3 to ensure data quality;

[0027] Step 5: The cloud server evaluates the carbon reduction effect, economic efficiency, technical adaptability and construction period of different low-carbon technical solutions based on the processed data and combined with the information in the database and the input project information, and gives the priority of the solutions;

[0028] Step 6: Automatically recommend the best low-carbon technology solution based on the decision analysis results, and make dynamic optimization adjustments based on real-time data during the construction process;

[0029] Step 7: Transmit the recommended optimal low-carbon technology solution to the terminal device for users to view the technology solution evaluation results and generate a decision report;

[0030] Step 8: During the construction process, the platform continuously monitors on-site data, and through real-time analysis of construction progress, energy consumption, carbon emissions and other information, automatically provides feedback on the implementation effect of low-carbon technical solutions during the construction process and provides real-time optimization suggestions.

[0031] The invention provides a rapid decision-making platform and method for low-carbon construction technology solutions for construction projects. The platform is an integrated decision-making platform that can conduct comprehensive evaluations from multiple dimensions (such as carbon emission reduction effects, cost-effectiveness, technical feasibility, construction period, etc.) and accurately recommend the optimal solution.

[0032] Secondly, the platform can collect various data from the construction site in real time and automatically adjust technical solutions according to on-site conditions to ensure the continuous achievement of low-carbon goals.

[0033] At the same time, the platform uses a decision analysis module based on big data and artificial intelligence, which can automatically evaluate, optimize and recommend low-carbon technology solutions, reduce human decision-making bias, and improve the accuracy and efficiency of decision-making.

[0034] In addition, from the initial project planning to the end of construction, the platform provides full-process low-carbon technical decision-making support, and can dynamically adjust and optimize according to actual conditions during the construction process to ensure the realization of low-carbon construction goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0036] Figure 1 This is a schematic diagram of the structure of the rapid decision-making platform for low-carbon construction technology solutions for this building project.

[0037] Figure 2 This is a flow chart of the rapid decision-making method for the low-carbon construction technology solution for this building project. DETAILED DESCRIPTION

[0038] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below with reference to specific diagrams.

[0039] In view of the above-mentioned technical problems existing in the implementation of existing low-carbon construction technology solutions for construction projects, the purpose of the present invention is to provide a rapid decision-making platform for low-carbon construction technology solutions for construction projects, which can make efficient decisions and optimize low-carbon construction technology solutions in real time, thereby promoting the construction industry to achieve low-carbon and green construction goals.

[0040] This solution provides a rapid decision-making platform for low-carbon construction technology solutions for building projects. Figure 1 , which includes a collection device 100, a cloud device 200 and a terminal device 300.

[0041] The acquisition device 100 is a front-end acquisition system, and the acquisition device 100 includes a first acquisition component, a second acquisition component, a third acquisition component, a fourth acquisition component and a fifth acquisition component.

[0042] The first collection component is used to input basic information of the engineering project on the platform. Based on this basic information, the platform can automatically push appropriate low-carbon technology solutions as a preliminary reference for subsequent decision-making.

[0043] Basic project information includes but is not limited to: project type (such as residential, commercial buildings, infrastructure, etc.); project scale (such as building area, construction period, etc.); budget information (such as total construction budget, low-carbon technology budget, etc.); construction environment (such as geographical location, climate conditions, resource supply, etc.).

[0044] Among them, the second collection component is used to collect energy consumption data, which includes but is not limited to the energy consumption of electricity, diesel, gas, etc.

[0045] The third collection component is used to collect carbon emission data. The third collection component collects carbon emissions from various links such as the production and transportation of construction materials and the use of equipment during the construction process.

[0046] The fourth collection component is used to collect material usage data. The fourth collection component collects the types, quantities and sources of various types of building materials used in the construction process.

[0047] The fifth acquisition component is used to collect construction progress data, and the fifth acquisition component is used to monitor the construction progress, resource usage, personnel arrangements, etc. of the project in real time.

[0048] As an example, the collection components here include but are not limited to sensors, Internet of Things devices, and smart metering devices. The specific selection can be determined according to actual conditions.

[0049] The above data is transmitted to the cloud device 200 of the platform through the data acquisition module for data preprocessing.

[0050] The cloud device 200 interacts with the data collection device 100. The cloud device 200 is the core computing server of the platform. The data collected by the collection device 100 is transmitted to the cloud device 200, and data processing, big data analysis, and algorithm operation are performed through the cloud device 200. The cloud device 200 preferably uses a high-performance computing cluster to support large-scale data processing, computing, and storage requirements, ensuring that the platform can operate stably and efficiently under the condition of concurrent use by multiple projects and users. The cloud platform can flexibly expand resources as needed, support real-time synchronization and remote access of data, and ensure that users can obtain the latest decision results at any time.

[0051] The cloud device 200 includes a data acquisition module, a data preprocessing module, a database module, a decision analysis module, a decision support and optimization module, and a human-computer interaction module.

[0052] The data acquisition module interacts with the data acquisition equipment, and the data acquisition module obtains data from the sensors and monitoring equipment in the on-site acquisition equipment in real time.

[0053] The data preprocessing module interacts with the data acquisition module and is used to preprocess the data acquired by the data acquisition module. The data preprocessing module here includes a denoising unit, a cleaning unit, and a data standardization and formatting unit.

[0054] The denoising unit interacts with the data acquisition module to remove interference factors from the construction data collected by the data acquisition module after receiving the construction data, so as to ensure the accuracy of the data.

[0055] For example, if the collected energy consumption data is [100, 102, 5000, 101, 99], the denoising unit detects that 5000 deviates too much from the mean (noise), and replaces it with the mean of adjacent values: (102+101) / 2=101.5, and the result is: [100, 102, 101.5, 101, 99].

[0056] The cleaning unit interacts with the denoising unit data to check the consistency of the denoised data, remove abnormal data, and fill in missing values ​​to ensure data quality for subsequent decision analysis.

[0057] The data consistency check is used to compare data from different sources to check whether there are logical conflicts or timestamp errors. For example, if there is a time difference between the carbon emission data and energy consumption data of the same device, the system will mark and prompt the possible data consistency problem.

[0058] Abnormal data removal is used by the system to automatically identify and remove obviously unreasonable data according to the set thresholds and rules (such as equipment power exceeding the expected range, abnormally high carbon emissions, etc.). For example, if the carbon emission value collected by a sensor within the normal working range is [50, -10, 60], the negative value -10 is removed, and the result is: [50, 60].

[0059] Missing value filling is used to fill in missing data that occurs during the collection process. The system uses interpolation methods (such as linear interpolation or filling based on the average value) to ensure data integrity. For example, if the energy consumption data for a certain period of time is [200,_,300] (the second value is missing), it can be filled by interpolation of the previous and next values: (200+300) / 2=250, and the result is: [200,250,300].

[0060] The data standardization and formatting unit interacts with the cleaning unit data to standardize and format the cleaned data so that data from different sources can be compared horizontally and subsequently analyzed.

[0061] Data standardization and formatting are used to convert all collected data into a standard format (such as a unified timestamp format, unified units, etc.) and perform normalization processing so that data from different sources can be compared horizontally and subsequently analyzed.

[0062] For example, if the collected carbon emission data (unit: kg) is [50, 100, 150], it is normalized to the range of [0, 1] using the formula (value-min) / (max-min), and the result is: [0.0, 0.5, 1.0].

[0063] If the collected timestamp is ["11 / 12 / 2024 12:00","2024-12-11T12:00:00"], the unified format is the ISO standard: ["2024-12-11T12:00:00","2024-12-11T12:00:00"].

[0064] The database module is used to store information on various low-carbon technology solutions, including the basic principles, technical parameters, application cases, carbon reduction effects, etc. The database module includes a processing unit, a classification and sorting unit, and a storage unit.

[0065] The processing unit is used to process the collected low-carbon technology information, which includes data cleaning (de-duplication, correction of format errors) and standardization (unification of technical parameter units and indicators).

[0066] The classification and sorting unit interacts with the processing unit data, and the data processed by the processing unit can be classified and dimensionally sorted according to technology type, application scenario, and emission reduction effect.

[0067] The storage unit interacts with the classification and sorting unit data to store the data sorted by the classification and sorting unit in a structured manner.

[0068] Secondly, this database module also includes a dynamic update unit, which receives data streams from policies, industry research, and project feedback in real time and adopts an incremental update mechanism to ensure the real-time and accuracy of the data.

[0069] In addition, this database module also includes an extension unit. The extension unit adopts an extensible architecture design to allow new data tables, fields and indexes to be added as needed, ensuring that the system can adapt to the access and management of more low-carbon technology solutions in the future.

[0070] The decision analysis module is used to conduct multi-dimensional evaluation of different low-carbon technology solutions based on big data analysis and artificial intelligence algorithms to help users make the best decision.

[0071] The decision analysis module interacts with the data preprocessing module and the database module respectively. The platform uses the low-carbon technology database of the database module and combines the basic information of the project with the data processed by the data preprocessing module to match different low-carbon technology solutions and conduct a comprehensive evaluation.

[0072] Specifically, the decision analysis module calls the low-carbon technology database in the database module to obtain data such as the basic principles, application scenarios, and carbon reduction effects of the technology, and combines the basic information of the project (such as building type, scale, budget, geographical environment, etc.) and the real-time monitoring data processed by the data preprocessing module (such as energy consumption, temperature, humidity, etc.) to match different low-carbon technology solutions and conduct a comprehensive evaluation. The decision analysis module includes a screening unit, an evaluation unit, and a sorting unit.

[0073] Among them, the screening unit is used to screen applicable technical solutions based on project requirements. For example, if a project is located in a high-humidity area, priority will be given to technologies that adapt to high-humidity environments.

[0074] The evaluation unit interacts with the screening unit’s data, conducts a comprehensive evaluation of the options screened by the screening unit, and uses a multi-dimensional weighting method to score the carbon emission reduction effect, economy, and feasibility.

[0075] The dimensions assessed here include:

[0076] Carbon reduction effect: The amount of carbon emissions that different technical solutions can reduce during the construction process. Therefore, the assessment unit assigns weights to the carbon reduction effect according to the unit emission reduction.

[0077] Economic efficiency: The implementation cost and expected benefits of the plan, including the economic benefits brought by energy cost savings and reduced carbon emissions, etc. Therefore, the evaluation unit weights economic efficiency according to the unit return on investment.

[0078] Feasibility: Whether the implementation of the technical solution can shorten the construction period and optimize the use of resources. Therefore, the evaluation unit gives weights to the construction period and resource utilization efficiency.

[0079] The sorting unit interacts with the evaluation unit in data exchange. The sorting unit sorts the comprehensive scores calculated by the evaluation unit and ultimately recommends the solution with the highest comprehensive score to ensure the applicability of the technology and the scientific nature of the decision.

[0080] The decision support and optimization module interacts with the decision analysis module to analyze the output of the decision analysis module, including the quantitative scores and advantages and disadvantages of the technical solutions in terms of carbon emission reduction effect, economy and construction period. The decision support and optimization module includes a scoring screening unit and an optimization unit.

[0081] The scoring and screening unit is used to screen the program scores output by the decision analysis module. For example, assume that the output shows that: Technology A (solar heating system) scores 90 points, with significant carbon emission reduction effects but high initial costs; Technology B (integrated insulation materials) scores 85 points, with strong adaptability and a short implementation cycle but average emission reduction effects. Therefore, the scoring and screening unit automatically recommends Technology A as the optimal solution by using a weighted algorithm and comprehensively considering user needs (such as priority emission reduction or cost control).

[0082] The optimization unit interacts with the scoring and screening unit data. The optimization unit provides dynamic optimization suggestions based on real-time monitoring data, such as adjusting the design scale of solar heating to balance the initial cost and carbon emission reduction effect, ultimately ensuring that the solution recommendation is accurate and meets the actual needs of the project.

[0083] Secondly, during the construction process, if unforeseen factors such as progress delays, changes in resource supply, etc. occur, the decision support and optimization module can adjust the original plan in real time and re-evaluate it.

[0084] Suppose during the construction process, the project progress is delayed, resulting in the failure to start the originally planned low-carbon technology solution (such as solar heating system) on time, or the use of building insulation materials is insufficient due to material supply problems. The decision support and optimization module of the platform will receive construction progress and resource supply data in real time, and re-evaluate the original plan based on these new changes.

[0085] First, the progress and resource data are acquired through the data acquisition module, and the data preprocessing module processes and inputs them into the decision analysis module. Then, the decision analysis module recalculates the scores of each technical solution according to the new project conditions (such as the extension of the construction period due to progress delays or the reduction of the supply of insulation materials), and adjusts the adaptability, implementation cycle and carbon emission reduction effect of the technical solution. Then, based on the evaluation results, the recommended solution is automatically adjusted, and the implementation steps, resource requirements and expected effects are provided.

[0086] Assuming that the original solution (solar heating) has affected the expected carbon emission reduction effect due to delays, the platform may recommend technologies that are more suitable for the current progress (such as energy-efficient lighting systems) as alternatives and provide new implementation paths, such as speeding up material supply, adjusting construction steps, etc. At the same time, the platform will update the expected carbon emission reduction effect and cost-effectiveness in real time to ensure that the new recommended solution can maximize the low-carbon goals of the project.

[0087] At the same time, the decision support and optimization module also monitors the data of the construction site in real time and tracks the implementation effect of the low-carbon technical solution. If there are deviations or new requirements, the platform can provide continuous feedback and adjustment suggestions based on the real-time changing data. Users can make real-time scheduling through the platform to ensure that the project always follows the low-carbon goal and adopts timely technical solution adjustments through intelligent algorithms.

[0088] For example, if a low-carbon technology solution fails to achieve the expected energy-saving effect during implementation, the platform will identify the problem and recommend alternative solutions or adjust the construction method to ensure that carbon emissions continue to be reduced during the construction process.

[0089] The human-computer interaction module is used to provide project managers with an intuitive operating interface, which graphically displays the evaluation results, optimization suggestions and implementation steps of various technical solutions.

[0090] The human-computer interaction module can also input basic information of the construction project, including project type, scale, budget, construction environment, etc.

[0091] The terminal device 300 is connected with the cloud device 200 to allow users to access the platform and perform operations such as project data input, technical solution viewing, and decision report generation.

[0092] The terminal device 300 can generate a detailed decision report based on the final decision result of the cloud device 200. The report includes:

[0093] Recommended low-carbon technology solution: detailed introduction of the solution’s principles, implementation methods, required materials and equipment, etc.

[0094] Carbon emission reduction forecast: The amount of carbon emissions that the technical solution is expected to reduce during the implementation of the project.

[0095] Cost analysis and benefit evaluation: the specific cost of implementing the plan and the long-term economic benefits it brings, including energy and material savings.

[0096] Implement risk assessment: potential technical difficulties, construction risks and countermeasures.

[0097] Decision reports can be exported as PDF files or shared online with relevant managers to support project management decisions.

[0098] Here, the terminal device 300 includes but is not limited to PC, smart phone, tablet and other devices, and the specific selection can be determined according to the actual situation.

[0099] Based on the rapid decision-making platform for low-carbon construction technology solutions for construction projects provided by the above scheme, this scheme also provides a rapid decision-making method for low-carbon construction technology solutions for construction projects, see Figure 2 , the method comprises the following steps:

[0100] Step 1: Enter the basic information of the project on the platform.

[0101] Step 2: Collect various data from the construction site through collection equipment, including but not limited to energy consumption data, carbon emissions, construction progress, resource usage, etc.

[0102] Step 3: Transmit various data of the construction site collected by the collection equipment to the cloud server via the transmission medium.

[0103] Step 4: The cloud server denoises, cleans, standardizes and formats the data collected in step 3 to ensure data quality.

[0104] Step 5: The cloud server evaluates the carbon reduction effect, economic efficiency, technical adaptability and construction period of different low-carbon technical solutions based on the processed data and combined with the information in the database and the input project information, and gives the priority of the solutions.

[0105] Step 6: Automatically recommend the optimal low-carbon technology solution based on the decision analysis results, and make dynamic optimization adjustments based on real-time data during the construction process.

[0106] Step 7: Transmit the recommended optimal low-carbon technical solution to the terminal device for users to view the technical solution evaluation results and generate decision reports, etc.

[0107] Step 8: During the construction process, the platform continuously monitors on-site data, and through real-time analysis of construction progress, energy consumption, carbon emissions and other information, automatically provides feedback on the implementation effect of low-carbon technical solutions during the construction process and provides real-time optimization suggestions.

[0108] In summary, a rapid decision-making platform and method for low-carbon construction technology solutions for construction projects is described. The platform integrates big data, artificial intelligence and other technologies, and significantly improves the efficiency of selecting low-carbon technology solutions through real-time data analysis and decision support systems.

[0109] Secondly, the platform can automatically optimize technical solutions based on real-time changes at the construction site to ensure the continued achievement of low-carbon goals.

[0110] At the same time, from project planning to the end of construction, the platform provides full-process low-carbon technical decision-making support to help project managers optimize resource utilization and reduce carbon emissions.

[0111] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A rapid decision-making platform for low-carbon construction technology solutions for building projects, characterized by: It includes a collection device, a cloud device and a terminal device. The collection device interacts with the cloud device to collect basic project information and various data on the construction site and transmits them to the cloud device. The cloud device interacts with the terminal device to pre-process the construction site data collected by the collection device and gives the optimal low-carbon technical solution in combination with the database and the basic information of the project and transmits it to the terminal device. The terminal device is used to view the technical solution evaluation results and generate a decision report.

2. A rapid decision-making platform for low-carbon construction technology solutions for construction projects according to claim 1, characterized in that: The acquisition device includes a first acquisition component, a second acquisition component, a third acquisition component, a fourth acquisition component and a fifth acquisition component; The first collection component is used to input basic information of the engineering project on the platform, the second collection component is used to collect energy consumption data, the third collection component is used to collect carbon emission data, the fourth collection component is used to collect material usage data, and the fifth collection component is used to collect construction progress data.

3. According to claim 1, a rapid decision-making platform for low-carbon construction technology solutions for construction projects is characterized by: The cloud device includes a data acquisition module, a data preprocessing module, a database module, a decision analysis module, a decision support and optimization module, and a human-computer interaction module; The data acquisition module interacts with the data preprocessing module, and the data acquisition module acquires data from on-site sensors and monitoring equipment in real time, and transmits the data to the data preprocessing module for preprocessing the collected data; the database module is used to store information on a variety of low-carbon technology solutions, and the decision analysis module interacts with the data preprocessing module and the database module respectively. The platform uses the low-carbon technology database of the database module, and combines the basic information of the project and the data processed by the data preprocessing module to match different low-carbon technology solutions and conduct a comprehensive evaluation. The decision support and optimization module interacts with the decision analysis module, and is used to automatically recommend the most suitable low-carbon technology solution for the project based on the output of the decision analysis module, and provide dynamic optimization suggestions. The human-computer interaction module is used to provide an intuitive operation interface for project managers, and graphically display the evaluation results, optimization suggestions and implementation steps of various technical solutions.

4. A rapid decision-making platform for low-carbon construction technology solutions for construction projects according to claim 3, characterized in that: The data preprocessing module includes a denoising unit, a cleaning unit and a data standardization and formatting unit. The denoising unit interacts with the data acquisition module to denoise the collected data. The cleaning unit interacts with the denoising unit to check the consistency of the denoised data, eliminate abnormal data and fill in missing values. The data standardization and formatting unit interacts with the cleaning unit to standardize and format the cleaned data.

5. According to claim 1, a rapid decision-making platform for low-carbon construction technology solutions for construction projects is characterized by: The database module includes a processing unit, a classification and sorting unit and a storage unit. The processing unit is used to clean and standardize the collected low-carbon technology information. The classification and sorting unit interacts with the processing unit data, and the data processed by the processing unit can be classified and dimensionally sorted as required. The storage unit interacts with the classification and sorting unit data, and the data sorted by the classification and sorting unit is structuredly stored.

6. A rapid decision-making platform for low-carbon construction technology solutions for construction projects according to claim 5, characterized in that: The database module also includes a dynamic update unit, which uses an incremental update mechanism to ensure the real-time and accuracy of data through the real-time received data stream.

7. A rapid decision-making platform for low-carbon construction technology solutions for construction projects according to claim 6, characterized in that: The database module also includes an expansion unit, which allows adding new data tables, fields and indexes according to needs by adopting an expandable architecture design.

8. The low-carbon construction technology solution rapid decision-making platform for construction projects according to claim 1 is characterized by: The decision analysis module includes a screening unit, an evaluation unit and a ranking unit. The screening unit is used to screen applicable technical solutions based on project requirements. The evaluation unit interacts with the screening unit data and uses a multi-dimensional weight method to comprehensively evaluate the solutions screened by the screening unit. The ranking unit interacts with the evaluation unit data and ranks the comprehensive scores calculated by the evaluation unit.

9. A rapid decision-making platform for low-carbon construction technology solutions for construction projects according to claim 1, characterized in that: The decision support and optimization module includes a scoring screening unit and an optimization unit. The scoring screening unit is used to screen the scheme scores output by the decision analysis module. The optimization unit interacts with the scoring screening unit data, and the optimization unit provides dynamic optimization suggestions based on real-time monitoring data.

10. A method for rapid decision-making on low-carbon construction technology solutions for building projects, characterized in that: The decision-making method comprises the following steps: Step 1: Enter the basic information of the project on the platform; Step 2: Collect various data on the construction site through collection equipment, including but not limited to energy consumption data, carbon emissions, construction progress, and resource usage; Step 3: Transmit various data of the construction site collected by the collection equipment to the cloud server through the transmission medium; Step 4: The cloud server performs denoising, cleaning, standardization and formatting on the data collected in step 3 to ensure data quality; Step 5: The cloud server evaluates the carbon reduction effect, economic efficiency, technical adaptability and construction period of different low-carbon technical solutions based on the processed data and combined with the information in the database and the input project information, and gives the priority of the solutions; Step 6: Automatically recommend the best low-carbon technology solution based on the decision analysis results, and make dynamic optimization adjustments based on real-time data during the construction process; Step 7: Transmit the recommended optimal low-carbon technology solution to the terminal device for users to view the technology solution evaluation results and generate a decision report; Step 8: During the construction process, the platform continuously monitors on-site data, and through real-time analysis of construction progress, energy consumption, carbon emissions and other information, automatically provides feedback on the implementation effect of low-carbon technical solutions during the construction process and provides real-time optimization suggestions.

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