Construction waste recovery intelligent management method and device based on LCA and GIS

Abstract

The embodiment of the invention discloses a construction waste recovery intelligent management method and device based on LCA and GIS. The method comprises the following steps: carrying out classification and information integration on construction waste by utilizing a BIM technology to obtain a three-dimensional building model with construction waste classification information; performing spatial analysis and remote control on the construction waste of the three-dimensional building model by using GIS and BIM technologies; information of monitoring equipment installed in the garbage recycling vehicle is obtained so as to drive the garbage recycling vehicle to recycle the construction garbage; waste treatment and resource recovery are optimized by utilizing an artificial intelligence technology; the construction waste recycling process is optimized through life cycle evaluation and a geographic information system. By implementing the method provided by the embodiment of the invention, the construction waste can be automatically classified and identified, the classification and recovery efficiency is improved, the workload and time of manual classification and treatment are reduced, and the resource utilization of the construction waste is realized.

Description

Technical Field

[0001] The present invention relates to a method for recycling and management of construction waste, and more specifically to an intelligent management method and device for construction waste recycling based on LCA and GIS. Background Art

[0002] Construction waste is solid waste generated during the construction, reconstruction, expansion or demolition of buildings. Construction waste has a wide range of erosive effects on the living environment. If construction waste is left unmanaged for a long time, it will have a bad impact on urban environmental sanitation, living conditions, land quality assessment, etc. Therefore, it is necessary to recycle construction waste.

[0003] Traditional methods for recycling construction waste mainly rely on manual classification and processing, and this method has many problems and challenges. First of all, there are many types of construction waste, including different types of materials such as bricks, concrete, wood, glass, plastic, etc., which need to be manually classified and processed one by one, resulting in a large workload, low efficiency, and easy to cause secondary pollution and environmental damage. Secondly, the traditional recycling method is costly, requiring a large amount of manual participation, plus the costs of transportation, storage and other links, making the cost of the entire recycling process remain high and difficult to meet the market demand and achieve sustainable development. In addition, since construction waste contains a large amount of harmful substances, if not properly treated, it will cause serious harm to workers and the environment, posing a safety hazard.

[0004] Therefore, it is necessary to design a new method to achieve automatic classification and identification of construction waste, improve the classification and recycling efficiency, reduce the workload and time of manual classification and processing, and realize the resource utilization of construction waste. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and provide an intelligent management method and device for construction waste recycling based on LCA and GIS.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: An intelligent management method for construction waste recycling based on LCA and GIS, including: Using BIM technology to classify and integrate information of construction waste to obtain a three-dimensional building model with construction waste classification information; Using GIS and BIM technologies to conduct spatial analysis and remote control of the construction waste in the three-dimensional building model; Obtaining information of monitoring devices installed in waste collection vehicles to drive the waste collection vehicles to recycle construction waste; Using artificial intelligence technology to optimize waste treatment and resource recovery; Optimizing the construction waste recycling process through life cycle assessment and geographic information system.

[0007] Its further technical solution is as follows: classifying and integrating the information of construction waste by using BIM technology to obtain a three-dimensional building model with construction waste classification information, including: Creating a building information model by using BIM technology; Adding waste classification information to the building information model; Collecting the data of construction waste collected by sensors and Internet of Things devices integrated in the building; Analyzing and identifying the construction waste data by using BIM technology, and classifying the construction waste through a training algorithm; Establishing a real-time monitoring system and data analysis based on the construction waste data to optimize the construction waste management process, so as to obtain a three-dimensional building model with construction waste classification information.

[0008] Its further technical solution is as follows: spatially analyzing and remotely controlling the construction waste of the three-dimensional building model by using GIS and BIM technologies, including: Obtaining the data related to construction waste and importing it into the GIS system; Obtaining the spatial distribution of the three-dimensional building model and construction waste by using BIM and GIS technologies; Recycling the construction waste through remote control technology; Establishing a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

[0009] Its further technical solution is as follows: optimizing waste treatment and resource recovery by using artificial intelligence technology, including: Conducting a comprehensive waste audit on the three-dimensional building model to obtain an audit result; Setting waste treatment goals; Identifying and evaluating recycling opportunities by using BIM; Formulating a comprehensive waste disposal plan according to the audit result, the waste treatment goal, and the recycling opportunity; Adopting AI analysis tools and machine learning tools to continuously monitor and improve the waste disposal process.

[0010] Its further technical solution is as follows: conducting a comprehensive waste audit on the three-dimensional building model to obtain an audit result, including: Using BIM to conduct 3D scanning on the three-dimensional building model to evaluate the type and quantity of waste generated by the construction project, and classifying the waste to obtain an audit result; Among them, the process of waste classification is optimized by using machine learning.

[0011] Its further technical solution is: Optimizing the construction waste recycling process through life cycle assessment and geographic information system, including: Collecting relevant information on construction waste; Performing spatial analysis and time analysis using the geographic information system based on the collected relevant information to obtain an analysis result; Performing environmental impact assessment using life cycle assessment based on the collected relevant information to obtain an assessment result; Formulating an optimization strategy based on the analysis result and the assessment result; Sending the optimization strategy to the corresponding equipment and continuously monitoring the effect of the recycling process.

[0012] Its further technical solution is: Performing spatial analysis and time analysis using the geographic information system based on the collected relevant information to obtain an analysis result, including: Using a spatial analysis tool based on the collected relevant information to determine the geographical relationship between the construction waste generation points and the treatment facilities, find the areas where the transportation efficiency meets the requirements, and propose an optimization plan; Combining the time characteristics of construction activities, analyzing the time distribution of construction waste generation, and predicting the peak generation period; Among them, the analysis result includes the optimization plan and the peak generation period.

[0013] Its further technical solution is: Performing environmental impact assessment using life cycle assessment based on the collected relevant information to obtain an assessment result, including: Setting the goals for the entire life cycle of the construction project; Performing life cycle inventory analysis and life cycle impact assessment using life cycle assessment based on the collected relevant information to obtain the LCA assessment result; Generating optimization suggestions based on the LCA assessment result in combination with the goal to obtain the assessment result.

[0014] The present invention also provides an intelligent management device for construction waste recycling based on LCA and GIS, including: A model generation unit for classifying and integrating information on construction waste using BIM technology to obtain a three-dimensional building model with construction waste classification information; An analysis and control unit for performing spatial analysis and remote control on the construction waste in the three-dimensional building model using GIS and BIM technologies; An acquisition unit for acquiring information of monitoring devices installed in the waste recycling vehicle to drive the waste recycling vehicle to recycle construction waste; An artificial intelligence optimization unit for optimizing waste treatment and resource recovery using artificial intelligence technology; A recycling optimization unit for optimizing the construction waste recycling process through life cycle assessment and geographic information system.

[0015] The beneficial effects of the present invention compared with the prior art are as follows: By using BIM technology to construct a three-dimensional building model with construction waste classification information, the present invention uses GIS and BIM technologies to conduct spatial analysis and remote control of construction waste, optimizes through obtaining the monitoring information of the monitoring equipment in the recycling process by using artificial intelligence technology, and optimizes the construction waste recycling process through life cycle assessment and geographic information system, realizing automatic classification and identification of construction waste, improving the classification and recycling efficiency, reducing the workload and time of manual classification and treatment, and realizing the resource utilization of construction waste.

[0016] The following further describes the present invention in conjunction with the accompanying drawings and specific embodiments. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 A schematic diagram of the application scenario of the intelligent management method for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention; Figure 2 A schematic flowchart of the intelligent management method for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention; Figure 3 A schematic diagram of the spatial distribution of the main production sources of construction waste and the waste treatment and recycling sites provided by the embodiment of the present invention; Figure 4 A schematic block diagram of the intelligent management device for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention; Figure 5 A schematic block diagram of the computer device provided by the embodiment of the present invention. Detailed Embodiments

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0020] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0021] It should also be understood that the terminology used in this specification of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly dictates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0022] It should be further understood that the term "and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0023] Please refer to Figure 1 and Figure 2 , Figure 1 is a schematic diagram of the application scenario of the intelligent management method for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention. Figure 2 is a schematic flowchart of the intelligent management method for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention. This intelligent management method for construction waste recycling based on LCA and GIS is applied to a server. The server conducts data interaction with terminals, sensors and garbage collection vehicles. Through automation and intelligent technologies, the workload and time of manual participation can be reduced, and the risks of workers in dangerous environments can be lowered. At the same time, these technologies can improve the accuracy and efficiency of construction waste treatment and recycling, thereby reducing the impact on the environment and enhancing the environmental protection of construction waste treatment and recycling. Moreover, the method of this embodiment also adopts artificial intelligence technology to finely classify and process construction waste to achieve the recycling of resources. For example, converting construction waste into recycled building materials or energy, etc., to promote the effective recycling of resources and achieve the goal of circular economy. In addition, the method of this embodiment uniformly manages and coordinates the resources of all parties involved in construction waste recycling in the whole region, which helps to improve the classification and recycling efficiency. By promptly and reasonably recycling and utilizing construction waste, the transfer time of garbage can be reduced, thereby significantly reducing the carbon emissions of the entire region or city and making a positive contribution to environmental protection and sustainable development.

[0024] The construction waste mentioned in this embodiment refers to the surplus mud, slag, slurry and other waste generated during the construction, demolition, repair of buildings and the decoration of houses by residents. Classified by source, construction waste can be divided into five categories: land excavation, road excavation, old building demolition, construction and building materials production waste, which are mainly composed of muck, crushed stones, waste mortar, broken bricks and tiles, concrete blocks, asphalt blocks, waste plastics, waste metal materials, waste bamboo and wood, etc. The construction waste management plan aims to effectively handle and dispose of the waste generated at the construction site to reduce the impact on the environment and achieve a reduction in carbon emissions.

[0025] As the construction process progresses, the construction waste is mainly divided into 5 categories, as shown in Table 1.

[0026] Table 1. Classification of Construction Waste

[0027] The building types include rural buildings, building buildings, factory buildings, etc., and the output order of waste types for each building is different.

[0028] In urban building buildings, on the time axis, as the construction progress, the first generated is metal waste, followed by organic, brick and tile, muck and hazardous waste. That is, given the construction progress and construction time of the construction site, it is possible to estimate which type of main construction waste is generated at the construction site during this period.

[0029] Figure 2 It is a schematic flow chart of the intelligent management method for construction waste recycling based on LCA and GIS provided by the embodiment of the present invention. As Figure 2 shown, the method includes the following steps S110 to S150.

[0030] S110. Use BIM technology to classify and integrate construction waste information to obtain a three-dimensional building model with construction waste classification information.

[0031] In this embodiment, the three-dimensional building model with construction waste classification information refers to a three-dimensional model with waste classification information, building structure and building materials and other information.

[0032] In one embodiment, the above step S110 may include steps S111~S115.

[0033] S111. Use BIM technology to create a building information model.

[0034] In this embodiment, the building information model refers to using BIM technology to model and present all aspects of the building in the form of a three-dimensional model, and the model should include all relevant information of the building, including components, materials and equipment, etc.

[0035] S112. Add waste sorting information to the building information model.

[0036] In this embodiment, waste sorting information is added to each component and material in the model to facilitate subsequent classification.

[0037] Specifically, in the building information model (BIM model), waste sorting information is added to each component and material, including information such as the type of material used for the component and the recyclability of the material, which helps to more easily classify construction waste when it is generated.

[0038] S113. Collect construction waste data collected by sensors and Internet of Things devices integrated in the building.

[0039] In this embodiment, integrated sensors and Internet of Things devices monitor and identify construction waste to achieve automated classification.

[0040] Specifically, sensors and Internet of Things devices are integrated in the building for monitoring and identifying construction waste. These devices include cameras, laser scanners, RFID tags, etc., which are used to collect information on construction waste.

[0041] S114. Use BIM technology to analyze and identify the construction waste data, and perform construction waste sorting through a training algorithm.

[0042] In this embodiment, BIM technology is used to analyze and identify the collected construction waste data. Through a training algorithm, automated construction waste sorting can be achieved.

[0043] Specifically, collect data related to construction waste, including building design documents, material lists, construction process records, etc. Label the construction waste data, including classification labels and attribute information, to facilitate the training algorithm to identify different types of waste. Clean, normalize, and process the data to ensure data quality and consistency, and prepare for subsequent algorithm training. Select a suitable machine learning or deep learning model, such as a convolutional neural network (CNN) or a recurrent neural network (RNN), for the classification and identification of construction waste. Use the labeled construction waste dataset to train the selected model so that it can accurately identify and classify different types of construction waste. Optimize and tune the trained model to improve the accuracy and efficiency of construction waste sorting. Integrate the trained model into the BIM system to achieve real-time analysis and identification of construction waste data, thereby realizing the function of automated construction waste sorting.

[0044] Through the above steps, by combining BIM technology with machine learning algorithms, automatic classification and recognition of construction waste can be achieved, improving the efficiency and accuracy of construction waste treatment, and providing support for the sustainable development and resource recycling of the construction industry.

[0045] S115. Establish a real-time monitoring system and data analysis based on the construction waste data to optimize the construction waste management process, so as to obtain a 3D building model with construction waste classification information.

[0046] In this embodiment, a real-time monitoring system is established to ensure the timely sorting and treatment of construction waste. Through BIM technology, waste information can be continuously updated during the construction and use stages of the building, improving the accuracy of the system. Analyze the collected data to optimize the construction waste management process. Through continuous optimization, improve the classification accuracy and treatment efficiency of construction waste.

[0047] Specifically, install sensors at key positions in the construction site and inside the building to monitor the generation, flow, and treatment of construction waste in real time. Collect construction waste-related data through sensors, including information such as type, quantity, and location, to ensure timely acquisition of the latest status of waste. Transmit the data collected by the sensors to the monitoring system in real time to ensure the timeliness and accuracy of the data. Establish a real-time monitoring system that integrates sensor data and displays the real-time situation of construction waste, including the generation volume, classification information, treatment progress, etc. Combine the real-time monitoring system with BIM technology to achieve the update and synchronization of construction waste information during the construction and use stages of the building, improving the accuracy and practicality of the system. Based on BIM technology and machine learning algorithms, achieve automatic identification and classification of construction waste, improving the efficiency and accuracy of construction waste treatment. Set up a warning mechanism for abnormal situations to detect problems in a timely manner and take corresponding measures. At the same time, establish a feedback mechanism to continuously optimize and improve the monitoring system and treatment process.

[0048] Through the above steps, a real-time monitoring system can be established, using BIM technology to continuously update construction waste information, ensuring the timely sorting and treatment of construction waste, improving the accuracy and efficiency of the system, and promoting the sustainable development of the construction industry.

[0049] S120. Use GIS and BIM technologies to conduct spatial analysis and remote control of the construction waste in the 3D building model.

[0050] In this embodiment, by using GIS to conduct spatial analysis on the construction waste site and combining BIM technology and remote control data, the function of opening or unlocking construction waste treatment facilities can be achieved. For example, when it is necessary to recycle steel bars, the password of the steel bar recycling cage can be input on the terminal to open the recycling cage. The system will record information such as the time of transporting the waste, license plate number, and driver, and monitor and manage the recycling process.

[0051] Through digital technology, the intelligent management of construction waste treatment facilities is realized, improving management efficiency and accuracy. It can monitor the construction waste treatment process in real time, including links such as recycling and transportation, ensuring the transparency and controllability of the entire treatment process. The system can record key information such as time and vehicle information, facilitating subsequent data analysis and tracking, and helping to optimize the management process and resource utilization. Through password protection and remote control, the security of construction waste treatment facilities is strengthened, avoiding unauthorized operations and management out-of-control situations. It promotes the effective recycling and utilization of construction waste, reduces resource waste and environmental pollution, and conforms to the concept of sustainable development.

[0052] In summary, by combining GIS, BIM, and remote control technologies, the intelligent system for opening or unlocking construction waste treatment facilities can improve management efficiency, data tracking accuracy, and resource recycling utilization rate. At the same time, it helps to enhance environmental awareness and promote the construction industry to develop in a more sustainable direction.

[0053] In one embodiment, the above step S120 may include steps S121 to S124.

[0054] S121. Obtain construction waste-related data and import it into the GIS system.

[0055] Specifically, collect construction waste-related data, including information such as types, quantities, sources, and treatment methods. Import this data into GIS (Geographic Information System) for spatial analysis and visual display.

[0056] S122. Use BIM and GIS technologies to obtain the three-dimensional building model and the spatial distribution of construction waste.

[0057] In this embodiment, by using BIM (Building Information Modeling) and GIS (Geographic Information System) technologies, obtain the spatial distribution of buildings and construction waste, and achieve the classification of construction waste in space.

[0058] Specifically, using Geographic Information System (GIS) technology, collect the geographic information data around the construction site, including spatial information such as terrain, landform, and road network. Associate and analyze the building information in the BIM model with the geographic information in the GIS system to determine the positional relationship between the building and the construction waste treatment facility in the geographical space. Add corresponding classification marks for the construction waste treatment facility and the waste stacking area in the BIM model to identify and manage different types of construction waste. Use BIM and GIS software to visually display and analyze the integrated data to achieve the classification and management of construction waste in space. Establish a data update mechanism to ensure that the construction waste information in the BIM model and the GIS system can be updated in real time and achieve real-time monitoring of the spatial distribution of construction waste.

[0059] Through the above steps, it is possible to use BIM and GIS technologies to obtain the spatial distribution of buildings and construction waste and achieve the classification of construction waste in space. This will help improve the accuracy and efficiency of construction waste management, promote the reasonable classification and treatment of construction waste, and thus drive the construction industry towards a more sustainable development direction.

[0060] S123. Recycle construction waste through remote control technology.

[0061] In this embodiment, through remote control technology, for example, by entering the password of the steel bar recycling cage on a mobile phone, the recycling cage can be opened. The system records information such as the time of transporting the waste, the license plate number, and the driver to achieve the recycling of construction waste.

[0062] S124. Establish a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

[0063] In this embodiment, establish a data sharing platform to share the collected construction waste data, GIS data, BIM data, etc. with relevant participants, such as relevant departments, waste treatment companies, and construction enterprises, to promote the resource utilization and environmental protection management of construction waste. This helps improve the efficiency and transparency of construction waste treatment and promotes the development of circular economy.

[0064] Specifically, ensure that the collected construction waste data, GIS data, and BIM data comply with unified data standards and formats to facilitate sharing and integration. Build a secure and reliable data sharing platform, which can be a cloud-based data storage and sharing platform, to ensure data security and accessibility. Establish a strict permission management mechanism on the data sharing platform to ensure that only relevant parties can access and use the corresponding data, protecting data privacy and security. Develop clear data sharing agreements, including content such as the scope of data use, time limit, and responsibilities, to regulate data sharing behaviors and clarify the rights and obligations of all parties. Actively promote the benefits of data sharing to relevant departments, waste treatment companies, and construction enterprises, prompting all parties to realize the importance of information sharing for improving the efficiency of construction waste treatment and environmental protection management. Provide relevant training and support to the participating parties to help them understand how to obtain and use the shared construction waste data, GIS data, and BIM data to fully utilize the benefits of data sharing. Establish a supervision mechanism to regularly evaluate the usage of the data sharing platform and make timely adjustments and improvements when problems are found.

[0065] Through the above measures, a data sharing platform can be established to share the collected construction waste data, GIS data, BIM data, etc. with relevant departments, waste treatment companies, and construction enterprises. This will help improve the efficiency and transparency of construction waste treatment, promote the development of circular economy, and drive the in-depth development of construction waste resource utilization and environmental protection management work.

[0066] S130. Obtain information from the monitoring equipment installed in the garbage collection vehicle to drive the garbage collection vehicle to recycle construction waste.

[0067] In this embodiment, by installing sensors and monitoring equipment, such as load cells, GPS positioning devices, and cameras, on the garbage collection cage, real-time monitoring and management of the garbage collection cage can be achieved. Once the sensors detect that the garbage collection cage has reached its full load state, the system will initiate the recycling process of construction waste. Such an intelligent monitoring system can effectively improve the efficiency of garbage collection, ensure the timely removal of construction waste, and thus promote the reuse of resources and the development of circular economy.

[0068] S140. Optimize waste treatment and resource recovery using artificial intelligence technology.

[0069] In this embodiment, in terms of the recycling and reuse of construction waste, GIS can be used for spatial analysis, and BIM and remote control technologies can be used to manage construction waste. For example, when recycling steel bars, enter the password on the mobile phone to open the recycling cage, and the system will record the time of transporting the waste, the license plate number, and the driver information to achieve the recycling of construction waste such as steel bars; thereafter, create a comprehensive waste treatment plan, which requires careful consideration of waste classification, predictive analysis of waste generation, and various other factors, and helps to understand the quantity of construction waste according to the construction progress of the construction site and provide the determined data for the raw materials of green building materials in advance. That is, use artificial intelligence technology to manage construction waste, improve resource utilization efficiency, and reduce the environmental burden.

[0070] In one embodiment, the above step S140 may include steps S141 to S145.

[0071] S141. Conduct a comprehensive waste audit on the building three-dimensional model to obtain an audit result.

[0072] In this embodiment, the audit result refers to the result obtained by conducting a waste audit on the building three-dimensional model.

[0073] Specifically, use BIM to perform 3D scanning on the building three-dimensional model to evaluate the types and quantities of waste generated by the construction project, and conduct waste classification to obtain an audit result; Among them, the process of waste classification is optimized using machine learning.

[0074] In this embodiment, use BIM technology to perform 3D scanning of the building to obtain the detailed structure and information of the building. Combine sensor technology to collect data inside and outside the building, including information such as material types, quantities, and locations. Analyze the scanned data with the help of BIM software to identify the types and quantities of different materials in the building. Use data analysis tools to classify the waste and determine the types and quantities of recyclable and non-recyclable materials. Introduce a BIM recognition system and sensor technology to build an intelligent waste classification platform. Use machine learning algorithms to automatically classify and sort the waste to distinguish between recyclable and non-recyclable materials. Based on real-time data and feedback, continuously optimize the machine learning algorithm to improve the accuracy and efficiency of waste sorting. Conduct data analysis, discover and solve problems in the sorting process, and continuously improve the system performance. Establish a real-time monitoring system to track the waste treatment process, promptly discover problems and take measures. Design a suitable data report and visualization interface to facilitate managers to understand the waste treatment situation and make decisions.

[0075] Through the above steps, it is possible to achieve 3D scanning of the building using BIM, evaluate the types and quantities of waste, achieve intelligent waste classification and sorting, and continuously optimize the processing process through machine learning to improve efficiency and accuracy.

[0076] S142. Set waste treatment goals.

[0077] In this embodiment, to achieve the goals of waste reduction, reuse, and recycling, clear and measurable goals need to be set, and predictive analysis of waste generation needs to be integrated to predict future patterns. At the same time, by analyzing historical data with the help of AI algorithms, future waste generation patterns can be predicted, and resource allocation and waste collection plans can be optimized based on real-time data.

[0078] First of all, clear goals need to be set, such as reducing the amount of waste, increasing the reuse rate or recycling rate of waste, etc. These goals should be specific and measurable so that progress can be monitored and evaluated.

[0079] Next, integrate the predictive analysis of waste generation, which means collecting and analyzing historical data on construction projects, including information such as waste types, quantities, times, and locations of generation. With the help of AI algorithms, these data can be analyzed to discover patterns and trends in waste generation.

[0080] Based on the analysis of historical data, AI algorithms can be used to predict future waste generation patterns. By considering different factors of construction projects, such as scale, type, construction period, etc., the types and quantities of waste expected to be generated in a specific future time period can be predicted.

[0081] Finally, using real-time data, resource allocation and waste collection plans can be continuously optimized. By monitoring real-time data, the frequency, capacity, and method of waste collection can be adjusted to ensure the effective use of resources and the efficient treatment of waste.

[0082] In summary, by setting clear goals, integrating predictive analysis, and using AI algorithms for data analysis, future waste generation patterns can be predicted, and resource allocation and waste collection plans can be continuously optimized based on real-time data to achieve the goals of waste reduction, reuse, and recycling.

[0083] S143. Use BIM to identify and evaluate recycling opportunities.

[0084] In this embodiment, by using BIM technology, recycling opportunities in construction projects can be identified and evaluated. This includes opportunities to use recycled aggregates in building materials and applying BIM technology to improve the efficiency of material recycling, thereby improving the quality of recycled materials.

[0085] First of all, by using BIM technology, various materials used in construction projects can be identified and recorded in detail. By analyzing the building design and structure, it can be determined which materials can be recycled, for example, old concrete can be reused as recycled aggregates.

[0086] Secondly, with the help of BIM technology, the process of material recycling and sorting can be optimized. By marking and tracking the location and quantity of recyclable materials in the building model, these materials can be separated and processed more effectively, ensuring that they are not wasted or mixed with other materials.

[0087] Finally, by applying BIM technology, the quality of recycled materials can be improved. By accurately recording and managing information about recycled materials, such as their sources and quality, it can be ensured that these materials meet relevant standards and requirements, enhancing their reuse value and quality.

[0088] In summary, using BIM to identify and evaluate recycling opportunities, especially the application of recycled aggregates in building materials, and optimizing the sorting of material recycling through BIM technology to improve the quality of recycled materials contribute to achieving the goals of waste reduction and resource recycling in sustainable building projects.

[0089] S144. Develop a comprehensive waste disposal plan based on the audit results, the waste treatment goals, and the recycling opportunities.

[0090] In this embodiment, a comprehensive waste disposal plan is developed for non-recyclable waste, using AI to optimize the selection of landfills, considering environmental impact, distance, and cost. An AI algorithm is integrated to predict the waste disposal cost and dynamically adjust the budget allocation according to real-time cost predictions.

[0091] Specifically, a comprehensive waste disposal plan is developed to take action on non-recyclable waste. With the help of AI technology, the selection of landfills can be optimized, taking into account factors such as environmental impact, distance, and cost. At the same time, an AI algorithm is integrated to predict the cost of waste disposal and flexibly adjust the budget allocation according to real-time cost predictions.

[0092] First of all, for non-recyclable waste, a detailed waste treatment plan needs to be developed. By evaluating different treatment methods, such as landfilling and incineration, we can determine the most suitable solution to handle these wastes. Secondly, using AI technology, we optimize the selection of landfills. By considering various factors, such as environmental impact, distance, and cost, AI can find the most suitable landfill location. This can minimize the negative impact on the environment while reducing transportation costs and time. Then, an AI algorithm is integrated to predict the cost of waste disposal. By analyzing historical data and real-time information, AI can accurately predict the cost of waste disposal, including the costs of treatment, transportation, and other aspects. Finally, the budget allocation is dynamically adjusted according to real-time cost predictions. By continuously monitoring cost changes and prediction results, the budget allocation can be adjusted in a timely manner to ensure the smooth implementation of the waste disposal plan and maximize cost savings.

[0093] In summary, using AI to optimize landfill selection, predict waste disposal costs, and dynamically adjust budget allocation helps to effectively handle non-recyclable waste and reduce costs and improve efficiency during the waste disposal process.

[0094] S145. Continuously monitor and improve the waste disposal process using AI analysis tools and machine learning tools.

[0095] Specifically, implement AI analysis tools to continuously monitor waste management activities. By using machine learning techniques, historical waste management data can be analyzed to identify patterns and areas for improvement.

[0096] Suppose N construction sites all adopt the artificial intelligence-based construction waste recycling management method for treatment, then various types of waste recycling data of N construction sites will be obtained. Next, the life cycle assessment (LCA) method can be used to screen, sort, train, and optimize this data.

[0097] First, an AI analysis tool can be used to monitor and analyze this waste recycling data. AI can identify potential problems and bottlenecks in the waste management process, such as low recycling efficiency and resource waste. Second, with the help of machine learning techniques, in-depth analysis of historical waste management data can be carried out to identify patterns and trends therein. By understanding the impact of different factors on waste management, areas for improvement can be found, and corresponding measures and strategies can be formulated. Finally, using the LCA method, the data can be screened, sorted, trained, and optimized. LCA considers the entire life cycle from resource acquisition to waste disposal. By evaluating and optimizing waste management data, resource consumption can be reduced and environmental impacts can be minimized.

[0098] In summary, by implementing AI analysis tools to continuously monitor waste management activities and using machine learning to analyze historical waste management data to identify patterns and areas for improvement. Finally, using the LCA method to screen, sort, train, and optimize this data helps to improve the efficiency and sustainability of construction waste recycling management.

[0099] S150. Optimize the construction waste recycling process through life cycle assessment and geographic information system.

[0100] In this embodiment, the spatial and temporal analysis combining life cycle assessment and geographic information system can effectively optimize the construction waste recycling process. It mainly optimizes the waste recycling process involved in steps S120 - S140.

[0101] In one embodiment, the above step S150 may include steps S151 - S155.

[0102] S151. Collect relevant information on construction waste.

[0103] In this embodiment, information such as the generation quantity, type, and source location of construction waste is collected. At the same time, the location and capacity data of waste treatment facilities (such as recycling stations and landfills) are collected. In addition, relevant infrastructure data (such as road networks and traffic flows) and time-dynamic data (such as the time distribution of construction activities) also need to be collected.

[0104] S152. Perform spatial analysis and time analysis using a geographic information system based on the collected relevant information to obtain an analysis result.

[0105] In this embodiment, the analysis result includes two results obtained by performing spatial analysis and time analysis using a geographic information system based on the collected relevant information.

[0106] In one embodiment, the above step S152 may include steps S1521 to S1522.

[0107] S1521. Determine the geographical relationship between the construction waste generation points and the treatment facilities using a spatial analysis tool based on the collected relevant information, find the areas where the transportation efficiency meets the requirements, and propose an optimization plan. S1522. Combine the time characteristics of construction activities, analyze the time distribution of construction waste generation, and predict the peak generation period. Among them, the analysis result includes the optimization plan and the peak generation period.

[0108] In this embodiment, in GIS, spatial analysis mainly involves the creation, editing, and analysis of map data to reveal the relationships and patterns between different geographical elements. Use the spatial analysis tool of GIS to identify the geographical relationship between the construction waste generation points and the treatment facilities. By analyzing the distance between the generation location of construction waste and the recycling station, areas with low transportation efficiency can be found, and an optimization plan can be proposed, such as adding temporary recycling points or optimizing the layout of recycling stations. For the recycling of construction waste, the specific steps of spatial analysis optimization are as follows: Generation source location, specifically using GIS software to analyze the geographical location data of the main sources of construction waste such as concentrated areas of construction activities and large construction sites to determine the main generation points of construction waste; facility layout, specifically evaluating the distribution of existing recycling facilities through GIS spatial analysis tools, identifying service blind spots and determining the optimal locations to add new facilities or adjust the locations of existing facilities; transportation network, specifically using GIS to analyze the best transportation routes for construction waste from the generation source to the treatment facility, considering factors such as the shortest distance and traffic congestion to find the optimal logistics plan; hot spot area analysis, specifically identifying and marking hot spot areas with a large amount of construction waste generated through GIS spatial analysis and giving priority to recycling services; multi-criteria decision analysis, specifically using GIS multi-criteria decision analysis tools, combining the weights of various indicators, evaluating different recycling strategies, selecting the best plan and providing decision-making support.

[0109] In addition, combining the seasonality and periodicity of construction activities, analyze the temporal distribution characteristics of construction waste generation, predict the peak periods of waste generation, so as to make corresponding logistics arrangements and resource allocations before the peak demand. Temporal analysis involves analyzing data that changes over time to identify patterns and trends. For the recycling of construction waste, the specific optimization steps of temporal analysis are as follows: Generation pattern, by using time series data analysis to analyze the seasonal and periodic patterns of construction waste generation, predicting future waste generation volumes to provide a basis for resource planning; processing time, by evaluating the time required for construction waste from generation to treatment, identifying processing bottlenecks and optimizing the processing process to reduce processing time; activity scheduling, by combining generation pattern and processing time data, formulating a schedule and resource scheduling plan for the recycling of construction waste to ensure sufficient resources are invested during peak periods.

[0110] Through the above optimization steps of spatial and temporal analysis, the efficient management and resource utilization of the construction waste recycling process can be achieved, improving the recycling efficiency and reducing environmental impacts. At the same time, the application of GIS and temporal analysis tools can also help relevant departments better plan and monitor the construction waste recycling process to achieve sustainable development goals.

[0111] S153. Conduct an environmental impact assessment using life cycle assessment based on the collected relevant information to obtain an assessment result.

[0112] In this embodiment, the assessment result refers to the result obtained by conducting an environmental impact assessment on the relevant information using the LCA algorithm.

[0113] In one embodiment, the above step S153 may include steps S1531 to S1533.

[0114] S1531. Set the goals for the entire life cycle of the construction project; S1532. Conduct a life cycle inventory analysis and a life cycle impact assessment based on the collected relevant information using life cycle assessment to obtain the LCA assessment results.

[0115] In this embodiment, the LCA assessment results refer to the results obtained by conducting a life cycle inventory analysis and a life cycle impact assessment based on the collected relevant information using life cycle assessment.

[0116] S1533. Generate optimization suggestions based on the LCA assessment results in combination with the target to obtain the assessment results.

[0117] In this embodiment, LCA is used to evaluate the environmental impact in the process of construction waste recycling, including the energy consumption and emissions in each stage of waste collection, transportation, treatment, and recycling. Through LCA, the stage with the greatest environmental impact in the entire recycling chain can be identified, and improvement measures can be proposed accordingly. To implement the specific steps of the above LCA assessment in construction waste recycling, it can be carried out according to the following method: Goal and scope definition: Clearly define the goal and scope of LCA, including all stages of the entire life cycle of construction waste recycling, that is, from design, construction to use and demolition, as well as the waste treatment stage, identify the energy use and resource consumption in this process, and finally determine the goal of LCA as improving the waste recycling rate; determine the specific content of the assessment, such as the types, quantities, sources of waste, etc.

[0118] Life cycle inventory analysis (LCI): Identify the life cycle stages, that is, divide the construction waste recycling process into stages such as raw material acquisition, transportation, treatment, and recycling; establish an inventory, that is, list the inputs and outputs of each stage, including energy consumption, emissions, etc. Specifically, the inputs include raw materials, energy, chemicals, etc., while the outputs include products, waste, emissions, etc.; collect data, that is, collect the data involved in each stage, including the types, quantities, sources of construction waste, and ensure the accuracy and integrity of the data; quantify the data, that is, convert the data into comparable units, usually in units of mass or energy, which helps to compare between different stages and different products; standardize the data, that is, standardize the data for comparison and comprehensive analysis to ensure that they reflect the real life cycle situation; integrate the data, that is, summarize the data of each stage to form a comprehensive life cycle inventory, which helps to form a comprehensive view of life cycle impacts.

[0119] Life Cycle Impact Assessment (LCIA): Evaluate environmental impacts, that is, assess the environmental impacts during the construction waste recycling process by considering factors such as resource consumption, energy use, greenhouse gas emissions, etc.; identify environmental hotspots, that is, determine the links that may have significant impacts on the environment, such as stages with high energy consumption and serious emissions, and compare the environmental impacts of different waste treatment methods to determine the best waste management method.

[0120] Optimization suggestions: Based on the results of LCIA, put forward optimization suggestions, such as reducing the generation of construction waste, increasing the recycling rate, choosing more environmentally friendly treatment methods, etc.; formulate improvement measures: for the links with large environmental impacts, put forward specific improvement measures and management suggestions; Continuous monitoring and improvement: Establish a monitoring mechanism to regularly evaluate the environmental performance of the construction waste recycling process and continuously improve and optimize management measures.

[0121] By implementing the above steps, the environmental impacts during the construction waste recycling process can be comprehensively evaluated, and effective optimization suggestions can be put forward, thus promoting the sustainable development of construction waste recycling.

[0122] S154. Develop an optimization strategy according to the analysis results and evaluation results.

[0123] In this embodiment, the optimization strategy refers to the optimization plan for construction waste recycling.

[0124] Specifically, use Geographic Information System (GIS) technology to analyze the spatial and temporal factors during the construction waste collection and treatment process. According to the location information such as waste generation points, collection points, and treatment facilities, optimize the waste collection route to reduce the transportation distance and energy consumption. According to the results of the Life Cycle Assessment (LCA) conducted, identify the links with the greatest environmental impacts during the construction waste recycling process. Based on these analysis results, develop specific optimization strategies.

[0125] S155. Send the optimization strategy to the corresponding equipment and continuously monitor the effect of the recycling process.

[0126] Specifically, put the developed optimization strategy into practice, such as optimizing the waste collection route, improving the recycling technology, etc. Ensure that relevant personnel understand and operate according to the strategy to reduce environmental impacts. Use tools such as GIS and LCA to continuously monitor the recycling process to evaluate the effect of the implemented strategy. Through real-time data collection and analysis, judge whether the optimization strategy achieves the expected goal and make adjustments according to the actual effect. According to the monitoring results, identify and analyze the problems in the recycling process and take improvement measures in a timely manner. Continuous improvement is the key to ensuring the sustainable development of the construction waste recycling process.

[0127] By implementing the above steps, the environmental impact of the construction waste recycling process can be minimized, and the effective utilization of resources can be achieved. Specific benefits include: Reduce energy consumption and emissions: By optimizing waste collection routes and transportation distances, energy consumption and greenhouse gas emissions are reduced.

[0128] Improve resource recovery rate: Improve recycling technologies and treatment methods, increase the recyclability of waste, and reduce the demand for new resources.

[0129] Environmental protection: Reduce the negative impact of waste on the environment and protect the stability of natural resources and ecosystems.

[0130] Sustainable development: By comprehensively considering environmental, economic, and social factors, achieve the sustainable development of the construction industry and promote the popularization of green buildings and circular economy.

[0131] These implementation steps and benefits will help the construction industry effectively manage resources and the environment during the waste recycling process and achieve the goal of sustainable development.

[0132] For example: Suppose there is a large-scale construction project underway. Using this intelligent management method, construction waste can be efficiently classified, recycled, and processed.

[0133] First, use BIM technology to classify and integrate construction waste information. Through the building information model, waste classification information is added to the building's 3D model. At the same time, collect the data of construction waste collected by the integrated sensors and Internet of Things devices in the building.

[0134] Next, use GIS and BIM technologies to conduct spatial analysis and remote control of the construction waste in the building's 3D model. By importing the relevant data of construction waste in the GIS system, the spatial distribution of the building's 3D model and construction waste can be obtained. Then, use remote control technology to recycle the construction waste.

[0135] During this process, a data sharing platform can be established to share the collected construction waste data, GIS data, and BIM data to achieve information interconnection and collaborative management.

[0136] In addition, optimize waste treatment and resource recovery through artificial intelligence technology. Through a comprehensive waste audit of the building's 3D model, waste treatment goals can be set, and BIM can be used to identify and evaluate recycling opportunities. Based on the audit results, waste treatment goals, and recycling opportunities, a comprehensive waste disposal plan can be formulated. At the same time, use AI analysis tools and machine learning tools to continuously monitor and improve the waste disposal process.

[0137] Finally, optimize the construction waste recycling process through life cycle assessment and geographic information system. Collect relevant information on construction waste, and use the geographic information system for spatial analysis and temporal analysis to obtain analysis results. At the same time, adopt life cycle assessment for environmental impact assessment to obtain assessment results. Develop optimization strategies based on the analysis results and assessment results, and continuously monitor the effectiveness of the recycling process.

[0138] The above is a specific example of the intelligent management method for construction waste recycling based on LCA and GIS. This method realizes the efficient management and resource recycling of construction waste through technical means, and has positive significance for promoting sustainable development.

[0139] In addition, as Figure 3 shown, it presents the spatial distribution of the main sources of construction waste and waste treatment and recycling sites analyzed by geographic information system (GIS) technology. The blue parts in the figure represent the main sources of construction waste, which usually include construction sites, demolition sites, and other places related to construction activities, and they are the main locations where construction waste is generated. While the red parts indicate waste treatment and recycling sites, which include construction waste landfills, crushing stations, recycled material processing plants, etc., responsible for receiving, treating, and recycling construction waste. Through the GIS analysis map, the relative position relationship between the construction waste production sources and treatment sites can be intuitively observed, as well as their distribution within the entire city or region. This is of great significance for optimizing waste collection routes, improving resource recycling efficiency, reducing environmental pollution, etc.

[0140] Traditional methods for classifying and treating construction waste rely on manual operations, with low efficiency and difficult to guarantee accuracy. In contrast, artificial intelligence technology combined with technical means such as GIS and BIM can efficiently classify construction waste, improving classification efficiency and accuracy. For example, use BIM technology to conduct 3D scanning of construction waste to achieve precise classification of different types of waste, thereby enhancing classification efficiency and accuracy.

[0141] Traditional construction waste treatment methods rely on manual operations, which are time-consuming and energy-consuming. While artificial intelligence technology realizes the automatic treatment of construction waste through automated control technology. For example, use robot technology to automatically sort and treat construction waste, reducing manual intervention and improving treatment efficiency.

[0142] Traditional construction waste treatment is often limited to simple classification and processing, which makes it difficult to maximize resource utilization. The method of this embodiment can achieve fine processing of construction waste and maximize resource utilization with the help of data analysis and optimization algorithms in artificial intelligence technology. For example, GIS, BIM and artificial intelligence technology are combined to analyze and predict construction waste, so as to achieve fine resource utilization and maximum recycling. That is, the artificial intelligence technology of the method of this embodiment can be finely classified and processed through automated and intelligent means, and construction waste can be converted into recycled building materials, energy, etc., to achieve resource recycling. By obtaining the construction waste situation of each construction site in a certain area in real time, resources can be managed in a unified manner, recycling efficiency can be improved, transit time can be reduced, and carbon emissions can be significantly reduced.

[0143] GIS, BIM and artificial intelligence technologies are used to analyze and predict construction waste to achieve refined resource utilization and maximum recycling; at the same time, life cycle assessment and spatial and temporal analysis of geographic information systems are combined to effectively optimize the construction waste recycling process.

[0144] Traditional construction waste recycling methods consume a lot of manpower and material resources and are inefficient. The method of this embodiment uses BIM, machine learning and other technologies to achieve automatic classification and identification of construction waste, improve recycling efficiency, and reduce manual workload and time.

[0145] The method of this embodiment reduces manual involvement and reduces work risks through automation and intelligent technology, improves processing and recycling accuracy and efficiency, reduces environmental impact, and enhances environmental friendliness.

[0146] The above-mentioned intelligent management method for construction waste recycling based on LCA and GIS uses BIM technology to construct a three-dimensional building model with construction waste classification information, uses GIS and BIM technology to perform spatial analysis and remote control of construction waste, obtains monitoring information of monitoring equipment in the recycling process, uses artificial intelligence technology for optimization, and optimizes the construction waste recycling process through life cycle assessment and geographic information system, thereby realizing automatic classification and identification of construction waste, improving classification and recycling efficiency, reducing the workload and time of manual classification and processing, and realizing resource utilization of construction waste.

[0147] Figure 4 FIG. 3 is a schematic block diagram of an intelligent management device 300 for construction waste recycling based on LCA and GIS provided by an embodiment of the present invention. Figure 4As shown, corresponding to the above intelligent management method for construction waste recycling based on LCA and GIS, the present invention also provides an intelligent management device 300 for construction waste recycling based on LCA and GIS. The intelligent management device 300 for construction waste recycling based on LCA and GIS includes units for executing the above intelligent management method for construction waste recycling based on LCA and GIS, and this device can be configured in a server. Specifically, please refer to Figure 4 , the intelligent management device 300 for construction waste recycling based on LCA and GIS includes a model generation unit 301, an analysis and control unit 302, an acquisition unit 303, an artificial intelligence optimization unit 304, and a recycling optimization unit 305.

[0148] The model generation unit 301 is used to classify and integrate construction waste by using BIM technology to obtain a three-dimensional building model with construction waste classification information; the analysis and control unit 302 is used to perform spatial analysis and remote control on the construction waste of the three-dimensional building model by using GIS and BIM technologies; the acquisition unit 303 is used to obtain the information of the monitoring device installed in the garbage collection vehicle to drive the garbage collection vehicle to recycle construction waste; the artificial intelligence optimization unit 304 is used to optimize waste treatment and resource recycling by using artificial intelligence technology; the recycling optimization unit 305 is used to optimize the construction waste recycling process through life cycle assessment and geographic information system.

[0149] In one embodiment, the model generation unit 301 includes a model creation subunit, an information addition subunit, a data collection subunit, a classification subunit, and a monitoring subunit.

[0150] The model creation subunit is used to create a building information model by using BIM technology; the information addition subunit is used to add garbage classification information to the building information model; the data collection subunit is used to collect the building waste data collected by the sensors and Internet of Things devices integrated in the building; the classification subunit is used to analyze and identify the building waste data by using BIM technology and classify the construction waste through a training algorithm; the monitoring subunit is used to establish a real-time monitoring system and data analysis based on the building waste data to optimize the construction waste management process to obtain a three-dimensional building model with construction waste classification information.

[0151] In one embodiment, the analysis and control unit 302 includes an import subunit, a situation acquisition subunit, a control subunit, and a sharing subunit.

[0152] An import subunit for obtaining construction waste-related data and importing it into the GIS system; a situation acquisition subunit for obtaining the three-dimensional building model and the spatial distribution of construction waste by using BIM and GIS technologies; a control subunit for recycling construction waste through remote control technology; a sharing subunit for establishing a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

[0153] In one embodiment, the artificial intelligence optimization unit 304 includes an audit subunit, a processing target setting subunit, an opportunity assessment subunit, a plan formulation subunit, and a learning subunit.

[0154] The audit subunit is used to conduct a comprehensive waste audit on the three-dimensional building model to obtain an audit result; the processing target setting subunit is used to set waste treatment targets; the opportunity assessment subunit is used to identify and evaluate recycling opportunities by using BIM; the plan formulation subunit is used to formulate a comprehensive waste disposal plan according to the audit result, the waste treatment target, and the recycling opportunity; the learning subunit is used to continuously monitor and improve the waste disposal process by using AI analysis tools and machine learning tools.

[0155] In one embodiment, the audit subunit is used to perform a 3D scan on the three-dimensional building model by using BIM to evaluate the type and quantity of waste generated by a construction project and classify the waste to obtain an audit result; wherein, the process of waste classification is optimized by using machine learning.

[0156] In one embodiment, the recycling optimization unit 305 includes a relevant information collection subunit, an analysis subunit, an impact assessment subunit, a strategy formulation subunit, and a sending subunit.

[0157] The relevant information collection subunit is used to collect relevant information on construction waste; the analysis subunit is used to perform spatial analysis and temporal analysis by using a geographic information system according to the collected relevant information to obtain an analysis result; the impact assessment subunit is used to perform environmental impact assessment by using life cycle assessment according to the collected relevant information to obtain an assessment result; the strategy formulation subunit is used to formulate an optimization strategy according to the analysis result and the assessment result; the sending subunit is used to send the optimization strategy to the corresponding device and continuously monitor the effect of the recycling process.

[0158] In one embodiment, the analysis subunit includes a spatial analysis module and a temporal analysis module.

[0159] A spatial analysis module, which is used to determine the geographical relationship between the construction waste generation points and the treatment facilities by using spatial analysis tools according to the collected relevant information, find out the areas where the transportation efficiency meets the requirements, and propose optimization solutions; a time analysis module, which is used to analyze the time distribution of the generated construction waste in combination with the time characteristics of construction activities and predict the peak generation period; wherein, the analysis results include optimization solutions and the peak generation period.

[0160] In one embodiment, the impact assessment sub-unit includes a target setting module, an evaluation module, and a recommendation generation module.

[0161] The target setting module is used to set the goals for the entire life cycle of a construction project; the evaluation module is used to perform life cycle inventory analysis and life cycle impact assessment according to the collected relevant information by using life cycle assessment to obtain the LCA assessment results; the recommendation generation module is used to generate optimization recommendations according to the LCA assessment results in combination with the goals to obtain the assessment results.

[0162] It should be noted that those skilled in the art can clearly understand that the specific implementation processes of the above-mentioned intelligent management device 300 for construction waste recycling based on LCA and GIS and each unit can refer to the corresponding descriptions in the foregoing method embodiments. For the sake of convenience and conciseness of description, they will not be elaborated here.

[0163] The above-mentioned intelligent management device 300 for construction waste recycling based on LCA and GIS can be implemented in the form of a computer program, and this computer program can run on a computer device as shown in Figure 5 shown.

[0164] Please refer to Figure 5 , Figure 5 which is a schematic block diagram of a computer device provided by an embodiment of the present application. This computer device 500 can be a server. Among them, the server can be an independent server or a server cluster composed of multiple servers.

[0165] Refer to Figure 5 , this computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501. Among them, the memory can include a non-volatile storage medium 503 and an internal memory 504.

[0166] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. This computer program 5032 includes program instructions. When the program instructions are executed, the processor 502 can execute an intelligent management method for construction waste recycling based on LCA and GIS.

[0167] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0168] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute an intelligent management method for construction waste recycling based on LCA and GIS.

[0169] The network interface 505 is used for network communication with other devices. Those skilled in the art can understand that Figure 5 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device 500 to which the solution of this application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0170] Among them, the processor 502 is used to run the computer program 5032 stored in the memory to implement the following steps: Use BIM technology to classify and integrate construction waste information to obtain a three-dimensional building model with construction waste classification information; use GIS and BIM technology to perform spatial analysis and remote control of the construction waste in the three-dimensional building model; obtain the information of the monitoring device installed in the garbage collection vehicle to drive the garbage collection vehicle to recycle construction waste; use artificial intelligence technology to optimize waste treatment and resource recovery; optimize the construction waste recycling process through life cycle assessment and geographic information system.

[0171] In an embodiment, when the processor 502 implements the step of using BIM technology to classify and integrate construction waste information to obtain a three-dimensional building model with construction waste classification information, the following steps are specifically implemented: Use BIM technology to create a building information model; add garbage classification information to the building information model; collect the construction waste data collected by the sensors and Internet of Things devices integrated in the building; use BIM technology to analyze and identify the construction waste data, and perform construction waste classification through training algorithms; establish a real-time monitoring system and data analysis based on the construction waste data to optimize the construction waste management process to obtain a three-dimensional building model with construction waste classification information.

[0172] In an embodiment, when the processor 502 implements the step of using GIS and BIM technology to perform spatial analysis and remote control of the construction waste in the three-dimensional building model, the following steps are specifically implemented: Obtain relevant data on construction waste and import it into the GIS system; use BIM and GIS technologies to obtain the three-dimensional building model and the spatial distribution of construction waste; recycle construction waste through remote control technology; establish a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

[0173] In one embodiment, when the processor 502 implements the step of optimizing waste treatment and resource recovery using artificial intelligence technology, the following steps are specifically implemented: Conduct a comprehensive waste audit on the three-dimensional building model to obtain an audit result; set waste treatment goals; use BIM to identify and evaluate recycling opportunities; formulate a comprehensive waste disposal plan based on the audit result, the waste treatment goals, and the recycling opportunities; continuously monitor and improve the waste disposal process using AI analysis tools and machine learning tools.

[0174] In one embodiment, when the processor 502 implements the step of conducting a comprehensive waste audit on the three-dimensional building model to obtain an audit result, the following steps are specifically implemented: Use BIM to perform a 3D scan on the three-dimensional building model to evaluate the types and quantities of waste generated by the construction project and classify the waste to obtain an audit result; Among them, the process of waste classification is optimized using machine learning.

[0175] In one embodiment, when the processor 502 implements the step of optimizing the construction waste recycling process through life cycle assessment and geographic information system, the following steps are specifically implemented: Collect relevant information on construction waste; perform spatial analysis and time analysis using the geographic information system based on the collected relevant information to obtain an analysis result; perform environmental impact assessment using life cycle assessment based on the collected relevant information to obtain an assessment result; formulate an optimization strategy based on the analysis result and the assessment result; send the optimization strategy to the corresponding device and continuously monitor the effect of the recycling process.

[0176] In one embodiment, when the processor 502 implements the step of performing spatial analysis and time analysis using the geographic information system based on the collected relevant information to obtain an analysis result, the following steps are specifically implemented: Use spatial analysis tools based on the collected relevant information to determine the geographical relationship between the construction waste generation points and the treatment facilities, find areas where the transportation efficiency meets the requirements, and propose an optimization plan; combine the time characteristics of construction activities to analyze the time distribution of construction waste generation and predict the peak generation period; Among them, the analysis result includes the optimization plan and the peak generation period.

[0177] In one embodiment, when the processor 502 implements the step of performing an environmental impact assessment using life cycle assessment based on the collected relevant information to obtain an assessment result, the specific implementation is as follows: Set the goals for the entire life cycle of the construction project; perform life cycle inventory analysis and life cycle impact assessment using life cycle assessment based on the collected relevant information to obtain the LCA assessment result; generate optimization suggestions based on the LCA assessment result in combination with the goals to obtain the assessment result.

[0178] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0179] Those of ordinary skill in the art can understand that all or part of the processes in the methods of implementing the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, and the storage medium is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0180] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to execute the following steps: Classify and integrate the information of construction waste using BIM technology to obtain a three-dimensional building model with construction waste classification information; perform spatial analysis and remote control of the construction waste in the three-dimensional building model using GIS and BIM technologies; obtain the information of the monitoring device installed in the garbage collection vehicle to drive the garbage collection vehicle to collect construction waste; optimize waste treatment and resource recovery using artificial intelligence technology; optimize the construction waste recycling process through life cycle assessment and geographic information system.

[0181] In one embodiment, when the processor executes the computer program to implement the step of classifying and integrating information of construction waste using BIM technology to obtain a 3D building model with construction waste classification information, the specific implementation steps are as follows: Create a building information model using BIM technology; add waste classification information to the building information model; collect construction waste data collected by sensors and Internet of Things devices integrated in the building; analyze and identify the construction waste data using BIM technology, and classify the construction waste through a training algorithm; establish a real-time monitoring system based on the construction waste data and optimize the construction waste management process through data analysis to obtain a 3D building model with construction waste classification information.

[0182] In one embodiment, when the processor executes the computer program to implement the step of spatially analyzing and remotely controlling the construction waste of the 3D building model using GIS and BIM technologies, the specific implementation steps are as follows: Obtain construction waste-related data and import it into the GIS system; use BIM and GIS technologies to obtain the spatial distribution of the 3D building model and construction waste; recycle the construction waste through remote control technology; establish a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

[0183] In one embodiment, when the processor executes the computer program to implement the step of optimizing waste treatment and resource recovery using artificial intelligence technology, the specific implementation steps are as follows: Conduct a comprehensive waste audit on the 3D building model to obtain an audit result; set waste treatment goals; use BIM to identify and evaluate recycling opportunities; formulate a comprehensive waste disposal plan based on the audit result, the waste treatment goals, and the recycling opportunities; continuously monitor and improve the waste disposal process using AI analysis tools and machine learning tools.

[0184] In one embodiment, when the processor executes the computer program to implement the step of conducting a comprehensive waste audit on the 3D building model to obtain an audit result, the specific implementation steps are as follows: Use BIM to perform a 3D scan on the 3D building model to evaluate the type and quantity of waste generated by the construction project and classify the waste to obtain an audit result; Among them, the process of waste classification is optimized using machine learning.

[0185] In one embodiment, when the processor executes the computer program to implement the step of optimizing the construction waste recycling process through life cycle assessment and geographic information system, the specific implementation steps are as follows: Collect relevant information on construction waste; perform spatial analysis and temporal analysis using a Geographic Information System (GIS) based on the collected relevant information to obtain an analysis result; conduct an environmental impact assessment using Life Cycle Assessment (LCA) based on the collected relevant information to obtain an assessment result; formulate an optimization strategy according to the analysis result and the assessment result; send the optimization strategy to the corresponding equipment, and continuously monitor the effectiveness of the recycling process.

[0186] In one embodiment, when the processor executes the computer program to implement the step of performing spatial analysis and temporal analysis using a Geographic Information System (GIS) based on the collected relevant information to obtain an analysis result, the following steps are specifically implemented: Determine the geographical relationship between the construction waste generation points and the treatment facilities using a spatial analysis tool based on the collected relevant information, identify areas where the transportation efficiency meets the requirements, and propose an optimization plan; analyze the temporal distribution of construction waste generation in combination with the temporal characteristics of construction activities, and predict the peak generation period. Among them, the analysis result includes the optimization plan and the peak generation period.

[0187] In one embodiment, when the processor executes the computer program to implement the step of conducting an environmental impact assessment using Life Cycle Assessment (LCA) based on the collected relevant information to obtain an assessment result, the following steps are specifically implemented: Set the goals for the entire life cycle of the construction project; perform life cycle inventory analysis and life cycle impact assessment using Life Cycle Assessment (LCA) based on the collected relevant information to obtain the LCA assessment result; generate optimization suggestions based on the LCA assessment result in combination with the goals to obtain the assessment result.

[0188] The storage medium can be various computer-readable storage media such as a USB flash drive, a mobile hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disc that can store program codes.

[0189] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0190] In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0191] The steps in the method embodiments of the present invention can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of the present invention can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0192] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0193] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. The intelligent management method for construction waste recycling based on LCA and GIS is characterized by: include: Use BIM technology to classify and integrate construction waste to obtain a three-dimensional building model with construction waste classification information; Using GIS and BIM technology to perform spatial analysis and remote control of construction waste in the three-dimensional model of the building; Obtain information from monitoring equipment installed in a garbage collection truck to drive the garbage collection truck to collect construction waste; Using artificial intelligence technology to optimize waste treatment and resource recovery; Optimizing construction waste recycling processes through life cycle assessment and geographic information systems.

2. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 1 is characterized in that: The method of using BIM technology to classify and integrate construction waste to obtain a three-dimensional building model with construction waste classification information includes: Use BIM technology to create building information models; adding garbage classification information to the building information model; Collect construction waste data collected by sensors and IoT devices integrated in buildings; Analyze and identify the construction waste data using BIM technology, and classify the construction waste using a training algorithm; A real-time monitoring system and data analysis are established based on the construction waste data to optimize the construction waste management process, so as to obtain a three-dimensional building model with construction waste classification information.

3. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 1 is characterized in that: The use of GIS and BIM technology to perform spatial analysis and remote control of construction waste in the three-dimensional building model includes: Obtain construction waste related data and import it into the GIS system; Use BIM and GIS technology to obtain the three-dimensional model of the building and the spatial distribution of construction waste; Recycling of construction waste through remote control technology; Establish a data sharing platform to share the collected construction waste data, GIS data, and BIM data.

4. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 1 is characterized in that: The use of artificial intelligence technology to optimize waste treatment and resource recovery includes: Conducting a comprehensive waste audit on the three-dimensional model of the building to obtain audit results; setting waste disposal targets; Using BIM to identify and assess recycling opportunities; Develop a comprehensive waste disposal plan based on said audit results, said waste treatment goals, and said recycling opportunities; Employ AI analytics and machine learning tools to continuously monitor and improve the waste disposal process.

5. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 4 is characterized in that: A comprehensive waste audit is conducted on the three-dimensional building model to obtain audit results, including: 3D scanning of the three-dimensional model of the building using BIM to assess the type and amount of waste generated by the construction project and to classify the waste to obtain audit results; Among them, the process of waste classification is optimized using machine learning.

6. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 1 is characterized in that: The optimization of construction waste recycling process through life cycle assessment and geographic information system includes: Collect relevant information on construction waste; Based on the collected relevant information, use geographic information system to conduct spatial analysis and temporal analysis to obtain analysis results; Conduct environmental impact assessment using life cycle assessment based on the collected relevant information to obtain assessment results; Formulate an optimization strategy based on the analysis and evaluation results; The optimization strategy is sent to the corresponding device, and the effect of the recycling process is continuously monitored.

7. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 6 is characterized in that: The spatial analysis and temporal analysis are performed using a geographic information system based on the collected relevant information to obtain analysis results, including: Based on the collected relevant information, spatial analysis tools are used to determine the geographical relationship between construction waste generation points and treatment facilities, find out the areas where transportation efficiency meets the requirements, and propose optimization plans; Combined with the time characteristics of construction activities, the time distribution of construction waste generation is analyzed to predict the peak period of generation; The analysis results include optimization plans and peak periods.

8. The intelligent management method for construction waste recycling based on LCA and GIS according to claim 6 is characterized in that: The environmental impact assessment is conducted using life cycle assessment based on the collected relevant information to obtain the assessment results, including: Setting goals for the entire life cycle of a construction project; Use life cycle assessment to conduct life cycle inventory analysis and life cycle impact assessment based on the collected relevant information to obtain LCA assessment results; Generate optimization suggestions based on the LCA evaluation results and the objectives to obtain evaluation results.

9. The intelligent management device for construction waste recycling based on LCA and GIS is characterized by: include: A model generation unit, used to classify and integrate construction waste using BIM technology to obtain a three-dimensional building model with construction waste classification information; An analysis and control unit, used for performing spatial analysis and remote control of the construction waste of the three-dimensional building model by using GIS and BIM technology; An acquisition unit, used to acquire information from a monitoring device installed in a garbage collection vehicle, so as to drive the garbage collection vehicle to collect construction waste; AI Optimization Unit, which uses AI technology to optimize waste treatment and resource recovery; Recycling Optimization Unit for optimizing the construction waste recycling process through life cycle assessment and geographic information systems.

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