Building construction engineering carbon emission visualization method and system

Abstract

The invention provides a building construction engineering carbon emission visualization method and system, and the method comprises the steps: building a three-dimensional model of a construction site, and the three-dimensional model at least comprises a constructor foundation model, a building foundation model and a construction equipment foundation model; identifying constructors, buildings and construction equipment in a shot picture according to the shot picture of the monitoring camera, calculating carbon emission values of the constructors, the buildings and the construction equipment in real time, and meanwhile, matching a corresponding constructor basic model, a building basic model and a construction equipment basic model; according to the carbon emission numerical value, performing three-channel hybrid coding processing on each basic model to obtain a coding result, and displaying the coding result; wherein the coding result comprises hue, lightness and saturation, the hue is used for identifying the carbon emission source type, the lightness is used for representing the real-time emission intensity, the saturation is used for mapping the emission trend, and finally visualization of building construction engineering carbon emission is achieved.

Description

Technical Field

[0001] This invention belongs to the field of carbon emission visualization technology, and specifically relates to a method and system for visualizing carbon emissions in building construction projects. Background Technology

[0002] In the long run, controlling carbon emissions is conducive to the sustainable development of society and the economy. Current urban construction has clear requirements for carbon emissions from building construction projects. Specifically, regulations have been established regarding the scope, methods, and data collection for calculating building carbon emissions, providing a basis for the accounting of carbon emissions from building construction projects. It is clearly stipulated that the time boundary for calculating carbon emissions during the building construction phase should be from the start of the project to the completion and acceptance of the project, and that carbon emissions generated from the energy consumed during the use of machinery, small tools, temporary facilities, etc., within the construction site area should be included.

[0003] Currently, carbon emission data is often presented in numerical form, which does not provide a clear and intuitive representation of carbon emissions from different parts of a building construction project, thus affecting the user experience. Summary of the Invention

[0004] Based on this, the present invention provides a method and system for visualizing carbon emissions from building construction projects, which aims to visualize carbon emissions from building construction projects so that users can intuitively understand the distribution of carbon emissions and improve user experience.

[0005] A first aspect of this invention provides a method for visualizing carbon emissions from building construction projects, applied in a construction site setting where surveillance cameras are deployed. The method includes: A three-dimensional model of the construction site is established, which includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. Based on the footage captured by the surveillance camera, the system identifies the construction workers, buildings, and construction equipment in the footage, calculates the carbon emission values ​​of the construction workers, buildings, and construction equipment in real time, and matches the corresponding basic models of the construction workers, buildings, and construction equipment. Based on real-time calculations of carbon emissions from construction workers, buildings, and construction equipment, the construction worker foundation model, building foundation model, and construction equipment foundation model are subjected to three-channel hybrid encoding processing to obtain the encoding results, which are then displayed. The encoding result includes hue, lightness, and saturation, wherein the hue is used to identify the type of carbon emission source, the lightness is used to represent the real-time emission intensity, and the saturation is used to map emission trends.

[0006] Furthermore, the step of performing three-channel hybrid encoding processing on the construction worker foundation model, the building foundation model, and the construction equipment foundation model based on real-time calculated carbon emission values ​​of construction workers, buildings, and construction equipment to obtain the encoding result, and then displaying it, includes: Directional particle flow is superimposed on the surface of the current 3D model, and the 3D model is updated.

[0007] Furthermore, in the step of superimposing directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model, the directional particle flow includes particle density, particle velocity, and particle color, wherein the particle density is the carbon emission per unit area, the particle velocity is the rate of change of carbon emission rate, and the particle color is determined according to the type of carbon emission source. When the rate of change of carbon emission rate is accelerating, it is presented in the form of turbulence, and when the rate of change of carbon emission rate is decelerating, it is presented in the form of laminar flow.

[0008] Furthermore, the step of superimposing directional particle flow on the surface of the current 3D model and updating the 3D model includes: The 3D model of the construction site is divided into several work areas. According to the preset dimensions, each of the work areas is divided into several sub-regions; Based on time and space, the particle density, particle velocity, and particle color of the sub-regions are superimposed to obtain the final directional particle flow.

[0009] Furthermore, the step of superimposing the particle density, particle velocity, and particle color of the sub-region according to time and space to obtain the final directional particle flow includes: In the vertical direction at the same time, the particle density, particle velocity and particle color of the sub-regions in the same working area are superimposed to obtain the superposition result of each sub-region; In the horizontal direction at the same time, the superposition results of each sub-region are fused to obtain the final directional particle flow.

[0010] Furthermore, the step of fusing the superposition results of each sub-region along the horizontal axis at the same time to obtain the final directional particle flow includes: Obtain the particle density superposition result and particle velocity superposition result from the superposition result of each sub-region. Based on the statistical method, determine the abnormal results of particle density superposition and particle velocity superposition, and replace them with the weighted average of the neighborhood attributes respectively. Obtain the particle color superposition result in the superposition result of each sub-region, and perform multi-scale Gaussian blur on the particle color superposition result to generate feature maps of different scales; At each scale, the color contrast between the central sub-region and the surrounding sub-regions is calculated, and a directional contrast map is generated. The contrast maps at each scale and in each direction are normalized and then weighted and superimposed to obtain the saliency map. Map the value range of the saliency graph to the interval [0, 1] and determine whether it is greater than the threshold; If so, the corresponding sub-region is determined to be a salient region, wherein the smoothness of the salient region is reduced and the smoothness of the non-salient region is enhanced.

[0011] Furthermore, after the step of calculating and displaying the carbon emission values ​​of construction workers, buildings, and construction equipment in real time, performing three-channel hybrid encoding processing on the construction worker base model, the building base model, and the construction equipment base model respectively, the process further includes: Based on the construction schedule and historical data, a spatiotemporal prediction model is constructed using a graph neural network. The inputs to the spatiotemporal prediction model are equipment scheduling plans, personnel shift schedules, and weather data. The output of the spatiotemporal prediction model is a heat map of the spatiotemporal distribution of carbon emissions for a future preset time period. The heat map of the spatiotemporal distribution of carbon emissions is a heat map with a semi-transparent visual effect, where the current real scene is the entity and the prediction is the virtual image.

[0012] A second aspect of this invention provides a carbon emission visualization system for building construction projects, used to implement the carbon emission visualization method for building construction projects provided in the first aspect, the system comprising: A module is established to create a three-dimensional model of the construction site. The three-dimensional model includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. The calculation module is used to identify construction workers, buildings and construction equipment in the footage captured by the surveillance camera, calculate the carbon emission values ​​of construction workers, buildings and construction equipment in real time, and match the corresponding basic models of construction workers, buildings and construction equipment. The hybrid coding processing module is used to perform three-channel hybrid coding processing on the basic models of construction workers, buildings, and construction equipment based on the real-time calculated carbon emission values ​​of construction workers, buildings, and construction equipment, respectively, to obtain the coding results and display them. The encoding result includes hue, lightness, and saturation, wherein the hue is used to identify the type of carbon emission source, the lightness is used to represent the real-time emission intensity, and the saturation is used to map emission trends.

[0013] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the carbon emission visualization method for building construction projects provided in the first aspect.

[0014] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the carbon emission visualization method for building construction projects provided in the first aspect.

[0015] This invention provides a method and system for visualizing carbon emissions from building construction projects. By establishing a three-dimensional model of the construction site, including at least a basic model of construction workers, a basic model of buildings, and a basic model of construction equipment, the system identifies construction workers, buildings, and equipment in the surveillance footage. It calculates the carbon emissions of these elements in real time and matches the corresponding basic models of construction workers, buildings, and equipment. Based on the carbon emission values, each basic model undergoes three-channel hybrid encoding to obtain and display the encoding results. The encoding results include hue, brightness, and saturation. Hue identifies the type of carbon emission source, brightness represents the real-time emission intensity, and saturation maps emission trends. This ultimately visualizes the carbon emissions from building construction projects, allowing users to intuitively understand the distribution of carbon emissions. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the implementation of a method for visualizing carbon emissions in building construction projects, provided in Embodiment 1 of the present invention. Figure 2 This is a structural block diagram of a building construction carbon emission visualization system provided in Embodiment 2 of the present invention; Figure 3 This is a structural block diagram of an electronic device provided in Embodiment 3 of the present invention. Detailed Implementation

[0017] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0018] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0020] Example 1 According to an embodiment of the present invention, a method for visualizing carbon emissions from building construction projects is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0021] This first embodiment provides a method for visualizing carbon emissions from building construction projects, which can be used in electronic devices, such as computers. Please refer to [link / reference]. Figure 1 , Figure 1 The flowchart of a method for visualizing carbon emissions in building construction projects according to Embodiment 1 of the present invention is shown, specifically including steps S01 to S03.

[0022] Step S01: Establish a three-dimensional model of the construction site. The three-dimensional model includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment.

[0023] Specifically, Three.js can be used to achieve 3D visualization of the construction site. At the same time, a basic model library can be pre-built using BIM (Building Information Modeling) tools (such as Revit). The basic model library contains basic models of construction personnel, basic models of buildings, and basic models of construction equipment. Understandably, the basic models of construction personnel can be subdivided by job type (electrician, welder, crane operator, etc.) and include models of safety equipment (such as helmets and reflective vests). The basic models of buildings include concrete, steel, wood, etc. The basic models of construction equipment can be classified by type (excavator, tower crane, concrete pump truck) and energy consumption level (fuel / electric), with built-in equipment parameters (power, fuel type).

[0024] Step S02: Based on the footage captured by the surveillance camera, identify the construction workers, buildings, and construction equipment in the footage, calculate the carbon emission values ​​of the construction workers, buildings, and construction equipment in real time, and match the corresponding basic models of the construction workers, buildings, and construction equipment.

[0025] In this embodiment of the invention, after an object is identified, the corresponding carbon emission value is calculated based on the object's attributes. For example, the carbon emission of construction workers can be calculated by multiplying the amount of activity (such as walking distance and operation time) by the per capita carbon emission factor; the carbon emission of construction equipment can be calculated by collecting fuel consumption / electricity consumption in real time through IoT sensors or OBD interfaces, combined with emission factors (such as diesel 2.68kgCO2 / L); the carbon emission of building foundations can be determined by extracting material usage from the BIM model and matching it with the life cycle assessment (LCA) database.

[0026] It should be noted that the YOLOv7 or MaskR-CNN object detection algorithm in the monitoring video is used to identify objects in real time and match them with the corresponding items in the model library. The position update uses Kalman filtering to track dynamic objects, which completes the operation of matching the corresponding construction personnel basic model, building basic model and construction equipment basic model.

[0027] Step S03: Based on the real-time calculated carbon emission values ​​of construction workers, buildings, and construction equipment, perform three-channel hybrid encoding processing on the construction worker base model, the building base model, and the construction equipment base model respectively to obtain the encoding results and display them.

[0028] The encoding results include hue, lightness, and saturation. Hue is used to identify the type of carbon emission source, lightness is used to represent the real-time emission intensity, i.e., the carbon emission value, and saturation is used to map the emission trend. It can be understood that through the intuitive display of hue, lightness, and saturation, the carbon emission status of each construction worker's basic model, building basic model, and construction equipment basic model can be understood.

[0029] In this embodiment of the invention, the hue is blue when the carbon emission source is construction workers; red when the carbon emission source is construction equipment; and green when the carbon emission source is construction. For real-time emission intensity, 0% brightness corresponds to the minimum emission intensity, and 100% brightness corresponds to the maximum emission intensity. For mapped emission trends, low saturation corresponds to a decreasing trend, and high saturation corresponds to an increasing trend. For example, a rapidly increasing diesel generator can be displayed as high-saturation red (construction equipment) + 100% brightness (high intensity).

[0030] In addition, carbon emissions can be displayed on a daily or weekly basis, meaning that the daily or weekly emissions are reset and then recalculated, but the daily or weekly carbon emissions will be accumulated in the background.

[0031] Furthermore, to gain a comprehensive understanding of the carbon emissions at the construction site, directional particle flow is overlaid on the surface of the existing 3D model, and the model is then updated. Specifically, the directional particle flow includes particle density, particle velocity, and particle color. The particle density represents carbon emissions per unit area, the particle velocity represents the rate of change of carbon emissions, and the particle color is determined based on the type of carbon emission source. When the rate of change of carbon emissions is accelerating, it is presented as turbulent flow; when the rate of change of carbon emissions is decelerating, it is presented as laminar flow. For example, the tower crane hoisting area exhibits high-density red turbulent flow, while the manual masonry area displays low-velocity blue laminar flow.

[0032] Specifically, the step of superimposing directional particle flow on the surface of the current 3D model and updating the 3D model includes: The 3D model of the construction site is divided into several work areas. These areas can be divided by function. For example, the area can be divided into a tower crane hoisting work area, a manual masonry work area, and a concrete pouring work area. According to the preset size, each work area is divided into several sub-regions. It can be understood that the spatial range of the work area (such as a two-dimensional planar area) is determined and divided into multiple sub-regions (such as by grid division). Based on time and space, the particle density, particle velocity, and particle color of the sub-regions are superimposed to obtain the final directional particle flow. Specifically, in the vertical direction (vertical direction) at the same time, the particle density, particle velocity, and particle color of the sub-regions in the same work area are superimposed to obtain the superposition results of each sub-region. In this embodiment of the invention, the particle density superposition is performed by directly summing the densities of each sub-region in the same column; the particle velocity superposition is performed by decomposing the velocity of each sub-region in the same column into x and y components, summing them separately, and then combining them into a composite velocity; the particle color superposition is performed by using a weighted average method, with the weight being either particle density or sub-region area. The advantage of this approach is that carbon emissions generated at different heights in the vertical direction can be aggregated and represented. For example, the carbon emissions of construction workers, buildings, and construction equipment on different floors of a building can be statistically analyzed according to the divided sub-regions. In the horizontal direction at the same time, the superposition results of each sub-region are fused to obtain the final directional particle flow. Specifically, the particle density superposition result and particle flow velocity superposition result in the superposition results of each sub-region are obtained. According to statistical methods (such as the 3σ principle) or isolated forest machine learning model, abnormal results of particle density superposition and abnormal results of particle flow velocity superposition are determined, and the weighted average of neighborhood attributes is used to replace them respectively to avoid outliers from destroying the smoothness of fusion. Obtain the particle color superposition result in the superposition result of each sub-region, and perform multi-scale Gaussian blur (such as 1×1, 3×3, 5×5 pixel kernel) on the particle color superposition result to generate feature maps of different scales; At each scale, the color contrast between the central sub-region and the surrounding sub-regions is calculated, and a directional contrast map is generated. The contrast maps at each scale and in each direction are normalized and then weighted and superimposed to obtain the saliency map. Map the value range of the saliency graph to the interval [0, 1] and determine whether it is greater than the threshold; If so, the corresponding sub-region is determined to be a salient region. Specifically, the smoothness of the fusion is reduced for the salient region. During fusion, the influence weight of adjacent regions is reduced, for example, by using a smaller fusion window (fusion only with directly adjacent sub-regions) or increasing the weight of its own attributes to preserve feature details. The smoothness of non-salient regions is enhanced by applying Gaussian filtering to the color of non-salient regions to further smooth the transition and reduce visual interference.

[0033] In other embodiments of the present invention, a spatiotemporal prediction model is constructed based on the construction schedule and historical data through a graph neural network. The input of the spatiotemporal prediction model is the equipment scheduling plan, the personnel shift schedule and the weather data. The output of the spatiotemporal prediction model is a heat map of the spatiotemporal distribution of carbon emissions for a future preset time period. The heat map of the spatiotemporal distribution of carbon emissions is a heat map with a semi-transparent visual effect, where the current real scene is the entity and the prediction is the virtual image.

[0034] Specifically, in establishing a graph neural network to construct a spatiotemporal prediction model, the construction scene graph is first modeled, including nodes and edges. Nodes include spatial nodes and entity nodes. In the spatial nodes, the construction site is divided into a three-dimensional grid (e.g., 10m×10m×5m), with each grid being a node containing location coordinates and the current work process type (e.g., earthwork excavation, rebar tying). In the entity nodes, equipment (classified by model), materials (e.g., concrete, steel), and personnel teams are treated as independent nodes, associated with their attributes (power, usage, number of people). Edges include spatial adjacency edges, work process dependency edges, and interaction edges. Spatial adjacency edges represent the spatial connection relationship between adjacent grid nodes, work process dependency edges represent the sequence of nodes, such as the sequence of the "excavation" node and the "foundation pouring" node, and interaction edges represent the operational association between entity nodes and spatial nodes.

[0035] It should be noted that the graph neural network model architecture includes an input layer, a graph convolutional layer, a temporal layer, and an output layer. In the input layer, equipment scheduling, personnel shifts, and weather data are encoded as node features (e.g., equipment power → numerical features, process type → unique heat encoding). In the graph convolutional layer, neighboring node information is aggregated through message passing mechanisms (e.g., GCN, GAT) to capture spatiotemporal dependencies (e.g., the mutual influence of carbon emissions from adjacent work areas). In the temporal layer, LSTM or Transformer is used to process time-series features (e.g., the temporal patterns of historical 48-hour carbon emission data). The output layer generates predicted carbon emissions (tons CO2 / hour) for each grid node for the next 24 hours.

[0036] In summary, the carbon emission visualization method for construction projects described in the above embodiments of the present invention establishes a three-dimensional model of the construction site, which includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. Based on footage captured by surveillance cameras, the method identifies construction personnel, buildings, and construction equipment in the footage, calculates the carbon emission values ​​of these components in real time, and simultaneously matches the corresponding basic models of construction personnel, buildings, and equipment. Based on the carbon emission values, each basic model undergoes three-channel hybrid encoding processing to obtain and display the encoding results. The encoding results include hue, brightness, and saturation. Hue is used to identify the type of carbon emission source, brightness represents the real-time emission intensity, and saturation maps the emission trend. Ultimately, this method visualizes the carbon emissions of construction projects, allowing users to intuitively understand the distribution of carbon emissions.

[0037] Example 2 Please see Figure 2 , Figure 2This is a structural block diagram of a carbon emission visualization system for building construction projects provided in Embodiment 2 of the present invention. This carbon emission visualization system 200 is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0038] Specifically, the building construction carbon emission visualization system 200 includes: a creation module 21, a calculation module 22, and a hybrid encoding processing module 23, wherein: Module 21 is used to create a three-dimensional model of the construction site. The three-dimensional model includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. The calculation module 22 is used to identify construction workers, buildings and construction equipment in the captured images of the surveillance camera, calculate the carbon emission values ​​of construction workers, buildings and construction equipment in real time, and match the corresponding basic models of construction workers, buildings and construction equipment. The hybrid coding processing module 23 is used to perform three-channel hybrid coding processing on the construction personnel base model, the building base model, and the construction equipment base model according to the real-time calculated carbon emission values ​​of construction personnel, buildings, and construction equipment, respectively, to obtain the coding results and display them; The encoding result includes hue, lightness, and saturation, wherein the hue is used to identify the type of carbon emission source, the lightness is used to represent the real-time emission intensity, and the saturation is used to map emission trends.

[0039] Furthermore, in some optional embodiments of the present invention, the building construction carbon emission visualization system 200 further includes: The overlay module is used to overlay directional particle flows onto the surface of the current 3D model and update the 3D model. The directional particle flows include particle density, particle velocity, and particle color. The particle density is the carbon emissions per unit area, the particle velocity is the rate of change of carbon emission rate, and the particle color is determined according to the type of carbon emission source. When the rate of change of carbon emission rate is accelerating, it is presented in the form of turbulence, and when the rate of change of carbon emission rate is decelerating, it is presented in the form of laminar flow.

[0040] Furthermore, in some optional embodiments of the present invention, the superposition module includes: The first division unit is used to divide the three-dimensional model of the construction site into several work areas. The second division unit is used to divide each of the work areas into several sub-regions according to a preset size; The superposition unit is used to superimpose the particle density, particle velocity, and particle color of the sub-region according to time and space to obtain the final directional particle flow.

[0041] Furthermore, in some optional embodiments of the present invention, the superimposed unit includes: The superposition subunit is used to superimpose the particle density, particle velocity and particle color of the sub-regions of the same working area along the vertical axis at the same time to obtain the superposition result of each sub-region. The fusion subunit is used to fuse the superposition results of each sub-region in the horizontal direction at the same time to obtain the final directional particle flow. Specifically, it obtains the particle density superposition result and particle flow velocity superposition result in the superposition results of each sub-region, determines the abnormal results of particle density superposition and particle flow velocity superposition according to statistical methods, and replaces them with the weighted average of neighborhood attributes respectively. Obtain the particle color superposition result in the superposition result of each sub-region, and perform multi-scale Gaussian blur on the particle color superposition result to generate feature maps of different scales; At each scale, the color contrast between the central sub-region and the surrounding sub-regions is calculated, and a directional contrast map is generated. The contrast maps at each scale and in each direction are normalized and then weighted and superimposed to obtain the saliency map. Map the value range of the saliency graph to the interval [0, 1] and determine whether it is greater than the threshold; If so, the corresponding sub-region is determined to be a salient region, wherein the smoothness of the salient region is reduced and the smoothness of the non-salient region is enhanced.

[0042] Furthermore, in some optional embodiments of the present invention, the building construction carbon emission visualization system 200 further includes: The module is used to construct a spatiotemporal prediction model based on the construction schedule and historical data using a graph neural network. The inputs of the spatiotemporal prediction model are equipment scheduling plans, personnel shift schedules, and weather data. The output of the spatiotemporal prediction model is a heat map of the spatiotemporal distribution of carbon emissions for a future preset time period. The heat map of the spatiotemporal distribution of carbon emissions is a heat map with a semi-transparent visual effect, where the current real scene is the entity and the prediction is the virtual image.

[0043] Example 3 In another aspect, the present invention also proposes an electronic device, please refer to [link to relevant documentation]. Figure 3The electronic device shown is an embodiment of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor. When the processor 10 executes the computer program 30, it implements the above-described method for visualizing carbon emissions from building construction projects.

[0044] In some embodiments, the processor 10 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program code stored in memory 20 or process data, such as executing access restriction programs.

[0045] The memory 20 includes at least one type of readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 20 can be an internal storage unit of an electronic device, such as the hard disk of the electronic device. In other embodiments, the memory 20 can also be an external storage device of the electronic device, such as a plug-in hard disk, SmartMediaCard (SMC), SecureDigital (SD) card, FlashCard, etc., equipped on the electronic device. Furthermore, the memory 20 can include both internal and external storage units of the electronic device. The memory 20 can be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or will be output.

[0046] It should be pointed out that, Figure 3 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0047] This invention also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for visualizing carbon emissions from building construction projects.

[0048] Those skilled in the art will understand that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0049] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0050] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0051] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0052] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for visualizing carbon emissions from building construction projects, characterized in that, In a construction site setting where surveillance cameras are deployed, the method includes: A three-dimensional model of the construction site is established, which includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. Based on the footage captured by the surveillance camera, the system identifies the construction workers, buildings, and construction equipment in the footage, calculates the carbon emission values ​​of the construction workers, buildings, and construction equipment in real time, and matches the corresponding basic models of the construction workers, buildings, and construction equipment. Based on the real-time calculation of carbon emission values ​​of construction workers, buildings, and construction equipment, the basic models of construction workers, buildings, and construction equipment are subjected to three-channel hybrid encoding processing to obtain the encoding results, which are then displayed. The encoding result includes hue, lightness, and saturation, wherein the hue is used to identify the type of carbon emission source, the lightness is used to represent the real-time emission intensity, and the saturation is used to map emission trends.

2. The method for visualizing carbon emissions from building construction projects according to claim 1, characterized in that, The step of calculating and displaying the carbon emission values ​​of construction workers, buildings, and construction equipment in real time, followed by performing three-channel hybrid encoding on the basic models of construction workers, buildings, and construction equipment respectively, to obtain the encoding results, includes: A directional particle flow is superimposed on the surface of the current 3D model, and the 3D model is updated.

3. The method for visualizing carbon emissions from building construction projects according to claim 2, characterized in that, In the step of superimposing directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model, the directional particle flow includes particle density, particle velocity, and particle color. The particle density is the carbon emission per unit area, the particle velocity is the rate of change of carbon emission rate, and the particle color is determined according to the type of carbon emission source. When the rate of change of carbon emission rate is accelerating, it is presented in the form of turbulence, and when the rate of change of carbon emission rate is decelerating, it is presented in the form of laminar flow.

4. The method for visualizing carbon emissions from building construction projects according to claim 3, characterized in that, The steps of superimposing directional particle flow on the surface of the current 3D model and updating the 3D model include: The 3D model of the construction site is divided into several work areas. According to the preset dimensions, each of the work areas is divided into several sub-regions; Based on time and space, the particle density, particle velocity, and particle color of the sub-regions are superimposed to obtain the final directional particle flow.

5. The method for visualizing carbon emissions from building construction projects according to claim 4, characterized in that, The step of superimposing the particle density, particle velocity, and particle color of the sub-region according to time and space to obtain the final directional particle flow includes: In the vertical direction at the same time, the particle density, particle velocity and particle color of the sub-regions in the same working area are superimposed to obtain the superposition result of each sub-region; In the horizontal direction at the same time, the superposition results of each sub-region are fused to obtain the final directional particle flow.

6. The method for visualizing carbon emissions from building construction projects according to claim 5, characterized in that, The step of fusing the superposition results of the sub-regions along the horizontal axis at the same time to obtain the final directional particle flow includes: Obtain the particle density superposition result and particle velocity superposition result from the superposition result of each sub-region. Based on the statistical method, determine the abnormal results of particle density superposition and particle velocity superposition, and replace them with the weighted average of the neighborhood attributes respectively. Obtain the particle color superposition result in the superposition result of each sub-region, and perform multi-scale Gaussian blur on the particle color superposition result to generate feature maps of different scales; At each scale, the color contrast between the central sub-region and the surrounding sub-regions is calculated, and a directional contrast map is generated. The contrast maps at each scale and in each direction are normalized and then weighted and superimposed to obtain the saliency map. Map the value range of the saliency graph to the interval [0, 1] and determine whether it is greater than the threshold; If so, the corresponding sub-region is determined to be a salient region, wherein the smoothness of the salient region is reduced and the smoothness of the non-salient region is enhanced.

7. The method for visualizing carbon emissions from building construction projects according to claim 1, characterized in that, The step of calculating and displaying the carbon emission values ​​of construction workers, buildings, and construction equipment in real time, performing three-channel hybrid encoding on the basic models of construction workers, buildings, and construction equipment respectively, and then further includes: Based on the construction schedule and historical data, a spatiotemporal prediction model is constructed using a graph neural network. The inputs to the spatiotemporal prediction model are equipment scheduling plans, personnel shift schedules, and weather data. The output of the spatiotemporal prediction model is a heat map of the spatiotemporal distribution of carbon emissions for a future preset time period. The heat map of the spatiotemporal distribution of carbon emissions is a heat map with a semi-transparent visual effect, where the current real scene is the entity and the prediction is the virtual image.

8. A visualization system for carbon emissions in building construction projects, characterized in that, For implementing the carbon emission visualization method for building construction projects as described in any one of claims 1-7, the system comprises: A module is established to create a three-dimensional model of the construction site. The three-dimensional model includes at least a basic model of construction personnel, a basic model of buildings, and a basic model of construction equipment. The calculation module is used to identify construction workers, buildings and construction equipment in the footage captured by the surveillance camera, calculate the carbon emission values ​​of construction workers, buildings and construction equipment in real time, and match the corresponding basic models of construction workers, buildings and construction equipment. The hybrid coding processing module is used to perform three-channel hybrid coding processing on the basic model of construction workers, the basic model of buildings, and the basic model of construction equipment based on the real-time calculated carbon emission values ​​of construction workers, buildings, and construction equipment, respectively, to obtain the coding results and display them; The encoding result includes hue, lightness, and saturation, wherein the hue is used to identify the type of carbon emission source, the lightness is used to represent the real-time emission intensity, and the saturation is used to map emission trends.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the carbon emission visualization method for building construction projects as described in any one of claims 1-7.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the carbon emission visualization method for building construction projects as described in any one of claims 1-7.

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