A method and system for visualizing carbon emissions of a construction project

Abstract

The application provides a construction engineering carbon emission visualization method and system, which comprises the following steps: establishing a three-dimensional model of a construction site, wherein the three-dimensional model at least comprises a construction personnel basic model, a building basic model and a construction equipment basic model; identifying the construction personnel, the building and the construction equipment in a shooting picture of a monitoring camera according to the shooting picture, and calculating the carbon emission values of the construction personnel, the building and the construction equipment in real time; meanwhile, the corresponding construction personnel basic model, the building basic model and the construction equipment basic model are matched; according to the carbon emission values, the three basic models are subjected to three-channel mixed coding processing respectively, the coding results are obtained and displayed, wherein the coding results comprise hue, lightness and saturation, wherein the hue is used for identifying the carbon emission source type, the lightness is used for representing the real-time emission intensity, and the saturation is used for mapping the emission trend, and finally the visualization of the construction engineering carbon emission is realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of carbon emission visualization, and particularly relates to a building construction engineering carbon emission visualization method and system. BACKGROUND

[0002] In the long run, controlling carbon emissions is conducive to the sustainable development of social economy. In current urban construction, there are clear requirements for building construction engineering carbon emissions, and specific provisions are made for the calculation range, method, data collection, etc. of building carbon emissions, which provide a basis for the accounting of building construction engineering carbon emissions. It is specified that the carbon emission calculation time boundary of the building construction stage should be from the start of the project to the completion and acceptance of the project, and the carbon emissions generated by the use of energy of mechanical equipment, small tools, temporary facilities, etc. in the construction site area should be included.

[0003] The carbon emission data currently calculated is often in the form of numbers, which cannot well intuitively reflect the carbon emissions of each part of the building construction engineering, affecting the user experience. SUMMARY

[0004] Therefore, the embodiment of the application provides a building construction engineering carbon emission visualization method and system, which aims to visualize the carbon emissions of building construction engineering to enable users to intuitively understand the carbon emission distribution and improve the user experience.

[0005] The first aspect of the embodiment of the application provides a building construction engineering carbon emission visualization method applied to the scene of a construction site, wherein a monitoring camera is arranged in the construction site, and the method comprises the following steps:

[0006] establishing a three-dimensional model of the construction site, wherein the three-dimensional model at least includes a construction personnel basic model, a building basic model and a construction equipment basic model;

[0007] identifying construction personnel, buildings and construction equipment in a shooting picture of the monitoring camera according to the shooting picture, and calculating carbon emission values of the construction personnel, the buildings and the construction equipment in real time, while matching corresponding construction personnel basic models, building basic models and construction equipment basic models;

[0008] performing three-channel mixed coding processing on the construction personnel basic model, the building basic model and the construction equipment basic model according to the carbon emission values of the construction personnel, the buildings and the construction equipment calculated in real time, to obtain coding results, and displaying the coding results.

[0009] The coding results include hue, lightness and saturation, wherein the hue is used to identify the carbon emission source type, the lightness is used to represent the real-time emission intensity, and the saturation is used to map the emission trend.

[0010] Further, the step of calculating the carbon emission value of the construction personnel, the building and the construction equipment according to the real time, respectively processing the construction personnel basic model, the building basic model and the construction equipment basic model by three-channel mixed coding, obtaining the coding result, and displaying includes:

[0011] The directional particle flow is superimposed on the surface of the current three-dimensional model, and the three-dimensional model is updated.

[0012] Further, in the step of superimposing the 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 flow rate and particle color, wherein the particle density is the carbon emission per unit area, the particle flow rate is the carbon emission rate change rate, and the particle color is determined according to the carbon emission source type, and when the carbon emission rate change rate is acceleration, it is presented in the form of turbulent flow, and when the carbon emission rate change rate is deceleration, it is presented in the form of laminar flow.

[0013] Further, the step of superimposing the directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model includes:

[0014] The three-dimensional model of the construction site is divided into regions to obtain a plurality of work areas;

[0015] According to the predetermined size, each of the work areas is divided to obtain a plurality of sub-regions;

[0016] According to time and space, the particle density, particle flow rate and particle color of the sub-regions are superimposed to obtain the final directional particle flow.

[0017] Further, the step of superimposing the directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model includes:

[0018] In the longitudinal direction at the same time, the particle density, particle flow rate and particle color of the sub-regions of the same work area are respectively superimposed to obtain the superposition result of each of the sub-regions;

[0019] In the horizontal direction at the same time, the superposition results of each of the sub-regions are fused to obtain the final directional particle flow.

[0020] Further, the step of superimposing the directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model includes:

[0021] The particle density superposition result and the particle flow velocity superposition result in the superposition result of each sub-region are obtained, the particle density superposition anomaly result and the particle flow velocity superposition anomaly result are determined according to a statistical method, and the weighted average of neighborhood attributes is used for replacement respectively;

[0022] The particle color superposition result in the superposition result of each sub-region is obtained, and the particle color superposition result is subjected to multi-scale Gaussian blurring to generate feature maps of different scales;

[0023] Under each scale, the color contrast between the central sub-region and the surrounding sub-region is calculated, and a directional contrast map is generated;

[0024] After normalization and weighted superposition of the contrast maps in each scale and each direction, a saliency map is obtained;

[0025] The value range of the saliency map is mapped to the interval [0, 1], and it is judged whether it is greater than a threshold value;

[0026] If yes, the corresponding sub-region is determined as a saliency region, wherein the fusion smoothing degree of the saliency region is reduced, and the non-saliency region is strengthened.

[0027] Further, the step of performing three-channel hybrid coding processing on the construction personnel basic model, the building basic model and the construction equipment basic model according to the real-time calculation of the carbon emission values of the construction personnel, the building and the construction equipment to obtain an encoding result and display is further included after the step of performing three-channel hybrid coding processing on the construction personnel basic model, the building basic model and the construction equipment basic model according to the real-time calculation of the carbon emission values of the construction personnel, the building and the construction equipment to obtain an encoding result and display.

[0028] Based on the construction progress plan and historical data, a spatio-temporal prediction model is constructed through a graph neural network, the input of the spatio-temporal prediction model is a device scheduling plan, a personnel shift schedule and weather data, and the output of the spatio-temporal prediction model is a carbon emission spatio-temporal distribution heat map in a future preset time period, wherein the carbon emission spatio-temporal distribution heat map is a heat map with a semi-transparent visual effect, the current real scene is a solid, and the prediction is a ghost.

[0029] The second aspect of the embodiment of the application provides a building construction engineering carbon emission visualization system for realizing the building construction engineering carbon emission visualization method provided by the first aspect, and the system comprises:

[0030] The establishment module is configured to establish a three-dimensional model of the construction site, and the three-dimensional model comprises at least a construction personnel basic model, a building basic model and a construction equipment basic model;

[0031] The calculation module is configured to identify the construction personnel, the building and the construction equipment in the shooting picture according to the shooting picture of the monitoring camera, to calculate the carbon emission values of the construction personnel, the building and the construction equipment in real time, and to match the corresponding construction personnel basic model, the building basic model and the construction equipment basic model.

[0032] The mixed coding processing module is configured to perform three-channel mixed coding processing on the construction worker basic model, the building basic model and the construction equipment basic model respectively according to the real-time calculation of the carbon emission values of the construction workers, the building and the construction equipment, to obtain a coding result, and to display the coding result.

[0033] The coding result includes hue, lightness and saturation, wherein the hue is used to identify the carbon emission source type, the lightness is used to represent the real-time emission intensity, and the saturation is used to map the emission trend.

[0034] The third aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to realize the building construction project carbon emission visualization method provided in the first aspect.

[0035] The fourth aspect of the embodiment of the present application provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the program to realize the building construction project carbon emission visualization method provided in the first aspect.

[0036] The building construction project carbon emission visualization method and system provided in the embodiment of the present application establish a three-dimensional model of a construction site, which at least includes a construction worker basic model, a building basic model and a construction equipment basic model; identify the construction workers, the building and the construction equipment in a shooting picture of a monitoring camera according to the shooting picture, and calculate the carbon emission values of the construction workers, the building and the construction equipment in real time, while matching the corresponding construction worker basic model, building basic model and construction equipment basic model; perform three-channel mixed coding processing on each basic model according to the carbon emission values to obtain a coding result, and display the coding result; wherein the coding result includes hue, lightness and saturation, wherein the hue is used to identify the carbon emission source type, the lightness is used to represent the real-time emission intensity, and the saturation is used to map the emission trend, and finally realize the visualization of the building construction project carbon emission, so that the user can intuitively understand the carbon emission distribution. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The implementation flowchart of the building construction project carbon emission visualization method provided in the first embodiment of the present application;

[0038] Figure 2 The structural block diagram of the building construction project carbon emission visualization system provided in the second embodiment of the present application;

[0039] Figure 3 The structural block diagram of the electronic device provided in the third embodiment of the present application. DETAILED DESCRIPTION

[0040] For the purpose of promoting an understanding of the application, the application will now be described in greater detail with reference to the figures illustrative of embodiments thereof. The embodiments shown in the drawings are intended to explain the present application and are not meant to limit the present application. However, the present application can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and fully convey the scope of the application to those skilled in the art.

[0041] It is to be understood that where an element is referred to as being "on" another element, it can be directly on the other element or intervening elements can also be present. Where an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements can also be present. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0042] 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 application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0043] Embodiment One

[0044] According to the embodiment of the present application, a construction engineering carbon emission visualization method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0045] In this embodiment one, a construction engineering carbon emission visualization method is provided, which can be used in electronic devices such as computers. Please refer to Figure 1 , Figure 1 The implementation flowchart of the construction engineering carbon emission visualization method provided by the embodiment one of the present application is shown, which specifically includes steps S01 to S03.

[0046] Step S01, a three-dimensional model of the construction site is established, which at least includes a construction personnel base model, a building base model and a construction equipment base model.

[0047] Specifically, Three.js can be used to realize the three-dimensional visualization of the construction site, and a basic model library is pre-constructed using a BIM (Building Information Modeling) tool (such as Revit), which includes construction personnel basic models, building basic models, and construction equipment basic models. Understandably, the construction personnel basic models can be subdivided by type (electrician, welder, crane operator, etc.) and additional safety equipment (such as helmets, reflective clothing) models; the building basic models include concrete, steel, wood, etc.; the construction equipment basic models can be classified by type (excavator, tower crane, concrete pump truck) and energy consumption level (fuel / oil), with built-in device parameters (power, fuel type).

[0048] In step S02, according to the shooting picture of the monitoring camera, the construction personnel, the building and the construction equipment in the shooting picture are recognized, and the carbon emission values of the construction personnel, the building and the construction equipment are calculated in real time, and the corresponding construction personnel basic model, building basic model and construction equipment basic model are matched.

[0049] In the embodiment of the application, after the object is recognized, the corresponding carbon emission value is calculated according to the object attribute. For example, the carbon emission of the construction personnel can be calculated based on the activity amount (such as walking distance, operation time) multiplied by the carbon emission factor per capita; the carbon emission of the construction equipment can be calculated by real-time collection of oil consumption / electricity through IoT sensors or OBD interface, combined with the emission factor (such as diesel 2.68kgCO2 / L); the basic carbon emission of the building can be extracted from the BIM model and matched with the life cycle assessment (LCA) database to determine.

[0050] It should be noted that the object is recognized in real time by the YOLOv7 or MaskR-CNN target detection algorithm of the monitoring video, and the corresponding item in the model library is matched, and the Kalman filter is used to track the dynamic object for position updating, that is, the operation of matching the corresponding construction personnel basic model, building basic model and construction equipment basic model is completed.

[0051] In step S03, according to the real-time calculation of the carbon emission values of the construction personnel, the building and the construction equipment, the construction personnel basic model, the building basic model and the construction equipment basic model are respectively processed by three-channel mixed coding to obtain the coding result and display.

[0052] The coding 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, that is, the carbon emission value, and the saturation is used to map the emission trend. Understandably, through the intuitive display of hue, lightness and saturation, the carbon emission situation of each construction personnel basic model, building basic model and construction equipment basic model can be understood.

[0053] In the embodiments of the present application, when the carbon emission source type is a construction worker, the hue is blue; when the carbon emission source type is a construction device, the hue is red; and when the carbon emission source type is a building, the hue is green. For real-time emission intensity, 0% brightness corresponds to the minimum value of the emission intensity, and 100% brightness corresponds to the maximum value of the emission intensity. For the mapped emission trend, low saturation is for a downward trend, and high saturation is for an upward trend. For example, a rapidly rising diesel generator can be displayed as high-saturation red (construction device) + 100% brightness (high intensity).

[0054] In addition, the carbon emission display can be performed in units of days or weeks, i.e., the carbon emission is re-counted after zeroing every day or every week, but the carbon emission of each day or each week is accumulated in the background.

[0055] Further, in order to macroscopically and integrally understand the carbon emission situation of the construction site, a directional particle flow is superimposed on the surface of the current three-dimensional model, and the three-dimensional model is updated. Specifically, the directional particle flow includes particle density, particle flow velocity, and particle color, wherein the particle density is the carbon emission amount per unit area, the particle flow velocity is the carbon emission rate change rate, and the particle color is determined according to the carbon emission source type. When the carbon emission rate change rate is acceleration, it is presented in the form of turbulent flow, and when the carbon emission rate change rate is deceleration, it is presented in the form of laminar flow. For example, the tower crane hoisting operation area presents high-density red turbulent flow, and the manual masonry area displays low-speed blue laminar flow.

[0056] Specifically, the step of superimposing a directional particle flow on the surface of the current three-dimensional model and updating the three-dimensional model includes:

[0057] The three-dimensional model of the construction site is regionally divided to obtain a plurality of operation areas. For example, the operation areas are divided into a tower crane hoisting operation area, a manual masonry operation area, a concrete pouring operation area, etc. through functions.

[0058] According to the predetermined size, each of the operation areas is divided to obtain a plurality of sub-regions. It can be understood that the spatial range (such as a two-dimensional planar region) of the operation area is determined and divided into a plurality of sub-regions (such as grid division).

[0059] According to time and space, the particle density, particle flow rate and particle color of the sub-regions are superimposed to obtain the final directional particle flow. Specifically, the particle density, particle flow rate and particle color of the sub-regions in the same work area are respectively superimposed in the longitudinal direction at the same time, i.e. the vertical direction, to obtain the superposition results of the sub-regions. In the embodiment of the present application, the superposition processing of the particle density is the direct summation of the densities of the sub-regions in the same column, the superposition processing of the particle flow rate is to decompose the flow rates of the sub-regions in the same column into x and y components, and then synthesize the combined velocity after summation, and the superposition processing of the particle color is obtained by using weighted average processing, and the weight is the particle density or the area of the sub-region. The advantage of this is that the carbon emissions generated at different heights in the vertical direction can be summarized and reflected. For example, the carbon emissions of construction personnel, buildings and construction equipment on different floors of a building can be counted according to the divided sub-regions.

[0060] The superposition results of the sub-regions are fused in the horizontal direction at the same time to obtain the final directional particle flow. Specifically, the particle density superposition result and the particle flow rate superposition result in the superposition result of each sub-region are obtained, the particle density superposition abnormal result and the particle flow rate superposition abnormal result are determined according to a statistical method (such as the 3σ principle) or an isolated forest machine learning model, and the weighted average of the neighborhood attribute is replaced respectively to avoid the damage of abnormal values to the fusion smoothness.

[0061] The particle color superposition result in the superposition result of each sub-region is obtained, and the particle color superposition result is subjected to multi-scale Gaussian blur (such as 1x1, 3x3, 5x5 pixel kernel) to generate feature maps of different scales.

[0062] Under each scale, the color contrast between the central sub-region and the surrounding sub-regions is calculated, and a direction contrast map is generated.

[0063] The contrast maps of each scale and each direction are normalized and weighted superimposed to obtain a saliency map.

[0064] The value range of the saliency map is mapped to the interval [0, 1], and it is judged whether it is greater than a threshold value.

[0065] If yes, the corresponding sub-region is determined as a saliency region. Specifically, the influence weight of the adjacent region is reduced during fusion, for example, a smaller fusion window (only fused with the directly adjacent sub-region) or the weight of the own attribute is increased to retain the feature details. The color of the non-saliency region can be subjected to Gaussian filtering to further smooth the transition and reduce visual interference.

[0066] In some other embodiments of the present application, based on the construction progress plan and historical data, a spatio-temporal prediction model is constructed through a graph neural network, the input of the spatio-temporal prediction model is a device scheduling plan, a personnel shift schedule and weather data, and the output of the spatio-temporal prediction model is a carbon emission spatio-temporal distribution heat map of a future preset time period, wherein the carbon emission spatio-temporal distribution heat map is a heat map with a semi-transparent visual effect, the current real scene is a solid entity, and the prediction is a virtual image.

[0067] Specifically, in the process of establishing the graph neural network to construct the spatio-temporal prediction model, the construction scene graph is first modeled, which includes nodes and edges, and the nodes include spatial nodes and entity nodes. In the spatial nodes, the construction site is divided into three-dimensional grids (such as 10m×10m×5m), each grid is a node, containing position coordinates, current process type (such as earth excavation, steel binding), and in the entity nodes, the equipment (classified by model), materials (such as concrete, steel) and personnel teams are taken as independent nodes, and their attributes (power, usage, number of people) are associated. The edges include spatial adjacency edges, process dependence edges and interaction edges, the spatial adjacency edges are used to represent the spatial connection relationship of adjacent grid nodes, the process dependence edges are used to represent the sequence of nodes, such as the sequence of the "foundation excavation" node and the "foundation pouring" node, and the interaction edges are used to represent the work association of the entity nodes and the spatial nodes.

[0068] It should be noted that the graph neural network model architecture includes an input layer, a graph convolution layer, a time sequence layer and an output layer. In the input layer, the device scheduling, personnel scheduling, weather data are encoded into node features (such as device power → numerical feature, process type → one-hot encoding); in the graph convolution layer, the adjacent node information is aggregated through the message passing mechanism (such as GCN, GAT) to capture the spatio-temporal dependence relationship (such as the mutual influence of carbon emissions in adjacent work areas); in the time sequence layer, the time sequence features (such as the time sequence rule of historical 48-hour carbon emission data) are processed in combination with LSTM or Transformer; in the output layer, the carbon emission prediction value (ton CO2 / hour) of each grid node in the future 24 hours is generated.

[0069] To sum up, the building construction engineering carbon emission visualization method in the above embodiment can realize the visualization of the building construction engineering carbon emission, and enable the user to intuitively understand the carbon emission distribution.

[0070] Embodiment Two

[0071] Please refer to Figure 2 , Figure 2 is a structural block diagram of a building construction engineering carbon emission visualization system provided by Embodiment Two of the present application. The building construction engineering carbon emission visualization system 200 is used to realize the above embodiment and preferred embodiment, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiment is preferably realized in software, the realization of hardware, or a combination of software and hardware, is also possible and conceived.

[0072] Specifically, the building construction engineering carbon emission visualization system 200 comprises an establishing module 21, a calculating module 22 and a mixed encoding processing module 23, wherein:

[0073] The establishing module 21 is configured to establish a three-dimensional model of a construction site, wherein the three-dimensional model comprises at least a construction personnel basic model, a building basic model and a construction equipment basic model;

[0074] The calculating module 22 is configured to identify construction personnel, buildings and construction equipment in a shooting picture of a monitoring camera according to the shooting picture, and to calculate carbon emission values of the construction personnel, the buildings and the construction equipment in real time, while matching corresponding construction personnel basic models, building basic models and construction equipment basic models;

[0075] The mixed encoding processing module 23 is configured to perform three-channel mixed encoding processing on the construction personnel basic model, the building basic model and the construction equipment basic model according to the carbon emission values of the construction personnel, the buildings and the construction equipment calculated in real time, to obtain an encoding result, and to display the encoding result;

[0076] The coding result includes hue, brightness and saturation, wherein the hue is used to identify the carbon emission source type, the brightness is used to represent the real-time emission intensity, and the saturation is used to map the emission trend.

[0077] Further, in some optional embodiments of the present application, the building construction project carbon emission visualization system 200 further comprises:

[0078] The superposition module is configured to superimpose a directional particle flow on a surface of the current three-dimensional model and update the three-dimensional model, the directional particle flow comprising particle density, particle flow velocity and particle color, wherein the particle density is carbon emission per unit area, the particle flow velocity is a carbon emission rate change rate, and the particle color is determined according to the carbon emission source type, and when the carbon emission rate change rate is acceleration, the particle color is presented in a turbulent flow form, and when the carbon emission rate change rate is deceleration, the particle color is presented in a laminar flow form.

[0079] Further, in some optional embodiments of the present application, the superposition module comprises:

[0080] The first division unit is configured to divide the three-dimensional model of the construction site into a plurality of work areas.

[0081] The second division unit is configured to divide each of the work areas into a plurality of sub-areas according to a preset size.

[0082] The superposition unit is configured to superimpose the particle density, the particle flow velocity and the particle color of the sub-areas according to time and space to obtain a final directional particle flow.

[0083] Further, in some optional embodiments of the present application, the superposition unit comprises:

[0084] The superposition sub-unit is configured to superimpose the particle density, the particle flow velocity and the particle color of the sub-areas of the same work area in the longitudinal direction at the same time to obtain superposition results of the sub-areas.

[0085] The fusion sub-unit is configured to fuse the superposition results of the sub-areas in the horizontal direction at the same time to obtain a final directional particle flow, and specifically, the particle density superposition results and the particle flow velocity superposition results in the superposition results of the sub-areas are obtained, the particle density superposition abnormal results and the particle flow velocity superposition abnormal results are determined according to a statistical method, and the weighted average of neighborhood attributes is respectively adopted for replacement.

[0086] The particle color superposition results in the superposition results of the sub-areas are obtained, and the particle color superposition results are subjected to multi-scale Gaussian blur to generate feature maps of different scales.

[0087] At each scale, color contrast of the central sub-region and the peripheral sub-region is calculated, and a directional contrast map is generated;

[0088] After normalization and weighted superposition of the contrast maps of each scale and each direction, a saliency map is obtained;

[0089] The value range of the saliency map is mapped to the interval [0, 1], and it is determined whether it is greater than a threshold value;

[0090] If yes, the corresponding sub-region is determined as a saliency region, wherein the fusion smoothness of the saliency region is reduced, and the non-saliency region is strengthened.

[0091] Further, in some optional embodiments of the present application, the building construction project carbon emission visualization system 200 further comprises:

[0092] A construction module is configured to construct a spatio-temporal prediction model based on a construction progress plan and historical data through a graph neural network, wherein the input of the spatio-temporal prediction model is a device scheduling plan, a personnel roster and weather data, and the output of the spatio-temporal prediction model is a carbon emission spatio-temporal distribution heat map of a future preset time period, wherein the carbon emission spatio-temporal distribution heat map is a heat map with a semi-transparent visual effect, the current real scene is a solid entity, and the prediction is a virtual image.

[0093] Embodiment three

[0094] Another aspect of the present application also proposes an electronic device, please refer to Figure 3 , which is an electronic device in the embodiment three of the present application, comprising a memory 20, a processor 10 and a computer program 30 stored in the memory and executable on the processor, wherein the processor 10 implements the building construction project carbon emission visualization method as described above when executing the computer program 30.

[0095] Among them, the processor 10 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor or other data processing chip in some embodiments, used to run program codes or process data stored in the memory 20, such as executing access restriction programs.

[0096] The memory 20 includes at least one type of readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 20 can be an internal storage unit of the electronic device in some embodiments, such as a hard disk of the electronic device. The memory 20 can also be an external storage device of the electronic device in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Further, the memory 20 can include both the internal storage unit and the external storage device of the electronic device. The memory 20 can be used not only to store application software and various data of the electronic device, but also to temporarily store data that has been output or will be output.

[0097] It is noted that, Figure 3 The illustrated structure does not limit the electronic device, and in other embodiments, the electronic device can include fewer or more components than illustrated, or combine certain components, or arrange the components differently.

[0098] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program. The program is executed by a processor to implement the building construction project carbon emission visualization method.

[0099] Those skilled in the art can understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a list of executable instructions for implementing the logic function, which can be specifically implemented in any computer readable medium for use by or in conjunction with an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor or other system that can fetch and execute instructions from the instruction execution system, device or apparatus) or in conjunction with these instruction execution systems, devices or apparatus. For the purpose of the present specification, the "computer readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by or in conjunction with an instruction execution system, device or apparatus or in conjunction with these instruction execution systems, devices or apparatus.

[0100] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can also be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that is then employable by a computer. Examples of computer-readable media that are further within the spirit of the present application are a computer program product, a computer readable storage medium, and a computer.

[0101] It should be understood that aspects of the application can be implemented in hardware, software, firmware, or combinations thereof. In the embodiments described above, various steps or methods can be implemented, for example, by software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following techniques, which are well known in the art, can be used to implement the application: a hybrid of the above techniques, discrete logic circuit(s) having logic gates for implementing logic functions upon request pins of the discrete logic circuit(s), programmable logic array(s) (PLAs), field programmable gate array(s) (FPGAs), etc.

[0102] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples.

[0103] The above embodiments only express several implementation manners of the application, which are described in a more specific and detailed manner, but cannot be understood as a limitation on the patent scope of the application. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the application, which are all within the protection scope of the application. Therefore, the patent protection scope of the application should be subject to 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 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; 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 to obtain the encoding results, includes: Directional particle flow is superimposed on the surface of the current 3D model and the 3D model is updated. 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 carbon emission rate change rate, and the particle color is determined according to the carbon emission source type. When the carbon emission rate change rate is accelerating, it is presented in the form of turbulence, and when the carbon emission rate change rate is decelerating, it is presented in the form of laminar flow. 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. 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; Along the horizontal axis at the same time, the superposition results of the various sub-regions are fused to obtain the final directional particle flow, specifically including: 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.

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, 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.

3. A visualization system for carbon emissions in building construction projects, characterized in that, The system for implementing the carbon emission visualization method for building construction projects as described in any one of claims 1-2 includes: 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.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the carbon emission visualization method for building construction projects as described in any one of claims 1-2.

5. 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 1-2.

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