Organization carbon budget trend early warning dynamic tuning method and system

Abstract

The invention provides an organization carbon budget trend early warning dynamic tuning method and system. Relates to a data processing technology. The method comprises the steps that the lighting attribute of each lighting unit located in a production workshop is determined, and the public lighting carbon emission of the corresponding monitoring duration of each lighting unit with the corresponding lighting attribute of public lighting is determined; the method comprises the following steps: acquiring a collected video of a corresponding monitoring duration of each production node located in a production workshop, performing video analysis on the collected video for an actual lighting area of each lighting unit of special lighting for production based on lighting attributes, and determining each production lighting carbon emission of each product component corresponding to each production node, determining the total production carbon emission of each production lighting carbon emission corresponding to the same product part; and on the basis of the part number corresponding to each product part, carrying out discharge capacity equalization on the public lighting carbon discharge capacity, and on the basis of each obtained equalization discharge capacity, carrying out discharge capacity superposition on each production total carbon discharge capacity to obtain each updated total carbon discharge capacity. According to the invention, the accuracy of carbon budget is at least improved.

Description

Technical Field

[0001] This invention relates to data processing technology, and more particularly to a method and system for dynamic optimization of organizational carbon budget trend early warning. Background Technology

[0002] In the industrial manufacturing sector, manufacturers are increasingly demanding more refined control over carbon emissions. Organizing carbon budgets, as a key management tool for industrial enterprises to achieve energy consumption control, carbon emission constraints, and cost reduction and efficiency improvement, effectively guides production processes towards low-carbon and standardized development by quantifying and controlling carbon emissions throughout the entire production process. It has become an important support for the sustainable operation of modern factories. For industrial scenarios such as discrete manufacturing and assembly line production, workshop lighting, equipment operation, and auxiliary facilities all constitute major sources of carbon emissions. Therefore, building an organizational carbon budget system that aligns with actual production processes is an inevitable requirement for industrial enterprises to achieve low-carbon transformation.

[0003] The complexity and diversity of industrial production processes pose potential demands for the accuracy of organizational carbon budgeting. However, the current mainstream calculation logic for industrial carbon budgets remains at the overall planning level, failing to achieve precise coverage of specific components. In the industrial lighting sector, the accounting process only incorporates the total energy consumption of the lighting process into the company's overall emissions data, combining it with conventional accounting methods to derive the total emissions, failing to capture the specific carbon emissions of individual components throughout the entire production and installation process. With the increasing demand for low-carbon industrial lighting, this overall accounting model is no longer suitable for actual needs, limiting enterprises' accurate identification and targeted optimization of high-energy-consuming production processes, and restricting the depth and efficiency of industrial enterprises' low-carbon transformation. Summary of the Invention

[0004] Based on the above problems, this invention is proposed to provide a dynamic optimization method and system for organizational carbon budget trend early warning to overcome or at least partially solve the above problems.

[0005] According to one aspect of the present invention, a method for dynamic optimization of organizational carbon budget trend early warning is provided, comprising the following steps: Determine the lighting attributes of each lighting unit located in the production workshop, and determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration; Acquire the video for the corresponding monitoring duration at each production node in the production workshop. Perform video analysis on the acquired video based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting. Determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component. The carbon emissions of public lighting are evenly distributed based on the number of components in each product, and the total carbon emissions of each production are superimposed based on the obtained evenly distributed emissions to obtain the updated total carbon emissions.

[0006] Optionally, in the method according to the invention, determining the lighting attributes of each lighting unit located in the production workshop includes: Establish a virtual workshop model corresponding to the production workshop, wherein the virtual workshop model includes a virtual workbench and a virtual unit corresponding to each production workbench and lighting unit; Based on the reference lighting range corresponding to each lighting unit, each reference lighting area is generated on the bottom surface of the virtual workshop model, and the area overlap between each reference lighting area and the area overlap of each virtual workbench is determined. The lighting attributes of the lighting units corresponding to the areas whose overlap area with the region is greater than the preset overlap area are determined as production-specific lighting. Conversely, the lighting attributes of the lighting unit are defined as public lighting.

[0007] Optionally, in the method according to the present invention, video analysis is performed on the acquired video based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting to determine the carbon emissions of each production lighting for each product component corresponding to each production node, and the total production carbon emissions of each production lighting corresponding to the same product component are determined, including: Based on the collected video, the start and end times of production for each product component at each production node are determined. Based on the start and end times of production for the same product component, video clips are extracted from each collected video to obtain production videos for each product component. Based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, video analysis is performed on each production video to determine the carbon emissions of each production lighting for each product component corresponding to each production node. The total carbon emissions of each lighting component in the same product are summed to obtain the total carbon emissions of each product.

[0008] Optionally, in the method according to the present invention, determining the start and end times of production for different product components corresponding to each production node based on each acquired video includes: The video image frames that make up each captured video are identified, and image recognition is performed on each video image frame to determine the component area and mechanical area corresponding to different product parts and robotic arms. If any video image frame corresponding to any captured video does not include any component area, the video image frame is determined as an idle image frame; Based on the acquired video, the first video image frame containing the robotic arm area after the idle image frame is determined as the starting image frame, and the acquisition time corresponding to the starting image frame is determined as the starting production time. Based on the acquired video, the first video image frame without a mechanical area after the starting image frame is determined as the termination image frame that has a production-related relationship with the starting image frame, and the acquisition time corresponding to the termination image frame is determined as the production termination time. Based on the acquired video, image recognition is performed on each video image frame located between the starting image frame and the ending image frame that has a production relationship with the starting image frame to determine the product component corresponding to the starting production time and the ending production time.

[0009] Optionally, in the method according to the present invention, image recognition is performed on each video image frame between the acquired video and the starting image frame and the ending image frame which has a production-related relationship with the starting image frame to determine the product component corresponding to the starting production time and the ending production time, including: Based on the acquired video, image recognition is performed on each video image frame between the starting image frame and the ending image frame that has a production-related relationship with the starting image frame, and the component area that has an operational relationship with the mechanical area is determined as the operation area based on each video image frame. Determine the number of operations for each operating area corresponding to the same product component, and identify the product component corresponding to the maximum number of operations as the product component corresponding to the start production time and the end production time.

[0010] Optionally, in the method according to the present invention, video analysis is performed on each production video based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, to determine the carbon emissions of each production lighting for each product component corresponding to each production node, including: Pixel identification is performed on each production image frame that makes up each production video to obtain the production pixel value of each production pixel point that makes up each production image frame. Retrieve the reference pixel value corresponding to the lighting unit with the lighting attribute of production-specific lighting, calculate the difference between each production pixel value and the reference pixel value, and determine the absolute difference corresponding to each obtained pixel difference. The production pixel corresponding to the absolute difference within the retrieved difference range is determined as the lighting pixel; Based on a preset irradiance level table, each lighting pixel is divided into pixels to obtain the actual lighting areas corresponding to different irradiance levels. Based on each actual lighting area, video analysis is performed on each production video to determine the carbon emissions of each product component in the production video corresponding to each production node.

[0011] Optionally, in the method according to the present invention, each lighting pixel is divided into pixels based on a preset irradiation level table to obtain each actual lighting area corresponding to different irradiation levels, and video analysis is performed on each production video based on each actual lighting area to determine the carbon emissions of each production lighting for each product component in the production video corresponding to each production node, including: Retrieve a preset illumination level table, wherein the illumination level table includes each illumination level and each illumination pixel range corresponding to different illumination levels; Based on the preset illumination level table, each lighting pixel that is located in the same illumination pixel range and has an adjacent relationship is connected according to each production image frame to obtain each actual illumination area corresponding to different illumination levels. The component region corresponding to the product component in each production image frame that makes up the production video is determined as the target region; Based on each production image frame that makes up the production video, determine the overlapping sub-area of ​​each overlapping region that has a regional overlap relationship with each actual lighting region. The overlapping areas of each overlapping sub-area corresponding to the same production image frame are summed to obtain the overlapping area. If no production video contains any production image frame with an overlapping area greater than the preset overlap threshold, the carbon emission of the production lighting for the product component corresponding to the production video will be determined to be 0.

[0012] Optionally, in the method according to the invention, the method further includes: If any production video contains any overlapping area greater than the retrieved preset overlap threshold, the overlapping sub-areas corresponding to the production video are summed based on different illumination levels to obtain the level area of ​​each actual lighting area corresponding to different illumination levels. The average area corresponding to different irradiation levels is obtained by dividing the area of ​​the irradiation level by the number of images in each production image frame that makes up the production video. The acquisition time of the production video is determined based on the start and end times of the production video, and the carbon emission coefficients corresponding to different irradiation levels are retrieved. The carbon emission levels corresponding to different irradiation levels are calculated by multiplying the collection time, the average area corresponding to the same irradiation level, and the carbon emission coefficient. The carbon emission levels corresponding to the same production video are summed to obtain the carbon emission of the production lighting for the product component corresponding to the production video. If any production video has an illumination level other than Level 1 illumination, a Level 1 warning signal is output for the production node corresponding to the production video.

[0013] Optionally, in the method according to the invention, the method further includes: Based on the virtual workshop model, the reference area of ​​the corresponding reference lighting area is determined, and the reference area is multiplied by the number of units corresponding to each lighting unit with the lighting attribute of production-specific lighting to obtain the total reference lighting area. The baseline carbon emissions are calculated by multiplying the monitoring duration, the total area of ​​the reference lighting, and the corresponding Level 1 irradiation carbon emission coefficient. Determine the carbon emissions of dedicated lighting for each production lighting component corresponding to all product parts; The difference between the baseline carbon emissions and the carbon emissions for dedicated lighting is calculated, and the carbon emissions for public lighting are updated based on the obtained difference in dedicated carbon emissions. If the updated total carbon emissions of any product component are determined to be less than the preset carbon emissions threshold based on the updated public lighting carbon emissions, a level 2 warning signal will be output.

[0014] According to another aspect of the present invention, an organizational carbon budget trend early warning and dynamic optimization system is provided, comprising: The determination module is configured to determine the lighting attributes of each lighting unit located in the production workshop, and to determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration; The analysis module is configured to acquire video recordings for the corresponding monitoring duration at each production node in the production workshop, perform video analysis on the acquired videos based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component. The update module is configured to distribute the carbon emissions of public lighting equally based on the number of components of each product component, and to sum the carbon emissions of each production total based on the obtained average emissions to obtain the updated total carbon emissions.

[0015] According to the present invention, by first distinguishing the different attributes of public lighting and production-specific lighting in the lighting units of the production workshop, the carbon emissions of public lighting and production lighting of each product component within the corresponding monitoring period are accurately calculated. Then, by combining the collected video with the actual lighting area for video analysis, the carbon emissions of production lighting for different production nodes and different product components are accurately broken down and statistically analyzed. Finally, the carbon emissions of public lighting are reasonably distributed according to the number of product components and superimposed on the corresponding total carbon emissions of production. This can effectively avoid the calculation errors caused by the mixed calculation of carbon emissions of public lighting and production-specific lighting, and the inconsistency between reference lighting and actual lighting. It significantly improves the accuracy, completeness and rationality of carbon emission calculation of lighting in the production workshop down to individual product components, and provides reliable data support for workshop carbon emission control, energy-saving optimization and carbon budget early warning. Attached Figure Description

[0016] Figure 1 A flowchart of an organizational carbon budget trend early warning dynamic optimization method according to an embodiment of the present invention is shown; Figure 2 A schematic diagram of a virtual workshop model according to an embodiment of the present invention is shown; Figure 3 A structural block diagram of an organizational carbon budget trend early warning and dynamic optimization system according to another embodiment of the present invention is shown. Detailed Implementation

[0017] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0018] To address the problems existing in the aforementioned background art, the inventors proposed the solution of this invention. One embodiment of this invention provides a method for dynamic optimization of organizational carbon budget trend early warning, which can be executed in a computing device.

[0019] Figure 1 A flowchart of a dynamic optimization method for predicting organizational carbon budget trends, according to an embodiment of the present invention, is shown. This method is suitable for execution in a computing device.

[0020] like Figure 1 As shown, the dynamic optimization method for organizational carbon budget trend early warning proposed in this embodiment begins with step S102, which includes the following: Determine the lighting attributes of each lighting unit located in the production workshop, and determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting during the monitoring period.

[0021] For example, in this embodiment, since the lighting units in the production workshop have different uses, some lighting units are used to cover the public areas of the entire production workshop (such as passageways and rest areas), so the lighting attribute of such lighting units is public lighting; There are also some lighting units used for targeted illumination of production workbenches (such as assembly tables and testing tables). The lighting attribute of these lighting units is production-specific lighting, so it is necessary to first clarify the lighting attribute of each lighting unit. After determining the lighting attributes of each lighting unit in the production workshop, the server will further determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration. Among them, the monitoring duration refers to the pre-set carbon emission statistics period, which can be set to the duration of a standard production shift, such as 8 hours. This monitoring duration can be flexibly adjusted according to the actual production duration of the production workshop. Public lighting carbon emissions refer to the amount of public lighting carbon emissions generated by each lighting unit with the corresponding lighting attribute of public lighting during the monitoring period. The server can first obtain the public lighting area and the number of public lights of the lighting unit with the corresponding lighting attribute of public lighting, and then multiply the public lighting area and the number of public lights to calculate the total public lighting area. Finally, the server can multiply the monitoring duration, the total area of ​​public lighting, and the carbon emission coefficient of the lighting unit with the corresponding lighting attribute as public lighting to calculate the carbon emissions of public lighting. This embodiment distinguishes lighting attributes to avoid mixing the carbon emissions of public lighting and production-specific lighting, thus ensuring that the total carbon emissions of each product component that makes up each production node can be more accurately determined in the future.

[0022] Furthermore, the aforementioned "determining the lighting attributes of each lighting unit located in the production workshop" also includes the following steps: Establish a virtual workshop model corresponding to the production workshop, wherein the virtual workshop model includes virtual workstations and virtual units corresponding to each production workstation and lighting unit; Based on the reference lighting range corresponding to each lighting unit, each reference lighting area is generated on the bottom surface of the virtual workshop model, and the area overlap between each reference lighting area and the area overlap of each virtual workbench is determined. The lighting attributes of the lighting units corresponding to the areas overlapping with the region that are greater than the preset overlapping area are determined as production-specific lighting. Conversely, the lighting attributes of the lighting unit are defined as public lighting.

[0023] For example, in this embodiment, in order to more accurately determine the lighting attributes of each lighting unit located in the production workshop, the server will use 3D modeling technology to construct a virtual workshop model corresponding to the production workshop. The virtual workshop model includes a virtual workbench corresponding to each production workbench and a virtual unit corresponding to each lighting unit. Next, the server will generate reference lighting areas on the bottom surface of the virtual workshop model based on the reference lighting range of each lighting unit, and then determine the area of ​​overlap between each reference lighting area and the area of ​​each virtual workbench. The reference lighting range refers to the theoretical lighting range of each lighting unit under the standard illumination angle. Next, the server will compare the overlapping area of ​​the region with the retrieved preset overlapping area. The preset overlapping area is a judgment threshold set in advance in this embodiment, which can be set to 80% of the theoretical lighting range. The preset overlapping area can be flexibly adjusted according to the workshop layout and lighting requirements. When the overlapping area of ​​a region is greater than a preset overlapping area, it indicates that the lighting unit corresponding to that overlapping area is illuminating the production workbench. Therefore, the server will determine the lighting attribute of the lighting unit corresponding to the region with an overlapping area greater than the retrieved preset overlapping area as production-specific lighting. Figure 2 The solid circle shown; When the overlapping area of ​​a region is less than or equal to a preset overlapping area, it indicates that the lighting unit corresponding to that overlapping area is not illuminating the production workbench, but may be illuminating a public area. Therefore, the server will determine the lighting attribute of the lighting unit corresponding to the region with an overlapping area less than or equal to the retrieved preset overlapping area as public lighting. Figure 2 The hollow circle shown; This embodiment achieves accurate and automated determination of lighting attributes through virtual modeling and analysis of overlapping areas, ensuring the consistency and accuracy of lighting attribute classification.

[0024] Step S104 includes the following: Acquire video recordings for the corresponding monitoring duration at each production node in the production workshop. Perform video analysis on the acquired videos based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting. Determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component.

[0025] For example, in this embodiment, during the production process, a production unit may include multiple product components. For example, if the production unit is a car, the product components may include wheels, body, etc. Since the production time of different product components and the opening status of the corresponding production-specific lighting units are different, and the actual lighting range of the production-specific lighting units may be inconsistent with the reference lighting range due to factors such as the offset of the illumination angle, if the total carbon emissions of each product component are directly calculated based on the reference lighting range, the calculation result will be significantly biased. Therefore, it is necessary to acquire actual production scenarios by collecting videos and combine them with actual lighting areas to calculate the carbon emissions of production lighting. The videos can be acquired by high-definition cameras uniformly installed above each production node. Production lighting carbon emissions refer to the carbon emissions generated by the lighting unit of production-specific lighting during the production process of the corresponding product component. It is directly related to the production time of the product component and the actual lighting intensity. Total production carbon emissions refer to the sum of production lighting carbon emissions generated by the lighting units of production-specific lighting corresponding to different production nodes for the same product component within the monitoring time. This embodiment calculates the carbon emissions of production lighting based on captured video and actual lighting areas, which can avoid errors caused by the inconsistency between the reference lighting range and the actual lighting range. At the same time, it can accurately distinguish the carbon emissions of production lighting for different product components, making it easier for the management end to view and understand the carbon emissions of production lighting for different product components.

[0026] Furthermore, the aforementioned "video analysis of the collected video based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, determining the carbon emissions of each production lighting for each product component corresponding to each production node, and determining the total production carbon emissions of each production lighting for the same product component" also includes the following steps: Based on the collected video, the start and end times of production for each product component at each production node are determined. Based on the start and end times of production for the same product component, video clips are extracted from each collected video to obtain production videos for each product component. Based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, video analysis is performed on each production video to determine the carbon emissions of each production lighting for each product component corresponding to each production node. The total carbon emissions of each lighting component in the same product are summed to obtain the total carbon emissions of each product.

[0027] For example, in this embodiment, the same production node may alternately produce multiple product components within the monitoring period. Therefore, it is necessary to first determine the start and end times of production for each product component, and then extract each video from the collected video based on the start and end times of production for the same product component to obtain each production video for each product component, so as to distinguish the production time period of each product component and facilitate the subsequent accurate calculation of the carbon emissions of production lighting for each product component. Among them, the start production time refers to the specific time when the production node begins processing a certain product component, the end production time refers to the specific time when the production node completes processing a certain product component, and the production video refers to a video clip that contains only the production process of a certain product component, which can exclude interference from the production process of other product components and idle periods. Next, the server will perform video analysis on each production video based on the actual lighting area of ​​each lighting unit with lighting attributes designated as production-specific lighting, in order to determine the carbon emissions of each production lighting for each product component corresponding to each production node. Then, the carbon emissions of each production lighting for the same product component will be summed up, that is, the carbon emissions of production lighting generated by the same product component at different production times and by different production-specific lighting units will be accumulated to obtain the total carbon emissions of the product component. This embodiment achieves accurate calculation of carbon emissions from production lighting by dividing the production time periods of product components and extracting corresponding production videos, thereby further improving the accuracy of carbon emission calculation. At the same time, it simplifies the workload of subsequent video analysis and improves the efficiency of carbon emission calculation.

[0028] Furthermore, the aforementioned "determining the start and end times of production for different product components at each production node based on the collected video footage" also includes the following steps: The video image frames that make up each captured video are identified, and image recognition is performed on each video image frame to determine the component area and mechanical area corresponding to different product parts and robotic arms. If any video image frame corresponding to any captured video does not include any component area, the video image frame is determined as an idle image frame; Based on the acquired video, the first video image frame containing the robotic arm area after the idle image frame is determined as the starting image frame, and the acquisition time corresponding to the starting image frame is determined as the starting production time. Based on the acquired video, the first video image frame without a mechanical area after the starting image frame is determined as the termination image frame that has a production-related relationship with the starting image frame, and the acquisition time corresponding to the termination image frame is determined as the production termination time. Based on the acquired video, image recognition is performed on each video image frame located between the starting image frame and the ending image frame that has a production relationship with the starting image frame to determine the product component corresponding to the starting production time and the ending production time.

[0029] For example, in this embodiment, the production process of each production node is completed by a robotic arm. The operating state of the robotic arm is directly related to the production state of the product component. Moreover, the appearance characteristics of different product components are different and can be distinguished by image recognition. Therefore, by using image recognition technology and combining the regional characteristics of the robotic arm and the product component, the start time and end time of production of each product component can be determined. Among them, the component area refers to the pixel area where the product component is located in the video image frame, the mechanical area refers to the pixel area where the robotic arm is located in the video image frame, and the idle image frame refers to the image frame where no product component appears, which is the idle period of the corresponding production node. Specifically, if any video image frame corresponding to any captured video does not include any component area, the server will determine the video image frame as an idle image frame. The acquisition time of the first video image frame containing the robotic arm area after the idle image frame can represent the start of production operation for a new product component by the production node. Therefore, the server will determine the first video image frame containing the robotic arm area after the idle image frame as the starting image frame based on the captured video, and determine the acquisition time corresponding to the starting image frame as the starting production time. The acquisition time of the first video image frame without a mechanical area after the starting image frame can indicate that the production node has stopped producing the product part. Therefore, the server will determine the first video image frame without a mechanical area after the starting image frame as the termination image frame that has a production relationship with the above-mentioned starting image frame based on the acquired video, and determine the acquisition time of the corresponding termination image frame as the production termination time. The start and end image frames are key nodes that distinguish between production periods and idle periods, as well as the production periods of different product components, ensuring accurate positioning of production times. Finally, the server will perform image recognition on each video image frame between the captured video frame and the termination image frame that has a production relationship with the starting image frame, to determine the product component corresponding to the start production time and the termination production time.

[0030] Furthermore, the aforementioned "based on the acquired video, performing image recognition on each video image frame located between the starting image frame and the ending image frame that has a production-related relationship with the starting image frame, to determine the product component corresponding to the starting production time and the ending production time" also includes the following steps: Based on the acquired video, image recognition is performed on each video image frame between the starting image frame and the ending image frame that has a production-related relationship with the starting image frame, and the component area that has an operational relationship with the mechanical area is determined as the operation area based on each video image frame. Determine the number of operations for each operating area corresponding to the same product component, and identify the product component corresponding to the maximum number of operations as the product component corresponding to the start production time and the end production time.

[0031] For example, in this embodiment, since the production unit is formed by integrating multiple product components through multiple production nodes, it is possible that multiple product components may appear simultaneously on the production operation table corresponding to a production node, but only one of them needs to be produced based on that production node. Therefore, it is necessary to analyze the operation relationship between the component area and the machine area to determine the product component that performs the production operation during that time period. Specifically, the server will perform image recognition on each video image frame between the captured video frame and the ending image frame that has a production relationship with the starting image frame, and determine the component area that has an operational relationship with the mechanical area as the operation area based on each video image frame. Among them, the operation association relationship refers to the overlap or adjacency between the component area and the machine area, and the robot arm's action (such as gripping or assembling) is directed towards the component area, indicating that the robot arm is processing the product component. The operation area refers to the area where the product component operated by the robot arm is located. Subsequently, the server will determine the number of operations in each operation area corresponding to the same product component. The larger the number of operations, the more frequently the robotic arm processes the product component. That is, the operation area corresponds to the main product component processed by the robotic arm. Therefore, the server will determine the product component corresponding to the maximum number of operations as the product component corresponding to the start production time and end production time. This embodiment accurately identifies the product components that are produced during each production period by analyzing the operational relationships and the number of operations. This avoids misjudgments when multiple product components coexist, ensuring that subsequent carbon emission calculations can accurately correspond to specific product components and improving the targeting and accuracy of carbon emission calculations.

[0032] Furthermore, the aforementioned "video analysis of each production video based on the actual lighting area of ​​each lighting unit whose lighting attributes are production-specific lighting, to determine the carbon emissions of each production lighting for each product component corresponding to each production node" also includes the following steps: Pixel identification is performed on each production image frame that makes up each production video to obtain the production pixel value of each production pixel point that makes up each production image frame. Retrieve the reference pixel value corresponding to the lighting unit with the lighting attribute of production-specific lighting, calculate the difference between each production pixel value and the reference pixel value, and determine the absolute difference corresponding to each obtained pixel difference. The production pixel corresponding to the absolute difference within the retrieved difference range is determined as the lighting pixel; Based on a preset irradiance level table, each lighting pixel is divided into pixels to obtain the actual lighting areas corresponding to different irradiance levels. Based on each actual lighting area, video analysis is performed on each production video to determine the carbon emissions of each product component in the production video corresponding to each production node.

[0033] For example, in this embodiment, in order to ensure a certain production effect, the lighting intensity of the lighting unit corresponding to the production-specific lighting is itself high. In actual application, the actual lighting area of ​​the lighting unit of the production-specific lighting may overlap, resulting in a higher lighting intensity for a certain product component, which in turn leads to a higher carbon emission of the production lighting for that product component, which may cause a certain waste of resources. Therefore, the server first performs pixel recognition on each production image frame that makes up each production video to obtain the production pixel value of each production pixel point that makes up each production image frame. Then, it retrieves the reference pixel value corresponding to the lighting unit whose lighting attribute is production-specific lighting, and calculates the difference between each production pixel value and the reference pixel value. Since the difference result may be negative, the server will further determine the absolute difference corresponding to each obtained pixel difference. Next, the server retrieves the difference range, which is a threshold range preset in this embodiment. This range can be flexibly adjusted according to the ambient light and the parameters of the lighting unit. When the absolute difference is within the difference range, it means that the difference between the production pixel value of the production pixel corresponding to the absolute difference and the normal light is large, and it is closer to the reference pixel value of the lighting unit. Therefore, the server will determine the production pixel corresponding to the absolute difference within the retrieved difference range as the lighting pixel. Next, in order to determine whether there is any overlap in the actual lighting areas, the server will divide each lighting pixel point according to the preset illumination level table to obtain each actual lighting area corresponding to different illumination levels, and further perform video analysis on each production video based on each actual lighting area to determine the carbon emissions of each production lighting for each product component in the production video corresponding to each production node. This embodiment achieves accurate identification of the actual lighting area through pixel recognition and difference analysis.

[0034] Furthermore, the aforementioned "dividing each lighting pixel based on a preset illumination level table to obtain actual lighting areas corresponding to different illumination levels, and performing video analysis on each production video based on each actual lighting area to determine the carbon emissions of each production lighting for each product component in the production video corresponding to each production node" also includes the following steps: Retrieve a preset illumination level table, wherein the illumination level table includes each illumination level and each illumination pixel range corresponding to different illumination levels; Based on the preset illumination level table, each lighting pixel that is located in the same illumination pixel range and has an adjacent relationship is connected according to each production image frame to obtain each actual illumination area corresponding to different illumination levels. The component region corresponding to the product component in each production image frame that makes up the production video is determined as the target region; Based on each production image frame that makes up the production video, determine the overlapping sub-area of ​​each overlapping region that has a regional overlap relationship with each actual lighting region. The overlapping areas of each overlapping sub-area corresponding to the same production image frame are summed to obtain the overlapping area. If no production video contains any production image frame with an overlapping area greater than the preset overlap threshold, the carbon emission of the production lighting for the product component corresponding to the production video will be determined to be 0.

[0035] For example, in this embodiment, different levels of illumination for production-specific lighting correspond to different carbon emission coefficients, and only when the lighting unit of the production-specific lighting illuminates a product component that is undergoing production operation, the carbon emissions generated are considered as the carbon emissions of the production lighting for that product component. To ensure the accuracy of the final determination of the carbon emissions of production lighting for each product component, the carbon emissions of production lighting should not be included in the calculation when the lighting unit of the production-specific lighting illuminates a product component that is not in production operation. First, the server retrieves a preset illumination level table. The illumination level table includes various illumination levels and corresponding pixel ranges for different illumination levels. The preset illumination level table is a pre-defined level division standard in this embodiment, which can be divided into three levels: Level 1 illumination corresponds to the lighting intensity of one illumination unit, which is the lowest; Level 2 illumination corresponds to the lighting intensity of two illumination units superimposed on each other, which is medium; and Level 3 illumination corresponds to the lighting intensity of three illumination units superimposed on each other, which is the highest. Different illumination levels correspond to different carbon emission coefficients. Next, the server will connect the adjacent lighting pixels located in the same lighting pixel range based on the preset illumination level table and each production image frame to obtain the actual lighting areas corresponding to different illumination levels. Next, the server will determine the component area corresponding to the product component in each production image frame that makes up the production video as the target area, that is, the area corresponding to the product component that is being produced. Subsequently, the server will determine the overlapping sub-area of ​​each overlapping region that has a regional overlap relationship with each actual lighting region based on each production image frame that makes up the production video, and then sum up the overlapping sub-areas corresponding to the same production image frame to obtain each overlapping area. Finally, the server retrieves a preset overlap threshold. When no production video contains any production image frame with an overlap area greater than the preset overlap threshold, it means that no lighting unit of production-specific lighting is illuminating the product component that is undergoing production operation at that production node. Therefore, the server will determine the carbon emission of the production lighting for the product component corresponding to that production video as 0.

[0036] Furthermore, the above method also includes the following steps: If any production video contains any overlapping area greater than the retrieved preset overlap threshold, the overlapping sub-areas corresponding to the production video are summed based on different illumination levels to obtain the level area of ​​each actual lighting area corresponding to different illumination levels. The average area corresponding to different irradiation levels is obtained by dividing the area of ​​the irradiation level by the number of images in each production image frame that makes up the production video. The acquisition time of the production video is determined based on the start and end times of the production video, and the carbon emission coefficients corresponding to different irradiation levels are retrieved. The carbon emission levels corresponding to different irradiation levels are calculated by multiplying the collection time, the average area corresponding to the same irradiation level, and the carbon emission coefficient. The carbon emission levels corresponding to the same production video are summed to obtain the carbon emission of the production lighting for the product component corresponding to the production video. If any production video has an illumination level other than Level 1 illumination, a Level 1 warning signal is output for the production node corresponding to the production video.

[0037] For example, in this embodiment, if any production video has a production image frame with an overlapping area greater than the retrieved preset overlap threshold, it indicates that there is a lighting unit with dedicated production lighting at that production node illuminating the product component that is undergoing production operation. Since different illumination levels have different carbon emissions, the server will sum up the overlapping sub-areas corresponding to the production video at the same illumination level to obtain the level area of ​​each actual lighting area corresponding to different illumination levels. Next, the server will divide the area of ​​each level by the number of images in each production image frame that makes up the production video to obtain the average area corresponding to different illumination levels. This average area can reflect the average coverage area of ​​different levels of lighting during the production period, avoid the randomness of single frame images, and ensure the accuracy of the final calculation of carbon emissions of production lighting. Next, the server will determine the acquisition time of the corresponding production video based on the start and end times of the production video, i.e. the production time of the product component, and then retrieve the carbon emission coefficients corresponding to different irradiation levels. The server will multiply the collection time, the average area corresponding to the same irradiation level, and the carbon emission coefficient to obtain the carbon emission of the corresponding irradiation level. Then, it will sum up the carbon emission of each level corresponding to the same production video to obtain the carbon emission of the production lighting of the product component corresponding to the production video. Level 1 illumination is the standard lighting level required for production, which has the most reasonable carbon emissions and the best lighting effect. If any illumination level other than Level 1 occurs, it indicates that the lighting intensity is abnormal, which may not only increase carbon emissions but also affect product processing quality. Therefore, when any production video has an illumination level other than Level 1, the server will output a Level 1 warning signal for the production node corresponding to that production video, so that the management can promptly detect abnormal lighting intensity and make rapid adjustments, such as adjusting the lighting angle or lighting height of the lighting unit. This can not only reduce unnecessary carbon emissions and ensure the stability of the carbon budget, but also take into account the production effect of product components.

[0038] Step S106 includes the following: The carbon emissions of public lighting are evenly distributed based on the number of components in each product, and the total carbon emissions of each production are superimposed based on the obtained evenly distributed emissions to obtain the updated total carbon emissions.

[0039] For example, in this embodiment, the lighting unit of the public lighting is used to cover the public area in the production workshop. Its public lighting carbon emissions belong to the overall carbon emissions of the workshop and cannot be directly linked to a specific product component. However, carbon budget early warning needs to be accurate to the total carbon emissions of each product component. Therefore, the server will divide the carbon emissions of public lighting equally according to the number of components in the product, and then add the resulting equalized emissions to the total carbon emissions of each production to obtain the updated total carbon emissions. Among them, the number of components refers to the total number of product components produced during the monitoring period; the average carbon emission is the carbon emission of public lighting that should be borne by a single product component, which is the average carbon emission; and the updated total carbon emission is the sum of the total carbon emission of the product component and the average carbon emission, which is the total carbon emission of the product component during the monitoring period. This embodiment achieves accurate allocation of carbon emissions for public lighting by using an equal distribution and superposition method, ensuring that the total carbon emissions of each product component are calculated completely and reasonably, and avoiding subsequent warning deviations caused by the failure to allocate carbon emissions for public lighting.

[0040] Furthermore, the above method also includes the following steps: Based on the virtual workshop model, the reference area of ​​the corresponding reference lighting area is determined, and the reference area is multiplied by the number of units corresponding to each lighting unit with the lighting attribute of production-specific lighting to obtain the total reference lighting area. The baseline carbon emissions are calculated by multiplying the monitoring duration, the total area of ​​the reference lighting, and the corresponding Level 1 irradiation carbon emission coefficient. Determine the carbon emissions of dedicated lighting for each production lighting component corresponding to all product parts; The difference between the baseline carbon emissions and the carbon emissions for dedicated lighting is calculated, and the carbon emissions for public lighting are updated based on the obtained difference in dedicated carbon emissions. If the updated total carbon emissions of any product component are determined to be less than the preset carbon emissions threshold based on the updated public lighting carbon emissions, a level 2 warning signal will be output.

[0041] For example, in this embodiment, the server determines the reference area of ​​a single reference lighting area based on the virtual workshop model, and then multiplies the reference area with the number of units corresponding to each lighting unit whose lighting attribute is production-specific lighting to obtain the total reference lighting area. Next, the server will multiply the monitoring duration, the total area of ​​the reference lighting, and the corresponding first-level irradiation carbon emission coefficient to calculate the reference carbon emissions generated by all production-specific lighting units under standard conditions. Next, the server will sum up the carbon emissions of each production lighting for all product components to obtain the carbon emissions of dedicated lighting. Then, the difference between the baseline carbon emissions and the dedicated lighting carbon emissions will be calculated. If the difference in the dedicated carbon emissions is not zero, it means that there are production carbon emissions of any product component that have not been counted. Therefore, the server will include the difference in dedicated carbon emissions into the public lighting carbon emissions to distribute the difference in dedicated carbon emissions equally. If the updated total carbon emissions of any product component are less than the preset carbon emission threshold based on the updated public lighting carbon emissions, it indicates that the lighting unit of the corresponding production-specific lighting may not be turned on properly, has abnormal lighting, or has not been effectively identified. In this case, the server will output a level 2 warning signal to facilitate the management to promptly check the lighting status of each lighting unit of the production-specific lighting to ensure the production effect of each product component.

[0042] According to the present invention, by first distinguishing the different attributes of public lighting and production-specific lighting in the lighting units of the production workshop, the carbon emissions of public lighting and production lighting of each product component within the corresponding monitoring period are accurately calculated. Then, by combining the collected video with the actual lighting area for video analysis, the carbon emissions of production lighting for different production nodes and different product components are accurately broken down and statistically analyzed. Finally, the carbon emissions of public lighting are reasonably distributed according to the number of product components and superimposed on the corresponding total carbon emissions of production. This can effectively avoid the calculation errors caused by the mixed calculation of carbon emissions of public lighting and production-specific lighting, and the inconsistency between reference lighting and actual lighting. It significantly improves the accuracy, completeness and rationality of calculating carbon emissions of lighting in the production workshop down to individual product components, and provides reliable data support for workshop carbon emission control, energy-saving optimization and carbon budget early warning.

[0043] Another embodiment of the present invention provides an organizational carbon budget trend early warning and dynamic optimization system. Figure 3 Its corresponding system block diagram includes: The determination module is configured to determine the lighting attributes of each lighting unit located in the production workshop, and to determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration; The analysis module is configured to acquire video recordings for the corresponding monitoring duration at each production node in the production workshop, perform video analysis on the acquired videos based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component. The update module is configured to distribute the carbon emissions of public lighting equally based on the number of components of each product component, and to sum the carbon emissions of each production total based on the obtained average emissions to obtain the updated total carbon emissions.

[0044] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used with the examples of this invention. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing preferred embodiments of the invention.

[0045] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0046] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof.

[0047] Those skilled in the art will understand that modules, units, or components of the devices disclosed in the examples herein can be arranged in the devices described in this embodiment, or alternatively, can be located in one or more devices different from the devices in this example. The modules in the foregoing examples can be combined into a single module or, in addition, can be divided into multiple sub-modules.

[0048] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components.

[0049] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of the invention and form different embodiments.

[0050] Furthermore, some of the embodiments described herein are methods or combinations of method elements that can be implemented by a processor of a computer system or by other means of performing the functions. Therefore, a processor having the necessary instructions for implementing the methods or method elements forms means for implementing the methods or method elements. Furthermore, the elements described herein in the apparatus embodiments are examples of means for implementing the functions performed by elements for the purposes of carrying out the invention.

[0051] As used herein, unless otherwise specified, the use of ordinal numbers such as “first,” “second,” “third,” etc., to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects being described must have a given order in time, space, ordering, or any other manner.

[0052] Although the invention has been described with respect to a limited number of embodiments, those skilled in the art will understand from the foregoing description that other embodiments are conceivable within the scope of the invention described herein. Furthermore, it should be noted that the language used in this specification has been chosen primarily for readability and edibility purposes, and not for the purpose of explaining or limiting the subject matter of the invention.

Claims

1. A method for dynamic optimization and early warning of organizational carbon budget trends, characterized in that, include: Determine the lighting attributes of each lighting unit located in the production workshop, and determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration; Acquire the video for the corresponding monitoring duration at each production node in the production workshop. Perform video analysis on the acquired video based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting. Determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component. The carbon emissions of public lighting are evenly distributed based on the number of components in each product, and the total carbon emissions of each production are superimposed based on the obtained evenly distributed emissions to obtain the updated total carbon emissions.

2. The method according to claim 1, characterized in that, Determine the lighting attributes of each lighting unit located in the production workshop, including: Establish a virtual workshop model corresponding to the production workshop, wherein the virtual workshop model includes a virtual workbench and a virtual unit corresponding to each production workbench and lighting unit; Based on the reference lighting range corresponding to each lighting unit, each reference lighting area is generated on the bottom surface of the virtual workshop model, and the area overlap between each reference lighting area and the area overlap of each virtual workbench is determined. The lighting attributes of the lighting units corresponding to the areas whose overlap area with the region is greater than the preset overlap area are determined as production-specific lighting. Conversely, the lighting attributes of the lighting unit are defined as public lighting.

3. The method according to claim 2, characterized in that, Based on the actual lighting area of ​​each lighting unit designated as production-specific lighting, video analysis is performed on the collected video to determine the carbon emissions of each production lighting for each product component at each production node, and to determine the total production carbon emissions for each production lighting unit corresponding to the same product component, including: Based on the collected video, the start and end times of production for each product component at each production node are determined. Based on the start and end times of production for the same product component, video clips are extracted from each collected video to obtain production videos for each product component. Based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, video analysis is performed on each production video to determine the carbon emissions of each production lighting for each product component corresponding to each production node. The total carbon emissions of each lighting component in the same product are summed to obtain the total carbon emissions of each product.

4. The method according to claim 3, characterized in that, Based on the captured video, the start and end times of production for each production node and corresponding product component are determined, including: The video image frames that make up each captured video are identified, and image recognition is performed on each video image frame to determine the component area and mechanical area corresponding to different product parts and robotic arms. If any video image frame corresponding to any captured video does not include any component area, the video image frame is determined as an idle image frame; Based on the acquired video, the first video image frame containing the robotic arm area after the idle image frame is determined as the starting image frame, and the acquisition time corresponding to the starting image frame is determined as the starting production time. Based on the acquired video, the first video image frame without a mechanical area after the starting image frame is determined as the termination image frame that has a production-related relationship with the starting image frame, and the acquisition time corresponding to the termination image frame is determined as the production termination time. Based on the acquired video, image recognition is performed on each video image frame located between the starting image frame and the ending image frame that has a production relationship with the starting image frame to determine the product component corresponding to the starting production time and the ending production time.

5. The method according to claim 4, characterized in that, Based on the acquired video, image recognition is performed on each video image frame located between the starting image frame and the ending image frame that has a production-related relationship with the starting image frame to determine the product component corresponding to the starting production time and the ending production time, including: Based on the acquired video, image recognition is performed on each video image frame between the starting image frame and the ending image frame that has a production-related relationship with the starting image frame, and the component area that has an operational relationship with the mechanical area is determined as the operation area based on each video image frame. Determine the number of operations for each operating area corresponding to the same product component, and identify the product component corresponding to the maximum number of operations as the product component corresponding to the start production time and the end production time.

6. The method according to claim 5, characterized in that, Based on the actual lighting area of ​​each lighting unit designated as production-specific lighting, video analysis is performed on each production video to determine the carbon emissions of each production lighting for each product component at each production node, including: Pixel identification is performed on each production image frame that makes up each production video to obtain the production pixel value of each production pixel point that makes up each production image frame. Retrieve the reference pixel value corresponding to the lighting unit with the lighting attribute of production-specific lighting, calculate the difference between each production pixel value and the reference pixel value, and determine the absolute difference corresponding to each obtained pixel difference. The production pixel corresponding to the absolute difference within the retrieved difference range is determined as the lighting pixel; Based on a preset irradiance level table, each lighting pixel is divided into pixels to obtain the actual lighting areas corresponding to different irradiance levels. Based on each actual lighting area, video analysis is performed on each production video to determine the carbon emissions of each product component in the production video corresponding to each production node.

7. The method according to claim 6, characterized in that, Based on a preset illumination level table, each illumination pixel is divided into pixels to obtain the actual illumination areas corresponding to different illumination levels. Then, based on each actual illumination area, video analysis is performed on each production video to determine the carbon emissions of each product component's production lighting for each production node, including: Retrieve a preset illumination level table, wherein the illumination level table includes each illumination level and each illumination pixel range corresponding to different illumination levels; Based on the preset illumination level table, each lighting pixel that is located in the same illumination pixel range and has an adjacent relationship is connected according to each production image frame to obtain each actual illumination area corresponding to different illumination levels. The component region corresponding to the product component in each production image frame that makes up the production video is determined as the target region; Based on each production image frame that makes up the production video, determine the overlapping sub-area of ​​each overlapping region that has a regional overlap relationship with each actual lighting region. The overlapping areas of each overlapping sub-area corresponding to the same production image frame are summed to obtain the overlapping area. If no production video contains any production image frame with an overlapping area greater than the preset overlap threshold, the carbon emission of the production lighting for the product component corresponding to the production video will be determined to be 0.

8. The method according to claim 7, characterized in that, The method further includes: If any production video contains any overlapping area greater than the retrieved preset overlap threshold, the overlapping sub-areas corresponding to the production video are summed based on different illumination levels to obtain the level area of ​​each actual lighting area corresponding to different illumination levels. The average area corresponding to different irradiation levels is obtained by dividing the area of ​​the irradiation level by the number of images in each production image frame that makes up the production video. The acquisition time of the production video is determined based on the start and end times of the production video, and the carbon emission coefficients corresponding to different irradiation levels are retrieved. The carbon emission levels corresponding to different irradiation levels are calculated by multiplying the collection time, the average area corresponding to the same irradiation level, and the carbon emission coefficient. The carbon emission levels corresponding to the same production video are summed to obtain the carbon emission of the production lighting for the product component corresponding to the production video. If any production video has an illumination level other than Level 1 illumination, a Level 1 warning signal is output for the production node corresponding to the production video.

9. The method according to claim 8, characterized in that, The method further includes: Based on the virtual workshop model, the reference area of ​​the corresponding reference lighting area is determined, and the reference area is multiplied by the number of units corresponding to each lighting unit with the lighting attribute of production-specific lighting to obtain the total reference lighting area. The baseline carbon emissions are calculated by multiplying the monitoring duration, the total area of ​​the reference lighting, and the corresponding Level 1 irradiation carbon emission coefficient. Determine the carbon emissions of dedicated lighting for each production lighting component corresponding to all product parts; The difference between the baseline carbon emissions and the carbon emissions for dedicated lighting is calculated, and the carbon emissions for public lighting are updated based on the obtained difference in dedicated carbon emissions. If the updated total carbon emissions of any product component are determined to be less than the preset carbon emissions threshold based on the updated public lighting carbon emissions, a level 2 warning signal will be output.

10. A dynamic optimization system for early warning of organizational carbon budget trends, characterized in that, include: The determination module is configured to determine the lighting attributes of each lighting unit located in the production workshop, and to determine the carbon emissions of public lighting for each lighting unit with the corresponding lighting attribute of public lighting for the corresponding monitoring duration; The analysis module is configured to acquire video recordings for the corresponding monitoring duration at each production node in the production workshop, perform video analysis on the acquired videos based on the actual lighting area of ​​each lighting unit whose lighting attribute is production-specific lighting, determine the carbon emissions of each production lighting for each product component corresponding to each production node, and determine the total carbon emissions of each production lighting for the same product component. The update module is configured to distribute the carbon emissions of public lighting equally based on the number of components of each product component, and to sum the carbon emissions of each production total based on the obtained average emissions to obtain the updated total carbon emissions.

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