A carbon emission monitoring, early warning, and analysis system and method based on edge computing

Abstract

This invention discloses a carbon emission monitoring, early warning, and analysis system and method based on edge computing, comprising: a carbon emission benchmark range setting interface, used to set carbon emission benchmark ranges for different environmental emission sources in different areas of a city and obtain energy consumption data of different production enterprises within the carbon emission benchmark range setting; an emission source activity area distribution interface, used to construct a reference area distribution map of environmental emission source activity in different areas based on energy consumption data of different production enterprises in geological records; and a sensor and equipment monitoring interface, used to generate dynamic carbon emission coefficients based on the reference area distribution map of environmental emission source activity in different areas and adjustment instructions received from the edge computing server according to the resolution of the monitoring sensors, and to control the changes in carbon emissions of different production enterprises. This invention improves the problem of low monitoring efficiency caused by low resolution and enhances the accuracy of carbon emission monitoring in cities.

Description

Technical Field

[0001] This invention relates to the field of urban carbon emission monitoring and early warning, and in particular to a carbon emission monitoring and early warning analysis system and method based on edge computing. Background Technology

[0002] With increasing global focus on carbon emission control, accurate and efficient carbon emission monitoring and early warning analysis systems have become key tools for governments and businesses worldwide to address climate change and achieve sustainable development. Traditional carbon emission monitoring systems primarily rely on centralized data processing platforms, remotely collecting and analyzing data from various sensors. However, these methods often face challenges such as inconsistent data collection standards among production enterprises, low accuracy of detection equipment, and data transmission delays, leading to low monitoring efficiency. Especially during monitoring across different production enterprises, monitoring errors are often unavoidable, posing a significant challenge to accurate carbon emission assessment and timely early warning.

[0003] A major drawback of existing technologies is the issue of monitoring errors, particularly when multiple production enterprises use different types of equipment and methods for detection. The accumulation of these errors can significantly impact the overall monitoring accuracy of the system. Differences in production processes, scale, and equipment performance among different enterprises lead to inconsistencies and biases in carbon emission data. For example, some enterprises may use rudimentary detection equipment, resulting in lower data accuracy. Even in complex production environments, equipment readings may differ significantly from actual emissions. Furthermore, traditional systems typically rely on periodic data acquisition and remote analysis, which makes data updates untimely and unable to quickly reflect potential sudden emissions during production, thus affecting the accuracy and timeliness of early warnings. Summary of the Invention

[0004] In view of the problems existing in the background technology, the purpose of this invention is to provide a carbon emission monitoring, early warning and analysis system and method based on edge computing, so as to realize accurate monitoring of edge computing servers of different production enterprises based on monitoring sensors.

[0005] A first aspect of the present invention provides a carbon emission monitoring, early warning, and analysis system based on edge computing, comprising:

[0006] The carbon emission baseline range setting interface is used to set carbon emission baseline ranges for environmental emission source activities in different areas of the city and obtain energy consumption data of different production enterprises for carbon emission baseline range settings.

[0007] The interface for the distribution of emission source activity areas is used to set energy consumption data of different production enterprises and urban environmental protection process data obtained from the urban database at the monitoring and sensing device platform layer according to the carbon emission benchmark range, match the energy consumption data of different production enterprises in the geological record file, and construct a distribution map of environmental emission source activity areas in different regions based on the energy consumption data of different production enterprises in the geological record file.

[0008] The sensor and equipment monitoring interface is used to generate dynamic carbon emission coefficients based on the distribution map of environmental emission source activities in different regions and the edge computing server adjustment instructions received according to the resolution of the monitoring sensor device. It also controls the changes in carbon emissions of different production enterprises based on the dynamic carbon emission coefficients and obtains unit time energy consumption data within the activities of environmental emission sources in different regions.

[0009] The early warning analysis interface is used to perform early warning analysis on the activity area distribution map of environmental emission sources in different reference regions based on energy consumption data per unit time, obtain the latest activity area distribution map of environmental emission sources in different reference regions, and perform feature extraction and adjustment on the dynamic carbon emission coefficient based on the latest activity area distribution map of environmental emission sources in different reference regions to obtain the latest carbon emission coefficient per unit time.

[0010] The carbon emission change control interface is used to control the carbon emission changes of different production enterprises based on the latest carbon emission coefficient per unit time, and to obtain energy consumption data of different production enterprises at different unit times.

[0011] Furthermore, the carbon emission benchmark range setting interface includes:

[0012] The emission source activity data feature extraction unit is used to obtain urban environmental protection process data from the urban database of the platform layer of the monitoring and sensing device, and to identify environmental emission source activities in different areas from the urban environmental protection process data.

[0013] The feature extraction unit for climate and environmental impact factors data is used to extract the climate and environmental impact factors data of the carbon emission benchmark range setting parameters from urban environmental protection process data, based on the carbon emission benchmark range setting parameter requirements of different regional environmental emission source activities.

[0014] The carbon emission coefficient determination unit is used to generate carbon emission coefficients for the carbon emission benchmark range setting based on the carbon emission benchmark range setting parameters, climate and environmental impact factor data, and the carbon emission benchmark range setting parameter requirements of environmental emission source activities in different regions.

[0015] The carbon emission benchmark range setting monitoring unit is used to control the carbon emission changes of different production enterprises in different areas of the city's environmental emission source activities according to the carbon emission coefficient set by the carbon emission benchmark range, and to obtain the energy consumption data of different production enterprises within the carbon emission benchmark range.

[0016] Furthermore, the distribution interface of the emission source activity area includes:

[0017] The climate and environmental impact factor data determination unit is used to determine the climate and environmental impact factors of carbon dioxide concentration changes of emission source activities in different regions. It acquires urban environmental protection process data from the urban database of the monitoring and sensing device platform layer, and extracts the corresponding climate and environmental impact factor data of carbon dioxide concentration changes of emission source activities from the urban environmental protection process data.

[0018] The carbon dioxide concentration change determination unit is used to determine the carbon dioxide concentration changes of environmental emission source activities in different regions based on climate and environmental impact factor data on carbon dioxide concentration changes of emission source activities.

[0019] The carbon absorption efficiency data feature extraction unit is used to extract the interval change value features of energy consumption data of different production enterprises within the carbon emission benchmark range based on the interval change value feature extraction strategy corresponding to the change of carbon dioxide concentration of emission source activities, so as to obtain the carbon absorption efficiency data of carbon dioxide concentration change of emission source activities in different channels.

[0020] The carbon absorption efficiency feature extraction and calculation unit for different seasons is used to extract and calculate the carbon absorption efficiency for different seasons based on the carbon absorption efficiency data of carbon dioxide concentration changes of all emission sources in the cloud monitoring of different production enterprises.

[0021] The reference area distribution map construction unit is used to construct a regional distribution map of environmental emission source activities in different regions based on the energy consumption data of different production enterprises in the geological record files of carbon absorption efficiency in different seasons.

[0022] Furthermore, the sensor and device monitoring interface includes:

[0023] The carbon emission rate range construction unit is used to determine the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times based on the regional distribution map of environmental emission source activities in different regions, and to generate the carbon emission rate range of different production enterprises in the process of carbon emission change based on the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times and the regional distribution map of environmental emission source activities in different regions.

[0024] The edge computing server transmits wireless signal units to transmit the carbon emission rate range of different production enterprises to the edge computing server monitoring end according to the resolution of the monitoring sensor device, and receives the corresponding wireless signal instructions.

[0025] The carbon emission coefficient generation unit is used to adjust and correct the production capacity per unit area of ​​carbon emission changes of different production enterprises at different time periods according to the adjustment instructions of the edge computing server in the wireless signal instructions, to obtain the adjusted production capacity per unit area of ​​carbon emission changes of different production enterprises, and to generate dynamic carbon emission coefficients based on the adjusted production capacity per unit area of ​​carbon emission changes of different production enterprises.

[0026] The unit for obtaining changes in carbon emissions per unit time is used to control the changes in carbon emissions of different production enterprises based on the unit time carbon emission coefficient in the dynamic carbon emission coefficient and to obtain unit time energy consumption data of environmental emission source activities in different regions.

[0027] Furthermore, the carbon emission rate range construction unit includes:

[0028] The traffic emission location detection unit is used to determine the horizontal and vertical axis data representation of different altitudes of environmental emission source activities in different regions based on the distribution map of environmental emission source activities in different regions, and to determine the traffic emission location of the vehicle ownership in each different region at different altitudes of environmental emission source activities in different regions.

[0029] The traffic emission magnitude detection unit is used to divide the environmental emission source activity area distribution map of different regions into multiple interval emission source activity area distribution maps with different carbon absorption efficiency interference. In the multiple interval emission source activity algorithm, the vehicle ownership sources of different regions that interact with the corresponding traffic emission locations are identified as the sources of traffic emission magnitude.

[0030] The carbon matter type detection unit is used to take the midpoint of the line connecting the sources of traffic emissions as the emission source activity at different time periods, and fit the carbon matter type of the environmental emission source activity in different areas based on all the relatively different time periods.

[0031] The carbon deposition rate assessment unit is used to generate carbon emission rate ranges for different production enterprises based on the air moisture characteristics of different altitudes of environmental emission source activities in different regions, the clustering algorithm corresponding to environmental emission source activities in different regions, and the carbon types of environmental emission source activities in different regions.

[0032] Furthermore, the carbon deposition rate evaluation unit includes:

[0033] The component for determining carbonaceous material types at different temperatures is used to determine the tangents of carbonaceous material types from environmental emission sources in different regions at different time periods of emission source activity in different channels. The component includes the emission source activity at different time periods as the emission source activity axis for carbonaceous material types at different temperatures.

[0034] The component for determining the frequency of severe convective weather at different temperatures is used to determine the vehicle ownership in all different regions where different temperature carbon types of environmental emission source activities intersect. After taking the dynamic carbon environmental digestion size of the corresponding emission source activities at different times, the component determines the frequency of severe convective weather at different temperatures at different altitudes in different regions after taking the dynamic carbon environmental digestion size of the emission source activities at different times.

[0035] The carbon deposition rate assessment component is used to input the frequency of severe convective weather at different temperatures after the dynamic carbon digestion of the environment at different time periods of emission source activity into the clustering algorithm of emission source activity in different regions. It determines the degree of shear slip damage at different time periods of emission source activity, and assesses the carbon deposition rate of carbon types of emission source activity in different regions based on the degree of shear slip damage, generating carbon emission rate ranges for different production enterprises' carbon emission change processes.

[0036] Furthermore, the early warning analysis interface includes:

[0037] The carbon stock early warning analysis unit is used to adjust the carbon stock carbon emission coefficient in the dynamic carbon emission coefficient based on the energy consumption data per unit time.

[0038] The dynamic regional distribution map update unit is used to perform early warning analysis on the regional distribution maps of environmental emission sources in different reference areas based on energy consumption data per unit time, and to obtain the latest regional distribution maps of environmental emission sources in different reference areas.

[0039] The energy consumption visualization unit is used to visualize the macro-energy consumption of emission source activities based on the latest regional distribution map of environmental emission source activities in different regions, the unit time carbon emission coefficient in the dynamic carbon emission coefficient, and the energy consumption data of different production enterprises in the geological record file.

[0040] The adjustment transmission unit is used to transmit the macroscopic energy consumption of emission source activities to the edge computing server monitoring end for display according to the resolution of the monitoring sensor device, and to receive the unit time monitoring adjustment command input by the edge computing server monitoring end;

[0041] The early warning analysis unit is used to extract and adjust the dynamic carbon emission coefficient according to the unit time monitoring and adjustment instructions to obtain the latest unit time carbon emission coefficient.

[0042] Furthermore, the energy consumption visualization unit includes:

[0043] The overload detection unit is used to determine the display lag time and predicted display advance time of the edge computing server at the edge computing server monitoring end, generate the corresponding predicted display time period, and determine the unit time overload of the actual vehicle ownership in different regions of different production enterprises in the unit area of ​​the reference carbon emission change of different production enterprises corresponding to the dynamic carbon emission coefficient.

[0044] The vehicle inventory detection unit for different regions is used to find overload based on the predicted time period and unit time, and to determine the vehicle inventory in different regions at a unit time by referring to the production capacity per unit area of ​​different manufacturers' carbon emission changes.

[0045] The carbon absorption efficiency retrieval unit for different seasons is used to determine the magnitude of the horizontal and vertical axis prediction display parameters based on the vehicle ownership in different regions and the distribution map of environmental emission source activity areas in different regions. Based on the data representation of the magnitude of the horizontal and vertical axis prediction display parameters, the interference energy consumption data and corresponding geological record files are retrieved from the existing detection cloud of different production enterprises to display the parameter magnitude.

[0046] The energy consumption correction generation unit is used to correct the energy consumption of the interference data based on the difference between the horizontal and vertical axis predicted display parameters and the display parameters in the geological record file, so as to obtain the macroscopic energy consumption of emission source activities per unit time.

[0047] Furthermore, the carbon emission change control interface includes:

[0048] The energy utilization rate confirmation unit is used to control the carbon emission changes of different production enterprises based on the latest carbon emission coefficient per unit time until the latest energy consumption data meets the energy utilization rate monitoring trigger conditions. Then, according to the resolution of the monitoring sensor device, it sends an energy utilization rate confirmation command to the edge computing server monitoring end and receives a confirmation wireless signal command input from the edge computing server monitoring end.

[0049] The energy utilization rate control unit is used to control the changes in energy utilization rate and carbon emissions of different production enterprises according to the confirmed wireless signal command, and to obtain energy consumption data of different production enterprises at different unit times.

[0050] A second aspect of the present invention provides a carbon emission monitoring and early warning analysis method based on edge computing, comprising the following steps:

[0051] S1. Set carbon emission benchmark ranges for environmental emission source activities in different areas of the city, and obtain energy consumption data of different production enterprises for carbon emission benchmark ranges.

[0052] S2. Based on the carbon emission benchmark range, set the energy consumption data of different production enterprises and the urban environmental protection process data obtained from the urban database in the monitoring and sensing device platform layer, match the energy consumption data of different production enterprises in the geological record file, and construct a regional distribution map of environmental emission source activities in different regions based on the energy consumption data of different production enterprises in the geological record file.

[0053] S3. Based on the distribution map of environmental emission source activities in different regions and the edge computing server adjustment instructions received according to the resolution of the monitoring sensor device, a dynamic carbon emission coefficient is generated. Based on the dynamic carbon emission coefficient, the changes in carbon emissions of different production enterprises are controlled to obtain the unit time energy consumption data of environmental emission source activities in different regions.

[0054] S4. Based on the energy consumption data per unit time, conduct early warning analysis on the activity area distribution map of environmental emission sources in different reference regions to obtain the latest activity area distribution map of environmental emission sources in different reference regions. Based on the latest activity area distribution map of environmental emission sources in different reference regions, perform feature extraction and adjustment on the dynamic carbon emission coefficient to obtain the latest carbon emission coefficient per unit time.

[0055] S5. Based on the latest carbon emission coefficient per unit time, control the carbon emission changes of different production enterprises and obtain energy consumption data of different production enterprises at different unit times.

[0056] Beneficial Effects: By matching energy consumption data from different production enterprises with the carbon emission benchmark range obtained from the carbon emission benchmark range of environmental emission sources in different urban areas, and by constructing a regional distribution map of environmental emission source activities in different areas, dynamic carbon emission coefficients are generated by combining monitoring and adjustment instructions transmitted from edge computing servers. Preliminary monitoring of different production enterprises is then conducted based on these pre-generated dynamic carbon emission coefficients, reducing monitoring errors during the detection process and improving the low monitoring efficiency caused by low resolution. Furthermore, the early warning analysis based on the unit-time energy consumption data obtained during the detection process, using the regional distribution map of environmental emission source activities in different areas, continuously improves monitoring accuracy through iterative processes, thereby enhancing urban safety. Edge computing, by distributing data processing tasks to edge nodes closer to the data source, effectively reduces data transmission time and network latency, thus improving the unit-time performance of data processing. This method is particularly suitable for unit-time monitoring within production enterprises because edge computing can directly perform data analysis and processing on-site, avoiding the remote data transmission latency of traditional cloud computing models. Furthermore, edge computing systems can be customized to suit the specific needs of each enterprise, optimizing monitoring algorithms and reducing the impact of inter-device errors on overall monitoring efficiency. By deploying efficient edge nodes within an enterprise, carbon emission data can be collected and analyzed more accurately, effectively improving the overall efficiency of carbon emission monitoring. Attached Figure Description

[0057] Figure 1 This is a diagram showing the interface composition of a carbon emission monitoring, early warning, and analysis system based on edge computing according to the present invention.

[0058] Figure 2 This is a flowchart illustrating the operation of a carbon emission monitoring and early warning analysis method based on edge computing according to the present invention. Detailed Implementation

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0060] like Figure 1 As shown, this invention provides a carbon emission monitoring, early warning, and analysis system based on edge computing, comprising:

[0061] The carbon emission benchmark range setting interface is used to set carbon emission benchmark ranges for environmental emission source activities in different areas of the city, and to obtain energy consumption data of different production enterprises in the carbon emission benchmark range setting. The energy consumption data of different production enterprises in the carbon emission benchmark range setting is the energy consumption data of some emission source activities that include environmental emission source activities in different areas of the city, which is obtained during the carbon emission benchmark range setting process.

[0062] Based on the process of setting the carbon emission benchmark range for cities and the energy consumption data of different production enterprises obtained from the carbon emission benchmark range, a reference is provided for the subsequent matching and display of the energy consumption data of different production enterprises.

[0063] The interface for the distribution of emission source activity areas is used to set energy consumption data of different production enterprises and urban environmental protection process data obtained from the urban database of the monitoring and sensing device platform layer according to the carbon emission benchmark range. It matches the energy consumption data of different production enterprises in the geological record file, which is the existing energy consumption data of different production enterprises in the carbon absorption efficiency detection stored in the monitoring and sensing device platform layer, which is similar to the urban environmental protection process data of the city per unit time. Based on the energy consumption data of different production enterprises in the geological record file, a regional distribution map of environmental emission source activity areas in different regions is constructed, which is the regional distribution map of environmental emission source activity at different altitudes in different regions constructed based on the existing energy consumption data of different production enterprises.

[0064] Based on the carbon emission benchmark range obtained by setting carbon emission benchmark range for different environmental emission sources in different areas of the city, the energy consumption data of different production enterprises are matched with the energy consumption data of different production enterprises in the geological record file, and a regional distribution map of environmental emission source activities in different areas is constructed to realize the early prediction of the shape of environmental emission source activities in different areas. This provides an important data foundation for the subsequent generation of dynamic carbon emission coefficients that can control the working parameters of different production enterprises throughout the detection process.

[0065] The sensor and equipment monitoring interface is used to receive adjustment instructions from the edge computing server based on the distribution map of environmental emission source activities in different regions and the resolution of the monitoring sensor device. The edge computing server adjustment instructions are issued by the edge computing server monitoring end. The edge computing server monitoring end transmits the edge computing server adjustment instructions to the carbon emission monitoring and early warning analysis system based on the gateway access function provided by the resolution, generates dynamic carbon emission coefficients, and controls the changes in carbon emissions of different production enterprises based on the dynamic carbon emission coefficients to obtain unit time energy consumption data within the activities of environmental emission sources in different regions. That is, the energy consumption data within the activities of environmental emission sources in different regions obtained by different production enterprises based on the objective lens on them when the carbon emissions of different production enterprises change in the activities of environmental emission sources in different regions.

[0066] Dynamic carbon emission coefficients are generated based on the constructed regional distribution map of environmental emission sources and the monitoring and adjustment instructions transmitted by the edge computing server. Preliminary monitoring of different production enterprises is then conducted based on the pre-generated dynamic carbon emission coefficients. This reduces the involvement of engineers in the detection process of different production enterprises, improves the degree of automation, and thus improves the low monitoring efficiency and range caused by low resolution.

[0067] The early warning analysis interface is used to perform early warning analysis on the activity area distribution map of environmental emission sources in different reference regions based on energy consumption data per unit time, and obtain the latest activity area distribution map of environmental emission sources in different reference regions. That is, the activity area distribution map of environmental emission sources in different reference regions obtained after early warning analysis based on energy consumption data per unit time, and to perform feature extraction and adjustment on the dynamic carbon emission coefficient based on the latest activity area distribution map of environmental emission sources in different reference regions, to obtain the latest carbon emission coefficient per unit time, and the dynamic carbon emission coefficient obtained after feature extraction and adjustment.

[0068] The carbon emission change control interface is used to control the carbon emission change of different production enterprises according to the latest carbon emission coefficient per unit time, and to obtain energy consumption data of different production enterprises at different unit times. This is the final energy consumption data of different regional environmental emission source activities required for the test after the test is completed.

[0069] Based on the energy consumption data per unit time obtained during the detection process, and by referring to the regional distribution map of environmental emission sources in different areas, early warning analysis is performed to adjust the dynamic carbon emission coefficient per unit time. Based on the carbon emission coefficient per unit time obtained after the early warning analysis, carbon emission change control is implemented for different production enterprises. This process continuously improves the monitoring accuracy through iteration, further ensuring the monitoring accuracy of different production enterprises during the detection process.

[0070] The carbon emission benchmark range setting interface includes:

[0071] The emission source activity data feature extraction unit is used to obtain urban environmental protection process data from the urban database of the platform layer of the monitoring and sensing device, and to identify environmental emission source activities in different areas from the urban environmental protection process data.

[0072] The climate and environmental impact factor data feature extraction unit is used to set parameter requirements for the carbon emission benchmark range of environmental emission source activities in different regions, that is, to set the carbon emission coefficient requirements for the carbon emission benchmark range of environmental emission source activities in different regions. For example, the carbon emission benchmark range setting parameters are represented by a list of carbon emission coefficients set by climate and environmental impact factor data. The carbon emission benchmark range setting parameters, climate and environmental impact factor data, are extracted from urban environmental protection process data. That is, the data included in the carbon emission benchmark range setting parameter requirements for environmental emission source activities in different regions is used to determine the carbon emission coefficients set by the carbon emission benchmark range. This data is extracted from the features of urban environmental protection process data. For example, the age of the city is the carbon emission benchmark range setting parameter, climate and environmental impact factor data.

[0073] The carbon emission coefficient determination unit is used to generate carbon emission coefficients for the carbon emission benchmark range setting based on the carbon emission benchmark range setting parameters, climate and environmental impact factor data, and the carbon emission benchmark range setting parameter requirements for environmental emission source activities in different regions. Based on the carbon emission benchmark range setting parameters, climate and environmental impact factor data, it retrieves a list of carbon emission coefficients for the carbon emission benchmark range setting parameters, climate and environmental impact factor data, and carbon emission benchmark range setting parameters for different regions, determines a corresponding parameter related to the carbon emission benchmark range setting process, and further determines the carbon emission coefficient for the carbon emission benchmark range setting process based on the determined parameter related to the carbon emission benchmark range setting process.

[0074] The aforementioned emission source activity data feature extraction unit, climate and environmental impact factor data feature extraction unit, and carbon emission coefficient determination unit realize the automatic determination process of environmental emission source activities in different regions. It also realizes the determination of carbon emission benchmark range setting parameters, climate and environmental impact factor data based on the carbon emission benchmark range setting parameter requirements of environmental emission source activities in different regions. Then, the two are combined to further determine the carbon emission coefficient for the carbon emission benchmark range setting. This generates a carbon emission benchmark range setting carbon emission coefficient that can automatically complete the carbon emission benchmark range setting for cities by monitoring different production enterprises. This automates the carbon emission benchmark range setting process and further reduces the degree of engineer involvement in the detection process of different production enterprises.

[0075] The carbon emission benchmark range setting monitoring unit is used to control the carbon emission changes of different production enterprises in different areas of the city's environmental emission source activities according to the carbon emission coefficient set by the carbon emission benchmark range setting, and to obtain energy consumption data of different production enterprises within the carbon emission benchmark range setting.

[0076] Based on the aforementioned carbon emission benchmark range, carbon emission coefficients are set to control the changes in carbon emissions of different production enterprises. The carbon emission benchmark range setting process has been fully automated and intelligent.

[0077] The distribution interface of emission source activity areas includes:

[0078] The climate and environmental impact factor data determination unit is used to determine the climate and environmental impact factors of carbon dioxide concentration changes of emission source activities in different regions. It acquires urban environmental protection process data from the urban database of the monitoring and sensing device platform layer, and extracts the corresponding climate and environmental impact factor data of carbon dioxide concentration changes of emission source activities from the urban environmental protection process data.

[0079] Based on climate and environmental impact factor data, the unit determines the climate and environmental impact factor data of carbon dioxide concentration changes of emission source activities;

[0080] The carbon dioxide concentration change determination unit is used to determine the carbon dioxide concentration changes of environmental emission source activities in different regions based on climate and environmental impact factor data on carbon dioxide concentration changes of emission source activities.

[0081] The carbon dioxide concentration change determination unit determines the carbon dioxide concentration change of the emission source activity;

[0082] The carbon absorption efficiency data feature extraction unit is used to extract the feature of the interval change value corresponding to the change of carbon dioxide concentration of emission source activities based on the feature extraction strategy. That is, it is a feature extraction method to extract the feature parameters of emission source activities corresponding to the change of carbon dioxide concentration of emission source activities from the energy consumption data of different production enterprises. The interval change value feature extraction is performed on the energy consumption data of different production enterprises within the carbon emission benchmark range to obtain the carbon absorption efficiency data of the change of carbon dioxide concentration of emission source activities in different channels. That is, the specific parameters corresponding to the change of carbon dioxide concentration of emission source activities in the city during the urban environmental protection process.

[0083] The carbon absorption efficiency feature extraction unit extracts carbon absorption efficiency data from the energy consumption data of different production enterprises within the carbon emission baseline range, thereby extracting carbon absorption efficiency data based on the changes in carbon dioxide concentration of emission source activities.

[0084] The carbon absorption efficiency feature extraction and calculation unit for different seasons is used to extract and calculate the carbon absorption efficiency for different seasons based on the carbon absorption efficiency data of carbon dioxide concentration changes of all emission source activities in the cloud of different production enterprises. That is, the detected carbon absorption efficiency is similar to the carbon absorption efficiency data of carbon dioxide concentration changes of the same emission source activities determined per unit time. The detected carbon absorption efficiency is the carbon absorption efficiency data of relevant record data obtained when the same emission source activities in other cities were detected and stored in the monitoring sensor device platform.

[0085] The carbon absorption efficiency data determined by the carbon absorption efficiency data feature extraction unit is used as the reference for feature extraction calculation. The carbon absorption efficiency in different seasons is calculated by feature extraction, which provides basic data for the subsequent construction of regional distribution maps of environmental emission sources in different regions.

[0086] The reference area distribution map construction unit is used to construct a reference area distribution map of environmental emission source activity in different regions based on the energy consumption data of different production enterprises in the geological record files of carbon absorption efficiency in different seasons. The unit reconstructs the horizontal and vertical axes of the interval variation values ​​in the energy consumption data of different production enterprises in the geological record files, and splices and fits the horizontal and vertical axis-modified parts according to the acquisition order of the interval variation values ​​to obtain the reference area distribution map of environmental emission source activity in different regions.

[0087] Based on the horizontal and vertical axis transformation of the range variation values ​​of energy consumption data of different production enterprises in geological record files, a regional distribution map of environmental emission source activity in different regions is constructed to realize the early prediction of the activity shape of environmental emission sources in different regions. This provides an important data foundation for the subsequent generation of dynamic carbon emission coefficients that can control the working parameters of different production enterprises throughout the detection process.

[0088] In this embodiment, the change in carbon dioxide concentration of emission source activities is the appearance feature of emission source activities used to distinguish the environmental emission source activities in different regions. This change in carbon dioxide concentration of emission source activities can be extracted from the energy consumption data obtained from different production enterprises.

[0089] Sensor and device monitoring interfaces, including:

[0090] The carbon emission rate range construction unit is used to determine the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times based on the regional distribution map of environmental emission source activities in different regions. In other words, it is used to initially determine the production capacity per unit area of ​​carbon emission changes of different production enterprises in different regions during the detection period. Based on the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times and the regional distribution map of environmental emission source activities in different regions, the carbon emission rate range of carbon emission changes of different production enterprises is generated.

[0091] The carbon emission rate range of different production enterprises during the carbon emission change process will be obtained by combining the carbon emission rate per unit area of ​​different production enterprises with the carbon emission rate change per unit area of ​​different production enterprises by referring to the regional distribution maps of environmental emission source activities in different regions, thus realizing the algorithmic calculation of the carbon emission rate per unit area of ​​different production enterprises during different periods.

[0092] The edge computing server transmits wireless signal units, which are used to transmit the carbon emission rate range of the carbon emission change process of different production enterprises to the edge computing server monitoring end according to the resolution of the monitoring sensor device, and receive the corresponding wireless signal instructions. That is, the edge computing server monitoring end receives the wireless signal content of the carbon emission rate range of the carbon emission change process of different production enterprises, including the edge computing server adjustment instructions for the production capacity per unit area of ​​the carbon emission change of different production enterprises at different time periods.

[0093] The algorithmic results of the carbon emission change process of different production enterprises based on the carbon emission change per unit area of ​​the production capacity of different production enterprises at different time periods are automatically generated and sent to the edge computing server monitoring end and receive wireless signal instructions from engineers. This enables engineers to participate in the decision-making of the carbon emission change per unit area of ​​different production enterprises, thereby making the decision on the dynamic carbon emission coefficient of different production enterprises more flexible. Furthermore, the reliability of the dynamic carbon emission coefficient is further guaranteed due to the participation of engineers in the decision-making.

[0094] The carbon emission coefficient generation unit is used to adjust the capacity per unit area of ​​carbon emission changes of different production enterprises according to the adjustment instructions from the edge computing server in the wireless signal instructions. That is, after receiving the carbon emission rate range of the carbon emission change process of different production enterprises, the edge computing server monitoring end issues the instruction to adjust the capacity per unit area of ​​carbon emission change of different production enterprises in different time periods. For example, the modified capacity per unit area of ​​carbon emission change of different production enterprises marked on the edge computing server input display screen is directly used as the adjusted capacity per unit area of ​​carbon emission change of different production enterprises. The adjusted capacity per unit area of ​​carbon emission change of different production enterprises is obtained. That is, the capacity per unit area of ​​carbon emission change of different production enterprises is adjusted and modified according to the adjustment instructions from the edge computing server. And the dynamic carbon emission coefficient is generated based on the adjusted capacity per unit area of ​​carbon emission change of different production enterprises. That is, the carbon emission change of different production enterprises is controlled according to the capacity per unit area of ​​carbon emission change of different production enterprises. It can include control parameters such as the maximum carbon emission value, the direction of carbon emission change, and the distance of carbon emission change of different production enterprises.

[0095] Based on the edge computing server adjustment instructions in the wireless signal instructions, the production capacity per unit area of ​​carbon emission changes of different production enterprises at different time periods is adjusted and corrected. Furthermore, dynamic carbon emission coefficients are generated based on the corrected production capacity per unit area of ​​carbon emission changes of different production enterprises. The decision-making process of dynamic carbon emission coefficients adds an engineer decision-making link, which further ensures the reliability of the determined dynamic carbon emission coefficients.

[0096] The unit for obtaining carbon emission change per unit time is used to control the carbon emission change of different production enterprises according to the unit time carbon emission coefficient in the dynamic carbon emission coefficient and to obtain the unit time energy consumption data of environmental emission source activities in different regions.

[0097] The unit obtains the change in carbon emissions per unit time to complete the preliminary control of carbon emission changes of different production enterprises during the detection process.

[0098] Carbon emission rate range building blocks include:

[0099] The traffic emission location detection unit is used to determine the horizontal and vertical axis data representation of different altitudes of environmental emission source activities in different regions based on the distribution map of environmental emission source activities in different regions, and to determine the traffic emission location of the vehicle ownership in each different region at different altitudes of environmental emission source activities in different regions.

[0100] The traffic emission magnitude detection unit is used to divide the activity area distribution map of environmental emission sources in different regions into multiple interval emission source activity area distribution maps with different carbon absorption efficiencies. In the multiple interval emission source activity algorithms, it determines the different regional vehicle ownership sources that interact with the corresponding traffic emission locations. That is, the different regional vehicle ownership sources contain the different regional vehicle ownership belonging to the multiple interval emission source activity algorithms. The traffic emission locations at different altitudes of environmental emission source activities in different regions interact with the vehicle ownership in these multiple different regions and are determined as the traffic emission magnitude sources.

[0101] The carbon emission type detection unit is used to take the midpoint of the line connecting the sources of traffic emissions as the emission source activity at different time periods, and to fit the carbon emission source activity carbon type of different regions based on all the relatively different time periods (that is, to use the regional distribution map obtained by fitting all emission source activities at different time periods according to the general direction of carbon emission changes of different production enterprises as the carbon emission source activity carbon type of different regions).

[0102] The midpoint of the line connecting the vehicle ownership in multiple different regions among the sources of traffic emissions is taken as the center point of emission source activity. Furthermore, the carbon material type of the environmental emission source activity in different regions is fitted based on the center point of emission source activity. This ensures that the production capacity per unit area of ​​the carbon emission change of different production enterprises is located as close as possible to the center of the environmental emission source activity in different regions. This guarantees the field of vision of the energy consumption data obtained by different production enterprises. Therefore, when the carbon emission of different production enterprises changes due to the carbon material type of the environmental emission source activity in different regions, the obstruction of the field of vision of the inner wall of the emission source activity during the carbon emission change process can be minimized.

[0103] The carbon deposition rate assessment unit is used to generate carbon emission rate ranges for different production enterprises based on the air moisture characteristics of different altitudes of environmental emission source activities in different regions, namely, the air moisture data of different vehicle ownership on the surface of environmental emission source activities in different regions, the clustering algorithm corresponding to environmental emission source activities in different regions, and the carbon material types of environmental emission source activities in different regions.

[0104] Determining the maximum carbon emissions of different production enterprises at different altitudes based on the air moisture characteristics of different regional environmental emission source activities at different altitudes can ensure that the instantaneous carbon emission change rate of different production enterprises corresponds to the air moisture of different regional environmental emission source activities at different altitudes. This improves the flexibility of the carbon emission change rate of different production enterprises in different regional environmental emission source activities and ensures the observability of energy consumption data obtained during the carbon emission change process of different production enterprises.

[0105] In this embodiment, the clustering algorithm is a pre-trained algorithm that uses a large amount of air moisture characteristic data of different regional environmental emission source activities at different altitudes and the maximum carbon emission value per unit area within the corresponding different regional environmental emission source activities as samples. This algorithm can determine the maximum carbon emission value of the number of vehicles in each different region at the carbon material type of different regional environmental emission source activities by using the input air moisture characteristic data of different regional environmental emission source activities at different altitudes.

[0106] The carbon deposition rate assessment unit includes:

[0107] The component for determining carbonaceous material types at different temperatures is used to determine the tangents of carbonaceous material types from environmental emission sources in different regions at different time periods of emission source activity in different channels. The component takes the different time periods of emission source activity as the emission source activity axis for the different time periods of emission source activity, and determines the plane perpendicular to the extension direction of emission source activity in different regions.

[0108] Based on the different types of carbonaceous materials at different temperatures, the component can determine the emission source activity axis perpendicular to the direction of emission source activity in different regions;

[0109] The component for determining the frequency of severe convective weather at different temperatures is used to determine the vehicle ownership in all different regions where the activity of environmental emission sources at different altitudes and the carbonaceous material types at different temperatures intersect with the emission source activity axis. After taking the dynamic carbonaceous material environmental digestion size at different times of the corresponding emission source activity, the frequency of severe convective weather at different temperatures after determining the dynamic carbonaceous material environmental digestion size at different times of the emission source activity at different altitudes in different regions.

[0110] The carbon deposition rate assessment component is used to input the frequency of severe convective weather at different temperatures after the dynamic carbon digestion of the environment at different time periods of emission source activities into the clustering algorithm of emission source activities in different regions. It determines the degree of shear slip damage at different time periods of emission source activities, and assesses the carbon deposition rate of carbon types of emission source activities in different regions based on the degree of shear slip damage. This means that the extension process of carbon types of emission source activities in different regions is extended according to the determined degree of shear slip damage at different time periods of all emission source activities, generating carbon emission rate ranges for the carbon emission change process of different production enterprises.

[0111] Based on a pre-trained clustering algorithm and the frequency of strong convective weather at different temperatures representing the maximum curvature of the dynamic carbon environment after digestion at different time periods of emission source activity, the degree of shear slip damage at different time periods of emission source activity is determined. This allows for a reasonable rate of change in carbon emissions from different production enterprises along different regional emission source carbon types, ensuring the observability of energy consumption data obtained during the carbon emission change process of different production enterprises. In this embodiment, the frequency of strong convective weather at different temperatures representing the maximum curvature of the dynamic carbon environment after digestion at different time periods of emission source activity is one way to express the air moisture characteristics of different altitudes in different regional emission source activities. Correspondingly, the clustering algorithm in this embodiment is also a pre-trained algorithm that uses a large number of strong convective weather frequencies at different temperatures representing the maximum curvature of the dynamic carbon environment after digestion at different time periods of emission source activity and the maximum carbon emissions in different regional emission source activities at different time periods as samples. This algorithm can determine the degree of shear slip damage at different time periods of emission source activity in different channels at different emission source types in different regional emission source activities by using the input strong convective weather frequencies at different temperatures representing the maximum curvature of the dynamic carbon environment after digestion at different time periods of emission source activity.

[0112] The early warning analysis interface includes:

[0113] The carbon stock early warning analysis unit is used to adjust the carbon stock carbon emission coefficient in the dynamic carbon emission coefficient (i.e., the carbon emission coefficient of the carbon stock parameters of the carbon stock equipment set up in different production enterprises (the climate, environmental impact factors, etc. of the carbon stock equipment)) based on the energy consumption data per unit time (i.e., to adjust the carbon stock carbon emission coefficient in the dynamic carbon emission coefficient based on the display effect of the acquired energy consumption data per unit time).

[0114] This enables early warning analysis and control of carbon stock carbon emission coefficients in dynamic carbon emission coefficients for different production enterprises during the carbon emission change process (detection process), ensuring the effectiveness of the energy consumption data obtained per unit time.

[0115] The dynamic regional distribution map update unit is used to perform early warning analysis on the regional distribution map of environmental emission sources in different reference areas based on energy consumption data per unit time, and obtain the latest regional distribution map of environmental emission sources in different reference areas (that is, to reconstruct the horizontal and vertical axes based on energy consumption data per unit time, to obtain a new local regional distribution map of environmental emission sources in different areas corresponding to the vehicle ownership in different areas, and to update the newly constructed local regional distribution map of environmental emission sources in different reference areas).

[0116] To enable early warning analysis of different production enterprises based on the regional distribution maps of environmental emission sources in different regions during the process of carbon emission changes;

[0117] The energy consumption visualization unit is used to visualize the macro-energy consumption of emission source activities (i.e., the interval change value of different regional environmental emission source activities obtained from the predicted vehicle ownership of different regions after a certain period of time) based on the latest regional distribution map of environmental emission source activities in different regions and the unit time carbon emission coefficient in the dynamic carbon emission coefficient (i.e., the carbon emission coefficient executed by different production enterprises at a unit time moment, such as the parameters for monitoring the instantaneous carbon emission change rate and the unit time carbon emission change direction of different production enterprises) and the energy consumption data of different production enterprises in the geological record file (the energy consumption data of different production enterprises in the geological record file matched with the carbon emission benchmark range obtained by setting the carbon emission benchmark range of different regional environmental emission source activities in different regions of the city).

[0118] Based on the latest regional distribution maps of environmental emission source activities in different regions, unit time control parameters, and energy consumption data of different production enterprises in geological records, macro-energy consumption data of emission source activities can be generated to predict the situation within the emission source activities in advance. This improves the low resolution of unit time energy consumption data sent to the edge computing server monitoring end and provides predictive reference for engineers at the edge computing server monitoring end to adjust monitoring, thereby improving the low monitoring efficiency to a certain extent.

[0119] The adjustment transmission unit is used to transmit the macroscopic energy consumption of emission source activities to the edge computing server monitoring end for display according to the resolution of the monitoring sensor device, and to receive the unit time monitoring adjustment command input by the edge computing server monitoring end, which is the command used to adjust the unit time monitoring of the unit time carbon emission change of different production enterprises.

[0120] Enables the mutual transmission of energy consumption data per unit time and monitoring and adjustment instructions per unit time between different production enterprises and edge computing server monitoring terminals;

[0121] The early warning analysis unit is used to perform feature extraction and adjustment on the dynamic carbon emission coefficient according to the unit time monitoring and adjustment instruction. It performs feature extraction processing on the regional distribution map obtained by fitting the carbon emission coefficient contained in the unit time monitoring and adjustment instruction with the previous dynamic carbon emission coefficient. The carbon emission coefficient in the regional distribution map after feature extraction is taken as the latest carbon emission coefficient at the corresponding time to obtain the latest unit time carbon emission coefficient, which is the carbon emission coefficient of the dynamic carbon emission coefficient adjusted according to the unit time monitoring and adjustment instruction at the unit time.

[0122] Based on the unit time monitoring and adjustment instructions, the dynamic carbon emission coefficient is feature extracted and adjusted, enabling engineers at the edge computing server monitoring end to adjust and monitor the dynamic carbon emission coefficient unit time. This function is not a necessary step to finally complete the testing projects of different production enterprises, but it can give engineers more monitoring options.

[0123] The carbon emission change control interface includes:

[0124] The energy utilization rate confirmation unit is used to control the carbon emission changes of different production enterprises based on the latest unit-time carbon emission coefficient until the latest energy consumption data meets the energy utilization rate monitoring trigger condition. (When the latest energy consumption data indicates that different production enterprises have reached the endpoint of the capacity per unit area of ​​the carbon emission change of different production enterprises, the latest energy consumption data is determined to meet the energy utilization rate monitoring trigger condition. For example, the engineer monitoring judgment method is used to determine whether the latest energy consumption data indicates the endpoint of the capacity per unit area of ​​the carbon emission change of different production enterprises, or a pre-trained endpoint vehicle ownership recognition algorithm is used to identify the latest energy consumption data. This endpoint vehicle ownership recognition algorithm is pre-used with a large number of environmental emission sources in different regions that have been identified as containing the endpoint vehicle ownership per unit area of ​​the capacity per unit area of ​​the carbon emission change of different production enterprises.) When the data (or interval change values) of the actual vehicle ownership in different regions during the activity are trained, the algorithm for identifying the vehicle ownership in different regions at the endpoint can identify the interval change values ​​of the vehicle ownership in different regions at the endpoint, which are the reference values ​​for the carbon emission changes per unit area of ​​different production enterprises in the energy consumption data obtained by different production enterprises. Then, according to the resolution of the monitoring sensor device, it sends an energy utilization rate confirmation instruction to the edge computing server monitoring end (used to confirm with the engineer at the edge computing server monitoring end whether energy utilization rate detection (i.e. whether energy utilization rate is monitored for changes in carbon emissions of different production enterprises)) and receives a confirmation wireless signal instruction from the edge computing server monitoring end (i.e., an instruction containing the confirmation wireless signal content of whether the engineer at the edge computing server monitoring end agrees to energy utilization rate detection (i.e. whether energy utilization rate is monitored for changes in carbon emissions of different production enterprises)).

[0125] The energy utilization rate control unit is used to control the changes in carbon emissions of energy utilization rate of different production enterprises according to the confirmed wireless signal instruction. That is, when the confirmed wireless signal instruction means that the engineer agrees to the energy utilization rate test, the control unit controls the changes in carbon emissions of energy utilization rate of different production enterprises and obtains energy consumption data of different production enterprises at different unit times.

[0126] like Figure 2 As shown, this invention provides a carbon emission monitoring and early warning analysis method based on edge computing, comprising the following steps:

[0127] Step S1: Set carbon emission benchmark ranges for environmental emission source activities in different areas of the city, and obtain energy consumption data of different production enterprises for carbon emission benchmark ranges.

[0128] Step S2: Based on the carbon emission benchmark range, set the energy consumption data of different production enterprises and the urban environmental protection process data obtained from the urban database in the monitoring and sensing device platform layer, match the energy consumption data of different production enterprises in the geological record file, and construct a distribution map of the activity area of ​​environmental emission sources in different regions based on the energy consumption data of different production enterprises in the geological record file.

[0129] Step S3: Based on the distribution map of environmental emission source activities in different regions and the edge computing server adjustment instructions received according to the resolution of the monitoring sensor device, a dynamic carbon emission coefficient is generated. Based on the dynamic carbon emission coefficient, the changes in carbon emissions of different production enterprises are controlled to obtain the unit time energy consumption data of environmental emission source activities in different regions.

[0130] Step S4: Based on the energy consumption data per unit time, perform early warning analysis on the activity area distribution map of environmental emission sources in different reference regions to obtain the latest activity area distribution map of environmental emission sources in different reference regions. Based on the latest activity area distribution map of environmental emission sources in different reference regions, perform feature extraction and adjustment on the dynamic carbon emission coefficient to obtain the latest carbon emission coefficient per unit time.

[0131] Step S5: Control the carbon emission changes of different production enterprises based on the latest carbon emission coefficient per unit time, and obtain energy consumption data of different production enterprises at different unit times.

[0132] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0133] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within this application. No drawing in the claims should be construed as limiting the scope of the claims.

Claims

1. A carbon emission monitoring, early warning, and analysis system based on edge computing, characterized in that, include: The carbon emission baseline range setting interface is used to set carbon emission baseline ranges for environmental emission source activities in different areas of the city and obtain energy consumption data of different production enterprises for carbon emission baseline range settings. The energy consumption data of different production enterprises in the carbon emission benchmark range are energy consumption data of some emission source activities that are obtained in the process of setting the carbon emission benchmark range, which includes environmental emission source activities in different areas of the city. The interface for the distribution of emission source activity areas is used to set energy consumption data of different production enterprises and urban environmental protection process data obtained from the urban database at the monitoring and sensing device platform layer according to the carbon emission benchmark range, match the energy consumption data of different production enterprises in the geological record file, and construct a distribution map of environmental emission source activity areas in different regions based on the energy consumption data of different production enterprises in the geological record file. The sensor and equipment monitoring interface is used to generate dynamic carbon emission coefficients based on the distribution map of environmental emission source activities in different regions and the edge computing server adjustment instructions received according to the resolution of the monitoring sensor device. It also controls the changes in carbon emissions of different production enterprises based on the dynamic carbon emission coefficients and obtains unit time energy consumption data within the activities of environmental emission sources in different regions. The early warning analysis interface is used to perform early warning analysis on the activity area distribution map of environmental emission sources in different reference regions based on energy consumption data per unit time, obtain the latest activity area distribution map of environmental emission sources in different reference regions, and perform feature extraction and adjustment on the dynamic carbon emission coefficient based on the latest activity area distribution map of environmental emission sources in different reference regions to obtain the latest carbon emission coefficient per unit time. The carbon emission change control interface is used to control the carbon emission changes of different production enterprises based on the latest carbon emission coefficient per unit time, and to obtain energy consumption data of different production enterprises at different unit times.

2. The carbon emission monitoring, early warning, and analysis system based on edge computing according to claim 1, characterized in that, The carbon emission benchmark range setting interface includes: The emission source activity data feature extraction unit is used to obtain urban environmental protection process data from the urban database of the platform layer of the monitoring sensor device, and to identify environmental emission source activities in different regions from the urban environmental protection process data. The feature extraction unit for climate and environmental impact factors data is used to extract the climate and environmental impact factors data of the carbon emission benchmark range setting parameters from urban environmental protection process data, based on the carbon emission benchmark range setting parameter requirements of different regional environmental emission source activities. The carbon emission coefficient determination unit is used to generate carbon emission coefficients for the carbon emission benchmark range setting based on the carbon emission benchmark range setting parameters, climate and environmental impact factor data, and the carbon emission benchmark range setting parameter requirements of environmental emission source activities in different regions. The carbon emission benchmark range setting monitoring unit is used to control the carbon emission changes of different production enterprises in different areas of the city's environmental emission source activities according to the carbon emission coefficient set by the carbon emission benchmark range, and to obtain the energy consumption data of different production enterprises within the carbon emission benchmark range.

3. The carbon emission monitoring, early warning, and analysis system based on edge computing according to claim 1, characterized in that, The distribution interface of the emission source activity area includes: The climate and environmental impact factor data determination unit is used to determine the climate and environmental impact factors of carbon dioxide concentration changes of emission source activities in different regions. It acquires urban environmental protection process data from the urban database of the monitoring and sensing device platform layer, and extracts the corresponding climate and environmental impact factor data of carbon dioxide concentration changes of emission source activities from the urban environmental protection process data. The carbon dioxide concentration change determination unit is used to determine the carbon dioxide concentration changes of environmental emission source activities in different regions based on climate and environmental impact factor data on carbon dioxide concentration changes of emission source activities. The carbon absorption efficiency data feature extraction unit is used to extract the interval change value features of energy consumption data of different production enterprises within the carbon emission benchmark range based on the interval change value feature extraction strategy corresponding to the change of carbon dioxide concentration of emission source activities, so as to obtain the carbon absorption efficiency data of carbon dioxide concentration change of emission source activities in different channels. The carbon absorption efficiency feature extraction and calculation unit for different seasons is used to extract and calculate the carbon absorption efficiency for different seasons based on the carbon absorption efficiency data of carbon dioxide concentration changes of all emission sources in the cloud monitoring of different production enterprises. The reference area distribution map construction unit is used to construct a regional distribution map of environmental emission source activities in different regions based on the energy consumption data of different production enterprises in the geological record files of carbon absorption efficiency in different seasons.

4. The carbon emission monitoring, early warning, and analysis system based on edge computing according to claim 1, characterized in that, The sensor and device monitoring interface includes: The carbon emission rate range construction unit is used to determine the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times based on the regional distribution map of environmental emission source activities in different regions, and to generate the carbon emission rate range of different production enterprises in the process of carbon emission change based on the production capacity per unit area of ​​carbon emission changes of different production enterprises at different times and the regional distribution map of environmental emission source activities in different regions. The edge computing server transmits wireless signal units to transmit the carbon emission rate range of different production enterprises to the edge computing server monitoring end according to the resolution of the monitoring sensor device, and receives the corresponding wireless signal instructions. The carbon emission coefficient generation unit is used to adjust and correct the production capacity per unit area of ​​carbon emission changes of different production enterprises at different time periods according to the adjustment instructions of the edge computing server in the wireless signal instructions, to obtain the adjusted production capacity per unit area of ​​carbon emission changes of different production enterprises, and to generate dynamic carbon emission coefficients based on the adjusted production capacity per unit area of ​​carbon emission changes of different production enterprises. The unit for obtaining changes in carbon emissions per unit time is used to control the changes in carbon emissions of different production enterprises based on the unit time carbon emission coefficient in the dynamic carbon emission coefficient and to obtain unit time energy consumption data of environmental emission source activities in different regions.

5. A carbon emission monitoring and early warning analysis system based on edge computing according to claim 4, characterized in that, The carbon emission rate range construction unit includes: The traffic emission location detection unit is used to determine the horizontal and vertical axis data representation of different altitudes of environmental emission source activities in different regions based on the distribution map of environmental emission source activities in different regions, and to determine the traffic emission location of the vehicle ownership in each different region at different altitudes of environmental emission source activities in different regions. The traffic emission magnitude detection unit is used to divide the environmental emission source activity area distribution map of different regions into multiple interval emission source activity area distribution maps with different carbon absorption efficiency interference. In the multiple interval emission source activity algorithm, the vehicle ownership sources of different regions that interact with the corresponding traffic emission locations are identified as the sources of traffic emission magnitude. The carbon deposition rate assessment unit is used to generate carbon emission rate ranges for different production enterprises based on the air moisture characteristics of different altitudes of environmental emission source activities in different regions, the clustering algorithm corresponding to environmental emission source activities in different regions, and the carbon types of environmental emission source activities in different regions.

6. The carbon emission monitoring, early warning, and analysis system based on edge computing according to claim 1, characterized in that, The early warning analysis interface includes: The carbon stock early warning analysis unit is used to adjust the carbon stock carbon emission coefficient in the dynamic carbon emission coefficient based on the energy consumption data per unit time. The dynamic regional distribution map update unit is used to perform early warning analysis on the regional distribution maps of environmental emission sources in different reference areas based on energy consumption data per unit time, and to obtain the latest regional distribution maps of environmental emission sources in different reference areas. The energy consumption visualization unit is used to visualize the macro-energy consumption of emission source activities based on the latest regional distribution map of environmental emission source activities in different regions, the unit time carbon emission coefficient in the dynamic carbon emission coefficient, and the energy consumption data of different production enterprises in the geological record file. The adjustment transmission unit is used to transmit the macroscopic energy consumption of emission source activities to the edge computing server monitoring end for display according to the resolution of the monitoring sensor device, and to receive the unit time monitoring adjustment command input by the edge computing server monitoring end; The early warning analysis unit is used to extract and adjust the dynamic carbon emission coefficient according to the unit time monitoring and adjustment instructions to obtain the latest unit time carbon emission coefficient.

7. A carbon emission monitoring and early warning analysis method based on edge computing, characterized in that, Includes the following steps: S1. Set carbon emission benchmark ranges for environmental emission source activities in different areas of the city, and obtain energy consumption data of different production enterprises within the carbon emission benchmark ranges; the energy consumption data of different production enterprises within the carbon emission benchmark ranges are energy consumption data of some emission source activities that include environmental emission source activities in different areas of the city, obtained during the process of setting carbon emission benchmark ranges. S2. Based on the carbon emission benchmark range, set the energy consumption data of different production enterprises and the urban environmental protection process data obtained from the urban database in the monitoring and sensing device platform layer, match the energy consumption data of different production enterprises in the geological record file, and construct a regional distribution map of environmental emission source activities in different regions based on the energy consumption data of different production enterprises in the geological record file. S3. Based on the distribution map of environmental emission source activities in different regions and the edge computing server adjustment instructions received according to the resolution of the monitoring sensor device, a dynamic carbon emission coefficient is generated. Based on the dynamic carbon emission coefficient, the changes in carbon emissions of different production enterprises are controlled to obtain energy consumption data per unit time within the activities of environmental emission sources in different regions. S4: Based on the energy consumption data per unit time, conduct early warning analysis on the activity area distribution maps of environmental emission sources in different reference regions to obtain the latest activity area distribution maps of environmental emission sources in different reference regions. Based on the latest activity area distribution maps of environmental emission sources in different reference regions, perform feature extraction and adjustment on the dynamic carbon emission coefficient to obtain the latest carbon emission coefficient per unit time. S5: Control the carbon emission changes of different production enterprises based on the latest carbon emission coefficient per unit time, and obtain energy consumption data of different production enterprises at different unit times.

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