Carbon data intelligent calculation management system

Abstract

The invention discloses a carbon data intelligent calculation management system, which comprises a carbon emission monitoring equipment acquisition module, a carbon emission information acquisition module, a calculation information acquisition module, a data processing module and an information sending module, the carbon emission monitoring equipment acquisition module is used for acquiring related information of carbon emission monitoring equipment; the carbon emission information acquisition module is used for acquiring carbon emission information of each region, including production park carbon emission related information, community carbon emission related information, road traffic carbon emission related information, building carbon emission related information and soil carbon emission related information; the calculation information acquisition module is used for acquiring carbon emission calculation related information; and the data processing module is used for processing the related information of the carbon emission monitoring equipment and generating monitoring equipment management information. According to the invention, more comprehensive carbon data intelligent calculation management can be carried out, so that carbon reduction and emission reduction can be better realized.

Description

Technical Field

[0001] The present invention relates to the field of management systems, and more particularly to a carbon data intelligent computing management system. Background Art

[0002] With the increasingly strict global carbon emission control, all fields urgently need to accurately master carbon emission data to achieve emission reduction goals. On the one hand, the booming development of technologies such as sensors, the Internet of Things, and big data provides technical support for carbon emission monitoring, data collection, transmission, and processing; on the other hand, industries, communities, transportation, buildings and other fields are facing emission reduction pressures and urgently need refined management of carbon emissions. In this context, the carbon data intelligent computing management system has emerged. It covers the collaborative operation of multiple modules and helps the main bodies at all levels to scientifically plan the dual-carbon path and achieve intelligent energy and carbon management by finely collecting and processing various carbon emission information;

[0003] In the process of intelligent carbon data management, the carbon data intelligent computing management system will be used.

[0004] The existing management systems have a single management type and cannot well achieve carbon emission management in different fields, which has a certain impact on the use of management systems. Therefore, a carbon data intelligent computing management system is proposed. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a carbon data intelligent computing management system, including a carbon emission monitoring device acquisition module, a carbon emission information acquisition module, a calculation information acquisition module, a data processing module, and an information sending module;

[0006] The carbon emission monitoring device acquisition module is used to acquire information related to carbon emission monitoring devices;

[0007] The carbon emission information acquisition module is used to acquire carbon emission information in each region, including carbon emission related information in production parks, carbon emission related information in communities, carbon emission related information in road traffic, carbon emission related information in buildings, and carbon emission related information in soil;

[0008] The calculation information acquisition module is used to acquire information related to carbon emission calculations;

[0009] The data processing module is used to process information related to carbon emission monitoring devices to generate monitoring device management information;

[0010] Process the carbon emission information in each region to generate park carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information, and soil carbon emission management information;

[0011] Process the information related to carbon emission calculations to generate calculation status evaluation information;

[0012] The information sending module is used to send the monitoring device management information, park carbon emission management information, factory carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information, soil carbon emission management information and calculation status evaluation information to a preset receiving terminal.

[0013] Furthermore, the specific process of the carbon emission monitoring device acquisition module for acquiring information related to the carbon emission monitoring device is as follows:

[0014] When the carbon emission monitoring device is installed, a plurality of pressure sensors are arranged between it and the installation surface to collect the pressure magnitude between the carbon emission monitoring device and the installation surface, that is, the installation force information is obtained;

[0015] Then, the position of the carbon emission monitoring device is collected. Taking the position of the carbon emission monitoring device as the center point and a preset length as the radius, a circle is drawn to obtain a determination range. The number of temperature anomaly sources (such as pipes with a temperature greater than the preset value) and the number of electromagnetic interference sources (other devices with an electromagnetic intensity greater than the preset value) within the determination range are collected. The number of temperature anomaly sources and the number of electromagnetic interference sources constitute the number of anomaly sources;

[0016] The carbon emission monitoring device is subjected to a status detection to detect the operating status of its cooling fan and the operating temperature information, and the operating status of the cooling fan and the operating temperature information constitute the device status information;

[0017] The carbon emission monitoring device is subjected to a system status detection to detect the CPU occupancy rate and memory occupancy rate during system operation, and the system status information is obtained;

[0018] The carbon emission monitoring device is subjected to a data acquisition test. A standard gas sample is sent to the sensor of the monitoring device, and the deviation between the measured value and the true value in the standard gas sample is compared to obtain the evaluation sensitivity. At the same time, the data transmission stability is monitored, and the data packet loss rate and transmission delay time are statistically counted. The evaluation sensitivity, data packet loss rate and transmission delay time constitute the device test data;

[0019] The installation force information, number of anomaly sources, system status information and device test data constitute the information related to the monitoring device.

[0020] Furthermore, the specific process of obtaining the monitoring device management information is as follows:

[0021] The obtained information related to the monitoring device is extracted, and the installation force information, number of anomaly sources, system status information and device test data are extracted from the information related to the monitoring device;

[0022] Analyze the installation force information, extract multiple pieces of collected installation force information, and generate monitoring device management information when any one of the multiple pieces of installation force information is less than the preset value (at this time, the content of the monitoring device management information has an area with too small force and needs to be maintained);

[0023] When all the multiple pieces of installation force information are greater than or equal to the preset value, calculate the differences between each pair of the multiple pieces of installation force information. When any one of the differences between each pair of the multiple pieces of installation force information is greater than the preset value, generate monitoring device management information (at this time, the content of the monitoring device management information is that the overall force is uneven and needs to be maintained and adjusted);

[0024] Analyze the number of abnormal sources. When the sum of the number of temperature abnormal sources and the number of electromagnetic interference sources is greater than the preset number, generate monitoring device management information (at this time, the content of the monitoring device management information is that the surrounding environment of the monitoring device needs to be adjusted);

[0025] Analyze the device status information, extract the operating status of the cooling fan. When the operating status of the cooling fan is abnormal, generate monitoring device management information. When the operating temperature information is abnormal, generate monitoring device management information (at this time, the content of the monitoring device management information is that the heat dissipation of the monitoring device is abnormal);

[0026] Analyze the system status information. When either the CPU occupancy rate or the memory occupancy rate during system operation is greater than the preset value for more than the preset duration, generate monitoring device management information (at this time, the content of the generated monitoring device management information is that the system of the monitoring device is abnormal and needs to be adjusted);

[0027] Analyze the device test data. When any one of the evaluation sensitivity being less than the preset value, the data packet loss rate being greater than the preset value, or the transmission delay time being greater than the preset value duration occurs, generate monitoring device management information (at this time, the content of the monitoring device management information is that the data test of the monitoring device is abnormal).

[0028] Furthermore, the process of determining the abnormal operating status of the cooling fan is as follows:

[0029] When the carbon emission monitoring device receives a heat dissipation instruction, extract the instruction generation time point and mark it as T1, and then collect the time point when the cooling fan operates and mark it as T2;

[0030] Calculate the difference between T2 and T1 to obtain the operating interval difference. When the operating interval difference is greater than the preset value, it indicates that the operating status of the cooling fan is abnormal;

[0031] Collect the real-time rotation speed of the cooling fan again. When the real-time rotation speed of the cooling fan is less than the standard rotation speed, it indicates that the operating status of the cooling fan is abnormal;

[0032] The abnormal determination process of the operating temperature information is as follows: When the operating temperature information continuously exceeds the preset a1 for a preset duration or the operating temperature is greater than the warning value a2, it indicates that the operating temperature information is abnormal, where a2 > a1.

[0033] Furthermore, the acquisition process of the park carbon emission management information is as follows:

[0034] Extract the collected park carbon emission related information, which includes the park's real-time carbon emission information and the park's carbon emission information of the previous year;

[0035] Compare the park's real-time carbon emission information with the historical carbon emission information. When the real-time carbon emission information exceeds the park's carbon emission information of the previous year, the park carbon emission management information is generated;

[0036] The acquisition process of the community carbon emission management information is as follows:

[0037] Extract the collected community carbon emission related information, which includes the community residents' energy consumption information, the community residents' quantity information, and the community public facilities' carbon emission information;

[0038] Mark the community residents' energy consumption information as K1, mark the community residents' quantity information as K2, and mark the community public facilities' carbon emission information as K3;

[0039] Through the formula (K1 + K3) / K2 = Kk, the comprehensive evaluation parameter Kk is obtained;

[0040] Collect the comprehensive evaluation parameter Kk within the past preset duration, and calculate the average value K of the comprehensive evaluation parameter Kk within the past preset duration 标 ;

[0041] When the comprehensive evaluation parameter Kk is greater than K 标 then the community carbon emission management information is generated.

[0042] Furthermore, during the generation process of the road traffic carbon emission management information, the real-time carbon emission amount is also collected, and the real-time carbon emission amount is analyzed to generate road auxiliary prompt information;

[0043] The specific acquisition process of the auxiliary road prompt information is as follows:

[0044] Set the collection frequency, continuously collect the real-time carbon emission amount K for m times, and import the m times of real-time carbon emission amount K into the preset database, where the traffic jam determination threshold is stored in the preset database;

[0045] When the number of times the real-time carbon emissions K exceed the traffic jam determination threshold in m times is greater than or equal to the preset value, an auxiliary road prompt message is generated. At this time, the content of the auxiliary road prompt message is that there may be a traffic jam situation and traffic guidance is needed;

[0046] When the number of times the real-time carbon emissions K exceed the traffic jam determination threshold in m times is less than the preset value, the m times of real-time carbon emissions K are plotted as a line chart for line chart analysis, and the number of angles between the line in the line chart and the x-axis exceeding the preset angle is extracted, that is, the analysis parameter. When the analysis parameter is greater than the preset value, an auxiliary road prompt message is generated. At this time, the content of the auxiliary road prompt message is that a traffic jam situation may be about to occur and traffic guidance needs to be carried out in advance.

[0047] Furthermore, the acquisition process of the road traffic carbon emission management information is as follows:

[0048] Extract the collected road traffic carbon emission related information, which includes the vehicle passing information per unit time of the road, the road width information and the road carbon emissions;

[0049] Mark the vehicle passing information per unit time of the road as V, mark the road width as W, and mark the road carbon emissions as C;

[0050] Obtain the road evaluation parameter P through the formula P = C / (V * W). When the road evaluation parameter P is greater than the preset value, the road traffic carbon emission management information is generated.

[0051] Furthermore, the acquisition process of the building carbon emission management information is as follows:

[0052] Extract the collected building carbon emission related information, which includes the building area and the building carbon emissions;

[0053] Regularly collect the change F1 of the building area and the change E1 of the building carbon emissions;

[0054] Mark the building area as F2 and the building carbon emissions as E2;

[0055] Obtain the building evaluation parameter Fe through the formula (F1 / F2) / (E1 / E2) = Fe;

[0056] When Fe ≥ 1, it indicates that the increase in area leads to a greater increase in carbon emissions, and there may be a problem of reduced energy utilization efficiency, and the building carbon emission management information is generated;

[0057] If Fe < 1, it means that during the area change process, the carbon emissions are relatively well controlled and no information is generated.

[0058] Furthermore, the process of obtaining soil carbon emission management information is as follows:

[0059] Extract the collected soil carbon emission related information, including the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil;

[0060] Collect the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil;

[0061] The organic carbon content in u soils is plotted into an organic carbon content line graph according to the order of collection time;

[0062] When the organic carbon content in any of the u soils is greater than the preset value, soil carbon emission management information is generated. When the organic carbon content in the u soils is less than the preset value, a trend analysis is performed on the organic carbon content line graph. When the organic carbon content line graph shows an upward trend, soil carbon emission management information is generated.

[0063] Enter the nitrous oxide content of each soil into a table, remove the data that exceeds the preset value, and then calculate the average and range (maximum value minus minimum value) of the remaining nitrous oxide concentration. The average value reflects the overall content level, and the range shows the degree of data dispersion. We can preliminarily understand the fluctuation of soil nitrous oxide content, collect the past nitrous oxide data of similar local land, and process them to obtain the upper limit of nitrous oxide safety content, that is, the benchmark value;

[0064] When the average residual nitrous oxide concentration at a certain time is higher than this baseline value, soil carbon emission management information is generated; it indicates that excessive nitrogen fertilizer may be applied or soil permeability is abnormal, and the fertilization plan and soil tillage methods need to be checked.

[0065] When the range is greater than the preset value, soil carbon emission management information is also generated;

[0066] Extract the carbon dioxide content in u soils, extract the collection time points of the carbon dioxide content in u soils, process the collection time points of the carbon dioxide content in u soils, extract the duration when the carbon dioxide content is greater than a preset value, and when the duration when the carbon dioxide content is greater than the preset value exceeds the preset duration, generate soil carbon emission management information;

[0067] Extract u nitrogen contents, remove the maximum and minimum values ​​among the u nitrogen contents, calculate the average of u-2 nitrogen contents, and obtain the average nitrogen content. When the average nitrogen content is greater than the preset value, soil carbon emission management information is generated;

[0068] Extract u methane contents, then extract the time points for collecting the u methane contents, and then analyze the time points of the u methane contents to obtain the total duration when the methane content is greater than a preset value. When the total duration when the methane content is greater than the preset value is greater than the preset value, soil carbon emission management information is generated;

[0069] The collection process of the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in u soils is as follows: The organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content are collected at the same position every preset duration, and collected continuously u times.

[0070] Furthermore, the process of obtaining the calculation status evaluation information is as follows:

[0071] Extract the information related to carbon emission calculation. The information related to carbon emission calculation includes calculation speed information, calculation accuracy, and hardware occupancy information during the calculation process;

[0072] Among them, the process of obtaining the calculation speed information and the calculation accuracy is as follows: Use simulation data for simulation calculation. After f simulation calculations, f simulation calculation speeds and f simulation calculation results are obtained;

[0073] Mark the f simulation calculation speeds as Qf, and obtain the calculation speed parameter Qq through the formula (Q1 + Q2 + Q3... Qf) / f * α = Qq, where α is a correction value, 0.9 ≤ α ≤ 1.1, and the magnitude of α is inversely proportional to the number of other calculation tasks executed by the system simultaneously during the calculation process;

[0074] Then extract the number of the f simulation calculation results whose similarity to the standard result is less than the preset value to obtain the accuracy parameter;

[0075] Extract the hardware occupancy information during the calculation process. The hardware occupancy information during the calculation process includes CPU occupancy rate, memory occupancy rate and hard disk storage occupancy rate;

[0076] Mark the CPU occupancy rate as Y1, the memory occupancy rate as Y2, and the hard disk storage occupancy rate as Y3;

[0077] Assign the weight u1 to Y1, the weight u2 to Y2, and the weight u3 to Y3;

[0078] u1 + u2 + u3 = 1, u2 > u1 > u3, and through the formula Y1 * u1 + Y2 * u2 + Y3 * u3 = Yy, the occupancy evaluation parameter Yy is obtained;

[0079] When the calculation speed parameter Qq is less than the preset value, the accuracy parameter is greater than the preset value, and the occupancy evaluation parameter Yy is less than the preset value, calculation status evaluation information is generated, and at this time, the calculation status evaluation information indicates that the calculation status is normal;

[0080] When any one of the calculation speed parameter Qq being greater than the preset value, the accuracy parameter being less than the preset value, and the occupancy evaluation parameter Yy being less than the preset value occurs, calculation status evaluation information is generated, and at this time, the calculation status evaluation information indicates an abnormal calculation status.

[0081] The beneficial effects of the present invention are reflected in:

[0082] In this carbon data intelligent calculation management system, the carbon emission monitoring device acquisition module ensures the stable operation of the carbon emission monitoring device itself and the high accuracy of data acquisition through a multi-dimensional and refined data acquisition method. This enables the system to obtain reliable original carbon emission data from the source, laying a solid foundation for subsequent analysis and decision-making, and effectively avoiding management mistakes caused by monitoring device failures or data deviations. The carbon emission information acquisition processes designed separately for different regions (production parks, communities, road traffic, buildings, etc.) fully consider the unique carbon emission characteristics of each region. Whether it is the complex industrial carbon emission structure within the park, the diverse carbon emission sources of community residents' lives and public facilities, the dynamic carbon emission changes of road traffic affected by traffic flow and road conditions, or the carbon emission patterns of buildings based on area, function, and energy consumption, they can all be accurately captured. Thus, it provides solid data support for formulating carbon emission management strategies tailored to each region and achieves precise carbon emission reduction.

[0083] Through simulation calculations to verify the calculation speed, accuracy, and fine evaluation of hardware occupancy, it is ensured that the carbon emission calculation results are both fast and accurate, avoiding misleading management decisions due to calculation errors or low efficiency. When an abnormal calculation status occurs, it can quickly give feedback, prompting technicians to promptly check algorithm loopholes, optimize hardware configurations, or adjust system task allocations, ensuring the efficient operation of the system and making this system more worthy of promotion and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0085] Figure 1 It is the system block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0086] The following will describe in detail the embodiments of the technical solutions of the present invention in conjunction with the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0087] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application shall have the ordinary meanings understood by those skilled in the art to which the present invention pertains.

[0088] As Figure 1 shown, this embodiment provides a technical solution: a carbon data intelligent computing management system, including a carbon emission monitoring device acquisition module, a carbon emission information acquisition module, a computing information acquisition module, a data processing module, and an information sending module;

[0089] The carbon emission monitoring device acquisition module is used to acquire information related to carbon emission monitoring devices;

[0090] The carbon emission information acquisition module is used to acquire carbon emission information of each region, including carbon emission related information of production parks, carbon emission related information of communities, carbon emission related information of road traffic, carbon emission related information of buildings, and carbon emission related information of soil;

[0091] The computing information acquisition module is used to acquire information related to carbon emission calculation;

[0092] The data processing module is used to process information related to carbon emission monitoring devices to generate monitoring device management information;

[0093] Process the carbon emission information of each region to generate park carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information, and soil carbon emission management information;

[0094] Process the information related to carbon emission calculation to generate calculation status evaluation information;

[0095] The information sending module is used to send the monitoring device management information, park carbon emission management information, factory carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information, soil carbon emission management information, and calculation status evaluation information to a preset receiving terminal.

[0096] It should be noted that the carbon data intelligent computing management system of this application can not only provide solid data support for formulating carbon emission management strategies tailored to each field to achieve precise emission reduction, but also monitor the greenhouse gas emissions in different fields to achieve precise emission reduction.

[0097] The specific process of the carbon emission monitoring device acquisition module acquiring information related to carbon emission monitoring devices is as follows:

[0098] When the carbon emission monitoring device is installed, a plurality of pressure sensors are arranged between it and the installation surface to collect the pressure magnitude between the carbon emission monitoring device and the installation surface, that is, installation force information is obtained;

[0099] Then collect the location of the carbon emission monitoring equipment, draw a circle with the location of the carbon emission monitoring equipment as the center point and the preset length as the radius, obtain the judgment range, collect the number of temperature anomaly sources (such as pipelines with temperatures greater than the preset value) and the number of electromagnetic interference sources (other equipment with electromagnetic intensity greater than the preset value) within the judgment range, and the number of temperature anomaly sources and the number of electromagnetic interference sources constitute the number of abnormal sources;

[0100] Perform status detection on the carbon emission monitoring device, detect the operating status and operating temperature information of its cooling fan, and obtain the operating status and operating temperature information of the cooling fan to form the device status information;

[0101] Perform system status detection on carbon emission monitoring equipment, detect CPU usage and memory usage when the system is running, and obtain system status information;

[0102] Conduct data collection tests on carbon emission monitoring equipment, send standard gas samples to the sensors of the monitoring equipment, compare the deviation between the measured value and the true value in the standard gas sample to obtain the evaluation sensitivity, and monitor the data transmission stability, statistical data packet loss rate and transmission delay time. The evaluation sensitivity, data packet loss rate and transmission delay time constitute the equipment test data;

[0103] Installation stress information, number of abnormal sources, system status information and equipment test data constitute the relevant information of the monitoring equipment;

[0104] The above process can accurately reflect the force distribution of the equipment after installation in real time and promptly discover possible installation risks. For example, in a high-vibration environment such as an industrial plant, if some pressure sensors show a force value lower than the preset value, it may mean that a corner of the equipment is loose. At this time, early warning can be given and targeted reinforcement can be carried out to effectively prevent data collection deviations caused by equipment displacement and shaking, ensure long-term stable operation of the equipment, and lay the foundation for continuous and accurate carbon emission monitoring.

[0105] In complex production scenarios such as chemical companies, high-temperature pipelines are crisscrossed and there are many electromagnetic devices. These interference sources can easily affect the sensor accuracy and data transmission stability of carbon emission monitoring equipment. By identifying and quantifying these interference factors in advance, managers can take timely measures such as insulation and shielding, adjust equipment layout or optimize surrounding facilities to ensure that the equipment is free from external interference, always maintain high-precision data collection capabilities, and improve the credibility of carbon emission monitoring data.

[0106] As a key component to ensure the normal operation of electronic components of equipment, the operating status of the cooling fan is directly related to the service life of the equipment and the stability of data acquisition. For example, in high temperatures in summer or when the equipment runs continuously for a long time, if the operating interval difference of the cooling fan is greater than the preset value or the real-time rotation speed is lower than the standard speed, it may cause the internal temperature of the equipment to be too high, which in turn affects the sensitivity of the sensor and even damages the equipment. Timely detection and handling of these heat dissipation problems can extend the service life of the equipment, reduce monitoring interruptions caused by equipment failures, and ensure the continuity of carbon emission data. At the same time, real-time monitoring of the operating temperature information and setting reasonable warning thresholds can quickly respond when the temperature rises abnormally and take cooling measures to further ensure the stable operation of the equipment.

[0107] On the one hand, detect the CPU occupancy rate and memory occupancy rate during system operation to obtain system status information. Through real-time monitoring, technicians can optimize system processes, clear caches, or upgrade hardware in a timely manner to ensure sufficient system resources when the equipment collects data, so that data can be collected and transmitted smoothly and in a timely manner, avoiding data acquisition defects caused by system performance bottlenecks.

[0108] On the other hand, send a standard gas sample to the sensor of the monitoring equipment for data acquisition testing to accurately evaluate the sensitivity, data packet loss rate, and transmission delay time, adding guarantee to the data acquisition quality. Sensitivity directly determines the ability of the sensor to capture changes in carbon emission concentration, which is particularly crucial in low-concentration emission monitoring scenarios; the data packet loss rate and transmission delay time reflect the reliability and timeliness of data transmission. By regularly testing and analyzing these indicators, problems such as sensor aging, signal attenuation, or transmission line failures can be discovered in a timely manner, and the sensor can be calibrated and the line repaired in a timely manner to ensure that the collected data completely and accurately reflects the actual carbon emission situation, providing solid data support for subsequent carbon emission analysis and management decisions.

[0109] This acquisition process is controlled from multiple dimensions including equipment installation, surrounding environment, its own operating status, and data acquisition performance, comprehensively ensuring that the carbon emission monitoring equipment can stably and accurately collect high-quality carbon emission-related information, laying a solid foundation for the effective operation of the entire carbon data intelligent computing management system.

[0110] The specific process of obtaining the management information of the monitoring equipment is as follows:

[0111] Extract the obtained monitoring equipment-related information, and extract installation force information, the number of abnormal sources, system status information, and equipment test data from the monitoring equipment-related information;

[0112] Analyze the installation force information, extract multiple pieces of collected installation force information. When any one of the multiple pieces of installation force information is less than the preset value, generate monitoring device management information (at this time, the content of the monitoring device management information has an area with too small force and needs to be maintained);

[0113] When all the multiple pieces of installation force information are greater than or equal to the preset value, calculate the differences between each pair of the multiple pieces of installation force information. When any one of the differences between each pair of the multiple pieces of installation force information is greater than the preset value, generate monitoring device management information (at this time, the content of the monitoring device management information is that the overall force is uneven and needs to be maintained and adjusted);

[0114] Analyze the number of abnormal sources. When the sum of the number of temperature abnormal sources and the number of electromagnetic interference sources is greater than the preset number, generate monitoring device management information (at this time, the content of the monitoring device management information is that the environment around the monitoring device needs to be adjusted);

[0115] Analyze the device status information, extract the operating status of the cooling fan. When the operating status of the cooling fan is abnormal, generate monitoring device management information. When the operating temperature information is abnormal, generate monitoring device management information (at this time, the content of the monitoring device management information is that the heat dissipation of the monitoring device is abnormal);

[0116] Analyze the system status information. When either the CPU occupancy rate or the memory occupancy rate during system operation is greater than the preset value for more than the preset duration, generate monitoring device management information (at this time, the content of the generated monitoring device management information is that the system of the monitoring device is abnormal and needs to be adjusted);

[0117] Analyze the device test data. When any one of the evaluation sensitivity being less than the preset value, the data packet loss rate being greater than the preset value, or the transmission delay time being greater than the preset value duration occurs, generate monitoring device management information (at this time, the content of the monitoring device management information is that the data test of the monitoring device is abnormal);

[0118] Ensure the physical installation stability of the device:

[0119] Through the fine analysis of the installation force information, potential problems in equipment installation can be detected in a timely manner. For example, in the installation of carbon emission monitoring equipment in a wind farm, due to the continuous vibration generated by the operation of the wind turbine, the preset lower limit of the force on the pressure sensor is generally set at 50 N (this value is based on the equipment installation manual and past experience to ensure that the equipment can be stably installed in a normal vibration environment). If the force value feedback by a certain pressure sensor is less than 50 N, this may mean that a bolt at the equipment installation base is loose. The system quickly generates management information for the monitoring equipment, prompting the maintenance personnel to tighten the bolt in time to prevent further displacement or even toppling of the equipment, ensuring the stable operation of the equipment and guaranteeing the coherence and accuracy of data collection. When the installation force information of multiple sensors is greater than or equal to 50 N, the difference between each pair is further calculated. If the preset difference value is set at 20 N (taking into account the allowable range of slight uneven settlement of the installation surface or slight deformation of the equipment itself), once a certain difference is greater than 20 N, such as in a large steel plant, due to uneven settlement of the equipment installation ground, resulting in uneven force on the equipment, the management system issues a warning, prompting the staff to recalibrate the installation plane to avoid damaging the precision components inside the equipment due to long-term uneven force.

[0120] Analyzing the number of abnormal sources provides a strong basis for creating a good equipment operation environment. Taking an oil refinery as an example, the plant is filled with high-temperature hot oil pipelines and high-power electromagnetic equipment. The preset total number of temperature abnormal sources and electromagnetic interference sources is usually set at 5 (obtained by combining the common interference source distribution density in the plant area and the anti-interference ability test of the equipment). If the total number of temperature abnormal sources and electromagnetic interference sources within the equipment determination range is detected to be greater than 5, it indicates that the interference around the equipment is serious. The generated management information will prompt the staff to install facilities such as heat insulation covers and electromagnetic shielding nets to reduce the interference of external factors on the sensor accuracy and data transmission stability, ensuring that the collected carbon emission data is true and reliable and accurately reflecting the actual emission situation.

[0121] Monitoring the device status information is crucial. In the hot summer, for the carbon emission monitoring device in a data center computer room, if the preset value of the running interval difference of the cooling fan is set to 10 seconds (determined based on the device's heat dissipation requirements and the normal startup response time of the fan), when the running interval difference of the cooling fan is greater than 10 seconds, it means that the cooling fan starts untimely, and heat accumulates inside the device, which may lead to a decline or even damage to the performance of electronic components. At this time, the system generates management information to remind the operation and maintenance personnel to check the fan control circuit or replace the fan; when the running temperature information is abnormal, such as the set temperature continuously exceeds the preset value a1 (a1 is set to 40°C, based on the upper limit of the normal operating temperature range of the device, considering a certain safety margin) for more than the preset duration (set to 30 minutes to avoid false alarms caused by short-term temperature fluctuations). For example, in a chemical workshop, due to long-term high-intensity work, the device cannot dissipate heat in time, and the temperature rises. Once the early warning is triggered, the staff can immediately increase the heat dissipation measures, such as turning on the auxiliary heat dissipation device, to ensure that the device operates at an appropriate temperature, avoid failures caused by overheating, and ensure that data collection is not interrupted.

[0122] Controlling the system status information effectively avoids device jams and data loss. During the busy production period in an intelligent factory, a large amount of data is processed interactively at the same time. If the preset value of the CPU occupancy rate during the operation of the carbon emission monitoring device system is set to 80% (based on the device's CPU performance and the principle of ensuring the priority operation of data collection tasks), and the preset duration is set to 10 minutes (to prevent misjudgment of short-term peaks), when the CPU occupancy rate is greater than 80% for more than 10 minutes, it may cause the device to respond slowly and data collection to be delayed. The management information generated by the system will prompt technicians to optimize the background running programs, close unnecessary processes, and release CPU resources to ensure smooth device operation and timely data collection and transmission; for the data collection test link, if the preset value of the evaluation sensitivity of the monitoring device in an environmental monitoring station is set to 95% (based on the sensor accuracy requirements of industry standards), when the evaluation sensitivity is less than 95%, it may not be able to accurately capture low-concentration harmful gas emissions. The preset value of the data packet loss rate is set to 0.1% (to ensure the integrity of data transmission). If it is greater than 0.1%, it will cause data loss. The preset value of the transmission delay time is set to 5 seconds (to ensure data timeliness). If it is greater than 5 seconds, the data timeliness will be greatly reduced. The system promptly feedbacks the problem, prompting the staff to calibrate the sensor and check the transmission line to ensure the quality of data collection and provide a solid data foundation for subsequent carbon emission analysis.

[0123] In summary, the process of obtaining management information for this monitoring device ensures the stable operation of the carbon emission monitoring device from multiple aspects. By promptly discovering and solving problems, it improves the reliability of data collection and the operation efficiency of the entire carbon data intelligent computing management system, providing strong support for accurate carbon emission control.

[0124] The process of determining the abnormal operation status of the cooling fan is as follows:

[0125] When the carbon emission monitoring device receives a heat dissipation instruction, it extracts the instruction generation time point, marks it as T1, and then collects the time point when the cooling fan runs, and marks it as T2;

[0126] Calculate the difference between T2 and T1 to obtain the running interval difference. When the running interval difference is greater than the preset value, it indicates that the running state of the cooling fan is abnormal;

[0127] Then collect the real-time rotation speed of the cooling fan. When the real-time rotation speed of the cooling fan is less than the standard rotation speed, it indicates that the running state of the cooling fan is abnormal;

[0128] The determination process of abnormal operation temperature information is as follows: When the operation temperature information continuously exceeds the preset a1 for more than the preset duration or the operation temperature is greater than the warning value a2, it indicates that the operation temperature information is abnormal, where a2 > a1.

[0129] The determination of the abnormal running state of the cooling fan also includes the following process: For the cooling fan exposed outside, an image acquisition device is set to collect the image information of the cooling fan. A label of a preset color is set on the blades of the cooling fan. When the blades rotate, the label rotates in a circle following the blades. After the label of the preset color is set, the area inside the circle where the label rotates following the blades is collected once and marked as the reference area;

[0130] After that, the image information of the cooling fan is processed, the real-time area inside the circle where the label rotates following the blades is extracted, and continuous multiple collections are made. Calculate the difference between the real-time area inside the circle collected multiple times and the reference area to obtain multiple differences. When the number of differences greater than the preset value exceeds the preset quantity, it indicates the running state of the cooling fan.

[0131] The process of obtaining the carbon emission management information of the park is as follows:

[0132] Extract the collected park carbon emission related information, which includes the park real-time carbon emission information and the park carbon emission information of the previous year;

[0133] Compare the park real-time carbon emission information with the historical carbon emission information. When the real-time carbon emission information exceeds the park carbon emission information of the previous year, the park carbon emission management information is generated;

[0134] The process of obtaining the carbon emission management information of the community is as follows:

[0135] Extract the collected community carbon emission related information, which includes the community residents' energy consumption information, the community residents' quantity information, and the community public facilities carbon emission information;

[0136] Mark the energy consumption information of community residents as K1, mark the number of community residents as K2, and mark the carbon emissions information of community public facilities as K3;

[0137] Through the formula (K1 + K3) / K2 = Kk, the comprehensive evaluation parameter Kk is obtained;

[0138] Collect the comprehensive evaluation parameter Kk within the past preset duration, and calculate the average value K of the comprehensive evaluation parameter Kk within the past preset duration 标 ;

[0139] When the comprehensive evaluation parameter Kk is greater than K 标 At this time, community carbon emission management information is generated;

[0140] By comparing the real-time carbon emissions information of the park with the carbon emissions information of the previous year, the abnormal changes in carbon emissions can be quickly detected, prompting the management personnel to intervene and investigate the reasons in the first time. It may be that a certain enterprise suddenly increases its production intensity, the energy consumption equipment fails, resulting in a soaring energy consumption, or a new high-carbon emission production link is introduced, etc. Timely control measures are taken to avoid the out-of-control of carbon emissions and ensure that the overall carbon emissions of the park are within the controllable range.

[0141] When comparing the real-time and the previous year's carbon emissions information, considering the normal factors such as the industrial development and scale expansion of the park, a reasonable allowable growth rate can be set as a preset value. For example, for a park mainly based on high-tech industries with relatively stable development, the preset value can be set at 5%. This means that when the real-time carbon emissions exceed the level of the same period of the previous year by less than 5%, the system will not generate emergency management information for the time being and is regarded as within the normal fluctuation range; but if it exceeds 5%, an alarm will be immediately triggered, indicating that there may be abnormal situations that need to be investigated in depth. The setting of this preset value needs to be comprehensively evaluated in combination with multiple factors such as the past development speed of the park, the frequency of industrial structure adjustment, and the stability of energy supply, and reviewed and adjusted regularly to ensure that both real anomalies can be captured and false alarms will not occur frequently due to excessive sensitivity.

[0142] Comprehensively considering the energy consumption of community residents, the number of residents, and the carbon emissions information of public facilities, by constructing the comprehensive evaluation parameter Kk, it comprehensively and accurately reflects the overall carbon emission level of the community. For example, if it is found that the high value of Kk is due to the large proportion of the energy consumption information K1 of residents, it may mean that the energy-saving awareness of community residents is insufficient, the household appliances are used frequently, the air-conditioning temperature is set unreasonably, etc. Subsequently, energy-saving publicity activities can be carried out targeted; if the carbon emissions information K3 of public facilities is the dominant factor, it indicates that energy-saving transformation or optimized operation management of public facilities such as community service centers and boiler rooms is required.

[0143] Dynamic tracking and continuous optimization: Collect Kk values ​​within the preset time period in the past and calculate the average K standard to achieve dynamic tracking of community carbon emissions. Over time, the living habits of community residents change, public facilities are updated, and carbon emissions will change accordingly. By regularly updating the K standard and comparing it with the real-time Kk value, the community carbon emission management strategy can be continuously optimized. For example, after the promotion of new energy vehicles, residents' transportation carbon emissions will decrease, and the Kk value will decrease accordingly. If it is still higher than the new K standard, the emission reduction potential of public facilities can be further explored to promote the community to move towards a low-carbon life.

[0144] The preset duration can generally be set to the past year. Selecting one year of data can not only cover the different energy consumption patterns of the four seasons (the demand for heating in winter and cooling in summer is very different), but also reflect the stability of the living habits of community residents over a longer period of time. For example, a community located in the north requires centralized heating in winter. By analyzing one year of data, the fluctuations in residents' energy consumption and carbon emissions during the heating and non-heating seasons can be fully captured, thereby calculating a more representative mean K standard.

[0145] Weight adjustment in K-standard calculation: If the community wants to focus more on the impact of a certain factor on carbon emissions, it can adjust the weight when calculating the K-standard. For example, for an aging community, where the frequency of use of public facilities is relatively high, the weight of K3 (community public facility carbon emission information) in the Kk calculation formula can be appropriately increased, such as from the default 1 / 3 each to K1 0.3, K2 0.2, and K3 0.5, so that the comprehensive assessment parameters are more in line with the actual carbon emission characteristics of the community and accurately locate the focus of emission reduction.

[0146] The process of obtaining the road traffic carbon emission management information is as follows:

[0147] Extract the collected information related to road traffic carbon emissions, which includes road vehicle traffic information per unit time, road width information and road carbon emissions;

[0148] The vehicle traffic information per unit time on the road is marked as V, the road width is marked as W, and the road carbon emissions are marked as C;

[0149] The road evaluation parameter P is obtained by the formula P=C / (V*W). When the road evaluation parameter P is greater than a preset value, the road traffic carbon emission management information is generated;

[0150] By constructing road evaluation parameters, the road carbon emissions, vehicle passing information per unit time on the road, and road width information are organically combined, and the carbon emission efficiency of road traffic is accurately quantified from a comprehensive dimension. It can intuitively reflect the carbon emissions generated per unit space under specific traffic flows and road conditions. For example, during the morning and evening rush hours, the traffic on the main road is dense. If the calculated P value is high at this time, it indicates that the road carbon emission efficiency is low during this period, prompting the traffic management department to quickly take measures to optimize the traffic flow, reduce vehicle idling and frequent starts and stops, and reduce carbon emissions.

[0151] Set a preset value as the judgment criterion. Once the road evaluation parameter P is greater than the preset value, road traffic carbon emission management information is immediately generated, which provides an efficient means for quickly locating sections with carbon emission problems. It's like setting up "carbon emission warning signal lights" in the urban traffic network. When a red light lights up (i.e., the value exceeds the standard) for a certain section, the management personnel can quickly focus on this section and check whether it is due to lane narrowing caused by road construction (affecting the P value), a sharp increase in traffic flow caused by a large event nearby (changing the P value), or a concentration of vehicle exhaust emission exceeding the standard (resulting in an abnormal P value), so as to formulate targeted solutions and timely improve the road traffic carbon emission situation.

[0152] Based on these data, when planning new roads, consideration can be fully given to how to optimize road design to improve the carbon emission efficiency of the future traffic network; in formulating traffic control policies, such as implementing tidal lanes and optimizing signal timing, historical value data can be referred to, and sections with low carbon emission efficiency and serious congestion can be preferentially adjusted to guide the traffic flow to be smoother and achieve the coordinated development of traffic and the environment.

[0153] During the process of generating road traffic carbon emission management information, real-time carbon emissions are also collected, and the real-time carbon emissions are analyzed to generate road auxiliary prompt information;

[0154] The specific process of obtaining the road auxiliary prompt information is as follows:

[0155] Set the collection frequency, continuously collect the real-time carbon emissions K for m times, and import the m times of real-time carbon emissions K into the preset database, which stores the traffic jam determination threshold;

[0156] When the number of real-time carbon emissions K exceeding the traffic jam determination threshold among the m times is greater than or equal to the preset value, the road auxiliary prompt information is generated. At this time, the content of the road auxiliary prompt information is that there may be a traffic jam situation and traffic guidance is needed;

[0157] When the number of times the real-time carbon emissions K exceed the traffic jam determination threshold in m times is less than the preset value, the m-time real-time carbon emissions K are plotted as a line chart for line chart analysis, and the number of angles between the line in the line chart and the x-axis exceeding the preset angle is extracted, that is, the analysis parameter. When the analysis parameter is greater than the preset value, an auxiliary road prompt message is generated. At this time, the content of the auxiliary road prompt message is that a traffic jam situation may be about to occur, and traffic guidance needs to be carried out in advance.

[0158] Through the above process, the set carbon emission monitoring equipment is utilized more fully. On the basis of realizing the intelligent calculation and analysis of carbon emissions, the function of assisting traffic control is realized.

[0159] The process of obtaining the building carbon emission management information is as follows:

[0160] Extract the collected building carbon emission-related information, where the building carbon emission-related information includes the building area and the building carbon emissions;

[0161] Regularly collect the change F1 of the building area and the change E1 of the building carbon emissions;

[0162] Mark the building area as F2 and the building carbon emissions as E2;

[0163] Through the formula (F1 / F2) / (E1 / E2) = Fe, obtain the building evaluation parameter Fe;

[0164] When Fe ≥ 1, it indicates that the increase in area leads to a greater increase in carbon emissions, and there may be a problem of reduced energy utilization efficiency, and building carbon emission management information is generated;

[0165] If Fe < 1, it means that during the area change process, the carbon emission control is relatively good, and no information is generated.

[0166] It can dynamically adapt to building changes. During the use of buildings, the area often increases or decreases due to reconstruction, expansion, and function adjustment. Continuously tracking the area change F1 and the carbon emission change E1 can measure the carbon emission change caused by the newly added area and judge whether it is reasonable. Once it is inappropriate, quickly promote energy-saving transformation and optimize the energy system to ensure that the building "grows" without increasing carbon emissions.

[0167] When Fe ≥ 1, it means that the carbon emissions increase too rapidly when the area increases, which often indicates problems in energy utilization, such as poor insulation in the newly added area and high energy consumption of lighting and air conditioning. This prompts managers to carefully check the energy use links, upgrade equipment, and optimize strategies to prevent energy waste and excessive carbon emissions.

[0168] The process of obtaining the soil carbon emission management information is as follows:

[0169] Extract the collected soil carbon emission related information, including the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil;

[0170] Collect the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil;

[0171] The organic carbon content in u soils is plotted into an organic carbon content line graph according to the order of collection time;

[0172] When the organic carbon content in any of the u soils is greater than the preset value, soil carbon emission management information is generated. When the organic carbon content in the u soils is less than the preset value, a trend analysis is performed on the organic carbon content line graph. When the organic carbon content line graph shows an upward trend, soil carbon emission management information is generated.

[0173] Enter the nitrous oxide content of each soil into a table, remove the data that exceeds the preset value, and then calculate the average and range (maximum value minus minimum value) of the remaining nitrous oxide concentration. The average value reflects the overall content level, and the range shows the degree of data dispersion. We can preliminarily understand the fluctuation of soil nitrous oxide content, collect the past nitrous oxide data of similar local land, and process them to obtain the upper limit of nitrous oxide safety content, that is, the benchmark value;

[0174] When the average residual nitrous oxide concentration at a certain time is higher than this baseline value, soil carbon emission management information is generated; it indicates that excessive nitrogen fertilizer may be applied or soil permeability is abnormal, and the fertilization plan and soil tillage methods need to be checked.

[0175] When the range is greater than the preset value, soil carbon emission management information is also generated;

[0176] Extract the carbon dioxide content in u soils, extract the collection time points of the carbon dioxide content in u soils, process the collection time points of the carbon dioxide content in u soils, extract the duration when the carbon dioxide content is greater than a preset value, and when the duration when the carbon dioxide content is greater than the preset value exceeds the preset duration, generate soil carbon emission management information;

[0177] Extract u nitrogen contents, remove the maximum and minimum values ​​among the u nitrogen contents, calculate the average of u-2 nitrogen contents, and obtain the average nitrogen content. When the average nitrogen content is greater than the preset value, soil carbon emission management information is generated;

[0178] Extract u methane contents, then extract the time points at which u methane contents were collected, and then analyze the time points of u methane contents to obtain the total duration when the methane content is greater than the preset value. When the total duration when the methane content is greater than the preset value is greater than the preset value, soil carbon emission management information is generated;

[0179] The collection process of the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content, and methane content in the soil is as follows: The organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content, and methane content are collected at the same location every preset time interval, and collected continuously for u times, where u ≥ 6.

[0180] First, it has strong systematicness. It comprehensively covers a variety of key indicators closely related to carbon emissions in the soil, including organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content, and methane content, without missing important information sources. It can accurately understand the soil carbon emission status from multiple perspectives and avoid one-sided understanding caused by single-index evaluation. For example, when studying a long-term cultivated farmland, monitoring these indicators simultaneously can not only detect the changes in nitrogen content and nitrous oxide content caused by fertilization, but also track the dynamic changes of carbon dioxide and methane emissions caused by the decomposition of organic carbon, and comprehensively grasp the entire picture of the soil carbon cycle.

[0181] Second, the advantage of dynamic monitoring is obvious. By continuously collecting u times according to the preset time interval, the changing trends of soil carbon emission indicators over time can be captured. Taking the organic carbon content as an example, plotting it as a line chart can visually show its increasing and decreasing trends, which is of great significance for promptly detecting the profit and loss of the soil carbon pool and early warning potential carbon emission risks. For a newly afforested land, if the line chart of the continuously monitored organic carbon content shows an upward trend, it means that the soil carbon sequestration ability is increasing; conversely, if it decreases, factors such as tree growth and soil disturbance need to be investigated.

[0182] Third, the data processing is rigorous and targeted. Appropriate analysis methods are adopted for different indicators. For example, for the nitrous oxide concentration, abnormal values are removed, and the mean value and range are calculated to accurately judge the content fluctuation and whether it exceeds the standard; for the carbon dioxide content, the duration greater than the preset value is concerned, focusing on the characteristics of high-emission periods. For example, in a intensive vegetable planting base, if the mean value of the nitrous oxide concentration is higher than the reference value, it immediately warns of nitrogen fertilizer problems; if the duration of high carbon dioxide content exceeds the standard, it indicates that there may be problems such as poor ventilation and abnormal decomposition of organic materials, prompting timely adjustment of management.

[0183] Finally, it has a good early warning function. Once each indicator touches the preset threshold, management information is generated. Whether it is the absolute value of the organic carbon content, the mean value of the nitrogen content, or the breakthrough of the duration and concentration thresholds of other gas contents, an alarm can be quickly sounded, guiding managers to respond quickly and take measures such as optimizing fertilization, improving soil ventilation, and adjusting the planting structure to effectively prevent and control soil carbon emissions.

[0184] Suppose there is an orchard with an area of 50 mu, the preset time interval is set to monthly, and data is collected continuously 12 times.

[0185] In terms of organic carbon content, if the value collected for the 8th time is suddenly much higher than the preset value, an information prompt is generated, indicating that there may be a large accumulation of fallen leaves and rapid decomposition in the near future. It is necessary to reasonably plow to accelerate humification and stabilize the carbon content. If the line chart shows a slow overall increase, it means that the soil fertility is accumulating well, and the current fruit tree pruning and green manure planting strategies should be maintained.

[0186] For nitrous oxide content, after processing, it is found that the average value is higher than the benchmark value of the local orchard, warning that nitrogen fertilizer is applied too frequently. It is recommended to adjust to fertilize according to demand and cooperate with nitrification inhibitors. At the same time, since the range is too large, check the areas with uneven soil air permeability and loosen the soil targeted.

[0187] For carbon dioxide content, if the duration of the carbon dioxide content being greater than the preset value in each of the 3 months in summer exceeds 20 days, it indicates that the soil respiration in the orchard is strong during the high-temperature period. It is necessary to increase irrigation to cool down, cover to conserve moisture, and reduce carbon emissions.

[0188] For nitrogen content, after removing the maximum and minimum values, the average value is high. Consider reducing the input of chemical fertilizers and increasing the application of organic fertilizers to balance the soil nitrogen. For methane content, if the total duration of being greater than the preset value exceeds 4 months, check the waterlogged areas in the orchard, improve drainage, and inhibit methane production.

[0189] The process of obtaining the calculation status evaluation information is as follows:

[0190] Extract the information related to carbon emission calculation. The information related to carbon emission calculation includes calculation speed information, calculation accuracy, and hardware occupancy information during the calculation process.

[0191] Among them, the process of obtaining the calculation speed information and calculation accuracy is as follows: Use simulation data for simulation calculation. After f times of simulation calculations, f simulation calculation speeds and f simulation calculation results are obtained.

[0192] Mark the f simulation calculation speeds as Qf. Through the formula (Q1 + Q2 + Q3... Qf) / f * α = Qq, the calculation speed parameter Qq is obtained, where α is a correction value, 0.9 ≤ α ≤ 1.1, and the magnitude of α is inversely proportional to the number of other calculation tasks executed by the system simultaneously during the calculation process.

[0193] After that, extract the number of simulation calculation results among the f simulation calculation results whose similarity to the standard result is less than the preset value to obtain the accuracy parameter, f ≥ 10.

[0194] Then extract the hardware occupancy information during the calculation process. The hardware occupancy information during the calculation process includes CPU occupancy rate, memory occupancy rate, and hard disk storage occupancy rate.

[0195] Mark the CPU occupancy rate as Y1, the memory occupancy rate as Y2, and the hard disk storage occupancy rate as Y3.

[0196] Assign weights u1 to Y1, u2 to Y2, and u3 to Y3.

[0197] u1 + u2 + u3 = 1, u2 > u1 > u3. By the formula Y1*u1 + Y2*u2 + Y3*u3 = Yy, the occupancy evaluation parameter Yy can be obtained.

[0198] When the calculation speed parameter Qq is less than the preset value, the accuracy parameter is greater than the preset value, and the occupancy evaluation parameter Yy is less than the preset value, the calculation status evaluation information is generated. At this time, the calculation status evaluation information indicates that the calculation status is normal.

[0199] When any one of the calculation speed parameter Qq being greater than the preset value, the accuracy parameter being less than the preset value, and the occupancy evaluation parameter Yy being less than the preset value occurs, the calculation status evaluation information is generated. At this time, the calculation status evaluation information indicates that the calculation status is abnormal.

[0200] The above process comprehensively considers the calculation speed, accuracy, and hardware occupancy information, and evaluates the carbon emission calculation status from multiple key dimensions. By considering the usage of each component (hardware resource) during the operation process, it ensures a comprehensive and in-depth understanding of the calculation status.

[0201] Multiple simulated calculation speeds are obtained through simulation calculations, and then the calculation speed parameter Qq is calculated in combination with the correction value. This method can more accurately reflect the calculation speed. The correction value α is adjusted according to the number of other parallel calculation tasks in the system, considering the impact of system resource competition on the calculation speed. Just like adjusting the vehicle speed under different road conditions to adapt to the actual situation, it makes the calculation speed evaluation more in line with the actual operation scenario.

[0202] Effectively evaluate the calculation accuracy: By comparing the similarity between the simulated calculation result and the standard result, the accuracy parameter is obtained, which provides a quantitative index for evaluating the accuracy of the calculation result.

[0203] Reasonably consider the hardware occupancy, comprehensively evaluate the hardware occupancy information, consider the CPU, memory, and hard disk storage occupancy rates, and assign different weights to calculate the occupancy evaluation parameter Yy. This reflects the differences in the importance of different hardware resources for the calculation task. For example, memory is crucial for data processing and storage, so the weight u2 is relatively large. In this way, it can accurately judge whether the hardware resources are reasonably utilized, and avoid calculation problems caused by tight or over-occupied hardware resources.

[0204] Discover abnormal status in a timely manner: By setting the preset value, it can quickly judge whether the calculation status is abnormal. When the evaluation parameters of the calculation speed, accuracy, and hardware occupancy deviate from the preset range, the evaluation information of the abnormal calculation status is generated, promptly reminding relevant personnel to troubleshoot problems, ensuring the accuracy and efficiency of carbon emission calculations, and avoiding mistakes in carbon emission management caused by calculation problems.

[0205] Through the above management system, it is possible to collect project basic and carbon emission accounting information step by step, analyze the compliance of the project industry with different green standards, evaluate the carbon reduction impact of carbon storage products and compare them with the benchmark values of similar projects, generate reports, and assist financial institutions and investors in screening investment projects with environmental benefits.

[0206] Based on the carbon peak and carbon neutrality path deduction model, conduct scenario rehearsals for carbon peak and carbon neutrality of multi-level entities such as regions, parks, industries, and enterprises, evaluate strategies from multiple dimensions, scientifically plan the carbon peak and carbon neutrality path, and assist in accurate carbon peak and carbon neutrality decision-making.

[0207] Key business support: Provide one-stop services for parks and enterprises, including finding out the carbon inventory, tapping the potential for emission reduction, deducing the carbon peak and neutralization path, assisting in carbon market transactions, and revitalizing carbon assets, improving the energy and carbon management ability, and supporting the achievement of the carbon peak and carbon neutrality goals with digitalization.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the specification of the present invention.

Claims

1. Carbon data intelligent management system, characterized by: It includes a carbon emission monitoring equipment collection module, a carbon emission information collection module, a calculation information collection module, a data processing module and an information sending module; The carbon emission monitoring equipment collection module is used to collect information related to the carbon emission monitoring equipment; The carbon emission information collection module is used to collect carbon emission information from various regions, including information related to carbon emission in production parks, information related to carbon emission in communities, information related to carbon emission in road traffic, information related to carbon emission in buildings, and information related to carbon emission in soils; The calculation information collection module is used to collect information related to carbon emission calculation; The data processing module is used to process the information related to the carbon emission monitoring equipment and generate monitoring equipment management information; Process the carbon emission information of each region to generate park carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information and soil carbon emission management information; Processing information related to carbon emission calculation to generate calculation status assessment information; The information sending module is used to send monitoring equipment management information, park carbon emission management information, factory carbon emission management information, community carbon emission management information, road traffic carbon emission management information, building carbon emission management information, soil carbon emission management information and calculation status evaluation information to a preset receiving terminal.

2. The carbon data intelligent management system according to claim 1, characterized in that: The specific process of the carbon emission monitoring equipment collection module collecting relevant information of the carbon emission monitoring equipment is as follows: When the carbon emission monitoring device is installed, multiple pressure sensors are set between it and the installation surface to collect the pressure between the carbon emission monitoring device and the installation surface, that is, to obtain the installation force information; Then collect the position of the carbon emission monitoring equipment, draw a circle with the position of the carbon emission monitoring equipment as the center point and a preset length as the radius, obtain the determination range, collect the number of temperature anomaly sources and the number of electromagnetic interference sources within the determination range, and the number of temperature anomaly sources and the number of electromagnetic interference sources constitute the number of abnormal sources; Perform status detection on the carbon emission monitoring device, detect the operating status and operating temperature information of its cooling fan, and obtain the operating status and operating temperature information of the cooling fan to form the device status information; Perform system status detection on carbon emission monitoring equipment, detect CPU usage and memory usage when the system is running, and obtain system status information; Conduct data collection tests on carbon emission monitoring equipment, send standard gas samples to the sensors of the monitoring equipment, compare the deviation between the measured value and the true value in the standard gas sample to obtain the evaluation sensitivity, and monitor the data transmission stability, statistical data packet loss rate and transmission delay time. The evaluation sensitivity, data packet loss rate and transmission delay time constitute the equipment test data; Installation stress information, number of abnormal sources, system status information and equipment test data constitute the monitoring equipment related information.

3. The carbon data intelligent management system according to claim 2 is characterized by: The specific process of obtaining the monitoring device management information is as follows: Extract the acquired monitoring equipment related information, and extract the installation stress information, the number of abnormal sources, the system status information and the equipment test data from the monitoring equipment related information; Analyze the installation force information, extract the collected multiple installation force information, and generate monitoring equipment management information when any one of the multiple installation force information is less than a preset value; When multiple installation force information are greater than or equal to the preset value, the difference between the multiple installation force information is calculated, and when any one of the difference between the multiple installation force information is greater than the preset value, the monitoring device management information is generated; Analyze the number of abnormal sources, and when the sum of the number of temperature abnormal sources and the number of electromagnetic interference sources is greater than a preset number, generate monitoring equipment management information; Analyze the device status information and extract the cooling fan operation status. When the cooling fan operation status is abnormal, generate monitoring device management information. When the operation temperature information is abnormal, generate monitoring device management information. Analyze the system status information. When any one of the CPU usage and memory usage during system operation is greater than a preset value for a preset period of time, monitoring device management information is generated. The device test data is analyzed, and when any of the following occurs: the evaluation sensitivity is less than a preset value, the data packet loss rate is greater than a preset value, or the transmission delay time is greater than a preset value, monitoring device management information is generated.

4. The carbon data intelligent management system according to claim 3 is characterized by: The process of determining the abnormal operation status of the cooling fan is as follows: When the carbon emission monitoring device receives a heat dissipation instruction, it extracts the time point when the instruction is generated and marks it as T1, and then collects the time point when the heat dissipation fan is running and marks it as T2; The difference between T2 and T1 is calculated to obtain the operation interval difference. When the operation interval difference is greater than a preset value, it indicates that the operation state of the cooling fan is abnormal. Then collect the real-time speed of the cooling fan. When the real-time speed of the cooling fan is less than the standard speed, it means that the cooling fan is operating abnormally. The process of determining the abnormality of the operating temperature information is as follows: when the operating temperature information is continuously greater than the preset value a1 for more than a preset time or the operating temperature is greater than the warning value a2, it indicates that the operating temperature information is abnormal, a2>a1.

5. The carbon data intelligent management system according to claim 1, characterized in that: The process of obtaining the park's carbon emission management information is as follows: Extract the collected information related to the park's carbon emissions, including the park's real-time carbon emissions information and the park's carbon emissions information from the previous year; Compare the park's real-time carbon emission information with historical carbon emission information. When the real-time carbon emission information exceeds the park's carbon emission information from the previous year, the park's carbon emission management information is generated; The process of obtaining community carbon emission management information is as follows: Extract the collected community carbon emission related information, which includes community residents' energy consumption information, community residents' number information and community public facilities carbon emission information; The energy consumption information of community residents is marked as K1, the number of community residents is marked as K2, and the carbon emission information of community public facilities is marked as K3; Through the formula (K1+K3) / K2=Kk, the comprehensive evaluation parameter Kk is obtained; Collect the comprehensive evaluation parameters Kk within the past preset time, and calculate the mean value K of the comprehensive evaluation parameters Kk within the past preset time 标 ; When the comprehensive evaluation parameter Kk is greater than K 标 When the community carbon emission management information is generated.

6. The carbon data intelligent management system according to claim 1, characterized in that: The process of obtaining the road traffic carbon emission management information is as follows: Extract the collected information related to road traffic carbon emissions, which includes road vehicle traffic information per unit time, road width information and road carbon emissions; The vehicle traffic information per unit time on the road is marked as V, the road width is marked as W, and the road carbon emissions are marked as C; The road evaluation parameter P is obtained through the formula P=C / (V*W). When the road evaluation parameter P is greater than a preset value, the road traffic carbon emission management information is generated.

7. The carbon data intelligent management system according to claim 6, characterized in that: In the process of generating road traffic carbon emission management information, real-time carbon emissions are also collected and analyzed to generate road auxiliary prompt information; The specific process of obtaining auxiliary road prompt information is as follows: The collection frequency is set to continuously collect m times of real-time carbon emissions K, and the m times of real-time carbon emissions K are imported into a preset database, which stores the traffic jam determination threshold; When the number of m real-time carbon emissions K that exceeds the traffic jam determination threshold is greater than or equal to the preset value, auxiliary road prompt information is generated. At this time, the content of the auxiliary road prompt information is that there may be a traffic jam and traffic diversion is required; When the number of m real-time carbon emissions K that exceeds the traffic jam determination threshold is less than a preset value, the m real-time carbon emissions K are plotted into a line graph, and the line graph analysis is performed to extract the number of angles between the broken lines in the line graph and the x-axis that exceed the preset angle, i.e., the analysis parameter. When the analysis parameter is greater than the preset value, an auxiliary road prompt message is generated. At this time, the content of the auxiliary road prompt message is that a traffic jam may be imminent and traffic diversion is required in advance.

8. The carbon data intelligent management system according to claim 1, characterized in that: The process of obtaining the building carbon emission management information is as follows: Extract the collected information related to building carbon emissions, which includes building area and building carbon emissions; Regularly collect the changes in building area F1 and building carbon emissions E1; The building area is marked as F2 and the building carbon emissions are marked as E2; The building assessment parameter Fe is obtained through the formula (F1 / F2) / (E1 / E2)=Fe; When Fe≥1, building carbon emission management information is generated; If Fe<1, no information is generated.

9. The carbon data intelligent management system according to claim 1, characterized in that: The process of obtaining soil carbon emission management information is as follows: Extract the collected soil carbon emission related information, including the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil; Collect the organic carbon content, nitrous oxide content, carbon dioxide content, nitrogen content and methane content in the soil; The organic carbon content in u soils is plotted into an organic carbon content line graph according to the order of collection time; When the organic carbon content in any of the u soils is greater than the preset value, soil carbon emission management information is generated. When the organic carbon content in the u soils is less than the preset value, a trend analysis is performed on the organic carbon content line graph. When the organic carbon content line graph shows an upward trend, soil carbon emission management information is generated. Enter the nitrous oxide content of each batch into a table, remove the data exceeding the preset value, and then calculate the remaining nitrous oxide concentration average and range. Collect the past nitrous oxide data of similar local land and process them to obtain the upper limit of nitrous oxide safety content, i.e., the benchmark value. When the average value of the remaining nitrous oxide concentration at a certain time is higher than this benchmark value, soil carbon emission management information is generated; When the range is greater than the preset value, soil carbon emission management information is also generated; Extract the carbon dioxide content in u soils, extract the collection time points of the carbon dioxide content in u soils, process the collection time points of the carbon dioxide content in u soils, extract the duration when the carbon dioxide content is greater than a preset value, and when the duration when the carbon dioxide content is greater than the preset value exceeds the preset duration, generate soil carbon emission management information; Extract u nitrogen contents, remove the maximum and minimum values ​​among the u nitrogen contents, calculate the average of u-2 nitrogen contents, and obtain the average nitrogen content. When the average nitrogen content is greater than the preset value, soil carbon emission management information is generated; Extract u methane contents, then extract the time points at which u methane contents were collected, and then analyze the time points of u methane contents to obtain the total duration when the methane content is greater than the preset value. When the total duration when the methane content is greater than the preset value is greater than the preset value, soil carbon emission management information is generated; The process of collecting the organic carbon content, amine oxide content, carbon dioxide content, nitrogen content and methane content in u pieces of soil is as follows: the organic carbon content, amine oxide content, carbon dioxide content, nitrogen content and methane content are collected once at the same location at a preset time interval, and collected continuously for u times.

10. The carbon data intelligent management system according to claim 1, characterized in that: The process of obtaining the computing status evaluation information is as follows: Extracting carbon emission calculation related information, including calculation speed information, calculation accuracy, and hardware occupancy information during the calculation process; The process of obtaining the calculation speed information and the calculation accuracy is as follows: using the simulation data to perform simulation calculations, after performing f simulation calculations, f simulation calculation speeds and f simulation calculation results are obtained; The f simulation calculation speeds are marked as Qf, and the calculation speed parameter Qq is obtained through the formula (Q1+Q2+Q3…Qf) / f*α=Qq, where α is a correction value, 0.9≤α≤1.1, and the size of α is inversely proportional to the number of other calculation tasks executed by the system during the calculation process; Then, the number of f simulation calculation results whose similarity with the standard results is less than a preset value is extracted to obtain the accuracy parameter; Then extract the hardware usage information during the calculation process, which includes CPU usage, memory usage and hard disk storage usage; Mark the CPU usage as Y1, the memory usage as Y2, and the hard disk storage usage as Y3; Assign weight u1 to Y1, weight u2 to Y2, and weight u3 to Y3; u1+u2+u3=1, u2>u1>u3, through the formula Y1*u1+Y2*u2+Y3*u3=Yy, the occupancy assessment parameter Yy is obtained; When the calculation speed parameter Qq is less than the preset value, the accuracy parameter is greater than the preset value, and the occupancy assessment parameter Yy is less than the preset value, the calculation state assessment information is generated, and at this time, the calculation state of the calculation state assessment information is normal; When any one of the calculation speed parameter Qq is greater than the preset value, the accuracy parameter is less than the preset value, and the occupancy assessment parameter Yy is less than the preset value, the calculation state assessment information is generated, and the calculation state of the calculation state assessment information is abnormal.

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