CN115619164A - A multi-dimensional carbon emission monitoring and analysis system based on big data processing - Google Patents

Abstract

The invention discloses a multi-dimensional carbon emission monitoring and analysis system based on big data processing, comprising: a data acquisition module, a data analysis and processing module, an early warning module, a data storage module and a data display module; the output end of the data acquisition module is connected with A data analysis and processing module, the output end of the data analysis and processing module is connected to an early warning module, the output end of the early warning module is connected to a data storage module, and the output end of the data storage module is connected to a data display module. The multi-dimensional carbon emission monitoring and analysis system based on big data processing, collects data through the data acquisition module, can fully understand the carbon emissions in different regions, facilitates later data planning, and transmits data to the data analysis and processing module for analysis. The data is transmitted to the data storage module for data storage, which is convenient for later calling and processing. The data display terminal displays the data, and the generated information can be transmitted through the data sending module.

Description

A multi-dimensional carbon emission monitoring and analysis system based on big data processing

technical field

The invention relates to the technical field of big data processing, in particular to a multi-dimensional carbon emission monitoring and analysis system based on big data processing.

Background technique

Carbon emission is a general term or abbreviation for greenhouse gas emission. The most important gas in the greenhouse gas is carbon dioxide, so the term carbon is used as a representative. Although not accurate, the quickest way for the public to understand is to simply understand "carbon emissions" as "carbon dioxide emissions". Most scientists and governments recognize that greenhouse gases have and will continue to bring disasters to the earth and human beings, so terms such as "(control) carbon emissions" and "carbon neutrality" have become easily understood, accepted, and adopted by most people. Cultural basis for action. Carbon dioxide is emitted during the production, transportation, use and recycling of some products. Carbon dioxide is a greenhouse gas. Carbon dioxide emissions are generally considered to be the main cause of global warming, which seriously affects the environment. In order to regulate and reduce carbon dioxide emissions On the one hand, it is necessary to encourage the adoption of a low-carbon lifestyle and reduce carbon emissions; on the other hand, it is necessary to achieve a balance through certain carbon offset measures. When planning and regulating carbon dioxide emissions, it is necessary to monitor and analyze carbon emissions.

At present, the existing carbon emission supervision system is not perfect, the data statistics are incomplete, it is impossible to understand the carbon emissions of various industries in an all-round way, and it is impossible to make a good data plan, and the carbon emission supervision work in most parts of the country is still limited. Manual reporting of carbon emission data is based on the energy consumption ledger of the regulated party, and a small part relies on the energy accounting system for checking on the basis of the original "energy consumption monitoring system". Therefore, it is easy to make mistakes or omissions in data statistics in this way, and the fairness and accuracy of data cannot be guaranteed, and it cannot dynamically reflect the emission situation of various places in real time, and it is difficult to expand functions. After adopting the offline fund collection statistics method, the finer the granularity of carbon emission calculation required, the higher the complexity of the fund collection, the greater the statistical workload, and the inability to pass part of the data analysis and judgment, which is not conducive to scientific and reasonable planning for the region. Carbon emissions governance policy.

Contents of the invention

The purpose of the present invention is to provide a multi-dimensional carbon emission monitoring and analysis system based on big data processing, so as to improve data collection efficiency, complete and accurate data statistics, and enable comprehensive understanding of carbon emissions in different regions.

In order to achieve the above purpose, the present invention provides the following technical solutions: a multi-dimensional carbon emission monitoring and analysis system based on big data processing, including: a data acquisition module, a data analysis and processing module, an early warning module, a data storage module and a data display module;

The output end of the data acquisition module is connected to a data analysis and processing module, the output end of the data analysis and processing module is connected to an early warning module, the output end of the early warning module is connected to a data storage module, and the output end of the data storage module is connected to a data display module.

Preferably, the data collection module includes: a regional coal, oil and natural gas consumption collection module, a regional electricity consumption collection module, a regional electricity carbon emission calculation module, an environmental protection bureau database, smart meter collection and electric carbon coefficient calculation;

The input end of the regional coal, oil and natural gas consumption acquisition module is connected to the database of the Environmental Protection Bureau.

Preferably, the input end of the regional electricity consumption collection module is connected to smart meter collection, and the input end of the regional electricity carbon emission calculation module is connected to electric carbon coefficient calculation.

Preferably, the data analysis and processing module includes: a data receiving module, a carbon emission data AI processing module, a current carbon emission data unit, a predicted carbon emission data unit, a past carbon emission data unit, and a data prediction unit;

The data analysis and processing module is connected with a data receiving module, and the data analysis and processing module is connected with a data prediction unit.

Preferably, the data analysis and processing module is connected to a carbon emission data AI processing module, the carbon emission data AI processing module is connected to a current carbon emission data unit, and the carbon emission data AI processing module is connected to a predicted carbon emission data unit, The carbon emission data AI processing module is connected with a past carbon emission data unit.

Preferably, the early warning module includes: data traceability, on-site investigation, expert diagnosis, alarm module, voice module, prompt module and network module;

The early warning module is connected with data traceability, the early warning module is connected with on-site investigation, and the early warning module is connected with expert diagnosis.

Preferably, the warning module is connected with an alarm module, the alarm module is connected with a voice module, the alarm module is connected with a prompt module, and the alarm module is connected with a network module.

Preferably, the data storage module includes: memory, RAM, ROM and cache memory;

The data storage module is connected with a memory, the memory is connected with a RAM, the memory is connected with a ROM, and the memory is connected with a cache memory.

Preferably, the data display module includes: a data display terminal, a data graph analysis unit, a data text analysis unit, a data report generation unit, a data sending module, a WIFI communication module, a G communication module and a Bluetooth communication module;

The data display terminal is connected with a data chart analysis unit, the data display terminal is connected with a data text analysis unit, and the data display terminal is connected with a data report generation unit.

Preferably, the data display terminal is connected with a data sending module, the data sending module is connected with a WIFI communication module, the data sending module is connected with a G communication module, and the data sending module is connected with a Bluetooth communication module .

Compared with the prior art, the beneficial effect of the present invention is that the multi-dimensional carbon emission monitoring and analysis system based on big data processing can collect data through the data acquisition module, and can fully understand the carbon emission in different regions, which is convenient for the later stage. Data planning, data transmission to the data analysis and processing module for analysis, data transmission to the data storage module for data storage, which is convenient for later call and processing, the data display terminal displays the data, and the generated information can be transmitted through the data transmission module.

1. Collect data through the data acquisition module, call the database of the Environmental Protection Agency to understand the regional coal, oil and natural gas consumption, and transmit the data to the regional coal, oil and natural gas consumption acquisition module, collect regional electricity consumption through smart meters, and Transfer the data to the regional electricity consumption acquisition module, and use the electric carbon coefficient to calculate the carbon emission content of regional electricity, where the carbon dioxide emission of household electricity (kg) = power consumption × 0.785, and the carbon dioxide emission of household natural gas (kg) = Natural gas use degree × 0.19, household tap water carbon dioxide emissions (kg) = tap water use degree × 0.91, the calculated data is transmitted to the regional power carbon emission calculation module, and the data is collected through the data acquisition module. The overall collection efficiency is greatly improved. The data statistics are complete and accurate, and the carbon emissions in different regions can be fully understood, which is convenient for later data planning;

2. The data is transmitted to the data analysis and processing module, the data is received through the data receiving module, and the data is processed through the carbon emission data AI processing module. The carbon emission data AI processing module includes the current carbon emission data unit, the predicted carbon emission data unit and the past Carbon emission data unit, so the current carbon emission data can be compared with past carbon emission data through the data prediction unit to obtain predicted carbon emission data, which is convenient for users to adjust carbon emission according to the data situation;

3. If there is any problem with the detected data, it will be transmitted to the early warning module. The early warning module uses data traceability, on-site investigation and expert diagnosis to judge whether the data is accurate. The module reminds the user to adjust according to the data. The network module transmits the data to the memory. If the information is wrong, the exclusion result is fed back to the memory. The standard value needs to be corrected, and if necessary, the parameter is fed back to the data processor through the standard management module;

4. The data is transmitted to the data storage module, and the memory stores the data. ROM is a read-only memory, which means that the memory can only be read and cannot be written. Therefore, data that does not need to be changed and needs to be stored can be written. RAM is a random access memory, that is Under normal working conditions, data can be read and written to the memory at any time, so RAM is used for storage most of the time, and cache memory is a first-level memory between the main memory and the CPU. It is composed of static memory chips and has a relatively small capacity. But the speed is much higher than that of the main memory, which is close to the speed of the CPU. Therefore, the more important data is stored in the cache memory, which improves the work efficiency. After the data is stored, it is convenient for later calling and processing. The external device performs data exchange processing on the data in the memory, and communicates through the network adapter;

5. After the data storage is completed, the data is displayed through the data display terminal, and the data display terminal calls the data display module, and uses the data chart analysis unit to process the data into a chart output, uses the data text analysis unit to process the data into text output, and uses the data The report generation unit processes the data into a report output, provides it to the user for review and analysis, and reacts the data dynamically in real time, which is convenient for the user to view. The generated information can be transmitted through the data sending module, through the WIFI communication module, 5G communication Module and Bluetooth communication module will transmit data.

Description of drawings

Fig. 1 is a structural representation of the present invention;

Fig. 2 is the structural representation of data acquisition module of the present invention;

Fig. 3 is a schematic structural diagram of the data analysis and processing module of the present invention;

Fig. 4 is a structural schematic diagram of the early warning module of the present invention;

Fig. 5 is a schematic structural diagram of the data storage module of the present invention;

Fig. 6 is a schematic structural diagram of the data display module of the present invention.

In the figure: 1. Data acquisition module; 11. Regional coal, oil and natural gas consumption acquisition module; 12. Regional electricity consumption acquisition module; 13. Regional electricity carbon emission calculation module; 14. Environmental protection bureau database; 15. Smart meter acquisition ;16. Electric carbon coefficient calculation; 2. Data analysis and processing module; 21. Data receiving module; 22. Carbon emission data AI processing module; 221. Current carbon emission data unit; 222. Predicted carbon emission data unit; 223. Past carbon emission data unit Emission data unit; 23. Data prediction unit; 3. Early warning module; 31. Data traceability; 32. On-site investigation; 33. Expert diagnosis; 34. Alarm module; 341. Voice module; 342. Prompt module; 343. Network module; 4. Data storage module; 41. Memory; 411. RAM; 412. ROM; 413. Cache memory; 5. Data display module; 51. Data display terminal; 511. Data chart analysis unit; 512. Data text analysis unit; 513. Report generating unit; 52. Data sending module; 521. WIFI communication module; 522. 5G communication module; 523. Bluetooth communication module.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

Please refer to Figures 1-4, the present invention provides a technical solution: a multi-dimensional carbon emission monitoring and analysis system based on big data processing, including: data acquisition module 1, data analysis and processing module 2, early warning module 3, and data storage module 4 and data display module 5.

The output end of the data acquisition module 1 is connected to the data analysis and processing module 2, the output end of the data analysis and processing module 2 is connected to the early warning module 3, the output end of the early warning module 3 is connected to the data storage module 4, and the output end of the data storage module 4 is connected to the data display module 5.

Data collection module 1, including: regional coal, oil and natural gas consumption collection module 11, regional electricity consumption collection module 12, regional electricity carbon emission calculation module 13, environmental protection bureau database 14, smart meter collection 15 and electricity carbon coefficient calculation 16, The input end of the regional coal, oil and natural gas consumption collection module 11 is connected to the database 14 of the Environmental Protection Bureau, and data collection is performed through the data collection module 1, and the database 14 of the Environmental Protection Bureau is called to understand the regional coal, petroleum and natural gas consumption, and the data is transmitted to the regional coal 1. In the oil and natural gas consumption collection module 11, the overall collection efficiency is greatly improved.

The input end of the regional power consumption acquisition module 12 is connected to the smart meter collection 15, and the input end of the regional power carbon emission calculation module 13 is connected to the electric carbon coefficient calculation 16. The smart meter collects 15 regional power consumption and transmits the data to the regional power consumption. The electricity collection module 12 makes the data statistics complete and accurate, and can fully understand the carbon emissions in different regions, and uses the electricity carbon coefficient calculation 16 to calculate the carbon emission content of regional electricity, wherein the carbon dioxide emissions (kg) of household electricity = power consumption Degree × 0.785, household natural gas carbon dioxide emission (kg) = natural gas usage degree × 0.19, household tap water carbon dioxide emission (kg) = tap water usage degree × 0.91, the calculated data is transmitted to the regional power carbon emission calculation module 13, through The data collection module 1 collects data, which is convenient for later data planning.

Data analysis and processing module 2, including: data receiving module 21, carbon emission data AI processing module 22, current carbon emission data unit 221, predicted carbon emission data unit 222, past carbon emission data unit 223 and data prediction unit 23, data analysis and processing The module 2 is connected with a data receiving module 21, the data analysis processing module 2 is connected with a data prediction unit 23, the data is transmitted to the data analysis processing module 2, the data is received by the data receiving module 21, and the current carbon emission data and Compared with the past carbon emission data, the predicted carbon emission data is obtained.

The data analysis and processing module 2 is connected to the carbon emission data AI processing module 22, the carbon emission data AI processing module 22 is connected to the current carbon emission data unit 221, the carbon emission data AI processing module 22 is connected to the predicted carbon emission data unit 222, and the carbon emission data The AI processing module 22 is connected with a past carbon emission data unit 223, and processes the data through the carbon emission data AI processing module 22, wherein the carbon emission data AI processing module 22 includes the current carbon emission data unit 221, the predicted carbon emission data unit 222 and the past carbon emission data unit 222. The emission data unit 223 is convenient for users to adjust carbon emission according to the data situation.

Carbon neutrality means that through energy conservation and emission reduction, energy substitution, industrial adjustment, etc., the emitted carbon dioxide is recycled to achieve positive and negative offsets, and finally achieve "zero emissions". The data analysis and processing module 2 also includes a carbon neutral prediction module, which is used to calculate the carbon neutral gap and the progress of carbon neutral according to the carbon emissions and carbon reduction, so as to control the regional carbon emissions , and at the same time extract the layout of the carbon reduction work, and can complete the tasks of carbon emission and carbon neutrality in a planned and targeted manner.

For example, the carbon neutralization of a county A mainly offsets the carbon emissions of county A through clean energy decarbonization and forest decarbonization. The carbon neutrality prediction module analyzes and predicts by establishing a carbon neutrality objective function. The objective function is as follows (1).

Des(x)＝F _{electric power} (x)+F _{non-electric power} (x)-G(x)-H(x) (1)

Wherein, x is a time series, and the present invention takes the year as the corresponding time series;

Des(x) refers to the difference between the annual carbon emissions corresponding to x and the total amount of carbon reduction. When the difference is less than or equal to 0, carbon neutrality is considered to be achieved;

F _Electricity (x) is the annual electricity carbon emissions corresponding to x;

F _{non-electricity} (x) is the annual non-electricity carbon emissions corresponding to x;

G(x) is the annual clean energy carbon reduction corresponding to x;

H(x) is the annual forest carbon reduction corresponding to x.

Assuming that non-electricity carbon emissions Fnon _-electricity (x) and forest carbon reduction H(x) remain stable, the corresponding values in 2021 are taken respectively. Electricity carbon emissions _Felectricity (x) increases with the increase in electricity demand, and through linear regression Analyze and predict the carbon emission value of electricity from 2022 to 2025, so as to calculate the annual clean energy carbon reduction gap from 2022 to 2025.

Table 1A Prediction of carbon reduction gap in counties from 2022 to 2025

As shown in Table 1 above, assuming that the carbon reduction of clean energy remains the same, the predicted carbon reduction gap in 2025 is 101,466,704.8KG, which is equivalent to 128,114,500 kWh of clean energy power generation. Therefore, from 2022 to 2025, an average of 32.03 million kilowatt-hours of new clean energy power generation will be required each year. According to the theory of 8-hour power generation, the installed capacity of clean energy needs to be increased by an average of 10,900 kilowatts per year to achieve zero carbon emissions in 2025. To sum up, the carbon neutral process prediction of county A is shown in Table 2 below.

Table 2A Prediction table of county-level carbon neutrality process

Early warning module 3, including: data traceability 31, on-site investigation 32, expert diagnosis 33, alarm module 34, voice module 341, prompt module 342 and network module 343, early warning module 3 is connected with data traceability 31, and early warning module 3 is connected with on-site investigation 32. The early warning module 3 is connected to an expert diagnosis 33. If there is any problem with the detected data, it will be transmitted to the early warning module 3. The early warning module 3 uses data traceability 31, on-site inspection 32 and expert diagnosis 33 to determine whether the data is accurate.

Early warning module 3 is connected with alarm module 34, and alarm module 34 is connected with voice module 341, and alarm module 34 is connected with prompting module 342, and alarm module 34 is connected with network module 343, if information is accurate, then call alarm module 34, voice module 341 carries out Voice broadcast, the prompt module 342 reminds the user to adjust according to the data, the network module 343 transmits the data to the memory 41, if the information is wrong, the elimination result is fed back to the memory 41, the memory 41 updates the information processing module, and records the error case sample data Analyze, judge whether the standard value needs to be corrected according to the error information, and if necessary, feed the parameter back to the data processor through the standard management module.

Data storage module 4, comprises: memory 41, RAM411, ROM412 and cache memory 413, data storage module 4 is connected with memory 41, is connected with RAM411 in memory 41, is connected with ROM412 in memory 41, is connected with cache memory in memory 41 413, the data is transmitted to the data storage module 4, and the memory 41 stores the data, wherein the ROM412 is a read-only memory 41, which means that the memory 41 can only be read and cannot be written, so the data that does not need to be changed and needs to be stored can be written, and the RAM411 is Random access memory 41, that is, data can be read and written to memory 41 at any time under normal working conditions, so RAM 411 is used for storage most of the time, and cache memory 413 is a primary memory 41 that exists between the main memory and the CPU. Composed of static memory chips, the capacity is relatively small but the speed is much higher than that of the main memory, which is close to the speed of the CPU. Therefore, the more important data is stored in the cache memory 413, which improves the work efficiency. After the data is stored, it is convenient for later call and Processing, the host performs data exchange processing on the data in the memory 41 with the external device through the I/O interface, and communicates through the network adapter.

The data display module 5 includes: a data display terminal 51, a data chart analysis unit 511, a data text analysis unit 512, a data report generation unit 513, a data sending module 52, a WIFI communication module 521, a 5G communication module 522 and a Bluetooth communication module 523, The data display terminal 51 is connected with a data chart analysis unit 511, the data display terminal 51 is connected with a data text analysis unit 512, and the data display terminal 51 is connected with a data report generation unit 513. After the data storage is completed, the data display terminal 51 will Data display, the data display terminal 51 calls the data display module 5, and uses the data chart analysis unit 511 to process the data into a chart output, uses the data text analysis unit 512 to process the data into text output, and uses the data report generation unit 513 to process the data into The report output is provided to the user for review and analysis, and the real-time dynamic response to the data is convenient for the user to view.

The data display terminal 51 is connected with a data sending module 52, the data sending module 52 is connected with a WIFI communication module 521, the data sending module 52 is connected with a 5G communication module 522, and the data sending module 52 is connected with a Bluetooth communication module 523, the generated Information can be transmitted through the data sending module 52 , and data can be transmitted through the WIFI communication module 521 , 5G communication module 522 and Bluetooth communication module 523 .

Working principle: When using the multi-dimensional carbon emission monitoring and analysis system based on big data processing, first collect data through the data collection module 1, call the database 14 of the Environmental Protection Bureau to understand the regional coal, oil and natural gas consumption, and transmit the data to In the regional coal, oil and natural gas consumption acquisition module 11, the smart meter collects 15 regional electricity consumption, and transmits the data to the regional electricity consumption acquisition module 12, and uses the electric carbon coefficient calculation 16 to calculate the carbon emission content of regional electricity. Carbon dioxide emissions from electricity consumption (kg) = electricity consumption × 0.785, household natural gas carbon dioxide emissions (kg) = natural gas usage × 0.19, household tap water carbon dioxide emissions (kg) = tap water usage × 0.91, calculated data Transmission to the regional power carbon emission calculation module 13, through the data acquisition module 1 for data collection, the overall collection efficiency is greatly improved, making the data statistics complete and accurate, and can fully understand the carbon emissions of different regions, which is convenient for later data planning. The data is transmitted to the data analysis and processing module 2, the data is received by the data receiving module 21, and the data is processed by the carbon emission data AI processing module 22, wherein the carbon emission data AI processing module 22 includes the current carbon emission data unit 221, the predicted carbon emission data unit 222 and past carbon emissions data unit 223.

Therefore, the current carbon emission data can be compared with the past carbon emission data through the data prediction unit 23 to obtain predicted carbon emission data, which is convenient for users to adjust carbon emission according to the data situation. If there is a problem with the detected data judgment, it will be transmitted To the early warning module 3, the early warning module 3 uses data traceability 31, on-site investigation 32 and expert diagnosis 33 to judge whether the data is accurate, if the information is accurate, then call the alarm module 34, the voice module 341 performs voice broadcast, and the prompt module 342 reminds the user to Data adjustment, the network module 343 transmits the data to the memory 41, if the information is wrong, the elimination result is fed back to the memory 41, the memory 41 updates the information processing module, and records and analyzes the sample data of the error case, and judges whether it needs to be corrected according to the error information Standard value, if needed, the parameter is fed back to the data processor through the standard management module, the data is transmitted to the data storage module 4, and the memory 41 stores the data, wherein ROM412 is a read-only memory 41, which means that the memory 41 can only be read and cannot Write, so you can write data that does not need to be changed and needs to be stored. RAM411 is a random access memory 41, that is, data can be read and written to memory 41 at any time under normal working conditions, so RAM411 is used for storage most of the time, and cache memory 413 is the first-level memory 41 between the main memory and the CPU, which is composed of static memory chips. Its capacity is relatively small but its speed is much higher than that of the main memory, and it is close to the speed of the CPU.

Therefore, the more important data is stored in the cache memory 413, which improves the efficiency of the work. After the data is stored, it is convenient for later call and processing. The host computer performs data exchange processing with the data in the memory 41 through the I/O interface and the external device, and Carry out communication through network adapter, after data storage is finished, with data display by data display terminal 51, data display terminal 51 transfers data display module 5, and uses data chart analysis unit 511 to process data into chart output, uses data text analysis unit 512 Process the data into text output, use the data report generation unit 513 to process the data into a report output, provide it to the user for review and analysis, and react the data dynamically in real time, which is convenient for the user to view, and the generated information can be sent through the data The module 52 transmits data through the WIFI communication module 521, 5G communication module 522 and Bluetooth communication module 523. The content not described in detail in this description belongs to the prior art known to those skilled in the art.

Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments, or perform equivalent replacements for some technical features. Within the spirit and principles of the invention, any modifications, equivalent replacements, improvements, etc., shall be included in the protection scope of the present invention.

Claims (10)

1. A multi-dimensional carbon emission monitoring and analysis system based on big data processing, including: data acquisition module (1), data analysis and processing module (2), early warning module (3), data storage module (4) and data display module (5), characterized in that; The output end of the data acquisition module (1) is connected with a data analysis processing module (2), the output end of the data analysis processing module (2) is connected with an early warning module (3), and the output end of the early warning module (3) is connected with a A data storage module (4), the data display module (5) is connected to the output end of the data storage module (4). 2. A multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 1, characterized in that: said data acquisition module (1) includes: regional coal, oil and natural gas consumption acquisition module (11 ), regional power consumption collection module (12), regional power carbon emission calculation module (13), environmental protection bureau database (14), smart meter collection (15) and electric carbon coefficient calculation (16); The input end of the regional coal, oil and natural gas consumption acquisition module (11) is connected with an environmental protection bureau database (14). 3. A kind of multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 2, characterized in that: the input end of the area electricity consumption collection module (12) is connected with a smart meter collection (15), The input end of the regional electric carbon emission calculation module (13) is connected with an electric carbon coefficient calculation (16). 4. A kind of multidimensional carbon emission monitoring and analysis system based on big data processing according to claim 1, characterized in that: said data analysis processing module (2) includes: data receiving module (21), carbon emission data AI processing module (22), current carbon emission data unit (221), predicted carbon emission data unit (222), past carbon emission data unit (223) and data prediction unit (23); The data analysis and processing module (2) is connected with a data receiving module (21), and the data analysis and processing module (2) is connected with a data prediction unit (23). 5. A kind of multidimensional carbon emission monitoring analysis system based on big data processing according to claim 4, characterized in that: said data analysis processing module (2) is connected with carbon emission data AI processing module (22), so The carbon emission data AI processing module (22) is connected with a current carbon emission data unit (221), and the carbon emission data AI processing module (22) is connected with a predicted carbon emission data unit (222), and the carbon emission data AI processing The module (22) is connected with a past carbon emission data unit (223). 6. A multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 1, characterized in that: the early warning module (3) includes: data traceability (31), on-site investigation (32), Expert diagnosis (33), alarm module (34), voice module (341), prompt module (342) and network module (343); The early warning module (3) is connected with data tracing (31), the early warning module (3) is connected with on-site investigation (32), and the early warning module (3) is connected with expert diagnosis (33). 7. A kind of multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 6, characterized in that: the early warning module (3) is connected with an alarm module (34), and the alarm module (34) A voice module (341) is connected, a prompt module (342) is connected to the alarm module (34), and a network module (343) is connected to the alarm module (34). 8. A multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 1, characterized in that: the data storage module (4) includes: memory (41), RAM (411), ROM (412) and cache memory (413); The data storage module (4) is connected with a memory (41), the memory (41) is connected with a RAM (411), the memory (41) is connected with a ROM (412), and the memory (41) A cache memory (413) is connected. 9. A multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 1, characterized in that: the data display module (5) includes: a data display terminal (51), a data chart analysis unit (511), data text analysis unit (512), data report generation unit (513), data sending module (52), WIFI communication module (521), 5G communication module (522) and Bluetooth communication module (523); The data display terminal (51) is connected with a data chart analysis unit (511), the data display terminal (51) is connected with a data text analysis unit (512), and the data display terminal (51) is connected with a data A report generation unit (513). 10. A multi-dimensional carbon emission monitoring and analysis system based on big data processing according to claim 9, characterized in that: the data display terminal (51) is connected with a data sending module (52), and the data sending module A WIFI communication module (521) is connected to the module (52), a 5G communication module (522) is connected to the data sending module (52), and a Bluetooth communication module (523) is connected to the data sending module (52).

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