A community-level carbon benefit system and its operation method

Abstract

This invention provides a community-level carbon credit system and its operation method. The community-level carbon credit system includes a carbon emission reduction calculation module, a carbon credit incentive feedback module, a public welfare feedback and community collaboration module, and a system optimization and iteration module. These modules are sequentially connected to form a closed-loop operating system encompassing data collection, scientific calculation, incentive feedback, public welfare feedback, and optimization iteration. In this invention, by sequentially connecting the multi-source carbon data collection module, carbon emission reduction calculation module, carbon credit incentive feedback module, public welfare feedback and community collaboration module, and system optimization and iteration module, the system starts with data collection, proceeds through calculation, incentives, and feedback, and ultimately optimizes and iterates to feed back to each module, achieving self-improvement and continuous evolution of the operating mechanism.

Description

Technical Field

[0001] This invention belongs to the field of carbon credit technology, specifically relating to a community-level carbon credit system and its operation method. Background Technology

[0002] Currently, carbon inclusion, as an important means to promote public participation in achieving the "dual carbon" goal, has been piloted in several cities, mainly in two application scenarios: city-level and regional-level. Existing carbon inclusion systems mostly focus on macro-level carbon emission reduction accounting and trading at the city level, such as Shenzhen's "Low-Carbon Planet" carbon inclusion platform, which achieves automated collection and points-based incentives for citizens' low-carbon behaviors by connecting to multiple data sources. Some community pilots focus on single low-carbon behaviors, building simple points redemption models, such as the "Public Welfare Hall + Carbon Account" model created by Jin'an Community in Huli District, Xiamen, which combines offline public welfare halls with online carbon accounts to quantify and incentivize carbon reduction through waste sorting.

[0003] In existing technologies, the operation of carbon credit systems mostly relies on the basic process of "data collection - points distribution - rights redemption". Some systems introduce blockchain technology to make points traceable, introduce smart contracts to automate accounting, and some community pilot projects combine public welfare assistance to build a simple circular model.

[0004] Existing city-level carbon credit systems fail to adequately adapt to the micro-level scenarios of communities, neglecting the diversity of residents' low-carbon behaviors and the personalized needs of community governance, making precise adaptation difficult. The operational models of single-community pilot projects are fragmented, lacking standardized operating mechanisms and hindering replication and scalability. Furthermore, existing community-level carbon credit systems often employ a single accounting standard, failing to develop differentiated accounting models tailored to the specific characteristics of each community. Carbon emission reduction calculations lack professional support, and some systems lack authoritative calculation teams and scientific formulas, resulting in unreliable results. Additionally, inconsistent accounting rules across different communities hinder cross-community comparisons and aggregation of carbon emission reductions.

[0005] Therefore, there is an urgent need to design a community-level carbon benefit system to solve the current technical problems. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a community-level carbon benefit system and its operation method, which achieves precise adaptation to community scenarios, scientific calculation of carbon emission reductions, and closed-loop operation processes. At the same time, it improves the system's replicability and sustainable operation capabilities, promotes the large-scale promotion of community-level carbon benefits, and helps to implement low-carbon actions for all citizens.

[0007] The technical solution of this invention is: a community-level carbon benefit system, comprising: The multi-source carbon data acquisition module is used to collect low-carbon behavior data of community residents, and adopts a triple verification mechanism of device verification, intelligent review and manual review to verify and de-identify the low-carbon behavior data. The carbon emission reduction calculation module is connected to the multi-source carbon data acquisition module and is used to automatically calculate the verified low-carbon behavior data into carbon emission reductions through smart contracts according to the preset community-level carbon emission reduction calculation standards and differentiated calculation models. The carbon benefit incentive feedback module is connected to the carbon emission reduction calculation module. It is used to convert the carbon emission reduction into carbon credits and distribute incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. The public welfare feedback and community collaboration module is connected to the carbon inclusive incentive feedback module. It is used to establish a community charity fund and inject the carbon credit exchange revenue and the community carbon emission reduction trading revenue into the community charity fund for targeted use in community public welfare undertakings, and to build a multi-party collaboration mechanism among the government, community, enterprises and residents. The system optimization and iteration module is connected to the public welfare feedback and community collaboration module. It is used to dynamically optimize the system operation mechanism based on system operation data and resident feedback information, and to form standardized operation specifications. The multi-source carbon data acquisition module, carbon emission reduction calculation module, carbon benefit incentive feedback module, public welfare support and community collaboration module, and system optimization and iteration module are connected in sequence to form a closed-loop operating system of data acquisition, scientific calculation, incentive feedback, public welfare support, and optimization and iteration.

[0008] Furthermore, the multi-source carbon data acquisition module includes: The offline data collection unit includes IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of smart meters, weight sensors, image recognition sensors, and QR code scanning recorders, which are used to collect residents' low-carbon behavior data in real time and upload it through IoT technology. The online data collection unit is used to connect to one or more third-party data sources, such as public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms, to automatically capture residents' online low-carbon behavior data and support residents to upload low-carbon behavior certificates independently, and verify their authenticity through image recognition technology. The data verification unit is used to perform a triple verification mechanism of device verification, intelligent auditing and manual review. The intelligent auditing verifies the data format and authenticity of the vouchers based on preset verification rules, and uses data usability-invisibility technology to de-identify residents' personal information.

[0009] Furthermore, the carbon emission reduction calculation module includes: The accounting standard setting unit is used to combine national and local carbon inclusiveness methodologies to develop community-level carbon emission reduction accounting standards and clarify the carbon emission factors and accounting formulas for various low-carbon behaviors. A differentiated accounting model unit is used to construct differentiated accounting models for different types of low-carbon behaviors. The accounting model includes: The waste sorting accounting model uses the following formula: Carbon emission reduction = Waste disposal volume × Carbon emission factor of the corresponding waste type; The green travel accounting model uses the following formula: Carbon emission reduction = Travel distance × Carbon emission factor of the corresponding travel mode; The energy conservation accounting model has the following formula: Carbon emission reduction = Energy conservation × Carbon emission factor of the corresponding energy source; The smart contract execution unit is used to embed the carbon emission factor library and calculation formula into the smart contract code, receive data in real time, and automatically calculate carbon emission reductions.

[0010] Furthermore, the carbon inclusive incentive feedback module includes: The carbon credit conversion unit is used to convert residents' personal carbon emission reductions into carbon credits at an adjustable preset ratio and store them in residents' personal carbon accounts. The multi-level incentive unit is used to establish a two-tier incentive mechanism that combines immediate incentives with long-term accumulation, and provides multiple channels for redeeming rights, including rights to redeem living materials, rights to redeem services, and rights to make charitable donations; the multi-level incentive unit also has a tiered incentive mechanism to issue additional incentives based on the residents' carbon credit accumulation level. The feedback collection unit is used to collect residents' opinions and suggestions on the system operation and incentive system, and to generate feedback reports regularly; The visualization update unit is used to periodically update the data of the offline visualization interaction device.

[0011] Furthermore, the public welfare feedback and community collaboration module includes: The public welfare feedback unit is used to inject the income from residents' carbon credits and the revenue from the community's carbon emission reduction trading into the community charity fund pool according to a preset ratio. The multi-party collaborative unit is used to clarify the rights and responsibilities of the government as the rule-maker and ecological maintainer, the community as the leader, enterprises as participants, and residents as practitioners. The government provides subsidies for the initial construction funds to build a collaborative operation model.

[0012] Furthermore, the system optimization iteration module includes: The data monitoring and analysis unit is used to monitor the operating data of each module in real time and to identify system operational shortcomings through big data analysis technology. The dynamic optimization unit is used to dynamically adjust the system operation mechanism based on data analysis results and resident feedback. The adjustment includes at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing the data collection method, and updating the carbon emission reduction accounting standard. Standardized iterative units are used to organize the optimized operating mechanisms and implementation processes into replicable operating specifications.

[0013] The operation method of a community-level carbon credit system, applied to any of the above-mentioned community-level carbon credit systems, includes the following steps: Step S1: Collect low-carbon behavior data of community residents through a multi-source carbon data acquisition module, and use a triple verification mechanism to verify and de-identify the data; Step S2: The carbon emission reduction calculation module automatically calculates the verified data into carbon emission reductions based on the preset community-level carbon emission reduction calculation standards and differentiated calculation models through smart contracts. Step S3: The carbon benefit incentive feedback module converts the carbon emission reductions into carbon credits and distributes incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. Step S4: The public welfare feedback and community collaboration module establishes a community charity fund, injects carbon credit exchange revenue and community carbon emission reduction trading revenue into the community charity fund for community public welfare undertakings, and runs a multi-party collaboration mechanism; Step S5: The system optimization and iteration module dynamically optimizes the system operation mechanism based on system operation data and resident feedback, and forms standardized operation specifications; Steps S1 to S5 are executed sequentially to form a closed-loop operation process of data collection, scientific accounting, incentive feedback, public welfare support, and optimization iteration.

[0014] Further, step S1 includes: Step S11: Collect residents' low-carbon behavior data in real time through IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of the following: smart meters, weight sensors, image recognition sensors, and barcode scanning and recording devices. Step S12: Connect to one or more third-party data sources, such as public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms, to automatically capture residents' online low-carbon behavior data, and support residents to upload low-carbon behavior certificates independently, and verify their authenticity through image recognition technology. Step S13: The authenticity of the collected data is verified by a triple verification mechanism of device verification, intelligent audit and manual review. The intelligent audit is based on preset verification rules to verify the data format and authenticity of the vouchers, and the personal information of residents is anonymized using data usability-invisibility technology.

[0015] Further, step S3 includes: Step S31: Convert individual carbon emission reductions into carbon credits according to an adjustable preset ratio and deposit them into individual carbon accounts. Step S32: Establish a two-tiered incentive mechanism that combines immediate incentives with long-term accumulation, and provide multiple channels for redeeming rights, including rights to redeem living supplies, rights to redeem services, and rights to make charitable donations; set up a tiered incentive mechanism to issue additional incentives based on residents' carbon credit accumulation levels; Step S33: Collect residents' opinions and suggestions on the system operation and incentive system, and generate feedback reports regularly; Step S34: Update the data of the offline visual interactive device every 10 seconds.

[0016] Further, step S5 includes: Step S51: Monitor the operating data of each module in real time, and use big data analysis technology to identify system operational shortcomings; Step S52: Based on the data analysis results and resident feedback, dynamically adjust the system operation mechanism. The adjustment includes at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing the data collection method, and updating the carbon emission reduction accounting standard. Step S53: Organize the optimized operating mechanism and implementation process into replicable operating specifications.

[0017] The beneficial effects of this invention are: (1) In this invention, by sequentially connecting the multi-source carbon data acquisition module, carbon emission reduction accounting module, carbon inclusive incentive feedback module, public welfare feedback and community collaboration module and system optimization iteration module, the one-way and breakpoint operation mode in the prior art is changed, forming a complete operation chain of data-driven and feedback closed loop. The system starts from data acquisition, goes through accounting, incentive and feedback, and finally feeds back to each module through optimization iteration, realizing the self-improvement and continuous evolution of the operation mechanism; (2) The carbon emission reduction accounting module provides quantitative basis for incentive feedback, the carbon inclusive incentive feedback module accumulates funds for public welfare feedback, and public welfare feedback improves residents’ participation, thereby feeding back into the data collection link, forming a positive cycle and enhancing the system’s sustainable operation capability in the community scenario; (3) The multi-source carbon data acquisition module adopts a triple verification mechanism to ensure the authenticity and accuracy of the source data; the carbon emission reduction calculation module uses smart contracts for automated calculation to eliminate human intervention factors; the system optimization and iteration module dynamically adjusts according to the operating data, so that the system can adapt to the actual changes in the community and maintain long-term stable and reliable operation. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the community-level carbon benefit system in this invention.

[0019] Figure 2 This is a flowchart of the operation method of the community-level carbon benefit system in this invention.

[0020] Figure 3 This is a flowchart of the operation of the multi-source carbon data acquisition module in this invention. Detailed Implementation

[0021] Various exemplary embodiments of the invention will now be described in detail with reference to the accompanying drawings. The descriptions of the exemplary embodiments are merely illustrative and are in no way intended to limit the invention or its application or use. The invention can be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to make the invention thorough and complete, and to fully express the scope of the invention to those skilled in the art. It should be noted that, unless otherwise specifically stated, the relative arrangement of components and steps, the composition of materials, numerical expressions, and values ​​set forth in these embodiments should be interpreted as merely exemplary and not as limiting.

[0022] The terms "first," "second," and similar words used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different parts. Words such as "including" or "comprising" mean that the element preceding the word encompasses the element listed after it, without excluding the possibility of encompassing other elements. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0023] like Figure 1 As shown, a community-level carbon benefit system is disclosed, comprising: Multi-source carbon data acquisition module 1 is used to collect low-carbon behavior data of community residents, and adopts a triple verification mechanism of equipment verification, intelligent review and manual review to verify and de-identify the low-carbon behavior data. The carbon emission reduction calculation module 2 is connected to the multi-source carbon data acquisition module 1. It is used to automatically calculate the verified low-carbon behavior data into carbon emission reductions through smart contracts according to the preset community-level carbon emission reduction calculation standards and differentiated calculation models. The carbon benefit incentive feedback module 3 is connected to the carbon emission reduction calculation module 2. It is used to convert carbon emission reductions into carbon credits and distribute incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. The public welfare feedback and community collaboration module 4 is connected to the carbon benefit incentive feedback module 3. It is used to establish a community charity fund and inject the carbon credit exchange revenue and the community carbon emission reduction trading revenue into the community charity fund for targeted use in community public welfare undertakings, and to build a multi-party collaboration mechanism among the government, community, enterprises and residents. System optimization and iteration module 5, connected to public welfare feedback and community collaboration module 4, is used to dynamically optimize the system operation mechanism based on system operation data and resident feedback information, and to form standardized operation specifications; The multi-source carbon data acquisition module 1, carbon emission reduction accounting module 2, carbon inclusive incentive feedback module 3, public welfare feedback and community collaboration module 4, and system optimization and iteration module 5 are connected in sequence to form a closed-loop operating system of data acquisition, scientific accounting, incentive feedback, public welfare feedback, and optimization and iteration.

[0024] In the above embodiment, the system starts with the multi-source carbon data acquisition module 1. After collecting residents' low-carbon behavior data, this module transmits the verified and processed data to the carbon emission reduction calculation module 2. After completing the carbon emission reduction calculation, the carbon emission reduction calculation module 2 transmits the calculation result to the carbon benefit incentive feedback module 3. The carbon benefit incentive feedback module 3 distributes incentives and collects feedback based on the calculation result, and then transmits the relevant data to the public welfare feedback and community collaboration module 4. After completing the fund collection and collaborative operation, the public welfare feedback and community collaboration module 4 transmits the system operation status data to the system optimization iteration module 5. The optimization iteration module ultimately feeds back the optimization results to the front-end modules, forming a closed loop. The closed-loop operation mechanism of this system includes a data closed loop and a value closed loop. The data closed loop starts from data collection, then to calculation, then to incentives and feedback, and finally guides a new round of data collection through optimization iteration, forming a data-driven closed-loop optimization. The value loop involves residents earning carbon credits through low-carbon behaviors, which are then exchanged for public welfare funds. These funds are used for community governance and resident services, and the improvement of the community environment further motivates residents to participate in low-carbon behaviors, thus forming a closed loop of value transmission.

[0025] Specifically, the multi-source carbon data acquisition module 1, as the input port of the closed loop, is responsible for solving the problems of where the data comes from and whether the data is reliable. Its triple verification mechanism ensures the data quality at the starting point of the closed loop.

[0026] The carbon emission reduction accounting module 2 serves as the quantification hub, transforming raw behavioral data into measurable and tradable carbon emission reductions. This solves the problem of how to quantify the value of behavior and provides a scientific basis for subsequent incentives.

[0027] The Carbon Benefit Incentive Feedback Module 3 serves as a value conversion interface, transforming carbon emission reductions into carbon credits and rights that residents can perceive, while also collecting resident feedback, thus solving the problems of how to transfer value and how to obtain demand.

[0028] Module 4, which focuses on public welfare feedback and community collaboration, acts as a value amplifier, extending personal incentives to the level of community public welfare. It also clarifies the rights and responsibilities of multiple parties, solving the problems of how to amplify value and how to ensure the sustainability of the system.

[0029] System optimization and iteration module 5, as the closed-loop control center, dynamically adjusts system parameters based on full-process operation data, solving the problem of how the system adapts to changes and how it improves itself.

[0030] This system, by sequentially connecting the multi-source carbon data acquisition module 1, carbon emission reduction calculation module 2, carbon benefit incentive feedback module 3, public welfare feedback and community collaboration module 4, and system optimization and iteration module 5, changes the unidirectional, breakpoint operation mode of existing technologies, forming a complete operation chain driven by data and with a feedback loop. Starting with data acquisition, the system goes through calculation, incentives, and feedback, ultimately optimizing and iterating to feed back to each module, achieving self-improvement and continuous evolution of the operation mechanism. The carbon emission reduction calculation module 2 provides quantitative basis for incentive feedback, the carbon benefit incentive feedback module 3 accumulates funds for public welfare feedback, and public welfare feedback further increases resident participation, thus feeding back to the data acquisition stage, forming a positive cycle and enhancing the system's sustainable operation capability in community scenarios. The multi-source carbon data acquisition module 1 adopts a triple verification mechanism to ensure the authenticity and accuracy of the source data; the carbon emission reduction calculation module 2 uses smart contracts for automated calculation, eliminating human intervention factors; and the system optimization and iteration module 5 dynamically adjusts according to operational data, enabling the system to adapt to actual changes in the community and maintain long-term stable and reliable operation.

[0031] In some embodiments, the multi-source carbon data acquisition module includes: The offline data collection unit includes IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of the following: smart meter 11, weight sensor 12, image recognition sensor 13, and barcode scanning and recording device 14. These devices are used to collect residents' low-carbon behavior data in real time and upload it through IoT technology. The online data collection unit is used to connect to one or more third-party data sources from public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms. It automatically captures residents' online low-carbon behavior data and supports residents to upload low-carbon behavior certificates independently, and verifies their authenticity through image recognition technology. The data verification unit is used to perform a triple verification mechanism of equipment verification, intelligent auditing and manual review. The intelligent auditing verifies the data format and authenticity of the vouchers based on preset verification rules, and uses data usability-invisibility technology to de-identify residents' personal information.

[0032] Specifically, the offline data collection unit constructs a physical data collection network by deploying IoT terminal devices within the community. Smart meters such as electricity meters, water meters, and gas meters monitor residents' energy consumption data in real time and calculate energy savings through differential calculations; weight sensors such as kitchen waste weight sensors and recyclable material weighing devices automatically weigh and record residents' waste disposal; image recognition sensors, such as those displaying photos of recycled items and records of participation in environmental activities, are used to identify low-carbon behavior credentials; and QR code check-in recorders, such as those for walking check-ins and volunteer activity sign-ins, are used by residents to actively record specific low-carbon behaviors. The data collected by various devices is uploaded to the system backend in real time via IoT communication modules, forming a digital record of offline behavior.

[0033] The online data collection unit connects to third-party data sources such as public transportation platforms (bus and subway card systems), shared bicycle platforms, and environmental protection company platforms via API interfaces to automatically acquire residents' low-carbon behavior data in online scenarios such as travel and consumption. Simultaneously, the system allows residents to independently upload low-carbon behavior vouchers, such as receipts for environmentally friendly products and certificates of donation of used goods, through mini-programs and other front-end platforms. After uploading, the system uses image recognition technology to verify the authenticity of the vouchers, identifying key information such as time, amount, and behavior type and comparing it with user declarations to prevent fraudulent uploads.

[0034] The data verification unit includes a built-in self-verification module in the IoT terminal device to verify the rationality of the collected data, determining whether the data is within a preset threshold range and whether there are any abrupt changes or anomalies. Only data that passes verification can be uploaded. The system backend automatically reviews online-captured data and data uploaded by residents based on preset verification rules. Verification rules include data format verification, voucher authenticity identification, and behavioral logic verification. Data that passes the review proceeds to the next stage; data that fails is marked as abnormal. For abnormal data that the intelligent review cannot determine, the system pushes it to community staff for manual review, and the review result serves as the final judgment. During the verification process, the data verification unit simultaneously anonymizes residents' personal information. Employing a data usability-but-not-visible technology, personal identity information is physically isolated or encrypted from carbon account data. This ensures that the system can only access anonymized behavioral data during calculations and incentive processes, and cannot associate it with specific individual identities, thus protecting privacy while ensuring data usability.

[0035] In some embodiments, the multi-source carbon data acquisition module 1 further includes a mobile auxiliary device 16; the mobile auxiliary device 16 is used to assist in collecting low-carbon behaviors that cannot be captured by IoT devices, such as donations of old items and participation in community environmental volunteer activities, through methods such as taking pictures and OCR recognition.

[0036] In some embodiments, the community-level carbon credit system further includes a visual interactive device 7 and a data storage device 6. The visual interactive device 7 is connected to the carbon emission reduction calculation module 2, the carbon credit incentive feedback module 3, the public welfare feedback and community collaboration module 4, and the system optimization and iteration module 5, respectively, to display data from the visual interactive device, allowing residents' carbon reduction behaviors to be seen, recorded, and incentivized, thereby enhancing residents' sense of participation. The data storage device 6 is connected to the carbon emission reduction calculation module 2, the carbon credit incentive feedback module 3, the public welfare feedback and community collaboration module 4, and the system optimization and iteration module 5, respectively, for data storage.

[0037] In some embodiments, the carbon emission reduction calculation module 2 includes: The accounting standard setting unit is used to combine national and local carbon inclusiveness methodologies to develop community-level carbon emission reduction accounting standards and clarify the carbon emission factors and accounting formulas for various low-carbon behaviors. The differentiated accounting model unit is used to build differentiated accounting models for different types of low-carbon behaviors. The accounting models include: The waste sorting accounting model uses the following formula: Carbon emission reduction = Waste disposal volume × Carbon emission factor of the corresponding waste type; The green travel accounting model uses the following formula: Carbon emission reduction = Travel distance × Carbon emission factor of the corresponding travel mode; The energy conservation accounting model has the following formula: Carbon emission reduction = Energy conservation × Carbon emission factor of the corresponding energy source; The smart contract execution unit is used to embed the carbon emission factor library and calculation formula into the smart contract code, receive data in real time, and automatically calculate carbon emission reductions.

[0038] Specifically, the accounting standard setting unit develops accounting standards applicable to this system based on national and local carbon credit methodology and considering the characteristics of the community scenario. This includes: for waste sorting behavior, referencing local residential community waste sorting carbon credit methodology to determine the carbon emission factors for various types of waste such as kitchen waste and recyclables; for green travel behavior, referencing local low-carbon public transportation carbon credit methodology to determine the carbon emission factors for different modes of transportation such as subway, bus, walking, and cycling; and for energy conservation behavior, referencing local power grid, water supply, and gas supply standards to determine the carbon emission factors for various energy sources such as electricity, water, and gas. This unit stores these standards in a structured manner, forming a carbon emission factor library that can be accessed by other units.

[0039] The waste sorting and accounting model is based on the principles of mass conservation and carbon emission reduction coefficients, multiplying the amount of various types of waste disposed of by residents by the corresponding carbon emission factor. Specifically, the carbon emission factor for kitchen waste is referenced to the emission reduction efficiency of on-site treatment equipment, while the carbon emission factor for recyclables is referenced to the carbon emissions from virgin material production avoided through the recycling of the corresponding materials. This model is applicable to scenarios such as recyclable waste collection and on-site kitchen waste treatment.

[0040] The green travel accounting model is based on the principle of travel mode substitution, multiplying the mileage traveled by residents choosing low-carbon travel modes by the corresponding carbon emission factor. The carbon emission factor reflects the emission reduction per unit mileage of that travel mode relative to the benchmark travel mode. The carbon emission factors for subways and buses are calculated based on the energy consumption and emissions per passenger trip of the public transportation system, while walking and cycling are calculated as zero-carbon emissions. This model is applicable to scenarios such as public transportation, subway travel, cycling, and walking.

[0041] The energy conservation accounting model is based on the principle of energy saving, multiplying the electricity, water, and gas savings of residents by the corresponding carbon emission factors. The savings are calculated by comparing historical energy consumption data for the same period or regional average energy consumption data, while the carbon emission factors are determined based on the unit emission intensity of the local energy supply structure. This model is applicable to scenarios involving saving electricity, water, and gas.

[0042] The above model is encapsulated in a formulaic form and automatically calculates carbon emission reductions after receiving behavioral parameters from the data acquisition module.

[0043] The smart contract execution unit writes the carbon emission factor library and differentiated accounting formula into smart contract code and deploys it in the system backend. Its operation process is as follows: Once the data acquisition module completes data verification and uploads the data, the system triggers the execution of the smart contract. Smart contracts automatically match the corresponding accounting model based on the behavior type identifier; The smart contract reads the carbon emission factor corresponding to the behavior type from the carbon emission factor library; Smart contracts input behavioral parameters into the calculation formula to complete the real-time calculation of carbon emission reductions; The calculation results are stored in residents' personal carbon accounts on the one hand, and summarized in the community's cumulative carbon emission reduction database on the other. Smart contracts simultaneously record the original data, the called models and factors, the calculation process, and the calculation results in the blockchain or system logs, enabling the accounting process to be traceable and verifiable.

[0044] In some embodiments, the carbon benefit incentive feedback module 3 includes: The carbon credit conversion unit is used to convert residents' personal carbon emission reductions into carbon credits at an adjustable preset ratio and store them in residents' personal carbon accounts. The multi-tiered incentive unit is used to establish a two-tiered incentive mechanism that combines immediate incentives with long-term accumulation, and provides multiple channels for redeeming rights, including rights to redeem living materials, rights to redeem services, and rights to make charitable donations; the multi-tiered incentive unit also has a tiered incentive mechanism to issue additional incentives based on the residents' carbon credit accumulation level. The feedback collection unit is used to collect residents' opinions and suggestions on the system operation and incentive system, and to generate feedback reports regularly; The visualization update unit is used to periodically update the data of the offline visualization interaction device.

[0045] Specifically, the carbon credit conversion unit receives individual carbon emission reduction data from the carbon emission reduction calculation module and converts the carbon emission reductions into carbon credits according to a preset conversion ratio. The preset conversion ratio can be configured based on the actual situation of the community, for example, converting 1 kg CO2 emission reduction to 1 carbon credit. This ratio is not fixed and can be dynamically adjusted by the system operator based on factors such as incentive intensity requirements, government subsidy budgets, and resident participation. After conversion, the carbon credits are automatically deposited into the resident's personal carbon account. The carbon account records the real-time balance, increase / decrease details, and validity period of the credits, which residents can check at any time via a mini-program.

[0046] A multi-tiered incentive system constructs a three-tiered progressive incentive structure. Each time a resident completes a low-carbon activity, the system sends a notification simultaneously with the crediting of carbon points, creating an immediate link between the activity and the reward, reinforcing positive feedback. Points continuously accumulate in residents' carbon accounts, forming a historical record of their low-carbon behavior and achievements, cultivating a habit of sustained participation. The system sets multiple threshold levels for each point level; when residents accumulate points to reach different levels, additional incentives are automatically issued, including doubled points, exclusive benefits, honorary badges, and community recognition. This tiered incentive system generates increasing marginal returns for long-term participation, motivating residents to strive for higher levels.

[0047] Regarding the redemption of benefits, a multi-tiered incentive system establishes an integrated online and offline redemption platform. Online, a redemption mall is set up through a community mini-program, allowing residents to browse and redeem various benefits. Offline, a redemption area is set up in the community's public welfare center, making it convenient for elderly residents unfamiliar with smart devices to participate. Redeemable benefits are divided into three categories: daily necessities, service benefits, and charitable donations. The system collaborates with local businesses, who provide some of the redeemable benefits, enriching the redemption options and reducing system operating costs.

[0048] The feedback collection unit has set up a dedicated feedback portal in the resident-facing mini-program, allowing residents to submit opinions and suggestions on system operation, incentive system, types of benefits, and redemption experience in the form of text, images, etc. The system backend categorizes, stores, and tags the feedback information, and regularly analyzes it together with the technical team to identify frequently occurring issues and common needs, generating structured feedback reports. These reports serve as input for system optimization and iteration modules, and also partially disclose content to residents, fostering a transparent and interactive relationship.

[0049] The visualization update unit connects to offline interactive visualization devices, retrieving the latest resident carbon account data, community cumulative carbon emission reduction data, and points redemption leaderboard from the system backend at preset intervals (e.g., every 10 seconds), driving the visualization devices to refresh the display. This high-frequency update ensures that the offline display content remains synchronized with online data, allowing residents to see their own carbon reduction achievements and the overall community progress in real time while engaging in activities in community public spaces, enhancing their sense of participation and community identity. The visualization display can include real-time rankings of individual points, community carbon emission reduction progress, and low-carbon behavior heatmaps, transforming data into intuitive visual information and increasing residents' awareness and willingness to participate in low-carbon behaviors.

[0050] In some embodiments, the public welfare feedback and community collaboration module 4 includes: The public welfare feedback unit is used to inject the income from residents' carbon credits and the revenue from the community's carbon emission reduction trading into the community charity fund pool according to a preset ratio. The multi-party collaborative unit is used to clarify the rights and responsibilities of the government as the rule-maker and ecological maintainer, the community as the leader, enterprises as participants, and residents as practitioners. The government provides subsidies for the initial construction funds to build a collaborative operation model.

[0051] Specifically, the funding sources for the public welfare feedback unit include two aspects. First, the income from residents' carbon credit redemption. When residents use carbon credits to redeem rights, the system transfers the corresponding funds to the fund pool according to the value of the redeemed rights, rather than the rights provider collecting the funds directly. Second, the revenue from community carbon emission reduction trading. After the system aggregates the community's cumulative carbon emission reductions, it sells them to enterprises with compliance requirements through the carbon trading platform, and the transaction revenue is injected into the fund pool according to a preset ratio.

[0052] The funding injection ratio can be preset to a fixed value. The system will automatically deduct funds from the carbon credit redemption process and carbon trading revenue based on this ratio and transfer them to a dedicated community charity fund account. The ratio setting needs to balance the intensity of incentives with the strength of philanthropic feedback, ensuring both the attractiveness of individual incentives for residents and the sustainable accumulation of charitable funds.

[0053] The funds in the fund pool are specifically used for community public welfare undertakings, including but not limited to assisting disadvantaged families in the area, rewarding outstanding students, carrying out community environmental protection publicity, improving community environmental infrastructure, and organizing community public welfare activities. The use of funds is led by the community and decided through open and transparent procedures to ensure the rational use of public welfare funds and positive social benefits.

[0054] Residents earn points for participating in low-carbon behaviors, which can be redeemed for public welfare funds. These funds are used for community public welfare projects, and the improvement of these projects enhances residents' sense of belonging to the community, further stimulating their enthusiasm for participating in low-carbon behaviors, thus creating a positive cycle.

[0055] The multi-party collaborative unit establishes a systematic and institutionalized collaborative operation model by clarifying the rights, responsibilities, and cooperation methods of the four main parties. The government's responsibilities include issuing policies to support the construction of community-level carbon credit systems and incorporating carbon credits into local dual-carbon work systems; formulating carbon emission reduction accounting standards and trading rules to provide a legal basis for system operation; providing initial construction funding subsidies to lower the system's startup threshold; and supervising and evaluating system operation to guide its standardized operation. The community's responsibilities include being responsible for the system's implementation, coordinating resources such as venues and personnel; building offline public service centers, deploying visual interactive equipment, and improving offline service facilities; organizing low-carbon activities, mobilizing residents to participate, and increasing resident participation rates; collecting resident feedback and coordinating solutions to practical problems encountered during operation; and managing community charitable funds to ensure the rational use of public welfare funds. Enterprises can participate in three ways: first, environmental protection companies, providing IoT terminal equipment, carbon emission reduction calculation services, and technical support, gaining brand exposure and market opportunities through participation; second, rights-providing merchants, such as supermarkets, convenience stores, and public transportation companies, offering redemption rights and gaining customer traffic and brand exposure through the system; and third, carbon trading companies, participating in community carbon emission reduction trading and purchasing carbon reductions for their own compliance or carbon neutrality. Residents' responsibilities include participating in various low-carbon activities to accumulate carbon credits; using credits to redeem rights and enjoy the benefits of low-carbon living; participating in community public welfare activities and contributing to community welfare; and providing feedback and suggestions through feedback channels to participate in system optimization.

[0056] In some embodiments, the system optimization iteration module 5 includes: The data monitoring and analysis unit is used to monitor the operating data of each module in real time and to identify system operational shortcomings through big data analysis technology. The dynamic optimization unit is used to dynamically adjust the system operation mechanism based on data analysis results and resident feedback. The adjustments include at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing the data collection method, and updating the carbon emission reduction accounting standard. Standardized iterative units are used to organize the optimized operating mechanisms and implementation processes into replicable operating specifications.

[0057] Specifically, the data monitoring and analysis unit sets up monitoring nodes in the system backend to collect and store operational data from each module in real time. The monitored data includes: resident participation rate, distribution of low-carbon behavior types, carbon emission reduction calculation data, points redemption data, and feedback data. The unit employs big data analytics techniques such as cluster analysis, association rule mining, and time series prediction to deeply analyze the monitoring data and identify system operational weaknesses. For example, if analysis reveals that the participation rate for a certain type of low-carbon behavior is significantly lower than other behaviors, or that the redemption rate for a certain type of benefit is extremely low, the system automatically marks it as an item requiring optimization.

[0058] The dynamic optimization unit generates and implements optimization plans based on the diagnostic results of the data monitoring and analysis unit and residents' opinions and suggestions from the feedback collection unit. When the participation rate of a certain type of low-carbon behavior is low, the conversion ratio of that behavior is appropriately increased to enhance the incentive intensity; when too many system points are issued, leading to increased redemption pressure, the conversion ratio is appropriately reduced to balance incentive costs. Based on the rights and interests reflected in residents' feedback, new redemption categories are added, and rights and interests with low redemption rates are removed to maintain the attractiveness of redemption rights. To address issues such as blind spots in data collection or insufficient data accuracy, data collection strategies are adjusted, such as increasing the deployment points of IoT terminal devices, optimizing image recognition algorithms, and adjusting the frequency of third-party data integration. In accordance with changes in national and local policies, the carbon emission factor database and calculation formulas are updated in a timely manner to ensure the compliance and scientific nature of the calculation results. After the optimization plan is confirmed by the system operator, it is issued and implemented through the backend configuration center, taking effect without code modification.

[0059] The standardized iterative unit structures and organizes the optimization results generated by the dynamic optimization unit into standardized operating specifications. These specifications include: data collection specifications, accounting standards, incentive rules, feedback mechanisms, and optimization processes. The operating specifications are output in text form and can be stored in the system knowledge base or created as a separate document for other communities to reference when replicating and promoting them. Simultaneously, the standardized iterative unit feeds the specifications back to the data monitoring and analysis unit, forming new monitoring baselines and achieving continuous closed-loop optimization of system operation.

[0060] like Figure 2 As shown, a method for operating a community-level carbon credit system is disclosed, applicable to the community-level carbon credit system in any of the above embodiments, including the following steps: Step S1: Collect low-carbon behavior data of community residents through a multi-source carbon data acquisition module, and use a triple verification mechanism to verify and de-identify the data; Step S2: The carbon emission reduction calculation module automatically calculates the verified data into carbon emission reductions based on the preset community-level carbon emission reduction calculation standards and differentiated calculation models through smart contracts. Step S3: The carbon benefit incentive feedback module converts carbon emission reductions into carbon credits and distributes incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. Step S4: The public welfare feedback and community collaboration module establishes a community charity fund, injects carbon credit redemption revenue and community carbon emission reduction trading revenue into the community charity fund for community public welfare undertakings, and runs a multi-party collaboration mechanism; Step S5: The system optimization and iteration module dynamically optimizes the system operation mechanism based on system operation data and resident feedback, and forms standardized operation specifications; Steps S1 to S5 are executed sequentially, forming a closed-loop operation process of data collection, scientific accounting, incentive feedback, public welfare support, and optimization iteration.

[0061] Starting from the data collection point, the data sequentially passes through the accounting, incentive, and feedback stages, finally reaching the optimization stage, completing one full process cycle. The optimization results of step S5 are then used to adjust system configurations and have a reverse effect on steps S1 to S4. For example, adjusting data collection strategies, updating accounting standards, optimizing incentive rules, and adjusting feedback ratios can further optimize the next round of process operation. As the process cycle is repeated continuously, the system's operational status is continuously optimized, resident participation gradually increases, and carbon emission reductions continue to grow, forming a self-reinforcing positive cycle.

[0062] In some embodiments, such as Figure 3 As shown, step S1 includes: Step S11: Collect residents' low-carbon behavior data in real time through IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of the following: smart meters, weight sensors, image recognition sensors, and barcode scanning and recording devices. Step S12: Connect to one or more third-party data sources, such as public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms, to automatically capture residents' online low-carbon behavior data, and support residents to upload low-carbon behavior certificates independently, and verify their authenticity through image recognition technology. Step S13: The authenticity of the collected data is verified by a triple verification mechanism of device verification, intelligent auditing and manual review. The intelligent auditing is based on preset verification rules to verify the data format and the authenticity of the vouchers, and the personal information of residents is anonymized using the data usability-invisibility technology.

[0063] Step S11 achieves automated collection of offline behavioral data through IoT terminal devices, while step S12 achieves automated capture of online behavioral data by connecting to third-party data sources and supporting self-upload. The combination of these two methods covers all scenarios of residents' daily low-carbon behaviors, avoiding data blind spots associated with single collection methods. Step S13 employs a triple verification mechanism of device verification, intelligent auditing, and manual review to ensure the collected data is rigorously checked at each level, effectively preventing data falsification and false alarms. Simultaneously, data usability-invisibility technology is used to anonymize residents' personal information, ensuring both data usability and protecting residents' privacy. The automated IoT collection in step S11 and the automated capture from third-party platforms in step S12 enable the system to primarily rely on automated collection, supplemented by manual uploading, significantly reducing the barrier to resident participation and the workload of community operations, while improving the efficiency and real-time nature of data collection.

[0064] In some embodiments, step S3 includes: Step S31: Convert individual carbon emission reductions into carbon credits according to an adjustable preset ratio and deposit them into individual carbon accounts. Step S32: Establish a two-tiered incentive mechanism that combines immediate incentives with long-term accumulation, and provide multiple channels for redeeming benefits, including the right to redeem living supplies, the right to redeem services, and the right to make charitable donations; set up a tiered incentive mechanism to issue additional incentives based on the residents' carbon credit accumulation level. Step S33: Collect residents' opinions and suggestions on the system operation and incentive system, and generate feedback reports regularly; Step S34: Update the data of the offline visual interactive device every 10 seconds.

[0065] In some embodiments, step S5 includes: Real-time monitoring of operational data from each module, and using big data analytics to identify system operational weaknesses; Based on data analysis results and resident feedback, the system operation mechanism will be dynamically adjusted, including at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing data collection methods, and updating carbon emission reduction accounting standards. The optimized operating mechanism and implementation process will be compiled into replicable operating specifications.

[0066] The various embodiments of the present invention have now been described in detail. To avoid obscuring the concept of the invention, some details known in the art have not been described. Those skilled in the art will fully understand how to implement the technical solutions disclosed herein based on the above description.

[0067] The embodiments described above only illustrate some implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A community-level carbon benefit system, characterized in that, include: The multi-source carbon data acquisition module is used to collect low-carbon behavior data of community residents, and adopts a triple verification mechanism of device verification, intelligent review and manual review to verify and de-identify the low-carbon behavior data. The carbon emission reduction calculation module is connected to the multi-source carbon data acquisition module and is used to automatically calculate the verified low-carbon behavior data into carbon emission reductions through smart contracts according to the preset community-level carbon emission reduction calculation standards and differentiated calculation models. The carbon benefit incentive feedback module is connected to the carbon emission reduction calculation module. It is used to convert the carbon emission reduction into carbon credits and distribute incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. The public welfare feedback and community collaboration module is connected to the carbon inclusive incentive feedback module. It is used to establish a community charity fund and inject the carbon credit exchange revenue and the community carbon emission reduction trading revenue into the community charity fund for targeted use in community public welfare undertakings, and to build a multi-party collaboration mechanism among the government, community, enterprises and residents. The system optimization and iteration module is connected to the public welfare feedback and community collaboration module. It is used to dynamically optimize the system operation mechanism based on system operation data and resident feedback information, and to form standardized operation specifications. The multi-source carbon data acquisition module, carbon emission reduction calculation module, carbon benefit incentive feedback module, public welfare support and community collaboration module, and system optimization and iteration module are connected in sequence to form a closed-loop operating system of data acquisition, scientific calculation, incentive feedback, public welfare support, and optimization and iteration.

2. The community-level carbon benefit system according to claim 1, characterized in that, The multi-source carbon data acquisition module includes: The offline data collection unit includes IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of smart meters, weight sensors, image recognition sensors, and QR code scanning recorders, which are used to collect residents' low-carbon behavior data in real time and upload it through IoT technology. The online data collection unit is used to connect to one or more third-party data sources, such as public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms, to automatically capture residents' online low-carbon behavior data and support residents to upload low-carbon behavior certificates independently, and verify their authenticity through image recognition technology. The data verification unit is used to perform a triple verification mechanism of device verification, intelligent auditing and manual review. The intelligent auditing verifies the data format and authenticity of the vouchers based on preset verification rules, and uses data usability-invisibility technology to de-identify residents' personal information.

3. The community-level carbon benefit system according to claim 1, characterized in that, The carbon emission reduction calculation module includes: The accounting standard setting unit is used to combine national and local carbon inclusiveness methodologies to develop community-level carbon emission reduction accounting standards and clarify the carbon emission factors and accounting formulas for various low-carbon behaviors. A differentiated accounting model unit is used to construct differentiated accounting models for different types of low-carbon behaviors. The accounting model includes: The waste sorting accounting model uses the following formula: Carbon emission reduction = Waste disposal volume × Carbon emission factor of the corresponding waste type; The green travel accounting model uses the following formula: Carbon emission reduction = Travel distance × Carbon emission factor of the corresponding travel mode; The energy conservation accounting model has the following formula: Carbon emission reduction = Energy conservation × Carbon emission factor of the corresponding energy source; The smart contract execution unit is used to embed the carbon emission factor library and calculation formula into the smart contract code, receive data in real time, and automatically calculate carbon emission reductions.

4. The community-level carbon benefit system according to claim 1, characterized in that, The carbon benefit incentive feedback module includes: The carbon credit conversion unit is used to convert residents' personal carbon emission reductions into carbon credits at an adjustable preset ratio and store them in residents' personal carbon accounts. The multi-level incentive unit is used to establish a two-tier incentive mechanism that combines immediate incentives with long-term accumulation, and provides multiple channels for redeeming rights, including rights to redeem living materials, rights to redeem services, and rights to make charitable donations; the multi-level incentive unit also has a tiered incentive mechanism to issue additional incentives based on the residents' carbon credit accumulation level. The feedback collection unit is used to collect residents' opinions and suggestions on the system operation and incentive system, and to generate feedback reports regularly; The visualization update unit is used to periodically update the data of the offline visualization interaction device.

5. The community-level carbon benefit system according to claim 1, characterized in that, The public welfare feedback and community collaboration module includes: The public welfare feedback unit is used to inject the income from residents' carbon credits and the revenue from the community's carbon emission reduction trading into the community charity fund pool according to a preset ratio. The multi-party collaborative unit is used to clarify the rights and responsibilities of the government as the rule-maker and ecological maintainer, the community as the leader, enterprises as participants, and residents as practitioners. The government provides subsidies for the initial construction funds to build a collaborative operation model.

6. The community-level carbon benefit system according to claim 1, characterized in that: The system optimization and iteration module includes: The data monitoring and analysis unit is used to monitor the operating data of each module in real time and to identify system operational shortcomings through big data analysis technology. The dynamic optimization unit is used to dynamically adjust the system operation mechanism based on data analysis results and resident feedback. The adjustment includes at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing the data collection method, and updating the carbon emission reduction accounting standard. Standardized iterative units are used to organize the optimized operating mechanisms and implementation processes into replicable operating specifications.

7. A method for operating a community-level carbon credit system, applied to the community-level carbon credit system according to any one of claims 1 to 6, characterized in that, Includes the following steps: Step S1: Collect low-carbon behavior data of community residents through a multi-source carbon data acquisition module, and use a triple verification mechanism to verify and de-identify the data; Step S2: The carbon emission reduction calculation module automatically calculates the verified data into carbon emission reductions based on the preset community-level carbon emission reduction calculation standards and differentiated calculation models through smart contracts. Step S3: The carbon benefit incentive feedback module converts the carbon emission reductions into carbon credits and distributes incentives to residents based on a multi-level incentive system, while collecting residents' feedback information. Step S4: The public welfare feedback and community collaboration module establishes a community charity fund, injects carbon credit exchange revenue and community carbon emission reduction trading revenue into the community charity fund for community public welfare undertakings, and runs a multi-party collaboration mechanism; Step S5: The system optimization and iteration module dynamically optimizes the system operation mechanism based on system operation data and resident feedback, and forms standardized operation specifications; Steps S1 to S5 are executed sequentially to form a closed-loop operation process of data collection, scientific accounting, incentive feedback, public welfare support, and optimization iteration.

8. The operation method of the community-level carbon benefit system according to claim 7, characterized in that, Step S1 includes: Step S11: Collect residents' low-carbon behavior data in real time through IoT terminal devices deployed in the community. The IoT terminal devices include at least one or more of the following: smart meters, weight sensors, image recognition sensors, and barcode scanning and recording devices. Step S12: Connect to one or more third-party data sources, such as public transportation platforms, shared bicycle platforms, and environmental protection enterprise platforms, to automatically capture residents' online low-carbon behavior data, and support residents to upload low-carbon behavior certificates independently, and verify their authenticity through image recognition technology. Step S13: The authenticity of the collected data is verified by a triple verification mechanism of device verification, intelligent audit and manual review. The intelligent audit is based on preset verification rules to verify the data format and authenticity of the vouchers, and the personal information of residents is anonymized using data usability-invisibility technology.

9. The operation method of the community-level carbon benefit system according to claim 7, characterized in that, Step S3 includes: Step S31: Convert individual carbon emission reductions into carbon credits according to an adjustable preset ratio and deposit them into individual carbon accounts. Step S32: Establish a two-tiered incentive mechanism that combines immediate incentives with long-term accumulation, and provide multiple channels for redeeming rights, including rights to redeem living supplies, rights to redeem services, and rights to make charitable donations; set up a tiered incentive mechanism to issue additional incentives based on residents' carbon credit accumulation levels; Step S33: Collect residents' opinions and suggestions on the system operation and incentive system, and generate feedback reports regularly; Step S34: Update the data of the offline visual interactive device every 10 seconds.

10. The operation method of the community-level carbon benefit system according to claim 7, characterized in that, Step S5 includes: Step S51: Monitor the operating data of each module in real time, and use big data analysis technology to identify system operational shortcomings; Step S52: Based on the data analysis results and resident feedback, dynamically adjust the system operation mechanism. The adjustment includes at least one or more of the following: adjusting the carbon credit conversion ratio, enriching the types of benefits, optimizing the data collection method, and updating the carbon emission reduction accounting standard. Step S53: Organize the optimized operating mechanism and implementation process into replicable operating specifications.

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