Carbon data transmission method and device, computer equipment and readable storage medium

Abstract

The invention relates to a carbon data transmission method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring device identifiers of a plurality of electric devices; for each equipment identifier, calling a driving module matched with the equipment identifier, so as to detect carbon data of the electric equipment matched with the equipment identifier by utilizing a protocol in the driving module; wherein a protocol associated with an equipment identifier is packaged in the driving module; performing semantic extraction on the carbon data of the plurality of electric devices to obtain carbon semantic data of the plurality of electric devices; fusing the carbon semantic data of the plurality of electric devices to obtain fused carbon data; and transmitting the fused carbon data to the block chain. By adopting the method, carbon data transmission can be efficiently carried out.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and in particular to a carbon data transmission method, apparatus, computer equipment, and readable storage medium. Background Art

[0002] With the advancement of "data factorization" and "carbon data ownership confirmation," more and more systems are attempting to store carbon data on the blockchain. Therefore, how to transfer carbon data to the blockchain has become a hot topic.

[0003] In traditional technologies, various types of electrical equipment such as smart meters, circuit breakers, inverters, sensors, etc. are widely deployed at carbon emission sources such as enterprises, parks, and communities, forming a massive heterogeneous carbon data collection network. At this time, the solution for transmitting carbon data to the blockchain includes: real-time monitoring of the carbon data of electrical equipment through a protocol that supports carbon data collection from all electrical equipment, and encrypting the carbon data to input the encrypted carbon data into the blockchain, thereby improving the security of carbon data transmission.

[0004] However, current carbon data transmission methods are not efficient enough. Summary of the Invention

[0005] Based on this, it is necessary to provide an efficient carbon data transmission method, device, computer equipment, computer-readable storage medium and computer program product to address the above technical problems.

[0006] In a first aspect, the present application provides a carbon data transmission method, comprising:

[0007] Obtain device identifications of multiple electrical devices;

[0008] For each device identifier, a driver module matching the device identifier is called to detect carbon data of the electrical device matching the device identifier using the protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier;

[0009] Perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices;

[0010] Fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0011] Transfer the fused carbon data to the blockchain.

[0012] In one embodiment, the carbon semantic data of multiple electrical devices are fused to obtain fused carbon data, including:

[0013] Detect the historical communication status of multiple electrical devices;

[0014] Based on the historical communication status of multiple electrical devices, the carbon semantic data of multiple electrical devices are fused to obtain fused carbon data.

[0015] In one embodiment, detecting historical communication status of multiple powered devices includes:

[0016] Detect the historical transmission success rate and historical data fluctuation information of multiple electrical devices. The historical transmission success rate represents the ratio of successfully transmitted data to all data to be communicated that has been transmitted to the blockchain during the historical time period. The historical data fluctuation information represents the data fluctuation amplitude and data fluctuation frequency of the data to be communicated during the transmission of the electrical device during the historical time period.

[0017] Based on the historical transmission success rate and historical data fluctuation information of each electric device, the historical communication status of the corresponding electric device is detected.

[0018] In one embodiment, the carbon semantic data of multiple electrical devices are fused to obtain fused carbon data, including:

[0019] For each electrical device, extract the device's electricity consumption information, regional carbon factor information, and collection timestamp information from the carbon semantic data, and generate the device's carbon data within the target time window based on the electricity consumption information, regional carbon factor information, and collection timestamp information;

[0020] The electrical equipment carbon data of all electrical equipment within the target time window are fused to obtain fused carbon data.

[0021] In one embodiment, transferring the fused carbon data to a blockchain includes:

[0022] Detect summary information of fused carbon data;

[0023] Use the pre-loaded private key to digitally sign the fused carbon data to obtain the signature information of the fused carbon data;

[0024] The summary information, signature information and fused carbon data are combined, and the combined fused carbon data is transmitted to the blockchain.

[0025] In one embodiment, the combined fused carbon data is transmitted to a blockchain, including:

[0026] Control the gateway on the blockchain side to extract the summary information, signature information and fused carbon data from the combined fused carbon data, and control the gateway to perform consistency verification on the summary information and signature information respectively;

[0027] When the verification result representation summary information is consistent with the standard summary information pre-stored by the gateway, and the signature information is consistent with the standard summary information pre-stored by the gateway, the fused carbon data is written into the blockchain.

[0028] In a second aspect, the present application further provides a carbon data transmission device, comprising:

[0029] An identification acquisition module, used to obtain device identifications of multiple electrical devices;

[0030] The protocol parsing module is used to call the driver module that matches the device identifier for each device identifier, so as to detect the carbon data of the electrical device that matches the device identifier using the protocol protocol in the driver module; wherein the driver module encapsulates the protocol protocol associated with the device identifier;

[0031] A semantic extraction module is used to perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices;

[0032] The data fusion module is used to fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0033] Data transmission module, used to transmit fused carbon data to the blockchain.

[0034] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] Obtain device identifications of multiple electrical devices;

[0036] For each device identifier, a driver module matching the device identifier is called to detect carbon data of the electrical device matching the device identifier using the protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier;

[0037] Perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices;

[0038] Fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0039] Transfer the fused carbon data to the blockchain.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0041] Obtain device identifications of multiple electrical devices;

[0042] For each device identifier, a driver module matching the device identifier is called to detect carbon data of the electrical device matching the device identifier using the protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier;

[0043] Perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices;

[0044] Fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0045] Transfer the fused carbon data to the blockchain.

[0046] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0047] Obtain device identifications of multiple electrical devices;

[0048] For each device identifier, a driver module matching the device identifier is called to detect carbon data of the electrical device matching the device identifier using the protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier;

[0049] Perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices;

[0050] Fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0051] Transfer the fused carbon data to the blockchain.

[0052] The above-mentioned carbon data transmission method, device, computer equipment, computer-readable storage medium and computer program product. Currently, the communication protocols of electrical devices are complex and the number of electrical devices is large, resulting in low efficiency in carbon data collection, which in turn affects the process of carbon data transmission. Therefore, the present application provides an efficient carbon data transmission method. During the entire process, the protocol is encapsulated in the driver module, so that the protocol of each electrical device is decoupled. That is, the driver module that matches each device identifier is encapsulated with a protocol that matches the device identifier. Compared with the complex protocol in the prior art that supports the collection of carbon data of all electrical devices, the protocol matched with the device identifier in the present application is simpler. Therefore, it can improve the efficiency of detecting carbon data of electrical devices with matching device identifiers, and further improve the efficiency of carbon data transmission; at the same time, after detecting the carbon data of electrical devices with matching multiple device identifiers, it can also extract key semantic information from the carbon data of the electrical devices, remove the interference of irrelevant data, reduce the amount of carbon data, and then the fused carbon data can be efficiently transmitted to the blockchain. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 A diagram showing an application environment of a carbon data transmission method according to an embodiment;

[0055] Figure 2 A schematic flow chart of a carbon data transmission method according to an embodiment;

[0056] Figure 3 A schematic flow chart of a carbon data transmission method according to another embodiment;

[0057] Figure 4 A schematic flow chart of a carbon data transmission method according to a detailed embodiment;

[0058] Figure 5 is a structural block diagram of a carbon data transmission device in one embodiment;

[0059] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are used to explain this application and are not intended to limit this application.

[0061] As carbon data monitoring and management become increasingly sophisticated, various types of electrical equipment, including smart meters, circuit breakers, inverters, and sensors, are widely deployed at carbon emission sources, such as enterprises, industrial parks, and communities. This has led to a massive and heterogeneous carbon emissions data collection network. These devices suffer from inconsistent communication protocols, diverse protocols, and a complex mix of device types. This results in inefficient data collection and integration, making it difficult to ensure data timeliness, impacting subsequent carbon emissions accounting, green certification, and compliance verification.

[0062] Therefore, there is an urgent need for an underlying mechanism that can build a "fused and unified collection channel" in a heterogeneous terminal environment to realize the transmission of carbon data on the chain and support the trustworthy and real-time construction of the carbon data monitoring and transmission system.

[0063] The carbon data transmission method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, terminal 102 communicates with blockchain 106 via edge server 104. The data storage system can store data that edge server 104 needs to process. The data storage system can be integrated with edge server 104 or placed in the cloud or other network servers.

[0064] The user selects the device identifications of multiple electrical devices to be used for carbon data transmission on the carbon data processing interface of the terminal 102, and triggers the carbon data uplink control; the terminal 102 responds to the trigger request of the carbon data uplink control, generates a carbon data transmission request, and the carbon data transmission request carries the device identifications of multiple electrical devices, and sends the carbon data transmission request to the edge server 104; the edge server 104 obtains the device identifications of multiple electrical devices; for each device identification, calls the driver module that matches the device identification, and uses the protocol in the driver module to detect the carbon data of the electrical device that matches the device identification; wherein the driver module encapsulates the protocol associated with the device identification; performs semantic extraction on the carbon data of multiple electrical devices to obtain carbon semantic data of multiple electrical devices; fuses the carbon semantic data of each electrical device to obtain fused carbon data; and transmits the fused carbon data to the blockchain 106.

[0065] The terminal 102 may include, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, smart car devices, and projector devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Head-mounted devices may include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like. The edge server 104 may be an independent physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0066] In an exemplary embodiment, Figure 2 As shown, a carbon data transmission method is provided, which is applied to Figure 1 The edge server 104 in FIG. 1 is used as an example for explanation.

[0067] S100: Obtain device identifications of multiple electrical devices.

[0068] Among them, electrical equipment refers to various devices that use electricity to work. In this application, electrical equipment refers to electrical equipment whose carbon data needs to be transmitted to the blockchain. Device identification refers to the identification that uniquely identifies the electrical equipment.

[0069] Specifically, the user selects the device identifications of multiple electrical devices to be used for carbon data transmission on the carbon data processing interface of the terminal, and triggers the carbon data uplink control; the terminal responds to the trigger request of the carbon data uplink control, generates a carbon data transmission request, and the carbon data transmission request carries the device identifications of multiple electrical devices, and sends the carbon data transmission request to the edge server; the edge server obtains the device identifications of multiple electrical devices.

[0070] S200 , for each device identifier, calling a driver module that matches the device identifier, and using a protocol in the driver module to detect carbon data of the electrical device that matches the device identifier.

[0071] The driver module encapsulates the protocol associated with the device identifier. This introduces a "protocol parsing plug-in mechanism," with each protocol corresponding to a parsing driver. This allows the driver module to support multi-protocol data acquisition from mainstream electrical terminals, including but not limited to RS485 (Recommended Standard 485, a serial communication physical interface standard), DLT645 (DL / T 645 communication protocol), Modbus (an industrial communication protocol), CAN (Controller Area Network), and LoRa (Long Range Radio). Furthermore, the driver module supports flexible configuration via hot-loading. Carbon data refers to quantitative information related to the energy consumption and carbon emissions of electrical equipment.

[0072] Specifically, since this application needs to transmit carbon data of multiple electrical devices, there are many types of terminal devices and complex communication protocols, including but not limited to RS485, Modbus, DLT645, MQTT (Message Queuing Telemetry Transport, message queue telemetry transmission protocol), etc., resulting in significant differences in structure, frequency, and semantics of data on the electrical device side, making unified collection and fusion difficult.

[0073] Therefore, in response to the diversity of terminal protocols, this application adopts a modular drive mechanism for decoupling design, that is, each protocol (such as Modbus, DLT645, MQTT, etc.) is encapsulated as an independent drive module, which contains command format, data frame parsing logic, exception handling strategy, etc.

[0074] The system is equipped with a unified driver scheduling interface, which loads the corresponding driver module according to the terminal identification during startup or operation, and uses the protocol in the driver module to detect the energy consumption and carbon emission-related quantitative information of the electrical equipment matching the device identification to obtain the carbon data of the electrical equipment; furthermore, the driver module supports hot-swappable loading, that is, a protocol driver module can be dynamically enabled, replaced or uninstalled without interrupting the main process of the system to adapt to new equipment or upgrade scenarios.

[0075] In addition, the call chain of the driver module is uniformly managed by the edge node to ensure a clear collection scheduling process and a unified collection data structure.

[0076] The above mechanism achieves "plug-and-play driver and flexible protocol adaptation", significantly reducing system maintenance costs and improving the compatibility of heterogeneous devices.

[0077] S300: Perform semantic extraction on the carbon data of multiple electrical devices to obtain the carbon semantic data of the multiple electrical devices.

[0078] Semantic extraction refers to the process of automatically identifying and extracting meaningful semantic information from unstructured or semi-structured data (such as text, images, and speech) and converting it into structured data. Its core goal is to understand the deeper meaning (i.e., "semantics") of the data, rather than just the superficial grammatical or symbolic level. Carbon semantic data refers to a structured description of the meaning, associations, and constraints of carbon data.

[0079] Specifically, due to the significant differences in structure, frequency and semantics of the data on the electrical equipment side, unified collection and integration are difficult. Therefore, semantic extraction can be performed on the collected carbon data of the electrical equipment to obtain the carbon semantic data of each electrical equipment.

[0080] Furthermore, semantic extraction of the collected carbon data of electrical devices is performed by abstracting the collected carbon data of electrical devices into a "carbon data standard object model". The "carbon data standard object model" of this application is an abstract structure that semantically unifies data from different terminals. An example of a unified carbon semantic data field is as follows:

[0081] {voltage: xxx, current: xxx, active energy: xxx, regional carbon factor: xxx, power factor: xxx, frequency: xxx, terminal number: device_id_xx, collection timestamp: timestamp, region code: region_code}.

[0082] That is to say, the carbon data of multiple electrical devices are semantically extracted using a semantically unified abstract structure, and the obtained carbon semantic data will be generated according to the semantically unified abstract structure.

[0083] S400: Fusing carbon semantic data of multiple electrical devices to obtain fused carbon data.

[0084] Specifically, the edge server is configured with edge computing capabilities, periodically aggregates carbon data from multiple electrical devices, detects the carbon semantic data corresponding to the carbon data of each electrical device, and then fuses the carbon semantic data of multiple electrical devices to obtain fused carbon data.

[0085] Among them, the method of fusing the carbon semantic data of multiple electrical devices can be direct fusion, that is, adding the carbon semantic data of multiple electrical devices; or it can be weighted fusion, that is, obtaining the weight coefficient corresponding to each electrical device, and weightedly adding the carbon semantic data of multiple electrical devices according to the weight coefficients corresponding to the multiple electrical devices.

[0086] S500, transfers fused carbon data to the blockchain.

[0087] Specifically, finally, the integrated carbon data is transmitted to the blockchain to store the carbon data of multiple power-consuming devices in the blockchain.

[0088] Furthermore, because blockchain focuses primarily on the "immutability of data after being uploaded to the chain," it lacks security guarantees for the "off-chain-on-chain" transmission process. Furthermore, the data collection chain on the power-consuming device side is complex and communication transfers are frequent. Once the front-end power-consuming devices are not effectively protected, the carbon data of the power-consuming devices are vulnerable to attacks such as tampering with network intermediate nodes, cache contamination, and forged uploads before being stored on the chain. This can lead to problems such as carbon data being tampered with, forged, or delayed on the chain, posing challenges to the credibility of the on-chain data and causing this method to have a systemic fault of "trusted on-chain, untrusted off-chain." Therefore, when transmitting the fused carbon data to the blockchain, it is also necessary to encrypt the fused carbon data to improve its tamper-proof capabilities.

[0089] In one embodiment, the present application also introduces a cache isolation mechanism to separate the carbon data collection cache area from the transmission buffer area, that is, the step of detecting the carbon data of the electrical equipment is decoupled from the step of transmitting the integrated carbon data to the blockchain, so as to avoid distortion of the current calculation due to residual data from the previous time.

[0090] In the above-mentioned carbon data transmission method, the communication protocols of the current electrical equipment are complex and the number of electrical equipment is large, resulting in low efficiency in carbon data collection, which in turn affects the process of carbon data transmission. Therefore, the present application provides an efficient carbon data transmission method. During the entire process, the protocol is encapsulated in the driver module, so that the protocol of each electrical equipment is decoupled. That is to say, the driver module that matches each device identifier is encapsulated with a protocol that matches the device identifier. Compared with the complex protocol in the prior art that supports the collection of carbon data of all electrical equipment, the protocol of the present application that matches the device identifier is simpler. Therefore, it can improve the efficiency of detecting carbon data of electrical equipment with matching device identifiers, and further improve the efficiency of carbon data transmission; at the same time, after detecting the carbon data of electrical equipment with matching multiple device identifiers, it can also extract key semantic information from the carbon data of the electrical equipment, remove the interference of irrelevant data, reduce the amount of carbon data, and then the fused carbon data can be efficiently transmitted to the blockchain.

[0091] In an exemplary embodiment, the carbon semantic data of multiple electrical devices are fused to obtain fused carbon data, including:

[0092] Detect the historical communication status of multiple electrical devices; based on the historical communication status of multiple electrical devices, fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data.

[0093] The historical communication status usually refers to the operating status, interaction process and related data records of the electrical equipment in a certain period of time in the past.

[0094] Specifically, in the process of carbon data fusion of multiple user devices, the influence of different device accuracy, network quality or physical location on data credibility is taken into consideration, and a weight correction mechanism is introduced. That is to say, instead of simply adding and fusing the carbon semantic data of multiple electrical devices, this embodiment also detects the historical communication status of each electrical device within the historical time period to determine the electrical device's own communication capability, and then corrects the fusion weight of each electrical device based on its own communication capability. Then, based on the corrected fusion weight, the carbon semantic data of multiple electrical devices are weightedly fused to obtain fused carbon data.

[0095] Furthermore, in the process of transmitting carbon data to the blockchain within a historical time period, information such as the establishment and disconnection of communication connections, the quality of data transmission (such as bandwidth, delay, packet loss rate), signal strength, device working mode (such as standby, transmission, fault), and user interaction records can be obtained to detect the historical communication status of electrical devices. Based on the historical communication status of multiple electrical devices, the carbon semantic data of multiple electrical devices can be fused to obtain fused carbon data.

[0096] Furthermore, the historical communication status of electrical devices can be quantified using status levels. In this case, the historical communication status can include quantification levels such as good, better, fair, poor, and bad. Based on the different quantification levels of each electrical device, each electrical device is assigned a different fusion weight. Each quantization level corresponds to a fusion weight, so that the carbon semantic data of multiple electrical devices can be weightedly fused.

[0097] In this embodiment, by detecting the historical communication status of multiple electric devices, the carbon semantic data of multiple electric devices in the current time period can be accurately integrated based on the communication status experience of the electric devices in the historical time period.

[0098] In an exemplary embodiment, detecting historical communication states of a plurality of powered devices includes:

[0099] Detect the historical transmission success rate and historical data fluctuation information of multiple power-consuming devices, where the historical transmission success rate represents the proportion of successfully transmitted data transmitted to the blockchain during the historical time period to all data to be communicated, and the historical data fluctuation information represents the data fluctuation amplitude and data fluctuation frequency of the data to be communicated of the power-consuming devices during the historical time period. Based on the historical transmission success rate and historical data fluctuation information of each power-consuming device, detect the historical communication status of the corresponding power-consuming device.

[0100] Among them, the historical transmission success rate measures the proportion of successful communications within the historical time period (such as the ratio of the number of successful requests / connections to the total number of times, which is generally used to represent the proportion of successfully transmitted data transmitted to the blockchain during the historical time period to all data to be communicated); data fluctuation information describes the instability of data during transmission, processing or storage (such as delay fluctuations, abnormal value jumps), which is generally used to represent the continuity characteristics of data fluctuation amplitude and data fluctuation frequency during transmission of data to be communicated by electrical equipment during the historical time period.

[0101] Specifically, the historical transmission success rates and historical data fluctuations of multiple power-consuming devices are detected. The historical transmission success rates essentially reflect the reliability of the power-consuming device's transmission, while the historical data fluctuations essentially reflect the stability of the power-consuming device's transmission. Therefore, by using the historical transmission success rates and historical data fluctuations of each power-consuming device, the reliability and stability of the power-consuming device's carbon data transmission to the blockchain can be tested. Based on the reliability and stability of the power-consuming device's carbon data transmission to the blockchain, the historical communication status of the power-consuming device can be determined. Based on the historical communication status of the power-consuming device, the fusion weight of each power-consuming device can be adjusted. For example, if the data packet loss rate in the past 10 minutes is high, the weight will be reduced.

[0102] Furthermore, data that has been successfully transmitted to the blockchain generally means that the data has arrived completely and accurately at the destination, and the recipient sends an ACK (Acknowledgement Character) response to confirm that it is correct. If the data packet does not receive an ACK receipt within the specified time, it is considered a failure. For example, if an electrical device initiated 1000 data transmissions in the past 24 hours, of which 950 were successful and 50 failed, then the historical transmission success rate = 950 / 1000 × 100% = 95%.

[0103] Historical data fluctuations include various types, such as:

[0104] 1. Abnormal fluctuations: Data points deviate significantly from the normal range (such as sudden surges or drops).

[0105] 2. Trend fluctuation: data continues to rise or fall over time (such as seasonal growth).

[0106] 3. Periodic fluctuations: The data shows regular repetition (such as daily peaks and weekly traffic fluctuations).

[0107] When obtaining the fluctuation type of each user device, the data fluctuation amplitude of the user device should be obtained for each fluctuation type. For example, the amplitude by which the data deviates from the normal range when obtaining an abnormal fluctuation type, or the amplitude by which the data continues to rise or fall over time when obtaining a trend fluctuation type.

[0108] The historical time period is divided into multiple historical sub-time periods. Based on the corresponding number of fluctuations in multiple historical sub-time periods, the data fluctuation frequency in the historical time period can be detected. For example, when abnormal fluctuations occur multiple times in the historical time period, the data fluctuation frequency of the user device is determined based on the number of fluctuations corresponding to the abnormal fluctuation type.

[0109] The historical transmission success rate of the user device and the historical data fluctuation information are then combined to detect the historical communication status of the corresponding electrical equipment. For example, when the historical data fluctuation information indicates that the user device frequently fluctuates abnormally or the historical transmission success rate is lower than the preset range threshold, the historical communication status of the user device will be quantified as poor; when the historical data fluctuation information indicates that the user device frequently fluctuates abnormally and the historical transmission success rate is lower than the preset range threshold, the historical communication status of the user device will be quantified as poor.

[0110] In the above embodiment, the historical transmission success rate and historical data fluctuation information of each of the multiple power-consuming devices are detected to detect the reliability and stability of the carbon data of the power-consuming devices transmitted to the blockchain, and then the historical communication status of the power-consuming devices can be accurately determined to improve the accuracy of the fusion of the carbon semantic data of multiple power-consuming devices.

[0111] In an exemplary embodiment, Figure 3 As shown, S400 includes:

[0112] S410 , for each electrical device, extracting the electrical consumption information, regional carbon factor information, and collection timestamp information of the electrical device from the carbon semantic data.

[0113] S420 : Generate carbon data of electrical equipment within a target time window based on the electricity consumption information, regional carbon factor information, and collection timestamp information.

[0114] S430: Fusion the electrical equipment carbon data of all electrical equipment within the target time window to obtain fused carbon data.

[0115] Electricity consumption refers to the total amount of electricity consumed by electrical devices (such as household appliances, industrial machinery, and vehicles) over a given period of time. It is a core indicator for measuring the scale and demand of electricity use. Regional carbon factor information is a key indicator for measuring carbon dioxide emissions per unit of economic activity or resource consumption within a specific region. It is used to assess a region's carbon emission intensity, low-carbon development level, and effectiveness in addressing climate change.

[0116] Specifically, the collection timestamp information of the electrical equipment is extracted from the carbon semantic data, and the carbon semantic data obtained from the same collection timestamp of multiple electrical equipment will enter the same time window processing pool after periodic collection.

[0117] Let the same time window processing pool be the target time window. For each electrical device in the target time window, since the carbon semantic data includes fields such as voltage, current, active power, regional carbon factor, power factor, frequency, terminal number, collection timestamp, and region code, the device's power consumption information and regional carbon factor information can be extracted from the carbon semantic data. Based on this power consumption information, regional carbon factor information, and collection timestamp information, the carbon data of the electrical device in the target time window is generated. The carbon data of all electrical devices in the target time window are then weighted and fused to obtain the fused carbon data.

[0118] Furthermore, electricity consumption information can be inferred from fields such as voltage, current, and sampling period in the carbon semantic data using the formula "voltage × current × sampling period." It can also be directly obtained from the active energy field. Regional carbon factor information is typically dynamically loaded into the carbon data based on device deployment locations for subsequent retrieval.

[0119] For example, the fused carbon data = Σki (power consumption information of power device i × regional carbon factor information), where ki is the fusion weight of power device i, and the power consumption information of power device i = voltage information of power device i x current information of power device i x sampling period of power device i.

[0120] In one embodiment, to enhance the stability and anti-interference capabilities of carbon data fusion results, this application, based on the aforementioned carbon data fusion, also introduces a sliding window-based low-pass filtering algorithm and an outlier rejection mechanism. The following steps are used: a window width N (e.g., 3-5) is set, and the most recent N sets of homologous data are taken each time, followed by average or median filtering to effectively smooth short-term fluctuations and obtain carbon data for electrical equipment within the target time window. For measurements that exhibit instantaneous spikes, the system sets a "variation threshold" (e.g., a data fluctuation exceeding 30% within 10 seconds), identifies them as outliers, and automatically removes them. For data streams with persistent jitter, a trend determination algorithm (e.g., linear fit residual analysis) is used to determine whether it is device jitter or signal interference, triggering down-weighting of the user device during the fusion phase. The aforementioned filtering and correction techniques, combined with the data weighting mechanism, significantly improve data quality while ensuring near-real-time performance.

[0121] In one embodiment, the present application may also aggregate the fused carbon data within multiple target time windows to obtain fused carbon data within a larger time range.

[0122] In the above embodiment, by extracting the power consumption information, regional carbon factor information and collection timestamp information of the electrical equipment from the carbon semantic data, the fused carbon data of all electrical equipment can be accurately generated.

[0123] In an exemplary embodiment, transferring fused carbon data to a blockchain includes:

[0124] Detect the summary information of the fused carbon data; use the preloaded private key to digitally sign the fused carbon data to obtain the signature information of the fused carbon data; combine the summary information, signature information and fused carbon data, and transmit the combined fused carbon data to the blockchain.

[0125] A digest, also known as a hash value or message digest, is a fixed-length binary string generated by applying a hash function to raw data of any length. A private key is a key parameter in asymmetric encryption algorithms. It is a secret string kept by the user and paired with a public key. A digital signature is a cryptographic technique used to verify the authenticity and integrity of a message.

[0126] Specifically, a hash algorithm is used on the fused carbon data, such as SHA256 (Secure Hash Algorithm-256) or the national secret SM3 algorithm, to obtain the summary information of the fused carbon data, and then the preloaded private key is used to digitally sign the fused carbon data to obtain the signature information of the fused carbon data to ensure the authenticity of the source. Finally, the summary information, signature information and fused carbon data are combined to form a set of verifiable trusted data structures, and the combined fused carbon data is transmitted to the blockchain.

[0127] Furthermore, this application also maintains a quasi-real-time connection with the access node of the blockchain through links such as WebSocket, MQTT or 4G / Ethernet; each signed carbon emission data will automatically call the uplink interface to write to the blockchain, and generate smart contract record data in the blockchain. The smart contract records the original text of the data packet, hash summary, power equipment identification, timestamp and other key fields. In addition, after the integrated carbon data is written to the blockchain, a unique on-chain index number is generated, such as TxID (transaction ID), etc., to support subsequent queries and verifications.

[0128] In the above embodiment, the summary information, signature information and fused carbon data are combined, and the combined fused carbon data is transmitted to the blockchain. The transmission process of the fused carbon data can be encrypted, reducing the possibility of the fused carbon data being tampered with during the transmission process.

[0129] In an exemplary embodiment, the combined fused carbon data is transmitted to the blockchain, including:

[0130] The gateway on the blockchain side is controlled to extract the summary information, signature information and fused carbon data from the combined fused carbon data, and the gateway is controlled to perform consistency verification on the summary information and signature information respectively; when the verification result indicates that the summary information is consistent with the standard summary information pre-stored in the gateway, and the signature information is consistent with the standard summary information pre-stored in the gateway, the fused carbon data is written into the blockchain.

[0131] Specifically, before the combined fused carbon data is written to the blockchain, the gateway on the blockchain side can also be controlled to extract the summary information, signature information and fused carbon data in the combined fused carbon data to perform consistency verification on the summary information and signature information respectively, that is, to verify whether the summary information is consistent with the standard summary information pre-stored in the gateway, and to verify whether the signature information is consistent with the standard summary information pre-stored in the gateway. If they are consistent, the combined fused carbon data will be transmitted to the blockchain.

[0132] In this embodiment, by performing consistency checks on the summary information and the signature information before writing into the blockchain, it is possible to verify whether data tampering occurs during the transmission of the combined fused carbon data, thereby improving the security of carbon data transmission.

[0133] In one embodiment, the present application also supports a two-way verification mechanism between on-chain data and off-chain cached data, wherein the two-way verification mechanism includes two dimensions:

[0134] On-chain → off-chain verification: Actively request the edge node to compare the locally cached original data with the signature through the data index stored in the on-chain smart contract (such as user device ID + timestamp + hash summary).

[0135] Off-chain → On-chain Verification: Edge nodes regularly review successful upload records from the past M minutes and compare the on-chain receipt records to see if they exist and have been tampered with (by comparing hash values, signature field consistency, etc.). If a discrepancy is found, an alarm mechanism is triggered and the abnormal data isolation process is initiated.

[0136] Furthermore, this application also provides a "data path tracking proof" function: it can trace back the terminal number, protocol, processing node, signer and other metadata of the source of each on-chain data; in abnormal scenarios (such as upload failure, inconsistent signature), the system automatically triggers logging and retransmission strategies; the entire process supports the supervision node to audit the entire link process of "data collection → fusion → signature → chaining".

[0137] This application proposes a carbon data transmission method. To address the current problems of multiple types of electrical equipment, complex communication protocols, and insufficient data credibility, a data protection channel off-chain and on-chain that integrates protocol decoupling, edge computing, data signatures, and trusted chaining is constructed to ensure the uniformity, low latency, and tamper-proof nature of the entire process of carbon data from collection to chaining. Figure 4 As shown, the carbon data transmission method will be described in detail in multiple modules below:

[0138] 1. Heterogeneous device protocol adaptation and data acquisition module:

[0139] Initiate carbon data collection for multiple electrical devices. Specifically, obtain device identifications of multiple electrical devices. For each device identification, call a driver module that matches the device identification to parse the carbon data of the electrical device that matches the device identification using the protocol in the driver module. The driver module encapsulates the protocol associated with the device identification. Semantically extract the carbon data of multiple electrical devices, map them uniformly into a standardized "carbon data standard object model", and use the "carbon data standard object model" corresponding to each electrical device as the carbon semantic data of each electrical device.

[0140] 2. Quasi-real-time fusion processing module on the edge side:

[0141] Detect the historical transmission success rate and historical data fluctuation information of multiple power-consuming devices, where the historical transmission success rate represents the proportion of successfully transmitted data transmitted to the blockchain during the historical time period to all data to be communicated, and the historical data fluctuation information represents the data fluctuation amplitude and data fluctuation frequency of the data to be communicated of the power-consuming devices during the historical time period. Based on the historical transmission success rate and historical data fluctuation information of each power-consuming device, detect the historical communication status of the corresponding power-consuming device.

[0142] Based on the historical communication status of multiple electric devices, fusion weights are assigned to the corresponding electric devices, and based on the fusion weights of each electric device, the carbon semantic data of multiple electric devices are fused to obtain fused carbon data.

[0143] Among them, the carbon semantic data of multiple electric devices are fused to obtain fused carbon data, including: for each electric device, the power consumption information, regional carbon factor information and collection timestamp information of the electric device are extracted from the carbon semantic data, and based on the power consumption information, regional carbon factor information and collection timestamp information, the carbon data of the electric device within the target time window is generated; the carbon data of all electric devices within the target time window are fused to obtain fused carbon data.

[0144] Furthermore, in the process of fusing the carbon semantic data of multiple electrical devices, time window aggregation and noise filtering correction processing may also be performed, which has been explained in the above embodiment and will not be repeated here.

[0145] 3. Data encryption and anti-tampering verification module:

[0146] Detect the summary information of the fused carbon data; use the preloaded private key to digitally sign the fused carbon data to obtain the signature information of the fused carbon data; combine the summary information, signature information and fused carbon data, and transmit the combined fused carbon data to the blockchain.

[0147] Before the combined fused carbon data is uploaded to the chain, the gateway on the blockchain side is controlled to extract the summary information, signature information and fused carbon data from the combined fused carbon data, and the gateway is controlled to perform consistency verification on the summary information and signature information respectively; when the verification results indicate that the summary information is consistent with the standard summary information pre-stored by the gateway, and the signature information is consistent with the standard summary information pre-stored by the gateway, the fused carbon data is written into the blockchain.

[0148] 4. Blockchain quasi-real-time synchronization and recording module:

[0149] The system maintains a quasi-real-time connection with the blockchain access node through links such as WebSocket, MQTT or 4G (Fourth-Generation, fourth-generation mobile communication technology) / Ethernet; each signed carbon data will automatically call the on-chain interface to write it into the blockchain, and the smart contract will record key fields such as the original text of the data packet, hash summary, terminal ID, timestamp, etc.; after the data is written to the chain, a unique on-chain index number is generated to support subsequent queries and verification.

[0150] 5. Data verification and channel integrity assurance module:

[0151] It supports a two-way verification mechanism between on-chain data and off-chain cached data, and the two-way verification mechanism includes two dimensions; it provides a "data path tracking proof" function: it can trace back the terminal number, protocol, processing node, signer and other meta-information of each on-chain data source; in abnormal scenarios (such as upload failure, inconsistent signatures), the system automatically triggers logging and retransmission strategies; the entire process supports regulatory nodes to audit the entire link process of "data collection → fusion → signature → chaining".

[0152] Based on the above modules, it can be seen that this application successfully solves the technical bottlenecks of difficult unified carbon emission data collection, difficult tamper-proofing, and difficult chain-up efficiency improvement in heterogeneous terminal environments by constructing an off-chain channel mechanism with protocol adaptation, integrated computing, secure signature, and trusted chain-up capabilities. It has the following significant technical effects:

[0153] 1. Open up the data collection process for heterogeneous terminals: Through protocol decoupling and standard data model mapping mechanisms, unified collection and processing of mainstream protocol devices such as RS485, DLT645, and Modbus is achieved, avoiding the fragmented access of multiple terminals and tedious manual configuration problems in the existing system.

[0154] 2. Improve the efficiency and real-time performance of carbon data fusion: Through edge computing devices, data fusion, filtering, correction and verification processing are completed in real time, achieving "minute-level" or "second-level" synchronization capabilities from terminal collection to fusion on the chain, which is significantly better than the traditional "hour-level" centralized collection solution.

[0155] 3. Ensure data source security and tamper-proofing: Use off-chain digital signature and data summary mechanisms to ensure that each piece of data is bound to the device identity and collection sequence before uploading. Any off-chain attack or middleman tampering will be detected immediately, strengthening the credibility of the carbon data ownership confirmation process.

[0156] 4. Form a closed-loop system for the trusted collection of carbon emission data: Through on-chain evidence storage and off-chain verification mechanisms, a complete process from user device to edge to blockchain is constructed, which supports the traceability, verification, and auditability of subsequent data, providing a trust basis for carbon asset registration, green electricity verification, etc.

[0157] 5. Engineering feasibility and platform adaptability: This solution is adaptable to a variety of deployment environments. It can be used for the integration of smart terminals under the China Southern Power Grid and industrial park power Internet of Things systems, and can also be extended to carbon emission online monitoring platforms and the integrated construction of "carbon-electricity-data" in industrial parks.

[0158] In summary, this application provides key channel support for building an underlying trusted carbon emission perception system, filling the gap between "on-chain trust" and "terminal trust", and is an important underlying foundation for the compliant flow of carbon emission data, trusted confirmation of carbon assets, and trusted governance of the carbon market.

[0159] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0160] Based on the same inventive concept, embodiments of the present application also provide a carbon data transmission device for implementing the aforementioned carbon data transmission method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more carbon data transmission device embodiments provided below can be found in the above-described limitations of the carbon data transmission method and are not further elaborated here.

[0161] In an exemplary embodiment, Figure 5 As shown, a carbon data transmission device is provided, comprising: an identification acquisition module 100, a protocol analysis module 200, a semantic extraction module 300, a data fusion module 400 and a data transmission module 500, wherein:

[0162] The identification acquisition module 100 is used to obtain device identifications of multiple electrical devices;

[0163] The protocol parsing module 200 is used to call the driver module that matches the device identifier for each device identifier, so as to detect the carbon data of the electrical device that matches the device identifier using the protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier;

[0164] A semantic extraction module 300 is used to perform semantic extraction on the carbon data of a plurality of electrical devices to obtain the carbon semantic data of the plurality of electrical devices;

[0165] The data fusion module 400 is used to fuse the carbon semantic data of multiple electrical devices to obtain fused carbon data;

[0166] The data transmission module 500 is used to transmit the fused carbon data to the blockchain.

[0167] In one embodiment, the data fusion module 400 is further configured to detect historical communication status of multiple electrical devices; based on the historical communication status of the multiple electrical devices, the carbon semantic data of the multiple electrical devices are fused to obtain fused carbon data.

[0168] In one embodiment, the data fusion module 400 is also used to detect the historical transmission success rate and historical data fluctuation information of each of the multiple power-consuming devices, wherein the historical transmission success rate represents the proportion of successfully transmitted data transmitted to the blockchain during the historical time period to all data to be communicated, and the historical data fluctuation information represents the data fluctuation amplitude and data fluctuation frequency of the data to be communicated of the power-consuming device during the historical time period; based on the historical transmission success rate and historical data fluctuation information of each power-consuming device, the historical communication status of the corresponding power-consuming device is detected.

[0169] In one embodiment, the data fusion module 400 is also used to extract the power consumption information, regional carbon factor information and collection timestamp information of each power-consuming device from the carbon semantic data, and generate the carbon data of the power-consuming device within the target time window based on the power consumption information, regional carbon factor information and collection timestamp information; and fuse the carbon data of all power-consuming devices within the target time window to obtain fused carbon data.

[0170] In one embodiment, the data transmission module 500 is also used to detect the summary information of the fused carbon data; use the preloaded private key to digitally sign the fused carbon data to obtain the signature information of the fused carbon data; combine the summary information, signature information and fused carbon data, and transmit the combined fused carbon data to the blockchain.

[0171] In one embodiment, the data transmission module 500 is also used to control the gateway on the blockchain side to extract the summary information, signature information and fused carbon data from the combined fused carbon data, and control the gateway to perform consistency verification on the summary information and signature information respectively; when the verification result indicates that the summary information is consistent with the standard summary information pre-stored by the gateway, and the signature information is consistent with the standard summary information pre-stored by the gateway, the fused carbon data is written into the blockchain.

[0172] Each module in the carbon data transmission device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0173] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data such as device identifications of multiple electrical devices. The input / output interface of the computer device is used to exchange information between the processor and external electrical devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a carbon data transmission method is implemented.

[0174] Those skilled in the art will understand that Figure 6 The structure shown in the figure is a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0175] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0176] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0177] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0178] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, artificial intelligence (AI) processors, and the like.

[0179] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0180] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A carbon data transmission method, characterized in that: The method comprises: Obtain device identifications of multiple electrical devices; For each device identifier, calling a driver module that matches the device identifier, and using a protocol in the driver module to detect carbon data of the electrical device that matches the device identifier; wherein the driver module encapsulates the protocol associated with the device identifier; Performing semantic extraction on the carbon data of the plurality of electrical devices to obtain the carbon semantic data of the plurality of electrical devices; fusing the carbon semantic data of the plurality of electrical devices to obtain fused carbon data; The fused carbon data is transmitted to the blockchain.

2. The method according to claim 1, characterized in that The fusing of the carbon semantic data of the plurality of electrical devices to obtain fused carbon data includes: Detecting historical communication states of the plurality of electrical devices; Based on the historical communication states of the plurality of electric devices, the carbon semantic data of the plurality of electric devices are fused to obtain fused carbon data.

3. The method according to claim 2, characterized in that The detecting the historical communication status of the plurality of electric devices includes: Detecting the historical transmission success rate and historical data fluctuation information of each of the plurality of electrical devices, wherein the historical transmission success rate represents the ratio of successfully transmitted data transmitted to the blockchain to all data to be communicated during a historical time period, and the historical data fluctuation information represents the data fluctuation amplitude and data fluctuation frequency of the data to be communicated of the electrical devices during transmission during a historical time period; Based on the historical transmission success rate and the historical data fluctuation information of each of the electric devices, a historical communication status of the corresponding electric device is detected.

4. The method according to claim 1, wherein The fusing of the carbon semantic data of the plurality of electrical devices to obtain fused carbon data includes: For each of the electrical devices, extract the power consumption information, regional carbon factor information, and collection timestamp information of the electrical device from the carbon semantic data, and generate carbon data of the electrical device within a target time window based on the power consumption information, the regional carbon factor information, and the collection timestamp information; The electric device carbon data of all the electric devices within the target time window are fused to obtain fused carbon data.

5. The method according to claim 1, wherein The transferring of the fused carbon data to the blockchain comprises: detecting summary information of the fused carbon data; Using a preloaded private key, digitally signing the fused carbon data to obtain signature information of the fused carbon data; The summary information, the signature information and the fused carbon data are combined, and the combined fused carbon data is transmitted to the blockchain.

6. The method according to claim 5, characterized in that The transferring of the combined fusion carbon data to the blockchain includes: Controlling the gateway on the blockchain side to extract the summary information, signature information, and fused carbon data from the combined fused carbon data, and controlling the gateway to perform consistency checks on the summary information and the signature information respectively; When the verification result indicates that the summary information is consistent with the standard summary information pre-stored in the gateway, and the signature information is consistent with the standard summary information pre-stored in the gateway, the fused carbon data is written into the blockchain.

7. A carbon data transmission device, characterized in that: The device comprises: An identification acquisition module, used to obtain device identifications of multiple electrical devices; A protocol parsing module, configured to, for each device identifier, call a driver module that matches the device identifier, and detect carbon data of the electrical device that matches the device identifier using a protocol in the driver module; wherein the driver module encapsulates the protocol associated with the device identifier; a semantic extraction module, configured to perform semantic extraction on the carbon data of the plurality of electrical devices to obtain the carbon semantic data of the plurality of electrical devices; a data fusion module, configured to fuse the carbon semantic data of the plurality of electric devices to obtain fused carbon data; A data transmission module is used to transmit the fused carbon data to the blockchain.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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