Trusted data processing method and device for environmental rights accounting of sustainable aviation fuel

Abstract

This invention discloses a reliable data processing method and device for environmental equity accounting of sustainable aviation fuel, comprising: acquiring raw data collected in real time by IoT data collection terminals at each stage of the sustainable aviation fuel supply chain; generating standardized data based on the raw data, and performing hash operations on the standardized data to obtain data fingerprints; storing the data fingerprints on a blockchain distributed ledger, and storing the raw data in an off-chain database, establishing a mapping relationship; verifying the raw data based on the raw data in the off-chain database and the data fingerprints on the blockchain; and determining the environmental equity accounting result of sustainable aviation fuel based on the verified raw data. Using this invention can improve the accuracy and reliability of environmental equity accounting for sustainable aviation fuel.

Description

Technical Field

[0001] This invention relates to the field of sustainable aviation fuel technology, and in particular to a reliable data processing method and device for environmental equity accounting of sustainable aviation fuel. Background Technology

[0002] As an alternative fuel designed to reduce carbon emissions from air transport, the authenticity and uniqueness of sustainable aviation fuel's environmental rights depend on the accurate calculation of carbon emission data across the entire supply chain. Taking sustainable aviation fuel produced from waste cooking oil through hydrogenation of esters and fatty acids as an example, the calculation of its carbon reduction benefits requires tracking carbon emission data throughout its entire lifecycle, from waste cooking oil collection and transportation, processing into industrial-grade blended fuel, transportation of the industrial-grade blended fuel, sustainable aviation fuel production, and transportation of sustainable aviation fuel to its storage at the airport. Missing or distorted data at any stage can lead to double counting or false declarations of environmental rights, thereby affecting the fairness and regulatory effectiveness of the carbon trading market. Therefore, ensuring the credibility of sustainable aviation fuel supply chain data from collection to environmental rights calculation is a crucial technical foundation for supporting the compliant registration and market trading of sustainable aviation fuel's environmental rights.

[0003] In existing technologies, some solutions achieve electronic data storage by deploying independent digital recording systems at each stage. For example, an enterprise resource planning system is used to record the amount of raw materials entering the warehouse and the amount of products leaving the warehouse, and a vehicle-mounted global positioning system is used to record the transportation trajectory. Then, the data from each stage is linked to the carbon accounting system through manual aggregation.

[0004] However, in the process of realizing this invention, the inventors discovered that the above-mentioned prior art has at least the following drawbacks: The digital systems at each stage are isolated, lacking a unified data interface and communication protocol. Key parameters required for carbon footprint accounting cannot be automatically transferred across stages, still requiring manual transcription and aggregation. Data lag and entry errors introduced by manual operation are difficult to avoid, and each participant lacks effective anti-tampering mechanisms for its own data. Furthermore, existing data is stored by a single institution in the form of centralized databases or paper documents, giving the data manager the ability to unilaterally modify or delete historical data. Other participants struggle to establish technical trust in the authenticity and integrity of the data, and this lack of cross-entity data trust further amplifies the credibility risks of the entire supply chain. The combination of these problems leads to a gradual decline in the credibility of data accumulated throughout the sustainable aviation fuel supply chain. Input parameters such as carbon emission values ​​and fuel quality, upon which environmental rights accounting is based, are difficult to guarantee in terms of accuracy and traceability. This, in turn, exposes carbon emission accounting and environmental rights registration to the technical risks of double counting and false declarations, hindering the market acceptance and trading efficiency of sustainable aviation fuel environmental rights.

[0005] Therefore, how to improve the real-time performance and accuracy of data collection from the source of the entire sustainable aviation fuel supply chain without changing the existing business system architecture of each participant, and how to enhance the anti-tampering capability and cross-entity verifiability of data in the process of cross-linking through technical mechanisms, thereby improving the credibility and traceability of the input data on which environmental rights accounting is based, is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] This invention provides a reliable data processing method, apparatus, and computer equipment for environmental rights accounting of sustainable aviation fuel, in order to construct a reliable data chain covering the entire sustainable aviation fuel supply chain, ensure the authenticity, integrity, and traceability of the input data on which environmental rights accounting is based, and improve the accuracy and reliability of environmental rights accounting results.

[0007] To address the aforementioned technical problems, embodiments of this application provide a reliable data processing method for sustainable aviation fuel environmental equity accounting, including: The system acquires raw data collected in real time by IoT data collection terminals at each stage of the sustainable aviation fuel supply chain. The entire supply chain includes at least the waste cooking oil collection and transportation stage, the waste cooking oil treatment stage, the industrial-grade blended oil transportation stage, the sustainable aviation fuel production stage, the sustainable aviation fuel transportation stage, and the airport warehousing stage. Based on the original data, standardized data is generated, and a hash operation is performed on the standardized data to obtain a data fingerprint; The data fingerprint is stored on the blockchain distributed ledger, and the original data is stored in an off-chain database to establish a mapping relationship between the original data and the data fingerprint. The original data is verified based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger. Based on the verified raw data, the environmental equity accounting results for sustainable aviation fuel are determined.

[0008] Optionally, the IoT data collection terminal for the waste cooking oil collection and transportation process includes a vehicle-mounted weighing sensor, a GPS module, and an RFID tag reader / writer; it acquires raw data from the waste cooking oil collection and transportation process, including: The RFID electronic tag reader reads the RFID electronic tag on the waste catering grease drum to obtain the drum number; The weight of waste cooking oil collected is obtained through the vehicle-mounted weighing sensor; The collection timestamp and collection location are obtained through the Global Positioning System module.

[0009] Optionally, the IoT data acquisition terminal for the waste cooking oil treatment process includes an inbound weighing sensor, an RFID reader / writer, a tank feed monitoring device, and an outbound weighing sensor; it acquires raw data from the waste cooking oil treatment process, including: The weight of waste cooking oil entering the warehouse is obtained through the inbound weighing sensor. The source information of waste cooking oil is obtained through the radio frequency identification reader / writer; The processing batch number is generated by the feeding monitoring device of the processing tank, and the processing batch number is associated with the source information and the weight of the goods entering the warehouse. The outbound weight of the industrial-grade mixed oil is obtained through the outbound weighing sensor.

[0010] Optionally, the IoT data acquisition terminal for the industrial-grade blended fuel transportation link and / or the sustainable aviation fuel transportation link includes a vehicle-mounted weighing sensor, a GPS module, and a RFID reader / writer; acquiring raw data from the industrial-grade blended fuel transportation link and / or the sustainable aviation fuel transportation link includes: The transport weight is obtained through the vehicle-mounted weighing sensor; The GPS module is used to obtain the driving trajectory and mileage of the transport vehicle.

[0011] Optionally, the IoT data acquisition terminal for the sustainable aviation fuel production process includes an industrial-grade blended fuel inbound weighing sensor, a radio frequency identification (RFID) reader / writer, a production unit feed monitoring device, and a sustainable aviation fuel outbound weighing sensor; acquiring raw data from the sustainable aviation fuel production process, including: The weight of the industrial-grade mixed oil upon entering the warehouse is obtained through the industrial-grade mixed oil weighing sensor. The source information of industrial-grade blended oil is obtained through the radio frequency identification reader / writer; The production batch number is generated by the material feeding monitoring equipment of the production device, and the production batch number is associated with the source information and the weight of the goods entering the warehouse. The weight of sustainable aviation fuel leaving the warehouse is obtained through the sustainable aviation fuel outbound weighing sensor.

[0012] Optionally, generating standardized data based on the original data includes: Convert the raw data into a JSON object format; Extract all keys from the JSON object and reorder all key-value pairs lexicographically; If the JSON object contains nested sub-objects or arrays, a recursive depth-sorting method is used to obtain the standardized data.

[0013] Optionally, storing the data fingerprint on the blockchain distributed ledger includes: The data fingerprint and basic index information are recorded in the blockchain distributed ledger to obtain a proof of evidence receipt, which includes the block height and transaction hash. The evidence receipt is associated with the original data and stored in the off-chain database.

[0014] Optionally, the step of verifying the original data based on the original data stored in the off-chain database and the data fingerprint stored in the blockchain distributed ledger includes: Obtain the original data to be verified from the off-chain database; The steps of generating standardized data and performing hash operations are performed on the original data to be verified to obtain the fingerprint of the data to be verified. The fingerprint of the data to be verified is compared with the fingerprint of the data stored in the blockchain distributed ledger; If the comparison matches, it is determined that the original data to be verified has not been tampered with.

[0015] To address the aforementioned technical problems, this application also provides a trusted data processing apparatus for sustainable aviation fuel environmental equity accounting, comprising: The data acquisition module is used to acquire raw data collected in real time by IoT acquisition terminals at each stage of the sustainable aviation fuel supply chain. The entire supply chain includes at least the waste catering oil collection and transportation stage, the waste catering oil treatment stage, the industrial-grade blended oil transportation stage, the sustainable aviation fuel production stage, the sustainable aviation fuel transportation stage, and the airport warehousing stage. The data processing module is used to generate standardized data based on the original data, and perform hash operations on the standardized data to obtain data fingerprints; The data storage module is used to store the data fingerprint on the blockchain distributed ledger and store the original data in an off-chain database, and establish a mapping relationship between the original data and the data fingerprint; The data verification module is used to verify the original data based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger. The equity accounting module is used to determine the environmental equity accounting results for sustainable aviation fuel based on the verified raw data.

[0016] To address the aforementioned technical problems, this application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the aforementioned trusted data processing method for sustainable aviation fuel environmental equity accounting.

[0017] To address the aforementioned technical problems, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned trusted data processing method for sustainable aviation fuel environmental equity accounting.

[0018] The credible data processing method, apparatus, computer equipment, and storage medium for sustainable aviation fuel environmental rights accounting provided in this invention deploy IoT data collection terminals at each stage of the supply chain to automatically acquire raw data in real time, replacing manual data entry, improving data collection efficiency and reducing the risk of human error and tampering. Data fingerprints are generated using hash operations and stored on the blockchain for verification, while the raw data is stored in an off-chain database with a mapping relationship established, achieving data tamper-proofing and traceability verification. Based on the verification mechanism of on-chain fingerprints and off-chain data, the authenticity of the input data used for environmental rights accounting is guaranteed. Finally, the accounting result is determined based on the verified data, improving the accuracy and credibility of sustainable aviation fuel environmental rights accounting and helping to solve the problems of double counting and false claims caused by unreliable data. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an exemplary system architecture diagram to which this application can be applied; Figure 2 This is a flowchart of an embodiment of the trusted data processing method for sustainable aviation fuel environmental equity accounting in this application; Figure 3 This is a schematic diagram of a structure of an embodiment of a trusted data processing apparatus for sustainable aviation fuel environmental equity accounting according to this application; Figure 4 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 ,like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0025] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc.

[0026] Terminal devices 101, 102, and 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 players (Moving Picture Experts Group Audio Layer IV), laptops, and desktop computers, etc.

[0027] Server 105 can be a server that provides various services, such as a backend server that supports the pages displayed on terminal devices 101, 102, and 103.

[0028] It should be noted that the trusted data processing method for sustainable aviation fuel environmental rights accounting provided in this application embodiment is executed by the server, and correspondingly, the trusted data processing device for sustainable aviation fuel environmental rights accounting is set in the server.

[0029] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included. The terminal devices 101, 102, and 103 in this embodiment can specifically correspond to application systems in actual production.

[0030] Please see Figure 2 , Figure 2 This invention illustrates a reliable data processing method for sustainable aviation fuel environmental equity accounting, as provided by an embodiment of the present invention, which is applied to... Figure 1 Taking the server-side as an example, the details are as follows: S201: Obtain raw data collected in real time by IoT data collection terminals at each stage of the sustainable aviation fuel supply chain. The entire supply chain includes at least the waste cooking oil collection and transportation stage, the waste cooking oil treatment stage, the industrial-grade blended oil transportation stage, the sustainable aviation fuel production stage, the sustainable aviation fuel transportation stage, and the airport warehousing stage.

[0031] Specifically, taking sustainable aviation fuel produced from waste cooking oil through a hydrogenation process of esters and fatty acids as an example, the entire supply chain of sustainable aviation fuel includes the collection and transportation of waste cooking oil, the processing of waste cooking oil into industrial-grade blended oil, the transportation of industrial-grade blended oil, the production of sustainable aviation fuel, and the transportation of sustainable aviation fuel to airport storage.

[0032] Among them, the hydrogenation treatment process for esters and fatty acids refers to the technical route of converting waste catering oils into renewable aviation kerosene that meets aviation fuel standards through chemical reactions such as hydrogenation deoxygenation, isomerization, and cracking.

[0033] It should be noted that IoT data acquisition terminals are combinations of sensing devices deployed at various physical links in the supply chain. Their function is to convert events occurring in the physical world, such as raw material transfers, weight changes, and location movements, into digital data that can be recognized and processed by a computer system in real time. Each terminal sends the collected data to a cloud-based data platform through a unified communication protocol, thereby providing raw input for subsequent data standardization processing.

[0034] In this specific optional embodiment, the IoT data collection terminal for the waste catering oil collection and transportation process includes a vehicle-mounted weighing sensor, a GPS module, and an RFID tag reader / writer; it acquires raw data from the waste catering oil collection and transportation process, including: The RFID electronic tag on the waste catering grease drum is read by an RFID electronic tag reader to obtain the drum number; The weight of waste cooking oil collected is obtained through vehicle-mounted weighing sensors; The collection timestamp and collection location are obtained through the Global Positioning System module.

[0035] In the collection and transportation of waste cooking oil, the IoT data collection terminal includes vehicle-mounted weighing sensors, GPS modules, and RFID electronic tag readers.

[0036] The system includes an onboard weighing sensor installed on the collection vehicle to measure the weight of the waste cooking oil loaded each time it is filled. This sensor can be a strain gauge load cell or a hydraulic load cell. A GPS module is used to record the geographical location and driving trajectory of the collection vehicle in real time. The technologies used include, but are not limited to, GPS and BeiDou satellite navigation systems. An RFID tag reader is used to read the electronic tags pre-installed on the waste cooking oil drums. The tags on the drums store information such as the drum number, the name of the source catering company, and historical collection records.

[0037] In the specific process, after arriving at the catering establishment, collection personnel move the waste cooking oil drums labeled with RFID tags onto the vehicle's onboard weighing sensor. The reader automatically senses and reads the drum number from the tag, and the weighing sensor simultaneously acquires the drum's gross weight. The system automatically calculates the net weight of the collected waste cooking oil based on pre-stored drum hull weight data. The GPS module records the latitude and longitude coordinates and timestamp of the current collection moment. This step, through the collaborative work of the aforementioned terminals, achieves automatic data collection of the quantity, source, and geographical location of waste cooking oil from the collection source, eliminating the need for manual weighing and handwritten records. This improves the efficiency and accuracy of data collection during the collection process and reduces the possibility of data distortion caused by manual entry.

[0038] In this specific optional embodiment of Example 1, the IoT data acquisition terminal for the waste catering oil treatment process includes an inbound weighing sensor, an RFID reader / writer, a processing tank feed monitoring device, and an outbound weighing sensor; it acquires raw data from the waste catering oil treatment process, including: The weight of waste cooking oil entering the warehouse is obtained through the inbound weighing sensor; Information on the source of waste cooking oil is obtained through radio frequency identification (RFID) readers. The processing batch number is generated by the feed monitoring equipment of the processing tank, and the processing batch number is associated with the source information and the weight of the incoming goods. The outbound weight of industrial-grade mixed oil is obtained by using an outbound weighing sensor.

[0039] In the waste cooking oil treatment process, IoT data collection terminals include inbound weighing sensors, RFID readers, infeed monitoring equipment for treatment tanks, and outbound weighing sensors.

[0040] The system includes: Inbound weighing sensors, typically installed in the raw material receiving area of ​​the processing plant in the form of weighbridges, to measure the total weight of waste cooking oil delivered to the plant; RFID readers installed in the raw material receiving area to read RFID tags on transport vehicles and oil drums to obtain the source information of the waste cooking oil; a processing tank feed monitoring device installed on the feed pipe of the processing tank to automatically generate a unique batch number when waste cooking oil is pumped into the tank, and to bind this batch number to the previously obtained source information and inbound weight of the waste cooking oil; and outbound weighing sensors installed in the outbound loading area of ​​the industrial-grade mixed oil to measure the outbound weight of the industrial-grade mixed oil produced after hydrogenation ester and fatty acid processing.

[0041] In the specific operation, after vehicles transporting waste cooking oil enter the raw material receiving area of ​​the processing plant, their weight is automatically measured by inbound weighing sensors. Simultaneously, RFID readers acquire the source information from the vehicle and oil drum tags. When the waste cooking oil is pumped into the designated processing tank, the tank's feed monitoring equipment generates a processing batch number and associates this batch number with the source information and inbound weight. After processing, the industrial-grade mixed oil is weighed by outbound weighing sensors in the outbound loading area before being loaded onto trucks. The system automatically associates the processing batch number with the outbound weight of the industrial-grade mixed oil and uploads this information. This step automatically binds the source information and inbound weight of the waste cooking oil with the processing batch number and the outbound weight of the industrial-grade mixed oil, achieving full-process data tracking from raw material input to intermediate product output. This improves the traceability of data in the processing stage and provides a data foundation for subsequent material balance verification.

[0042] In the industrial-grade blended oil transportation process, the IoT data collection terminals include vehicle-mounted weighing sensors, GPS modules, and RFID readers. The operation in this stage is similar to that of the waste cooking oil collection process. The vehicle-mounted weighing sensors are used to obtain the transport weight of the industrial-grade blended oil, the GPS module is used to record the vehicle's trajectory and mileage, and the RFID reader is used to read the electronic tags on the industrial-grade blended oil storage tanks or transport containers to confirm the origin of the goods.

[0043] Specifically, when the industrial-grade blended fuel is loaded onto the truck at the processing plant, the onboard weighing sensor records the weight of the loaded fuel. The transport vehicle then proceeds to the sustainable aviation fuel production plant, where a GPS module continuously records the route and cumulative mileage. This step, through the coordinated collection of transport weight and mileage data by the aforementioned sensors, provides input data for subsequent raw material receiving verification in the sustainable aviation fuel production process and for calculating transport emissions in the life-cycle carbon emissions accounting.

[0044] In this specific optional embodiment of Example 1, the IoT data acquisition terminal for the industrial-grade blended fuel transportation link and / or sustainable aviation fuel transportation link includes a vehicle-mounted weighing sensor, a GPS module, and an RFID reader / writer; acquiring raw data from the industrial-grade blended fuel transportation link and / or sustainable aviation fuel transportation link includes: The transport weight is obtained through on-board weighing sensors; The driving trajectory and mileage of the transport vehicles are obtained through the Global Positioning System module.

[0045] In this specific optional embodiment of Example 1, the IoT data acquisition terminal for the sustainable aviation fuel production process includes an industrial-grade blended fuel inbound weighing sensor, a radio frequency identification (RFID) reader / writer, a production unit feed monitoring device, and a sustainable aviation fuel outbound weighing sensor; it acquires raw data from the sustainable aviation fuel production process, including: The weight of industrial-grade mixed oil entering the warehouse is obtained by using an industrial-grade mixed oil weighing sensor. The source information of industrial-grade blended oil is obtained through an RFID reader / writer; The production batch number is generated by the feed monitoring equipment of the production unit, and the production batch number is associated with the source information and the weight of the goods entering the warehouse. The weight of sustainable aviation fuel leaving the warehouse is obtained through a sustainable aviation fuel outbound weighing sensor.

[0046] In the sustainable aviation fuel production process, IoT data collection terminals include industrial-grade blended fuel inbound weighing sensors, RFID readers, production unit feed monitoring equipment, and sustainable aviation fuel outbound weighing sensors.

[0047] The industrial-grade blended oil receiving weighing sensor is installed in the raw material receiving area of ​​the sustainable aviation fuel production plant to measure the incoming weight of the industrial-grade blended oil. An RFID reader is used to acquire the source information of the industrial-grade blended oil, including the batch number and processing plant information of the previous processing stage. The production unit feed monitoring equipment is installed on the production unit feed pipeline to automatically generate a unique production batch number when the industrial-grade blended oil enters the sustainable aviation fuel production unit, and binds this production batch number to the preceding industrial-grade blended oil source information and incoming weight. The sustainable aviation fuel outgoing weighing sensor is installed in the sustainable aviation fuel outgoing loading area to measure the outgoing weight of qualified sustainable aviation fuel produced after processing by the sustainable aviation fuel production process (including hydrodeoxygenation, isomerization, cracking, and subsequent distillation processes in the hydrotreated ester and fatty acid processes). This step, by associating the source information of the industrial-grade blended oil with the production batch number and the sustainable aviation fuel outgoing weight, achieves full-process data tracking from raw material input to finished product output, which is beneficial to improving the traceability and accuracy of material conversion data in the production process.

[0048] In the sustainable aviation fuel transportation segment, the IoT data collection terminals include vehicle-mounted weighing sensors, GPS modules, and RFID readers. This segment operates similarly to the industrial-grade blended fuel transportation segment. The vehicle-mounted weighing sensors acquire the weight of the sustainable aviation fuel being transported, the GPS module records the vehicle's trajectory and mileage, and the RFID reader reads the electronic tags on the sustainable aviation fuel storage tanks to confirm product origin and batch information. The transportation weight and mileage data collected in this segment provide input data for airport warehousing verification and for calculating finished product transportation emissions in the full lifecycle carbon emission accounting.

[0049] In this specific optional implementation of Embodiment 1, the IoT data acquisition terminal for the airport inbound process includes a sustainable aviation fuel inbound weighing sensor and a radio frequency identification (RFID) reader / writer; acquiring the raw data of the airport inbound process includes: The airport storage weight of sustainable aviation fuel is obtained through a sustainable aviation fuel storage weighing sensor. Information on the source of sustainable aviation fuel can be obtained through radio frequency identification (RFID) readers.

[0050] At the airport receiving stage, IoT data collection terminals include sustainable aviation fuel receiving weighing sensors and RFID readers. The sustainable aviation fuel receiving weighing sensors, which can be installed in the airport's sustainable aviation fuel receiving area in the form of weighbridges or pipeline flow meters, are used to measure the weight of sustainable aviation fuel entering the airport storage tanks. The RFID readers are used to read electronic tags on transport vehicles or sustainable aviation fuel storage tanks to obtain the source information of the sustainable aviation fuel (including production batch number, manufacturer information, etc.). In practice, after the tanker truck carrying sustainable aviation fuel arrives at the airport, the receiving weighing sensor measures the airport receiving weight, and the RFID reader simultaneously obtains the source information of the sustainable aviation fuel. The system packages and uploads the source information, receiving weight, and airport number, among other data. This stage completes the last-mile data collection for sustainable aviation fuel from the production plant to the consumer, providing the final data node for the closed loop of the entire supply chain data chain.

[0051] Through the collaborative work of the IoT data collection terminals at each stage, key data across the entire sustainable aviation fuel supply chain—from the source of waste cooking oil collection to the airport storage of sustainable aviation fuel—is automatically collected and uploaded in real time. Each terminal device is equipped with a device number and digital signature, and the collected data is accompanied by a trusted timestamp and device identification, making each piece of data traceable to its source terminal and collection time. This helps ensure the authenticity and non-repudiation of the original data, providing a reliable data source for subsequent data standardization processing and blockchain-based evidence storage.

[0052] Optionally, after acquiring the raw data from the aforementioned stages, the cloud-based data platform receives data packets uploaded from various IoT data acquisition terminals. Each terminal sends data to the data platform via a unified communication protocol. Upon receiving the data, the data platform parses and validates the data packets, extracts the raw data fields from each stage, and stores them according to a preset data model to facilitate data standardization processing in subsequent steps.

[0053] S202: Based on the original data, generate standardized data and perform hash operations on the standardized data to obtain data fingerprints.

[0054] In a specific optional implementation of this embodiment, generating standardized data based on raw data includes: converting the raw data into a JSON object format; extracting all keys in the JSON object, and reordering all key-value pairs in lexicographical order; if the JSON object contains nested sub-objects or arrays, performing deep sorting in a recursive manner to obtain the standardized data.

[0055] In a specific optional implementation of this embodiment, the performing a hash operation on the standardized data to obtain a data fingerprint includes: performing an operation on the standardized data using an MD5 or SHA series hash algorithm to generate the data fingerprint.

[0056] Specifically, after receiving the raw data packets uploaded by the IoT collection terminals at each link, the cloud data middle platform first parses and validates the data packets, extracts valid fields in the data payload, and then converts the valid data into a standardized format. In this embodiment, the standardized data refers to a data representation with a deterministic format obtained by reorganizing the raw data according to a unified data structure and encoding rule, which aims to eliminate differences in field naming, data types and structural hierarchies of data from different sources, so that subsequent hash operations can be performed on a consistent and reproducible input basis.

[0057] Further, the process of converting raw data into standardized data specifically includes the following processing manners. First, the raw data is converted into a JavaScript Object Notation (i.e., JSON) object format.

[0058] JSON is a lightweight data interchange format that adopts a key-value pair organization method, and has good structural expression capability and cross-platform compatibility.

[0059] For example, a JSON object formed after converting raw data uploaded in a certain transportation link can be expressed as {"transportWeight": 15000, "vehicleId": "E A12345", "gpsPoints": [{"lat":30.52, "lng": 114.32}, {"lat": 30.53, "lng": 114.33}]}. Subsequently, all keys in the JSON object are extracted, and all key-value pairs are rearranged in lexicographical order (that is, in alphabetical order of the key names).

[0060] If the JSON object contains nested sub-objects or arrays, a recursive approach is used to sort the data layer by layer, performing the same lexicographical sorting operation on the key-value pairs at each level until the innermost element is sorted, ultimately resulting in fully sorted standardized JSON data.

[0061] It's important to note that deterministically sorting the key-value pairs before hashing ensures that data with the same semantics generates JSON strings with completely consistent character sequences across different transmission batches and processing environments. This guarantees the consistency and reproducibility of subsequent hashing results. Without sorting, the order in which fields are uploaded by IoT terminals may vary due to network transmission or terminal implementation differences, potentially generating different hash values ​​for the same data, leading to mismatches during subsequent data verification.

[0062] Furthermore, after obtaining the standardized data, a hash operation is performed on the standardized data to generate a data fingerprint. A hash operation is a mathematical transformation process that maps input data of arbitrary length to a binary string of fixed length through a hash function. This transformation is unidirectional and collision-resistant, meaning that the original input cannot be derived from the hash value, and the probability of different input data producing the same hash value is extremely low.

[0063] In this embodiment, the data fingerprint is the fixed-length hash value output by the hash operation. As the unique digital identifier of the standardized data, it can be understood as the digital ID card of the data. Any modification to the original data content will cause the hash value to change, so that the recalculated hash value cannot match the original hash value.

[0064] Optional implementations of hash algorithms include, but are not limited to, MD5, SHA-1, SHA-256, and SHA-512 algorithms. These algorithms are all publicly available standard cryptographic hash functions with good computational efficiency and collision resistance.

[0065] Preferably, this embodiment uses the SHA-256 algorithm as the implementation method for hash operation to achieve a reasonable balance between security and computational efficiency. Alternatively, the MD5 algorithm or SHA-512 algorithm can be selected according to actual security requirements. Taking SHA-256 as an example, its output is a fixed-length 256-bit binary string, which is usually presented and stored as a 64-bit hexadecimal string.

[0066] Through this step, the original data is transformed into standardized JSON data with a unified format and defined structure. Furthermore, a data fingerprint, uniquely bound to the data content, is generated through hash calculation. Standardization eliminates the heterogeneity of data formats across different stages and terminals, providing a unified data format foundation for subsequent on-chain evidence storage. The fixed-length data fingerprint generated by hash calculation is smaller in size, easier to store and compare than the original data, facilitating efficient recording and rapid retrieval in the blockchain distributed ledger. Simultaneously, the one-way nature of hash values ​​ensures that even if the on-chain data fingerprint is made public, it is impossible to deduce the specific content of the original data from it, thus protecting the privacy of commercial data.

[0067] S203: Store the data fingerprint on the blockchain distributed ledger and store the original data in an off-chain database to establish a mapping relationship between the original data and the data fingerprint.

[0068] In a specific optional implementation of this embodiment, storing the data fingerprint on the blockchain distributed ledger includes: The data fingerprint and basic index information are recorded in the blockchain distributed ledger to obtain a proof of storage receipt, which includes the block height and transaction hash. The evidence receipt is associated with the original data and stored in an off-chain database.

[0069] Specifically, after generating the data fingerprint in step S202, this step records the data fingerprint into the blockchain distributed ledger. Simultaneously, the larger original data containing detailed business information is stored in a conventional off-chain database, and the two are linked through a mapping relationship. The blockchain distributed ledger is a decentralized data storage technology. Its core feature is that data is linked sequentially in blocks, each containing the hash value of the previous block, forming a chain structure. Tampering with the data in any block will invalidate the hash values ​​of all subsequent blocks, thus technically ensuring that data already on the chain is difficult to modify or delete.

[0070] It should be noted that the blockchain network used in this embodiment of the invention can be an underlying blockchain platform that supports smart contract deployment, such as Ethereum, Hyperledger Fabric, or FISCO BCOS, or other consortium blockchains or public blockchains with distributed consensus capabilities and data storage functions. Preferably, this embodiment uses a consortium blockchain architecture as the implementation method of the blockchain distributed ledger, so that all participants in the supply chain (including waste cooking oil collection and transportation companies, waste cooking oil processing companies, sustainable aviation fuel production companies, airlines, and regulatory authorities, etc.) can join the blockchain network and verify data after obtaining authorization, while avoiding the performance bottlenecks and data privacy issues that public blockchains may bring.

[0071] Furthermore, in the process of storing data fingerprints on the blockchain, in addition to the data fingerprint itself, basic index information also needs to be recorded in the blockchain distributed ledger. Basic index information refers to a set of index fields that uniquely identify the attributes of the data transaction, including at least the identifier of the supply chain link to which the data belongs, the data collection timestamp, and the batch number associated with the data. By recording the basic index information and data fingerprint together on the blockchain, it is convenient to retrieve and locate the data fingerprint on the chain by link, batch, or time range, quickly locking the target evidence record without traversing all on-chain data. For example, for data generated in the waste catering oil processing link, its basic index information could include the processing batch number, processing plant number, and waste catering oil storage time; for data generated in the sustainable aviation fuel transportation link, its basic index information could include the transportation vehicle number, sustainable aviation fuel production batch number, and transportation date.

[0072] Once the data fingerprint and basic index information are recorded in the blockchain distributed ledger, the blockchain network assigns a unique proof of authenticity (PEA) receipt to the transaction. This receipt includes the block height and transaction hash. The block height indicates the position number of the block in the blockchain where the transaction was confirmed, and the transaction hash is the unique identifier for the transaction. The PEA receipt serves as crucial evidence for subsequent data verification and traceability.

[0073] Specifically, the blockchain network packages the data fingerprint into a block and returns a proof receipt, which includes the block height and transaction hash.

[0074] Based on this, this embodiment associates and stores the evidence receipt with the original data in an off-chain database. The off-chain database can be a relational database (e.g., MySQL, PostgreSQL) or a non-relational database (e.g., MongoDB) to store the complete original data and the corresponding evidence receipt information, including block height and transaction hash. Through this mapping relationship, during subsequent verification, the original data to be verified and its corresponding evidence receipt can be retrieved from the off-chain database, and the corresponding on-chain data fingerprint can be read from the blockchain based on the transaction hash in the evidence receipt for comparison.

[0075] Through this process, data fingerprints are recorded in the blockchain's distributed ledger, leveraging the blockchain's tamper-proof nature to ensure their immutability. The original data is stored in an off-chain database, avoiding the storage costs and performance overhead of directly uploading large amounts of raw data to the blockchain. A one-to-one mapping relationship is established between the data fingerprints on the blockchain and the original data in the off-chain database. This ensures that any tampering with the original data can be detected promptly by recalculating the hash value and comparing it with the on-chain data fingerprint, thus establishing a verifiable link between the original data and the on-chain evidence, providing a foundation for subsequent data verification. Simultaneously, the presence of the original data in the off-chain database facilitates daily business inquiries and big data analysis for all participants in the supply chain. Complete business details can be obtained without frequent blockchain access, improving the efficiency and flexibility of data retrieval.

[0076] S204: Verify the original data based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger.

[0077] In this specific optional implementation of Embodiment 1, the original data is verified based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger, including: Retrieve the raw data to be verified from the off-chain database; The raw data to be verified is subjected to steps of generating standardized data and performing hash operations to obtain the fingerprint of the data to be verified; The fingerprint of the data to be verified is compared with the data fingerprint stored in the blockchain distributed ledger; If the comparison matches, it is determined that the original data to be verified has not been tampered with.

[0078] Specifically, in subsequent settlement, auditing, or environmental rights accounting stages, when it is necessary to verify the authenticity of a particular data item or batch, the data verification party performs this step to check whether the original data has been tampered with. The verification party can be any participant in the supply chain, including waste cooking oil collection and transportation companies, waste cooking oil processing companies, sustainable aviation fuel production companies, airlines, third-party auditing agencies, or regulatory authorities, etc. Any party can independently perform the verification operation without relying on the credit endorsement of other participants.

[0079] Furthermore, when performing data verification, the raw data to be verified is first retrieved from the off-chain database. The raw data to be verified can be a single data record from a certain link in the supply chain, or multiple data records associated with the same business batch.

[0080] Specifically, the verifier determines the scope of data to be verified based on business needs. By querying the original data table stored in the off-chain database, and using index fields such as data collection time, supply chain link identifier, or business batch number, the verifier obtains the corresponding original data record and its associated stored evidence receipt. The evidence receipt contains the block height and transaction hash corresponding to when the data was uploaded to the blockchain. Through the transaction hash, the data fingerprint stored when the data was uploaded to the blockchain distributed ledger can be accurately located and read.

[0081] After obtaining the original data to be verified, the steps of generating standardized data and performing hash operations as described in S202 are re-executed on the original data to be verified, namely: converting the original data to be verified into JSON object format, recursively sorting all key-value pairs in lexicographical order to obtain standardized data, and then using the same hash algorithm as in S202 to operate on the standardized data to generate the fingerprint of the data to be verified.

[0082] It should be noted that the hash algorithm used here must be completely consistent with the hash algorithm used in S202 to generate the original data fingerprint. For example, if the SHA-256 algorithm is used in S202, then the SHA-256 algorithm must also be used here. Otherwise, even if the original data has not been tampered with, different hash values ​​will be generated due to different algorithms, which may lead to misjudgment.

[0083] After obtaining the fingerprint of the data to be verified, the fingerprint of the data to be verified is compared with the fingerprint of the data obtained from the blockchain distributed ledger.

[0084] Specifically, the verifier initiates a query request to the blockchain network based on the transaction hash in the evidence receipt. The blockchain network returns the original data fingerprint recorded in the transaction (i.e., the data fingerprint stored on the chain in S203) based on the transaction hash. Then, the locally recalculated data fingerprint to be verified is compared byte by byte with the original data fingerprint returned on the chain.

[0085] If the comparison results are consistent, meaning the fingerprint of the data to be verified is exactly the same as the fingerprint stored on the blockchain, then it is determined that the original data to be verified has not been tampered with since the data fingerprint was generated and stored on the blockchain in S202, and the data possesses authenticity and integrity. For example, if the outbound weight data of a batch of sustainable aviation fuel is recorded as 15,230 kg in the off-chain database, and the value obtained by recalculating the hash during verification matches the data fingerprint stored on the blockchain, then it indicates that the outbound weight data has not been modified since the notarization. If the comparison results are inconsistent, it is determined that the original data to be verified has been tampered with, indicating that the authenticity of the data is questionable and should not be used for subsequent environmental rights accounting. In this case, the verifying party can also combine the block height and the timestamp corresponding to the transaction hash in the notarization receipt to trace the point in time when data tampering may have occurred, meaning that any modifications made to the original data after the on-chain notarization time can be detected.

[0086] Through this data verification step, the authenticity of the original data no longer relies on the credit commitment of the data management party, but is verified through hash comparison technology. Any party can independently complete the verification process without relying on authorization or endorsement from a centralized institution, which is conducive to improving the level of data trust in cross-entity collaborative scenarios. At the same time, because the hash value comparison results are deterministic and objective, there is no room for subjective judgment, thus ensuring the accuracy and reliability of the verification conclusions. For tamper-proof and trustworthy data, it can be safely used in subsequent environmental rights accounting steps, while tampered data can be detected and excluded in a timely manner, which helps to ensure the quality of the input data on which environmental rights accounting is based from the source.

[0087] S205: Determine the environmental equity accounting results for sustainable aviation fuel based on the verified raw data.

[0088] In a specific optional implementation of this embodiment, determining the environmental equity accounting result of sustainable aviation fuel based on the verified raw data includes: Extract the input parameters required for environmental equity accounting of sustainable aviation fuel from the verified raw data; Based on the input parameters, the environmental equity accounting results for sustainable aviation fuel are calculated according to the preset accounting standards.

[0089] Specifically, after completing data verification and confirming that the original data has not been tampered with in step S204, this step performs the calculation of environmental rights for sustainable aviation fuel based on the verified original data that is authentic and complete. Environmental rights for sustainable aviation fuel refer to the equity certificates corresponding to the carbon emission reductions achieved by sustainable aviation fuel compared to traditional aviation fuel throughout its entire life cycle. These rights can be used in scenarios such as airlines' carbon emission compliance, carbon quota trading, or carbon credit declarations in voluntary emission reduction markets. The accuracy of environmental rights calculation highly depends on the authenticity and traceability of basic data related to carbon emissions throughout the entire supply chain.

[0090] It should be noted that the environmental rights accounting involved in this embodiment does not refer to a simple summary of raw data. Rather, it involves performing prescribed calculations and processing on credible data collected and verified from all stages of the entire supply chain, based on industry-recognized accounting standards and calculation models, to ultimately output environmental rights accounting results that conform to a standard format. The accounting standards in this embodiment include, but are not limited to, the sustainable aviation fuel carbon accounting standards issued by the International Air Transport Association (IATA), the carbon emission reduction calculation method for sustainable aviation fuel under the CORSIA mechanism of the International Civil Aviation Organization (ICAO), the greenhouse gas emission reduction calculation method for sustainable aviation fuel specified in the EU Renewable Energy Directive (RED), and relevant accounting guidelines issued by the Civil Aviation Administration of China. The above standards clearly stipulate the carbon emission calculation boundaries, emission factor selection, baseline determination, and emission reduction calculation methods for the entire life cycle of sustainable aviation fuel.

[0091] Furthermore, when calculating the environmental rights accounting results, the input parameters required for sustainable aviation fuel environmental rights accounting are first extracted from the verified raw data. After being collected and standardized in steps S201 and S202, the raw data is stored in a structured form in an off-chain database. The semantics and units of each field have been standardized during the data standardization process. Therefore, the verifier can quickly and accurately locate and extract the corresponding data items from the database according to the parameter requirements specified in the accounting standard.

[0092] Optionally, the accounting party can submit a parameter extraction request to the off-chain database through a query interface, based on the specific accounting standard adopted. The database will then return the corresponding parameter values ​​according to a preset field mapping relationship. The input parameters required for accounting include at least the quality (i.e., production or delivery volume) of sustainable aviation fuel and the life-cycle carbon emissions of sustainable aviation fuel. The life-cycle carbon emissions are calculated based on the accounting standard using basic data such as transportation emissions, process energy consumption, and material consumption at each stage of the supply chain.

[0093] Taking a batch of sustainable aviation fuel as an example, the input parameters required for calculation may include the delivery quality of the batch of fuel (obtained from the airport warehousing stage), the transportation distance and weight of waste catering oil collection (obtained from GPS and weighing sensors at the collection stage), the transportation distance and weight of industrial-grade blended oil (obtained from GPS and weighing sensors at the industrial-grade blended oil transportation stage), the transportation distance and weight of sustainable aviation fuel (obtained from GPS and weighing sensors at the SAF transportation stage), and the process energy consumption data of sustainable aviation fuel production (obtained from the production unit), etc.

[0094] After extracting all the input parameters required for the accounting, the environmental equity accounting results for sustainable aviation fuel are calculated based on the preset accounting standards.

[0095] Specifically, the accounting party will perform calculations on the extracted input parameters according to the calculation formulas specified in the accounting standards. For example, it will calculate the percentage of emissions reduction over the entire life cycle of sustainable aviation fuel compared to the baseline of traditional aviation fuel, and then determine the amount of environmental rights that can be claimed for this batch of sustainable aviation fuel. The entire calculation process can be completed using the accounting engine built into the environmental rights application layer. This accounting engine is pre-configured with calculation models and parameter mapping rules under different accounting standards, and can automatically execute the complete calculation process from parameter input to accounting result output without manual intervention.

[0096] Thus, steps S201 to S205 constitute a complete closed loop from data collection, data processing and storage, data verification to environmental rights accounting. The environmental rights accounting results, generated based on a trusted data chain automatically collected by IoT terminals across the entire supply chain, stored on blockchain, and verified, can be fully traced and verified for authenticity. Through this process, the input parameters upon which environmental rights accounting relies no longer require manual entry and hierarchical verification, but instead come directly from a verified and trusted dataset. This fundamentally addresses the long-standing technical risks of duplicate calculations and false claims within the industry, improves the accuracy and efficiency of sustainable aviation fuel environmental rights accounting, and enhances the market credibility and acceptability of the accounting results.

[0097] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0098] Figure 3 This diagram illustrates the principle block diagram of a trusted data processing device for sustainable aviation fuel environmental equity accounting, corresponding one-to-one with the trusted data processing method for sustainable aviation fuel environmental equity accounting in the above embodiments. (See diagram for reference.) Figure 3As shown, the functional modules of the trusted data processing device for sustainable aviation fuel environmental equity accounting are described in detail below: The data acquisition module 301 is used to acquire raw data collected in real time by IoT acquisition terminals in all links of the sustainable aviation fuel supply chain. The supply chain links include at least the waste catering oil collection and transportation link, the waste catering oil treatment link, the industrial-grade blended oil transportation link, the sustainable aviation fuel production link, the sustainable aviation fuel transportation link, and the airport warehousing link. The data processing module 302 is used to generate standardized data based on the original data, and perform a hash operation on the standardized data to obtain a data fingerprint; The data storage module 303 is used to store the data fingerprint on the blockchain distributed ledger and store the original data in an off-chain database, and establish a mapping relationship between the original data and the data fingerprint; The data verification module 304 is used to verify the original data based on the original data stored in the off-chain database and the data fingerprint stored in the blockchain distributed ledger. The equity accounting module 305 is used to determine the environmental equity accounting results for sustainable aviation fuel based on the verified raw data.

[0099] Specific limitations regarding the trusted data processing device for sustainable aviation fuel environmental equity accounting can be found in the limitations of the trusted data processing method for sustainable aviation fuel environmental equity accounting described above, and will not be repeated here. Each module in the aforementioned trusted data processing device for sustainable aviation fuel environmental equity accounting can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0100] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0101] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected via a system bus. It should be noted that only the computer device 4 with components connected to the memory 41, processor 42, and network interface 43 is shown in the figure; however, it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0102] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0103] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or D-interface display memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and its external storage device of the computer device 4. In this embodiment, the memory 41 is typically used to store the operating system and various application software installed on the computer device 4, such as the program code of a trusted data processing method for sustainable aviation fuel environmental rights accounting. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or will be output.

[0104] In some embodiments, the processor 42 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run program code stored in the memory 41 or process data, such as program code for a trusted data processing method for sustainable aviation fuel environmental equity accounting.

[0105] The network interface 43 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 4 and other electronic devices.

[0106] This application also provides another embodiment, namely, a computer-readable storage medium storing an interface display program that can be executed by at least one processor to cause the at least one processor to perform the steps of the trusted data processing method for sustainable aviation fuel environmental equity accounting as described above.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0108] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A reliable data processing method for sustainable aviation fuel environmental equity accounting, characterized in that, include: The system acquires raw data collected in real time by IoT data collection terminals at each stage of the sustainable aviation fuel supply chain. The entire supply chain includes at least the waste cooking oil collection and transportation stage, the waste cooking oil treatment stage, the industrial-grade blended oil transportation stage, the sustainable aviation fuel production stage, the sustainable aviation fuel transportation stage, and the airport warehousing stage. Based on the original data, standardized data is generated, and a hash operation is performed on the standardized data to obtain a data fingerprint; The data fingerprint is stored on the blockchain distributed ledger, and the original data is stored in an off-chain database to establish a mapping relationship between the original data and the data fingerprint. The original data is verified based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger. Based on the verified raw data, the environmental equity accounting results for sustainable aviation fuel are determined.

2. The method according to claim 1, characterized in that, The IoT data acquisition terminal for the waste cooking oil collection and transportation process includes a vehicle-mounted weighing sensor, a GPS module, and an RFID tag reader / writer; it acquires raw data from the waste cooking oil collection and transportation process, including: The RFID electronic tag reader reads the RFID electronic tag on the waste catering grease drum to obtain the drum number; The weight of waste cooking oil collected is obtained through the vehicle-mounted weighing sensor; The collection timestamp and collection location are obtained through the Global Positioning System module.

3. The method according to claim 1, characterized in that, The IoT data acquisition terminal for the waste cooking oil treatment process includes an inbound weighing sensor, an RFID reader / writer, a tank feed monitoring device, and an outbound weighing sensor; it acquires raw data from the waste cooking oil treatment process, including: The weight of waste cooking oil entering the warehouse is obtained through the inbound weighing sensor. The source information of waste cooking oil is obtained through the radio frequency identification reader / writer; The processing batch number is generated by the feeding monitoring device of the processing tank, and the processing batch number is associated with the source information and the weight of the goods entering the warehouse. The outbound weight of the industrial-grade mixed oil is obtained through the outbound weighing sensor.

4. The method according to claim 1, characterized in that, The IoT data acquisition terminal for the industrial-grade blended fuel transportation link and / or the sustainable aviation fuel transportation link includes a vehicle-mounted weighing sensor, a GPS module, and an RFID reader / writer; it acquires raw data from the industrial-grade blended fuel transportation link and / or the sustainable aviation fuel transportation link, including: The transport weight is obtained through the vehicle-mounted weighing sensor; The GPS module is used to obtain the driving trajectory and mileage of the transport vehicle.

5. The method according to claim 1, characterized in that, The IoT data acquisition terminals for the sustainable aviation fuel production process include an industrial-grade blended oil inbound weighing sensor, a radio frequency identification reader, a production unit feed monitoring device, and a sustainable aviation fuel outbound weighing sensor. Obtain raw data from the sustainable aviation fuel production process, including: The weight of the industrial-grade mixed oil upon entering the warehouse is obtained through the industrial-grade mixed oil weighing sensor. The source information of industrial-grade blended oil is obtained through the radio frequency identification reader / writer; The production batch number is generated by the material feeding monitoring equipment of the production device, and the production batch number is associated with the source information and the weight of the goods entering the warehouse. The weight of sustainable aviation fuel leaving the warehouse is obtained through the sustainable aviation fuel outbound weighing sensor.

6. The method according to claim 1, characterized in that, The step of generating standardized data based on the original data includes: Convert the raw data into a JSON object format; Extract all keys from the JSON object and reorder all key-value pairs lexicographically; If the JSON object contains nested sub-objects or arrays, a recursive depth-sorting method is used to obtain the standardized data.

7. The method according to claim 1, characterized in that, The step of storing the data fingerprint on the blockchain distributed ledger includes: The data fingerprint and basic index information are recorded in the blockchain distributed ledger to obtain a proof of evidence receipt, which includes the block height and transaction hash. The evidence receipt is associated with the original data and stored in the off-chain database.

8. The method according to claim 1, characterized in that, The step of verifying the original data based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger includes: Obtain the original data to be verified from the off-chain database; The steps of generating standardized data and performing hash operations are performed on the original data to be verified to obtain the fingerprint of the data to be verified. The fingerprint of the data to be verified is compared with the fingerprint of the data stored in the blockchain distributed ledger; If the comparison matches, it is determined that the original data to be verified has not been tampered with.

9. A trusted data processing device for sustainable aviation fuel environmental equity accounting, characterized in that, include: The data acquisition module is used to acquire raw data collected in real time by IoT acquisition terminals at each stage of the sustainable aviation fuel supply chain. The entire supply chain includes at least the waste catering oil collection and transportation stage, the waste catering oil treatment stage, the industrial-grade blended oil transportation stage, the sustainable aviation fuel production stage, the sustainable aviation fuel transportation stage, and the airport warehousing stage. The data processing module is used to generate standardized data based on the original data, and to perform a hash operation on the standardized data to obtain a data fingerprint; The data storage module is used to store the data fingerprint on the blockchain distributed ledger and store the original data in an off-chain database, and establish a mapping relationship between the original data and the data fingerprint; The data verification module is used to verify the original data based on the original data stored in the off-chain database and the data fingerprints stored in the blockchain distributed ledger. The equity accounting module is used to determine the environmental equity accounting results for sustainable aviation fuel based on the verified raw data.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the trusted data processing method for sustainable aviation fuel environmental equity accounting as described in any one of claims 1 to 8.

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