Full-automation coal supply chain intelligent integration and one-key settlement method and system

Abstract

The application discloses a full-automatic coal supply chain intelligent integration and one-key settlement method and system, and particularly relates to the technical field of coal supply chain. Firstly, coal supply chain multi-source data sets are collected, and data interaction of each participant is carried out based on a system interface unit, and digital reconstruction, process state machine modeling and main intelligent contract generation are carried out. Then, for state transfer rules, authorized trusted data sources are bound, and real-time monitoring of on-chain event flow is carried out through a secondary intelligent integration module, and event filtering and verification, logical correlation and evaluation, and executable instruction output are sequentially completed. Finally, the system automatically captures and records price parameters of each participant for settlement, and generates final blockchain settlement vouchers. Through the one-key settlement module, the application realizes a full-automatic closed loop from settlement parameter capture to fund clearing, and the one-key confirmation operation of the buyer does not need manual intervention, and through blockchain storage, the legality and non-tamperability of the settlement result are ensured.

Description

Technical Field

[0001] This invention relates to the field of coal supply chain technology, specifically to a fully automated intelligent integration and one-click settlement method and system for the coal supply chain. Background Technology

[0002] As a core pillar of my country's energy system, coal's supply chain covers multiple links, including coal mining, storage, transportation, quality inspection, sales and end consumption. It involves diverse participants and lengthy business processes, covering key aspects such as contract signing, coal mining, transportation, quality inspection, acceptance and settlement.

[0003] Traditional coal supply chain management methods suffer from several problems. On the one hand, offline business processes are highly non-standardized, with contract terms and execution rules often expressed in natural language, lacking a unified execution framework and resulting in high process deviation rates. On the other hand, data generated during supply chain operations, such as transportation trajectories, coal quality testing, and weighing, are scattered and heterogeneous in format, making it difficult to verify the authenticity of the data and effectively support the automatic execution of rules and accurate settlement.

[0004] While some existing technologies attempt to apply blockchain and IoT to the coal supply chain, they suffer from several drawbacks: First, they lack a deep integration mechanism between "preset rules and real-time data," making it impossible to automatically execute business rules through dynamic data. Second, they lack a quantitative evaluation system and fail to define evaluation functions for key aspects such as state transition, data verification, and settlement accounting, resulting in poor feasibility. Third, the settlement process is disconnected from business execution, making it impossible to achieve atomic multi-party clearing based on trusted data throughout the entire process, still requiring manual intervention for verification, and failing to meet the demands of full automation. Therefore, a technical solution is needed that can not only complete the initial integration of digital modeling of business processes but also achieve a secondary integration of dynamic fusion of runtime data and rules, thereby enabling final settlement without human intervention. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a fully automated intelligent integration and one-click settlement method and system for the coal supply chain, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a fully automated intelligent integration and one-click settlement method for the coal supply chain, comprising: S1: Through IoT technology, service process data of different participants in the coal supply chain are collected to obtain a multi-source dataset of the coal supply chain, and data interaction among the participants is carried out based on the system interface unit. S2: Intelligently integrate the multi-source datasets of the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; S3: Bind the state transition rules in the process state machine model to an authorized trusted data source and format the data source output data into standard on-chain events; S4: The main smart contract listens to the on-chain event stream in real time and performs secondary smart integration, including event filtering and verification, logical association and evaluation, and output of executable instructions, driving the process state machine to complete deterministic transitions. S5: Throughout the entire process of the state machine evolution driven by secondary intelligent integration, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

[0007] Preferred, a fully automated intelligent integration and one-click settlement system for the coal supply chain includes: Coal supply chain multi-source data acquisition module: Through Internet of Things (IoT) technology, it collects service process data from different participants in the coal supply chain to obtain a multi-source dataset of the coal supply chain, and facilitates data interaction among the participants based on the system interface unit; The first intelligent integration module: intelligently integrates multi-source datasets from the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; Trusted Data Adaptation Module: Binds the state transition rules in the process state machine model to an authorized trusted data source and formats the data source output into standard on-chain events; Secondary intelligent integration module: The main smart contract listens to the on-chain event stream in real time and performs secondary intelligent integration, including event filtering and verification, logical association and evaluation, and output of executable instructions, driving the process state machine to complete deterministic transitions; One-click settlement module: Throughout the entire process of secondary intelligent integration driving state machine evolution, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

[0008] The technical effects and advantages of this invention are as follows: 1. This invention reconstructs digitalization, process state machine modeling, and generates a master smart contract through a single intelligent integration, transforming the originally non-standardized offline coal supply chain business into a quantifiable and executable digital process, achieving tamper-proof and traceable data throughout the entire process, and solving the industry pain points of opaque processes and difficulty in defining responsibilities in traditional trade. 2. This invention integrates scattered data into standard on-chain events through secondary intelligent integration, and performs precise filtering and matching based on the current business status and batch identifier to ensure that only legal and related events are included in the rule evaluation. At the same time, it automatically verifies multiple event conditions through logic and operations, replacing the tedious process of manually checking multiple source data in the traditional way, and ensuring the accuracy and automation of state transition. 3. This invention achieves a fully automated closed loop from settlement parameter capture to fund clearing through a one-click settlement module. The buyer's "one-click confirmation" operation triggers the execution of the smart contract, and the funds are automatically transferred to the accounts of the mining party, logistics party and other participating parties according to the preset ratio, without the need for manual intervention throughout the process. At the same time, all settlement rules and data have been stored on the blockchain to ensure the legality and immutability of the settlement results. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0010] Figure 2 This is a schematic diagram of the method flow of the present invention.

[0011] Figure 3 This is a schematic diagram of a single intelligent integration process according to the present invention. Detailed Implementation

[0012] 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 embodiments of the present invention, and not all embodiments. 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.

[0013] Please see Figure 1 As shown, the present invention provides a fully automated intelligent integration and one-click settlement system for the coal supply chain, including a coal supply chain multi-source data acquisition module, a primary intelligent integration module, a trusted data adaptation module, a secondary intelligent integration module, and a one-click settlement module.

[0014] The coal supply chain multi-source data acquisition module is connected to the primary intelligent integration module, the trusted data adaptation module is connected to both the primary and secondary intelligent integration modules, and the one-click settlement module is connected to the secondary intelligent integration module.

[0015] Coal supply chain multi-source data acquisition module: Through Internet of Things (IoT) technology, it collects service process data from different participants in the coal supply chain to obtain a multi-source dataset of the coal supply chain, and facilitates data interaction among the participants based on the system interface unit; The first intelligent integration module: intelligently integrates multi-source datasets from the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; Trusted Data Adaptation Module: Binds the state transition rules in the process state machine model to an authorized trusted data source and formats the data source output into standard on-chain events; Secondary intelligent integration module: The main smart contract listens to the on-chain event stream in real time and performs secondary intelligent integration, including event filtering and verification, logical association and evaluation, and output of executable instructions, driving the process state machine to complete deterministic transitions; One-click settlement module: Throughout the entire process of secondary intelligent integration driving state machine evolution, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

[0016] Please see Figure 2 As shown, the fully automated intelligent integration and one-click settlement method for the coal supply chain includes: S1: Collecting service process data from different participants in the coal supply chain through IoT technology to obtain a multi-source dataset of the coal supply chain, and conducting data interaction among the participants based on system interface units; S2: Performing an intelligent integration of the multi-source dataset of the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; S3: Binding authorized trusted data sources to the state transition rules in the process state machine model, and formatting the data source output data into standard on-chain events; S4: The main smart contract monitors the on-chain event stream in real time and performs a secondary intelligent integration, including event filtering and verification, logical association and evaluation, and executable instruction output, driving the process state machine to complete deterministic transitions; S5: Throughout the process of the secondary intelligent integration driving the state machine evolution, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

[0017] S1: Through IoT technology, service process data of different participants in the coal supply chain are collected to obtain a multi-source dataset of the coal supply chain, and data interaction among the participants is carried out based on the system interface unit. This embodiment requires specific explanation of the different participating parties, including coal mine owners, logistics providers, quality inspectors, and buyers; the service process data includes participating party data, coal batch data, and contract terms data; the participating party data includes a set of participating parties, their qualification information, credit information, and blockchain certification information; the coal batch data includes coal trade batch identifiers, transport order numbers, and production certificate numbers publicly disclosed by the coal mine owners; the contract terms data includes a set of parameters for calculating coal trade prices, a set of coal trade quality indicator parameters, and a set of parameters for coal trade status qualification nodes.

[0018] This embodiment specifically explains that the multi-source dataset for the coal supply chain consists of pre-processed data, including deduplication, noise reduction, invalid data removal, and supplementation using linear interpolation. IoT technology is deployed in production workshops and coal yards to collect real-time production and inventory levels. GPS trackers and temperature and humidity sensors are installed on coal transport vehicles to collect transportation trajectories and coal storage environment data. API interfaces are used to connect to the coal consumption systems of end-user power plants (end-user coal-consuming enterprises), the testing systems of third-party quality inspection agencies, and settlement systems. A manual data entry interface is also provided for inputting unstructured data such as special contract terms.

[0019] Please see Figure 3 As shown, S2: The multi-source datasets of the coal supply chain are intelligently integrated, including digital reconstruction, process state machine modeling, and main smart contract generation, resulting in the main smart contract, which includes the following steps: S2.1: Digital Restructuring: Includes: S2.1.1: Participant Digitization: Based on multi-source datasets of the coal supply chain, the participants in the coal supply chain are first statistically analyzed to obtain a participant set P, P={p1,p2,...,p...}. n}, where n is the number of participants, p nLet's consider the nth participant. Then, using a blockchain decentralized identity (DID) framework, a unique digital identity ID is generated for each participant (formatted as "Participant Type Code + Unique Serial Number", "Miner-001"). The participant's qualification information, credit information, and blockchain authentication information are encrypted and bound to the digital identity ID. An identity credibility assessment index F(ID) is calculated: F(ID) = a1×s1 + a2×s2 + a3×s3, where s1 is the participant's qualification score, weighted by a score based on whether each participant possesses a license and the license's validity period. The weights sum to 1, and the weight of the license score is greater than the weight of the license validity score. If a license is possessed and all required licenses are available, the license score is 1; if one required license is missing, the score is 0.5; if two or more licenses are missing, the score is 0; if the license validity period is greater than one year, the license validity score is 1; 6-12 months results in a score of 0.5; and less than 6 months results in a score of 0. s2 is the participant's credit score, obtained by weighting scores based on whether there are supply chain default records in the past 3 years (such as delayed delivery, substandard quality, etc.), on-time delivery rate, and whether there are blacklist records, with a corresponding weight c. 1. The sum of c2 and c3 is 1, c1 = c2, and both c1 and c2 are greater than c3, for example, c1 = 0.4, c2 = 0.4, and c3 = 0.2; the score for no supply chain default records in the past 3 years is 1, and a single default deducts 0.2, down to 0. If there is a refusal to perform, the score is directly 0, such as the buyer refusing to pay; the on-time performance rate score is the ratio of the number of on-time performances in the past 3 years to the total number of on-time performances; the blacklist record score is 1 if not included in the blacklist by industry associations or credit platforms, and 0 if included; s3 is the participant certification score, i.e., completing both blockchain basic account registration and enterprise operation. The blockchain verification of the business license and legal representative's ID card is 1; completing only basic account registration without verification is 0.5; and failing to complete basic account registration is 0. a1, a2, and a3 are the weights for the corresponding scores, satisfying a1+a2+a3=1, such as a1=0.4, a2=0.4, and a3=0.2. Differentiated weights are set according to the type of coal supply chain participant (mining party / logistics party / quality inspection party) (e.g., the weight of s1 for mining parties is increased to 0.5, with mining party qualifications as the core). If F(ID) ≥ the corresponding threshold (e.g., 0.8), the participant's identity is credible and they are allowed to participate in supply chain business; otherwise, their registration is rejected. In this embodiment, it should be specifically noted that the credit scores of the participants can be obtained through blockchain-shared performance records and public credit platform data, and blockchain authentication information can be obtained through blockchain authentication data.

[0020] S2.1.2: Coal Batch Digitization: Using blockchain technology, a unique batch identifier L_id is generated for each coal transaction. The format is: coal mine digital identity ID + coal production date + batch serial number (e.g., mine-001-20251021-001, mine 001, the first batch of coal produced on October 21, 2025). A fixed-format field (e.g., "last 3 digits of mine ID + last 4 digits of production date + batch serial number") corresponding to the coal batch is extracted from the transport order number and used as the batch identifier segment. This batch identifier segment is embedded in the transport order number. Then, the coal asset valuation index F(L_id) is calculated: F(L_id) = b1 × sc1 + b2 × sc2, where sc1 is the coal production certificate. The verification score is calculated using hash consistency verification technology. The hash value of the batch identifier is compared with the hash value of the "coal mine digital identity ID + coal production date + batch serial number" in the production certificate number published by the coal mine. If the hash values ​​match, the result is 1; if there is no match or the hash values ​​do not match, the result is 0. sc2 represents the coal transportation order score. Similarly, the hash value of the batch identifier is compared with the hash value of the "batch identifier segment" in the logistics company's transportation order number. If the hash values ​​match, the result is 1; if there is no match or the hash values ​​do not match, the result is 0. b1 and b2 are the weights of the corresponding scores, such as b1=0.65 and b2=0.35. If F(L_id) ≥ the corresponding threshold (e.g., 0.8), the coal asset information is complete and traceable, and digital registration is completed; otherwise, the production certificate number and transportation order number need to be corrected or supplemented. This embodiment specifically explains that the coal production certificate contains a fixed segment of the coal mine's digital identity ID + coal production date. Through a string segmentation extraction algorithm, the segment of "coal mine ID + production date" corresponding to a certain batch of L_id is extracted from the "production certificate database" of the blockchain. Then, the certificate number containing this segment is retrieved from the "production certificate database". Finally, a hash consistency verification is performed.

[0021] S2.1.3: Digitalization of Contract Terms: Based on trade contract texts signed by multiple parties in the coal supply chain, the core terms dataset is mapped to a standardized parameter set HD_std through a pre-defined coal industry-specific "terms-parameters" mapping rule library. HD_std = [gd_std, zd_std, jd_std], where gd_std is the standard parameter set for coal trade price calculation, zd_std is the standard parameter set for coal trade quality indicators, and jd_std is the standard parameter set for qualified coal trade status nodes. gd_std = [g1, g2, ..., g n ], g nThis is the price dataset for the nth participant, where n is the number of participants. For example, for the coal mine (i=1), the price dataset includes the base unit price of coal (800 yuan / ton), calorific value, and the corresponding adjustment coefficient K=0.02 yuan / (ton·kcal), etc.; for the logistics provider (i=2), the price dataset includes transportation distance, transportation time, etc.; zd_std=[z1,z2,...,z n1 ], z n1 This is the n1th quality indicator parameter, where n1 is the number of quality indicator parameters, including but not limited to coal calorific value, ash content upper limit, sulfur content upper limit, etc. jd_std=[j1,j2,...,j...] n2 ], j n2 This is the parameter for the n2th qualified node, where n2 is the number of qualified nodes, including but not limited to qualified loading status and qualified quality inspection status. This embodiment requires a detailed explanation of the pre-defined coal industry-specific "clause-parameter" mapping rule library: Based on the core clause categories in trade contracts signed by multiple parties in the coal supply chain, it is divided into three main categories: price calculation mapping rules, quality indicator mapping rules, and qualification node mapping rules. Price calculation mapping rules convert basic unit prices, premium / discount rules, and profit-sharing ratios described in natural language into standardized numerical parameters and calculation formulas. For example, "For every 100 kcal increase in calorific value above the standard, the unit price increases by 2 yuan / ton" is converted to "Adjustment coefficient K = 0.02 yuan / (ton·kcal)". Quality indicator mapping rules convert quality standards described in natural language into standardized threshold parameters. For example, "Coal calorific value not less than 5500 kcal, ash content not more than 20%" is converted to "Q_Stan". dard=5500 kcal / kg, A_Standard=20%”; The qualified node class mapping rule is used to convert the performance trigger conditions described in natural language into standardized state node parameters, such as converting “goods arrive at the port and enter the quality inspection stage after acceptance” into “the trigger node of the port pending inspection state → quality inspection state is the acceptance event”; The core mapping logic is: to use natural language processing technology to perform syntactic analysis on the contract text, match the corresponding clause category in the mapping rule library, and then convert the keywords and values ​​obtained from the syntactic analysis into standardized parameters according to the preset regular expression, and finally generate a standardized parameter set; Taking the coal mine as an example: the basic unit price of coal is 800 yuan / ton, and the basic unit price is [?(\d+\.?\d*) yuan / ton through the regular expression, and the parameter pr is extracted. i,base=800 yuan / ton, calorific value [standard]?[is]?(\d+\.?\d*) kcal, extract parameter Q_Standard=5500 kcal / kg; the final standardized parameter set has been obtained after conflict detection; for different clauses of the same quality indicator, if the threshold ranges have no intersection (such as 'ash content ≤12%' and 'ash content ≥15%'), it is judged as a conflict, prompting manual intervention; if the ranges have an inclusion relationship (such as 'ash content ≤12%' and 'ash content ≤10%'), the stricter threshold is taken, and no manual intervention is required.

[0022] S2.1.4: Calculate the total settlement price (PR) for each participant using a pre-defined template-driven expression generation technique. i It consists of the billing base function, the benchmark unit price, the standard values ​​of the parameters involved in the unit price adjustment, and the corresponding adjustment coefficients, i.e. f i (X) is the billing base function for the i-th participant, pr i,base Let G be the base unit price for the i-th participant, m be the number of parameters that the participant adjusts, and G be the base unit price. i,k (Δ) represents the adjustment amount for each adjustment parameter involved in the unit price adjustment, based on the measured value g of the adjustment parameter agreed upon in the contract of the i-th participating party. i,k Compared with the standard value g of this parameter i,k-std The deviation Δ is calculated to obtain G. i,k (Δ)=K k ×sgn k ×Δ, k=1,2,...,m,K k >0, K k Let sgn be the adjustment coefficient for the k-th adjustment parameter of the i-th participant. k The value is a directional sign, taking the form of +1 or -1. +1 indicates that the indicator is a "positive indicator" (the higher the better, such as calorific value), and -1 indicates that the indicator is a "negative indicator" (the lower the better, such as ash content and sulfur content). The unit of the adjustment coefficient is the benchmark unit price / deviation unit (e.g., calorific value adjustment coefficient K = 0.02 yuan / (ton·kcal), ash content adjustment coefficient K = 5 yuan / (ton·%)). This satisfies the requirement that G... i,k The result of (Δ) is related to the base unit price pr i,base The units are the same; the standard value of the parameter involved in the unit price adjustment is denoted as [g]. 1-std ,g 2-std ,...,g m-std ], g m-stdThis refers to the standard value of the parameter for the m-th participant in adjusting the unit price of the i-th participant when settling the unit price, where m is the number of parameters to be adjusted by that participant. For example, for the coal mine (i=1), the adjustment parameters include: measured values ​​of coal calorific value, measured values ​​of ash content, measured values ​​of sulfur content, and other quality indicators; for the logistics provider (i=2), the adjustment parameters include: actual transportation distance, transportation time, etc.; the corresponding adjustment coefficients are denoted as [K1,K2,...,K]. m ] is a coefficient that converts the deviation of the adjustment parameters into the price adjustment amount, with each adjustment parameter corresponding to an adjustment coefficient; where the billing base function f for different participants i (X) are different, for example, coal mine party f1(X)=W (charged by weight), logistics party f2(X)=W×D (charged by ton-kilometer), port party f3(X)=W×T (charged by ton-day), quality inspection party f4(X)=1 (fixed charge per batch) or f4(X)=W (charged by weight), etc.; In this embodiment, it should be specifically noted that all digital elements are stored on the blockchain to generate an immutable storage hash value, which constitutes the trusted baseline of the entire system. All hash consistency checks involved in this application use SHA-256 (Secure Hash Algorithm - 256 bits) as the default hash algorithm.

[0023] S2.2: Process State Machine Modeling: The coal supply chain business process is defined as a process state machine model MM containing a state set SS, a state transition path set TT, and a state transition rule set RR, where SS = (SS1, SS2, ..., SS...). n1 ), TT=(TT1,TT2,..,TT n1-1 ), RR=(RR1,RR2,..,RR n1-1 ), SS n1 For the n1th business state, the last state in the state set is defined as the completed settlement state, TT. n1-1 and RR n1-1 These are the (n1-1)th transition path and the transition rule corresponding to the (n1-1)th business state, respectively, where n1 and n1-1 are the number of states and the number of transitions, respectively. The state transition rule is triggered by an event where the result of the previous state is qualified, allowing entry into the next state. The validity of the model is verified by the state machine rationality evaluation function F(MM), where F(MM) = (1-N_Dead / n1) × (N_Valid / (n1-1)), where N_Dead is the number of deadlock states in the state set without a valid exit path, and N_Valid is the number of valid paths in the transition path set that conform to the business logic of the coal supply chain. When F(MM) ≥ the corresponding threshold (e.g., 0.9), the state machine model is reasonable; otherwise, the state definition or transition path needs to be optimized. This embodiment requires specific explanation of the following: the state set includes contract locked, loaded, en route, awaiting inspection at port, quality inspection completed, pending settlement, and settlement completed; the state transition path set includes contract locked → loaded → en route → awaiting inspection at port → quality inspection completed → pending settlement → settlement completed; and the state transition rule set includes the following: the mine completes coal preparation, the logistics company's truck fleet arrives at the mine and completes loading confirmation, allowing entry into the next en route state; the buyer confirms the quality inspection result, and the state machine captures the "quality inspection qualified" event, automatically entering the settlement pending trigger state.

[0024] S2.3: Main Smart Contract Generation and Deployment: Based on the main state machine model MM and the digital results of the participants, coal batches, and contract terms in the digital reconstruction, the main smart contract CC is first generated. Then, each participant uses its private key sk_p to digitally sign the main smart contract, generating a corresponding signature Sig. The validity of each signature Sig is verified by the signature validity evaluation function F(Sig,pk_p). If the participant's digital signature Sig = Sign(sk_p,CC) for the main smart contract, then F(Sig,pk_p) = 1, and the signature is valid. Otherwise, the output is 0, and the signature is invalid and needs to be re-signed. Sign() is a preset digital signature algorithm. Each participant has a blockchain public-private key pair (pk_p,sk_p). After all participants' signatures are valid, the main smart contract CC is deployed on the blockchain network, and the hash value Hash of the main smart contract deployment transaction is generated and stored as the proof of the contract. This embodiment requires specific explanation of the preset digital signature algorithm, such as ECDSA (Elliptic Curve Digital Signature Algorithm), which is a mature asymmetric encryption signature algorithm in the field of cryptography and has been widely used in scenarios such as blockchain and digital identity authentication. It belongs to the publicly available prior art.

[0025] S3: For the state transition rules in the process state machine model, bind them to authorized trusted data sources and format the data source output data as standard on-chain events. For each state transition rule RR in the process state machine model... J Bind at least one trusted data source (DD) authorized by the participating party. The trusted data source includes physical sensing devices and external information systems. Physical sensing devices include GPS devices for transport vehicles, electronic fence systems for destinations, and smart weighbridges, etc., while external information systems include third-party quality inspection systems, etc.; format the data output from the trusted data source into a standard on-chain event (EE). std EE std={E_ID,L_id,Time,g_Con,g_Sig}, where E_ID is the event identifier, L_id is the coal trade batch identifier, Time is the data acquisition timestamp, g_Con is the business data output by the data source (such as GPS latitude and longitude, coal quality testing data), and g_Sig is the digital signature of the data source. Then, the validity of the event is verified by the event credibility evaluation function F(EE), F(EE)=δ×S_ce+(1-δ)×S_For, where S_ce is the data source credibility score, with a value range of [0,1]. Authorized trusted data sources score 1, and unauthorized data sources score 0. S_For is the event format compliance score, with a value range of [0,1]. Events that fully comply with the preset standard chain event format score 1; otherwise, the score is determined based on the event data EE and the standard format template EE. std The degree of deviation between them is rated as a decimal between 0 and 1, where δ is the weight (e.g., 0.6), 0.5 < δ < 1. When F(EE) ≥ the corresponding threshold (e.g., 0.8), the event EE is credible, and the event credibility value Y(EE) = 1, allowing it to be used as the trigger condition for rule RR to enter the subsequent state transition process; otherwise, the event is uncredible, Y(EE) = 1, and the event is discarded or marked as an anomaly. This embodiment requires specific explanation of the event format compliance score S_For == 1 - (number of missing fields + number of fields with format errors) / total number of fields, where the total number of fields is the standard event EE. std The number of fields.

[0026] S4: The main smart contract monitors the on-chain event stream in real time and performs secondary smart integration, including event filtering and verification, logical association and evaluation, and executable instruction output, driving the process state machine to complete deterministic transitions, including the following steps: S4.1: Event Filtering and Verification: Based on the current coal batch identifier L_id and the current state of the process state machine SS. J Filter out events on unrelated chains and evaluate them using the event correlation evaluation function F(EE,L_id,SS). J Verify the relevance of the event to the current business. If the L_id of the on-chain event EE to be verified is consistent with the current coal batch identifier, and the triggering rule corresponding to EE belongs to state SS... J The transition rule is F(EE,L_id,SS). J If )=1, the event is relevant to the current business and will be transferred to subsequent processes; otherwise, if it is 0, it is an irrelevant event and will be filtered out directly. For example, if the current state is SS... JIf the status is "in transit", the only transfer rule is "in transit → arrival at port pending inspection" (the corresponding event EE is "GPS arrival at port + electronic fence trigger"). If an event EE with the rule "quality inspection completed → pending settlement" is received, this rule does not belong to the transfer rules for the "in transit" status and is therefore an irrelevant event. S4.2: Logical Connections and Evaluation: Based on the current state SS J The verified events will be matched with the corresponding transfer path rules RR. I Logical matching is performed, and the satisfaction of rule conditions is quantified using a dynamic condition satisfaction evaluation function. k1∈[1,K1],Y(EE k1 )=1 and g_Con k1 ∈Range k1 Then F(RR) I ,{EE1,EE2,...,EE K1})=1,{EE1,EE2,...,EE K1} is bound to rule RR I The set of all on-chain events, Y(EE) k1 ) for event EE k1 The credibility value of g_Con k1 For Event EE k1 Business data, Range k1 For rule RR I Preset g_Con k1 Valid data range (e.g., calorific value ≥ 5500 kcal); if F(RR) I ,{EE1,EE2,...,EE K1 If})=1, then rule RR I All conditions must be met; otherwise, the conditions are not met. S4.3: Output executable instructions: if and only if F(RR) I ,{EE1,EE2,...,EE K When})=1, the secondary intelligent integration is successful, and the output includes the current state SS. J Target state SS n1 The state transition instruction for the coal batch identifier L_id drives the state machine to complete the transition from state SS. J to state SS n1 Deterministic transfer; S5: Throughout the entire process of the state machine evolution driven by secondary intelligent integration, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically initiates the settlement process based on the state to be settled. Upon completion of the settlement process, the final blockchain settlement certificate is generated, including the following steps: S5.1: Throughout the entire process of the state machine evolution driven by secondary intelligent integration, the system automatically captures and records the price dataset g for each participant used for settlement. n Calculate the integrity assessment index F(g) for settlement parameters for each participant. n )=m1 n,act / m1 n m1 n,act and m1 n Let F(g) represent the number of parameters successfully captured and the number of price parameters for the nth participant, respectively. n If all values ​​are 1, the parameters are complete; otherwise, the missing price parameters are captured. S5.2: Using the legality evaluation function F(SS) J1 ,F(g n As a condition for triggering the automatic settlement process of the main smart contract CC, F(SS) J1 ,F(g n )) indicates that the process state machine is driven to the "pending settlement" state SS after secondary intelligent integration. J1 And F(g) of each participant n When both ) are 1, that is, F(SS) J1 ,F(g n If F(SS) = 1, then the settlement trigger is valid, and the main smart contract executes the settlement process; otherwise, F(SS) = 1. J1 ,F(g n If ))=0, then settlement is refused and the state machine returns to the previous state to supplement data; S5.3: The main smart contract executes the settlement process, based on the settlement price PR of each participant. i The total settlement price PR obtained tot The total settlement price is the sum of the settlement prices of all participants; at the same time, the profit share of each participant is calculated (AA). i AA i =PR tot ×w i w i Let the revenue sharing ratio of the i-th participant be such that the sum of the revenue sharing ratios of all participants is 1 (e.g., the mining party accounts for 0.7, the logistics party accounts for 0.2, and the quality inspection party accounts for 0.1). S5.4: The system displays the settlement price and total price of each participant to the buyer. The buyer clicks the "Confirm" button for one-click settlement, generating a confirmation signature Sig. The validity of the signature is verified through a signature validity evaluation function. After successful verification, the main smart contract CC distributes the settlement amount AA. iFunds are automatically transferred from the buyer's account to the accounts of each participating party, and a blockchain settlement certificate is generated, including the settlement amount, timestamp, and signature hash values ​​of each participating party. If the buyer has any objection to the settlement price or total price, they submit an objection application, specifying the objection type (parameter objection / accounting objection / other objection), the specific parameter or clause to which the objection is directed (such as "abnormal measured calorific value Q data"), and relevant supporting materials (such as their own testing report, on-site records, etc.). The system automatically generates a unique objection identifier ID and synchronizes it to the blockchain for evidence storage. At the same time, it triggers the state machine to jump from the "pending settlement" or "completed" state to the dedicated "objection processing" state S, freezing subsequent fund operations (if the funds have not been transferred, the transfer is suspended; if the funds have been transferred, the settlement permission for subsequent batches is suspended and adjusted in subsequent batches through "deduction" or "supplementation" to avoid duplicate payments). The system also conducts human-computer interaction based on the objection application.

[0027] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A fully automated intelligent integration and one-click settlement method for the coal supply chain, characterized by: include: S1: Through IoT technology, service process data of different participants in the coal supply chain are collected to obtain a multi-source dataset of the coal supply chain, and data interaction among the participants is carried out based on the system interface unit. S2: Intelligently integrate the multi-source datasets of the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; S3: Bind the state transition rules in the process state machine model to an authorized trusted data source and format the data source output data into standard on-chain events; S4: The main smart contract listens to the on-chain event stream in real time and performs secondary smart integration, including event filtering and verification, logical association and evaluation, and output of executable instructions, driving the process state machine to complete deterministic transitions. S5: Throughout the entire process of the state machine evolution driven by secondary intelligent integration, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

2. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The digital reconstruction in S2 includes: participant digitization: Based on a multi-source dataset of the coal supply chain, firstly, statistical analysis of coal supply chain participants is performed to obtain a participant set P, P={p1,p2,...,p...} n }, where n is the number of participants, p n Let n be the nth participant; then, using a blockchain decentralized identity framework, a unique digital identity ID is generated for each participant. The participant's qualification information, credit information, and blockchain authentication information are encrypted and bound to the digital identity ID. The identity credibility assessment index F(ID) is calculated. If F(ID) ≥ the corresponding threshold, the participant's identity is credible and they are allowed to participate in the supply chain business; otherwise, their registration is rejected. Coal Batch Digitization: Using blockchain technology, a unique batch identifier L_id is generated for each coal trade. The format is coal mine digital identity ID + coal production date + batch serial number. A fixed-format field corresponding to the coal batch is extracted from the transportation order number and used as a batch identifier segment. This batch identifier segment is then embedded into the transportation order number. The coal asset assessment index F(L_id) is then calculated. If F(L_id) ≥ the corresponding threshold, the coal asset information is complete and traceable, and digital registration is completed. Otherwise, the production voucher number and transportation order number need to be corrected or supplemented.

3. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The process state machine modeling in S2 is as follows: The coal supply chain business process is defined as a process state machine model MM, which includes a state set SS, a state transition path set TT, and a state transition rule set RR. The last state in the state set is defined as the completed settlement state. The state transition rule is triggered by an event that the result of the previous state is qualified, allowing entry into the next state. The validity of the model is verified by the state machine rationality evaluation function F(MM). If F(MM) ≥ the corresponding threshold, the state machine model is reasonable; otherwise, the state definition or transition path needs to be optimized.

4. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The generation and deployment of the main smart contract in S2: Based on the main state machine model MM and the digital results of the participants, coal batches, and contract terms in the digital reconstruction, the main smart contract CC is first generated. Then, each participant uses its private key sk_p to digitally sign the main smart contract, generating a corresponding signature Sig. The validity of each signature Sig is verified by the signature validity evaluation function F(Sig, pk_p). If the participant's digital signature Sig = Sign(sk_p, CC) for the main smart contract, then F(Sig, pk_p) = 1, and the signature is valid. Otherwise, the output is 0, and the signature is invalid and needs to be re-signed. Sign() is a preset digital signature algorithm. Each participant has a blockchain public-private key pair (pk_p, sk_p). After all participants' signatures are valid, the main smart contract CC is deployed on the blockchain network, and the hash value Hash of the main smart contract deployment transaction is generated and stored as the proof of the contract.

5. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The standard on-chain event in S3 refers to each state transition rule RR in the process state machine model. J Bind to at least one trusted data source (DD) authorized by the participating party, wherein the trusted data source includes physical sensing devices and external information systems; format the data output by the trusted data source into a standard on-chain event (EE). std EE std ={E_ID,L_id,Time,g_Con,g_Sig}, where E_ID is the event identifier, L_id is the coal trade batch identifier, Time is the data collection timestamp, g_Con is the business data output by the data source, and g_Sig is the digital signature of the data source. Then, the validity of the event is verified by the event credibility evaluation function F(EE). When F(EE) ≥ the corresponding threshold, the event EE is credible, and the event credibility value Y(EE) = 1, which allows it to be used as the trigger condition for rule RR to enter the subsequent state transition process. Otherwise, the event is unreliable, Y(EE)=1, and the event is discarded or marked as an anomaly.

6. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The implementation of S4 includes: S4.1: Event filtering and verification: based on the coal batch identifier L_id currently being processed and the current state SS of the process state machine. J Filter out events on unrelated chains and evaluate them using the event correlation evaluation function F(EE,L_id,SS). J Verify the relevance of the event to the current business. If the L_id of the on-chain event EE to be verified is consistent with the current coal batch identifier, and the triggering rule corresponding to EE belongs to state SS... J The transition rule is F(EE,L_id,SS). J If )=1, the event is related to the current business and will be transferred to the subsequent process; otherwise, if it is 0, it is an irrelevant event and will be filtered directly. S4.2: Logical Connections and Evaluation: Based on the current state SS J The verified events will be matched with the corresponding transfer path rules RR. I Logical matching is performed, and the satisfaction of rule conditions is quantified using a dynamic condition satisfaction evaluation function. k1∈[1,K1],Y(EE k1 )=1 and g_Con k1 ∈Range k1 Then F(RR) I ,{EE1,EE2,...,EE K1 })=1,{EE1,EE2,...,EE K1 } is bound to rule RR I The set of all on-chain events, Y(EE) k1 ) for event EE k1 The credibility value of g_Con k1 For Event EE k1 Business data, Range k1 For rule RR I Preset g_Con k1 Valid data range; if F(RR) I ,{EE1,EE2,...,EE K1 If})=1, then rule RR I All conditions must be met; otherwise, the conditions are not met. S4.3: Output executable instructions: if and only if F(RR) I ,{EE1,EE2,...,EE K When})=1, the secondary intelligent integration is successful, and the output includes the current state SS. J Target state SS n1 The state transition instruction for the coal batch identifier L_id drives the state machine to complete the transition from state SS. J to state SS n1 The deterministic transfer.

7. The fully automated intelligent integration and one-click settlement method for the coal supply chain according to claim 1, characterized in that: The implementation of S5 includes: S5.1: During the entire process of the secondary intelligent integration driving state machine evolution, the system automatically captures and records the price dataset g for each participant used for settlement. n Calculate the integrity assessment index F(g) for settlement parameters for each participant. n )=m1 n,act / m1 n m1 n,act and m1 n Let F(g) represent the number of parameters successfully captured and the number of price parameters for the nth participant, respectively. n If all values ​​are 1, the parameters are complete; otherwise, the missing price parameters are captured. S5.2: Using the legality evaluation function F(SS) J1 ,F(g n As a condition for triggering the automatic settlement process of the main smart contract CC, F(SS) J1 ,F(g n )) indicates that the process state machine has been driven to the "pending settlement" state SS through secondary intelligent integration. J1 And each participant's F(g) n When both ) are 1, that is, F(SS) J1 ,F(g n If F(SS) = 1, then the settlement trigger is valid, and the main smart contract executes the settlement process; otherwise, F(SS) = 1. J1 ,F(g n If ))=0, then settlement is refused and the state machine returns to the previous state to supplement data; S5.3: The main smart contract executes the settlement process, based on the settlement price PR of each participant. i The total settlement price PR obtained tot The total settlement price is the sum of the settlement prices of all participants; at the same time, the profit share of each participant is calculated (AA). i AA i =PR tot ×w i w i Let the revenue sharing ratio of the i-th participant be such that the sum of the revenue sharing ratios of all participants is 1. S5.4: The system displays the settlement price and total amount for each participant to the buyer. The buyer clicks the "Confirm" button for one-click settlement, generating a confirmation signature Sig. The validity of the signature is verified through a signature validity evaluation function. After successful verification, the main smart contract CC distributes the settlement amount AA. i Funds are automatically transferred from the buyer's account to the accounts of each participating party, and a blockchain settlement certificate is generated, including the settlement amount, timestamp, and signature hash value of each participating party. If the buyer has any objection to the settlement price and total price, they submit an objection application, specifying the objection type, the specific parameters or terms to which the objection is directed, and relevant supporting materials. The system automatically generates a unique objection identifier ID and synchronizes it to the blockchain for evidence storage. At the same time, the state machine is triggered to jump from the "pending settlement" or "completed" state to the "objection processing" state, freezing subsequent fund operations, and conducting human-computer interaction based on the objection application.

8. A fully automated intelligent integration and one-click settlement system for coal supply chains, used in accordance with the fully automated intelligent integration and one-click settlement method for coal supply chains as described in any one of claims 1-7, comprising: Coal supply chain multi-source data acquisition module: Through Internet of Things (IoT) technology, it collects service process data from different participants in the coal supply chain to obtain a multi-source dataset of the coal supply chain, and facilitates data interaction among the participants based on the system interface unit; The first intelligent integration module: intelligently integrates multi-source datasets from the coal supply chain, including digital reconstruction, process state machine modeling, and main smart contract generation, to obtain the main smart contract; Trusted Data Adaptation Module: Binds the state transition rules in the process state machine model to an authorized trusted data source and formats the data source output into standard on-chain events; Secondary intelligent integration module: The main smart contract listens to the on-chain event stream in real time and performs secondary intelligent integration, including event filtering and verification, logical association and evaluation, and output of executable instructions, driving the process state machine to complete deterministic transitions; One-click settlement module: Throughout the entire process of secondary intelligent integration driving state machine evolution, the system automatically captures and records the price parameters of each participant used for settlement. The main smart contract automatically starts the settlement process according to the state to be settled. When the settlement process ends, the final blockchain settlement certificate is generated.

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