Engineering project delivery process automation system and method based on intelligent contract driving

Abstract

The invention discloses an engineering project delivery process automation system and method based on smart contract driving, the system comprises a delivery node management module, a smart contract generation module, a block chain storage module and an automation trigger module, the delivery node management module defines key nodes and task conditions thereof in a delivery process; the smart contract generation module automatically generates a smart contract according to the configured delivery node condition, and deploys the smart contract in the block chain; the block chain storage module is responsible for recording key data and node states generated in the delivery process; and the automatic triggering module is used for monitoring delivery node conditions in real time, and when the node conditions are achieved, the system automatically triggers the next task through the smart contract. According to the scheme, the key nodes in the engineering project delivery process are subjected to standardized management through the smart contract and block chain technology, and automatic triggering and execution are realized, so that the problems of low efficiency, poor data credibility, insufficient process transparency and the like in the traditional delivery process are effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and more particularly to the technology of automating the project delivery process. Background Art

[0002] With the continuous deepening of the digital transformation of the construction industry, the management mode of engineering projects has gradually evolved from traditional manual operations and offline management towards informatization and intelligentization. In recent years, with the wide application of emerging technologies such as Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI), the digital delivery of engineering projects has become an inevitable trend in the industry. However, there are still many problems and bottlenecks in the existing delivery processes, mainly manifested as low delivery efficiency, opaque processes, easy data tampering, and poor multi-party collaboration.

[0003] Traditional delivery processes often rely on manual operations, where all parties transfer deliverables and confirmation documents through offline or email methods. This mode is not only inefficient and error-prone but also prone to problems such as data tampering, information asymmetry, data inconsistency, and communication errors during multi-party collaboration. At the same time, the acceptance process of deliverables is complex, involving multiple parties such as designers, constructors, supervisors, and owners. The process has many links and a long cycle, with a large number of manual participation links, which are prone to human negligence or errors, resulting in delays in the delivery schedule.

[0004] In addition, due to the lack of effective process management and traceability means, it is difficult to define responsibilities when disputes occur during the delivery process. For example, the BIM model completed in the design stage may deviate during the construction process due to design changes or changes in on-site construction conditions. Without an efficient delivery verification and version management mechanism, the final delivered as-built model may have a large difference from the actual construction status, thus affecting the data accuracy in the subsequent operation and maintenance stage.

[0005] Therefore, how to effectively improve the efficiency and data transparency of the engineering project delivery process is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] Aiming at the problems existing in the existing engineering project delivery process based on manual operations, the purpose of the present invention is to provide an automated solution for the digital delivery process of engineering projects driven by smart contracts, which realizes the automated management and data transparency of the engineering project delivery process through smart contracts and blockchain technology, improves the delivery efficiency, reduces the manual operation cost, and ensures the authenticity and consistency of delivery data.

[0007] To achieve the above object, the present invention provides an automated system for the engineering project delivery process driven by smart contracts, and the automated system for the engineering project delivery process includes:

[0008] Delivery node management module, which can define and manage key nodes in the engineering project delivery process, and can define and construct one or more attributes of corresponding delivery tasks, acceptance criteria, and trigger conditions for each node;

[0009] Smart contract generation module, which can interact with the delivery node management module, can generate a smart contract that can be executed on the blockchain and can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module. A trigger mechanism is set in the smart contract, which can automatically trigger the execution of the delivery tasks corresponding to the delivery nodes described in the smart contract when the preset trigger conditions are met;

[0010] Blockchain data storage module, which is used to obtain key data generated in the digital delivery process of engineering projects and store it on the blockchain. The key data includes at least one of the data of delivery node status, acceptance records, and task results;

[0011] Automated task trigger module, which can interact with the blockchain data storage module and the smart contract generation module, can monitor the key data obtained by the blockchain data storage module and stored on the blockchain, and can analyze and judge the status change events of each node in the delivery process through the monitored key data. It can compare and analyze the generated status change events with the trigger conditions in the smart contract on the blockchain, and can automatically trigger the execution of the corresponding delivery tasks in the smart contract when the trigger conditions are met.

[0012] In some embodiments of the present invention, in the delivery node management module, corresponding dependency trigger start relationships can be set between the defined and constructed key nodes according to the business logic of the engineering project delivery process.

[0013] In some embodiments of the present invention, the delivery node management module uses a directed acyclic graph to manage the defined and constructed key nodes, configures the vertices in the graph as corresponding key nodes, configures the directed edges in the graph as the dependency relationships between the corresponding key nodes, and configures the direction of the edges as the trigger order between the key nodes.

[0014] In some embodiments of the present invention, the smart contract generation module uses a predefined contract template and dynamically generates a smart contract in combination with the attributes of the defined key nodes.

[0015] In some embodiments of the present invention, the smart contract generation module uses a parsing algorithm based on reverse Polish notation to parse and configure acceptance criteria and trigger conditions for the generated smart contract.

[0016] In some embodiments of the present invention, the blockchain data storage module configures the state changes of the delivery nodes as transactions, generates a transaction for each state change, and records the transaction data in the block after hashing.

[0017] In some embodiments of the present invention, after the automation trigger module completes the corresponding node delivery task, it automatically updates the state of the corresponding delivery node and records the state change on the blockchain by calling the interface of the blockchain data storage module.

[0018] In some embodiments of the present invention, the engineering project delivery process automation system further includes a multi-party collaboration interface module, which conducts data interaction with the delivery node management module, the smart contract generation module, the blockchain storage module, and the automation trigger module, and can perform access right and interaction management.

[0019] To achieve the above object, the present invention provides an engineering project automatic delivery method driven by a smart contract. The engineering project automatic delivery method includes:

[0020] Define and manage the key nodes in the engineering project delivery process according to the business logic of the engineering project delivery process, and define and construct one or more attributes of the corresponding delivery tasks, acceptance criteria, and trigger conditions for each node;

[0021] Generate a smart contract that can be executed on the blockchain and can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module, and a trigger mechanism is set for the smart contract, which can automatically trigger the execution of the delivery tasks of the corresponding delivery nodes described in the smart contract when the preset trigger conditions are met;

[0022] Used to obtain the key data generated during the digital delivery process of the engineering project and store it on the blockchain. The key data includes at least one type of data such as the delivery node state, acceptance record, and task result;

[0023] Monitor the key data obtained by the blockchain data storage module and stored on the blockchain, and judge the state change events of each node in the delivery process through the monitored key data analysis. It can compare and analyze the generated state change events with the trigger conditions in the smart contract on the blockchain, and automatically trigger the execution of the corresponding delivery tasks in the smart contract when the trigger conditions are met.

[0024] In some embodiments of the present invention, the trigger mechanism of the event-driven model is adopted for the smart contract in the engineering project automatic delivery method.

[0025] The automated solution for the engineering project delivery process provided by the present invention addresses the problems in the traditional delivery process, such as low efficiency, poor data credibility, and insufficient process transparency. By introducing smart contracts and blockchain technology, it can achieve automated management and transparent operation of the delivery process, thus comprehensively improving the delivery efficiency and quality of engineering projects. At the same time, it can also reduce costs and increase data transparency.

[0026] The automated solution for the engineering project delivery process provided by the present invention has wide applicability and is applicable to scenarios such as the delivery of architectural engineering design, progress management during the construction phase, and operation and maintenance delivery. It can effectively reduce human errors and coordination costs during the delivery process and improve the overall level of engineering project management. At the same time, it can also be extended to other industry scenarios that require complex delivery and multi-party collaboration, such as large-scale infrastructure construction, industrial park development, and smart city projects, providing technical support and guarantee for the digital management of the entire life cycle of engineering projects. It has high industry application value and promotion prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below in conjunction with the drawings and specific embodiments.

[0028] Figure 1 is the system block diagram of the automated system for the engineering project delivery process driven by smart contracts in the present invention;

[0029] Figure 2 is the schematic diagram of the composition principle of the delivery node management module in the present invention;

[0030] Figure 3 is the schematic diagram of the composition principle of the smart contract generation module in the present invention;

[0031] Figure 4 is the schematic diagram of the composition principle of the automated task trigger module in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] In order to make the technical means, creative features, achieved objectives, and functions of the present invention easy to understand, the present invention will be further described below in conjunction with specific illustrations.

[0033] The present invention addresses the problems existing in the digital delivery solutions of existing engineering projects and introduces smart contracts and blockchain technology to construct an automated solution for the digital delivery process of engineering projects driven by smart contracts.

[0034] The smart contract introduced in the solution of the present invention can run on the blockchain and can automatically execute tasks according to preset conditions. By mapping the delivery process of engineering projects to smart contracts, the present invention can achieve automatic triggering and acceptance confirmation of delivery nodes, reduce manual operations, and improve the efficiency of process execution.

[0035] For example, in a digital delivery process, the integrity and compliance of a BIM model can be automatically verified through a smart contract. After successful acceptance, the next-stage tasks are automatically triggered, and relevant parties are notified in real time.

[0036] On this basis, the solution of the present invention further introduces a blockchain for secure and transparent management of data in the digital delivery process.

[0037] Based on the characteristics of the distributed ledger of the blockchain in the solution of the present invention, data can be stored and shared in a decentralized manner, ensuring data transparency, immutability, and traceability. Accordingly, for the delivery process of engineering projects, by storing delivery node status, acceptance records, and important documents in the blockchain, the authenticity and integrity of the data can be ensured, human tampering can be avoided, and the credibility of the data can be improved. At the same time, all delivery actions are recorded on the blockchain and are traceable, greatly enhancing the transparency of the delivery process and the traceability of responsibilities. In addition, the combination of smart contracts and blockchain technology can also optimize the payment and settlement mechanisms in the delivery process.

[0038] Based on the above solution mechanism, the present invention specifically provides an automated system for the delivery process of engineering projects driven by smart contracts. By deeply integrating smart contracts with blockchain technology, this system realizes the automation and intelligence of the digital delivery process throughout the entire life cycle of engineering projects.

[0039] See Figure 1 , which shows an example of the system composition of the automated system for the delivery process of engineering projects driven by smart contracts.

[0040] Based on the illustration, the automated system 100 for the delivery process of engineering projects driven by smart contracts given by the present invention mainly consists of a delivery node management module 110, a smart contract generation module 120, a blockchain data storage module 130, an automated task trigger module 140, and a multi-party collaboration interface module 150 that cooperate with each other.

[0041] The delivery node management module 110 in this system is used to define and manage the key nodes and their task conditions in the delivery process of engineering projects, ensuring the structuring and standardization of the delivery process.

[0042] For each key node defined in this delivery node management module 110, one or more attributes of corresponding delivery tasks, acceptance criteria, and trigger conditions are respectively configured.

[0043] The smart contract generation module 120 in this system automatically generates a smart contract containing interactive task terms, acceptance criteria, and trigger events based on the delivery node conditions configured by the delivery node management module 110, and deploys it on the blockchain.

[0044] Specifically, the smart contract generation module 120 can interact with the delivery node management module 110, and can generate a smart contract that can be executed on the blockchain and can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module 110. The smart contract contains information such as interaction task terms, acceptance criteria, and trigger events.

[0045] Furthermore, a trigger mechanism is set in the smart contract. The trigger mechanism is configured to automatically trigger the execution of the delivery task corresponding to the delivery node described in the smart contract when the preset trigger condition is met.

[0046] The blockchain storage module 130 in this system is used to obtain and record the key data generated during the digital delivery process of the engineering project, and store it on the blockchain to ensure the authenticity and immutability of the data.

[0047] The key data here includes at least one of the delivery node status, acceptance record, and task result data.

[0048] The automatic trigger module 140 in this system is used to monitor the trigger conditions of the corresponding delivery nodes in the digital delivery process of the engineering project in real time. When the node trigger condition is met, it triggers and executes the corresponding node delivery task in the smart contract.

[0049] Specifically, the automatic trigger module 140 interacts with the blockchain data storage module 130 and the smart contract generation module 120 to listen to the key data obtained and stored on the blockchain by the blockchain data storage module 130 in real time, and can further analyze and judge the state change events of each node in the delivery process by monitoring the key data. It can compare and analyze the generated state change events with the trigger conditions in the smart contract on the blockchain, and can automatically trigger the execution of the corresponding delivery task in the smart contract when the trigger condition is met.

[0050] The delivery tasks here include one or more of generating an acceptance report, updating the delivery status, sending a notification, or initiating a payment instruction.

[0051] The multi-party collaboration interface module 150 in this system can provide access right management and an interaction interface for all parties participating in the project by interacting with the delivery node management module 110, the smart contract generation module 120, the blockchain storage module 130, and the automatic trigger module 140, and support online viewing of the delivery status, acceptance result, and document generation situation.

[0052] When the resulting automated system 100 for project delivery processes is running, the delivery process of the project is mapped to a smart contract through the cooperation of the delivery node management module 110 and the smart contract generation module 120. On this basis, the blockchain storage module 130 collects and stores the key data in the digital delivery process of the project in real time, and the automated trigger module 140 automatically verifies the trigger conditions and triggers tasks based on the collected key data, realizing the automation of the digital delivery of the entire life cycle of the project from design, construction to operation and maintenance. The entire process takes the smart contract as the core, effectively improving the delivery efficiency, reducing the manual operation cost, and ensuring the transparency and reliability of the delivery process.

[0053] The present invention provides specific composition schemes for each functional module in the automated system 100 for project delivery processes.

[0054] The delivery node management module 110 in this system is specifically used to define and manage the key nodes in the digital delivery process of the project, and these key nodes specifically include design delivery nodes, construction progress nodes, acceptance nodes, completion delivery nodes, etc.

[0055] For each defined node, this delivery node management module 110 is further configured with various attributes such as corresponding delivery tasks, acceptance criteria, and trigger conditions.

[0056] On this basis, this delivery node management module 110 further configures a corresponding dependency trigger start relationship between the defined delivery nodes according to the sequentiality and logic between the delivery nodes in the digital delivery process of the project, that is, the completion condition of a certain node can be used as the trigger condition for the start of the next node, forming a complete delivery process chain.

[0057] See Figure 2 , which shows a specific composition example scheme of this delivery node management module 110.

[0058] Based on the illustration, this delivery node management module 110 is mainly composed of a node modeling sub-module 111, a node attribute configuration sub-module 112, a node status monitoring sub-module 113, and an exception handling sub-module 114 cooperating with each other.

[0059] Among them, the node modeling sub-module 111 is used to define and construct the key nodes in the digital delivery process of the project.

[0060] The node modeling sub-module 111 specifically uses an object-based modeling method to define and model the implementation delivery nodes. Each delivery node is constructed as an independent object and includes the following core attributes: node identifier (ID), node type (Type), participant role (Roles), task description (Task Description), acceptance criteria (Acceptance Criteria), trigger conditions (Trigger Conditions), and node status (Status).

[0061] Furthermore, based on the object-oriented programming (OOP) scheme, the node modeling sub-module 111 designs and constructs a class structure corresponding to the delivery nodes, such that each node instance is generated through the instantiation of a class. At the same time, the attribute information of each delivery node is stored in a relational database, and the integrity and consistency of the data are ensured through database table design.

[0062] Furthermore, to address the sequentiality and logic between delivery nodes in the digital delivery process of a corresponding engineering project, when constructing the delivery nodes, the node modeling sub-module 111 further uses a directed acyclic graph (DAG) to manage the delivery nodes. A vertex in the graph is configured as the corresponding delivery node, a directed edge in the graph is configured as the dependency relationship between the corresponding key nodes, and the direction of the directed edge is configured as the trigger order between the delivery nodes. At the same time, the construction of the dependency relationship is represented by the adjacency matrix or adjacency list of the graph and stored in the database.

[0063] In this way, when the delivery process is initialized, the node modeling sub-module 111 sorts the nodes based on the topological sorting algorithm to ensure that each node can only be started after all its preceding nodes are completed.

[0064] The time complexity of the topological sorting here is:

[0065] O(V + E);

[0066] where V is the number of nodes and E is the number of edges;

[0067] In this way, the sorting of dependency relationships can be efficiently completed in a complex delivery process.

[0068] As a further illustration, for the hierarchical process management of complex engineering projects, this node modeling sub-module 111 uses a hierarchical graph model to perform modeling. The delivery process of a large-scale engineering project is divided into several sub-processes, and the delivery nodes in each sub-process operate according to independent rules. After completion, the status is summarized to the main process.

[0069] Among them, the hierarchical graph model represents a nested graph structure. Each sub-process is configured as a node, and the node dependency relationships within the sub-process are represented by an internal graph, while the main process is represented by an outer graph.

[0070] Meanwhile, a recursive algorithm is adopted to parse the nested graph to ensure the recursive execution of the process and the state update.

[0071] The node attribute configuration sub-module 112 in this delivery node management module 110 interacts with the node modeling sub-module 111, and can perform corresponding attribute configurations for the delivery nodes established by the node modeling sub-module 111, such as configuring delivery tasks, trigger conditions, acceptance criteria, etc.

[0072] Among them, in order to support diverse acceptance criteria, the node attribute configuration sub-module 112 configures and executes the acceptance criteria through a built-in rule engine and by adopting a rule matching algorithm based on a decision tree.

[0073] Specifically, since each node can be associated with multiple rules (each rule corresponds to a corresponding acceptance criterion), and each rule consists of a set of conditional expressions, the syntax of the conditional expressions is composed of logical operators (such as AND, OR, NOT) and comparison operators (such as >, <, =).

[0074] In this regard, the node attribute configuration sub-module 112 parses the rule expressions based on the built-in rule engine and converts them into a decision tree structure, and uses the depth-first search (DFS) algorithm to traverse and match the decision tree, so as to judge whether the acceptance passes.

[0075] Meanwhile, the rule engine built into the node attribute configuration sub-module 112 is set to allow custom rules and perform dynamic loading and execution. This can further improve the flexibility of node attribute configuration and execution.

[0076] The node status monitoring sub-module 113 in this delivery node management module 110 interacts with the node modeling sub-module 111 and the node attribute configuration sub-module 112, and can monitor the status of the delivery nodes established by the node modeling sub-module 111. This node status monitoring sub-module 113 adopts an event-driven architecture (EDA) to monitor the status of the delivery nodes and trigger events, and can automatically generate events and trigger corresponding processing logics when the task status of a certain node changes.

[0077] Furthermore, the events here include types such as "task start", "task completion", "acceptance passed", "exception feedback", etc.; the generated event data is asynchronously transmitted using a message queue (such as Kafka or RabbitMQ) to ensure system performance and stability under high concurrency.

[0078] As a further explanation, in this solution, the event processing mode adopts the Publish-Subscribe Pattern, with the smart contract generation module and the automated trigger module as event subscribers. In this way, these two modules execute corresponding tasks when receiving the corresponding events, such as generating smart contracts, updating process status, or notifying relevant parties, etc.

[0079] The exception handling sub-module 114 in this delivery node management module 110 is used to handle exception events during the node definition and management process of the delivery node management module. This exception handling sub-module 114 specifically constructs an exception handling strategy based on a state machine (StateMachine).

[0080] Specifically, each delivery node in this solution has multiple states, including "not started", "in progress", "completed", "exception", etc. Here, a state machine (State Machine) is used to manage the state of each delivery node. The state transition of the state machine is driven by preset event trigger conditions. For example, task timeout will trigger the "exception" state, and acceptance failure will trigger the "resubmit" state. At the same time, the exception state is recorded on the blockchain to ensure the transparency and traceability of the exception handling process.

[0081] As a further explanation, this exception handling sub-module 114 also further sets up an exception feedback and handling mechanism. Based on the exception feedback and handling mechanism, it is allowed to submit supplementary documents or correction suggestions to the system, and when the exception is handled, the re-acceptance process will be automatically triggered.

[0082] When the delivery node management module 110 formed based on the above solution is specifically implemented, it can be presented through a corresponding visual interaction interface. In this way, users can flexibly configure the task content, acceptance criteria, and trigger conditions of the delivery node through the visual interface to ensure the standardization and regularization of the delivery process.

[0083] The smart contract generation module 120 in this system can, through effective data interaction with the delivery node management module 110, automatically generate a smart contract that can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module 110. This smart contract contains task terms, acceptance criteria, and trigger events, and can be executed on the blockchain, thus ensuring the flexibility, automation, and security of the contract.

[0084] See Figure 3 , which shows a specific example of the smart contract generation module 120 in this solution.

[0085] Based on the illustration, this smart contract generation module 120 mainly consists of a contract template generation sub-module 121, a parameterized configuration sub-module 122, a rule parsing sub-module 123, and a status monitoring and triggering sub-module 124 that cooperate with each other to generate a smart contract, and enable the generated smart contract to accurately describe the business logic of the delivery process and automatically trigger task execution when the conditions are met.

[0086] Among them, the contract template generation sub-module 121 in this smart contract generation module 120 adopts a template-based smart contract generation method, and dynamically generates contract code by combining predefined contract templates with the attributes of delivery nodes.

[0087] The contract templates here are written using a domain-specific language (DSL). The DSL syntax structure supports basic logical operations such as conditional judgment, loop, and trigger event, ensuring the generality and scalability of the templates.

[0088] As a further explanation, this contract template generation sub-module 121 specifically generates a smart contract through the following steps:

[0089] (1) Contract template parsing. The contract template generation sub-module 121 converts the template into an intermediate code representation (IR) through a DSL parser and extracts the placeholders therein;

[0090] (2) Parameter substitution. The contract template generation sub-module 121 fills the parameters in the delivery node (such as parties involved, task conditions, acceptance criteria, trigger rules, etc.) into the placeholders of the intermediate code, and finally generates the complete smart contract code.

[0091] When this contract template generation sub-module 121 generates a smart contract based on the above steps, through the separation of the template and parameters, it effectively realizes the flexible configuration and rapid generation of the smart contract.

[0092] The parameterized configuration sub-module 122 in this smart contract generation module 120 is used to dynamically inject key parameters such as predefined tasks, acceptance criteria, and trigger conditions in the delivery node management module 110 into the smart contract template to achieve the automatic generation and deployment of the contract.

[0093] This parameterized configuration sub-module 122 is specifically set to ensure the flexible adaptability and scalability of the smart contract through the cooperation of parameter parsing, variable mapping, dynamic rule setting, and template compilation.

[0094] Specifically, the parametric configuration sub-module 122 cooperates organically with the delivery node management module 110 to obtain key parameter data such as the task content, executor, acceptance criteria, and trigger conditions of the node, and parses the obtained key parameter data through a rule engine, converting it into a logical expression executable by a smart contract.

[0095] Furthermore, the parametric configuration sub-module 122 works in coordination with the blockchain data storage module 130 to ensure that the smart contract generated by the smart contract generation module 120 completes hash verification before being deployed to the blockchain and establishes a mapping relationship with the existing delivery process data. In addition, the parametric configuration sub-module 122 also forms a linkage with the automated task trigger module 140, dynamically adjusting the execution logic of the contract according to different task states and trigger conditions to achieve automatic triggering of task execution.

[0096] Furthermore, when the parametric configuration sub-module 122 performs parametric configuration during template compilation, it specifically uses a DSL (Domain-Specific Language) parsing engine to parse the contract template, processes dynamic parameters through an Abstract Syntax Tree (AST), and optimizes the calculation of the contract condition expression using a Reverse Polish Notation (RPN)-based logical operation.

[0097] The rule parsing sub-module 123 in the smart contract generation module 120 is used to parse and configure the acceptance criteria and trigger conditions in the smart contract generated by the contract template generation sub-module 121.

[0098] Specifically, the task terms, acceptance criteria, and trigger events included in the smart contract generated by the contract template generation sub-module 121 correspond to the task terms, acceptance criteria, and trigger events of the corresponding delivery nodes in the smart contract, and the acceptance criteria and trigger conditions in the delivery nodes exist in the form of complex logical expressions. In this regard, the rule parsing sub-module 123 uses a parsing algorithm based on Reverse Polish Notation (RPN) to convert the configured expressions corresponding to the acceptance criteria and trigger conditions into a logical tree structure executable by a computer.

[0099] Furthermore, the rule parsing sub-module 123 specifically uses a rule engine and an expression parser to work together to convert the configured expressions corresponding to the acceptance criteria and trigger conditions into a logical tree structure executable by a computer. The specific parsing and conversion process is as follows:

[0100] The rule parsing sub-module 123 first performs lexical and syntactic analysis on the expression through a parser to generate an Abstract Syntax Tree (AST);

[0101] Then, the AST is transformed into Reverse Polish Notation through Inorder Traversal, and the corresponding smart contract code logic is generated according to the RPN.

[0102] As an example, if the acceptance criteria for a delivery node is "design document submitted and reviewed and approved", the system will parse this condition into a boolean expression (DocSubmitted AND ReviewApproved), and convert it into a conditional judgment statement in the smart contract to ensure that the contract automatically updates the node status when the condition is met.

[0103] The status monitoring and triggering sub-module 124 in this smart contract generation module 120 adopts an Event-Driven Architecture (EDA) to build a corresponding event listening and triggering mechanism for the smart contract generated by the contract template generation sub-module 121, and can automatically generate an event and trigger the processing logic of the corresponding task in the smart contract when the task status of a certain node changes during the digital delivery process of the engineering project.

[0104] Specifically, this status monitoring and triggering sub-module 124 cooperates with the blockchain storage module 130 to implement the trigger mechanism setting for the trigger of the corresponding task of the smart contract based on the event listening and callback function of the blockchain.

[0105] As an example, for the smart contract generated by the contract template generation sub-module 121, this status monitoring and triggering sub-module 124 first embeds the corresponding status monitoring and triggering logic in the smart contract; on this basis, further configures the blockchain listening and callback function. When the blockchain network detects that the status of a certain node in the delivery process changes, the callback function of the smart contract is triggered to perform the corresponding operation.

[0106] This status monitoring and triggering sub-module 124 implements the event listening mechanism based on the event subscription function of the blockchain platform (such as Ethereum or Hyperledger Fabric). For the smart contract generated by the contract template generation sub-module 121, this status monitoring and triggering sub-module 124 subscribes to specific contract events (such as task completion, acceptance passed, etc.), and automatically calls the preset callback function when the event is triggered, thereby completing the status update and subsequent task triggering.

[0107] As a further illustration, to ensure the efficiency and real-time performance of the trigger mechanism, an asynchronous processing mechanism based on a message queue (such as Kafka or RabbitMQ) is also set in this status monitoring and triggering sub-module 124. By separating the processing of blockchain events and system tasks, the system latency is reduced and the concurrent processing ability is improved.

[0108] When the smart contract generation module 120 formed based on the above solution is specifically implemented, formal verification and static analysis techniques are further used to review and optimize the generated contract code, thereby ensuring the security of the smart contract and the credibility of its execution.

[0109] Here, formal verification specifically transforms the contract code into a logical model and uses model checking algorithms to verify its compliance and security. As an example, this smart contract generation module 120 detects whether there are common security vulnerabilities (such as re-entrancy attacks, integer overflows, etc.) in the contract through a verification tool, and automatically repairs the contract code that does not meet the security standards.

[0110] Here, static analysis optimizes redundant logic and improves the contract execution efficiency through code syntax tree and data flow analysis. In addition, all generated smart contracts use a distributed hash algorithm (such as SHA-256) to generate a unique hash value to ensure the integrity and anti-tampering of the contract.

[0111] When this smart contract generation module 120 is deployed, through the smart contract deployment interface of the blockchain, the generated contract code is deployed to the blockchain network, and the deployed contract address and related information are recorded. In this way, after the deployment is completed, the deployment status and execution log of the contract can be displayed to the project participants through the blockchain browser or interface, ensuring the transparency and traceability of the delivery process.

[0112] The blockchain storage module 130 in this system is used to store the key data generated during the digital delivery process of engineering projects on the blockchain to ensure the transparency, immutability, and traceability of the data. Here, the key data mainly includes delivery node status, acceptance records, task results, etc.

[0113] At the same time, this blockchain storage module 130 also conducts data interaction with the delivery node management module 110 and the smart contract generation module 120 to ensure the authenticity and integrity of the operation data of the entire system, avoid manual tampering, and improve the credibility of the data.

[0114] Specifically, this blockchain storage module 130 preferably adopts a chained block structure. Each block contains a block header and a block body. The block header records the hash value and timestamp of the previous block, and the block body stores the delivery data in the current block.

[0115] As an example, the smart contract generation module 120 in this system regards the state change of the delivery node during the digital delivery process of engineering projects as a transaction. Each state change generates a transaction. The smart contract generation module 120 processes the transaction data through hashing and records it in the block.

[0116] For the hash processing of transactions, it is preferable to use the SHA-256 algorithm to ensure the uniqueness and integrity of transactions. Even if the data changes slightly, the generated hash values will be completely different, thus preventing data tampering.

[0117] Furthermore, to improve data storage efficiency and query speed, the blockchain storage module 130 preferably adopts a hierarchical storage strategy, that is, storing key index data on the blockchain and storing specific deliverable data (such as BIM model files, inspection reports, etc.) in a distributed database off the chain (such as IPFS or a distributed file system).

[0118] The on-chain data and off-chain data here are associated through hash values. Only the hash index of the off-chain data is stored on the chain. When querying data, the blockchain storage module 130 retrieves the corresponding deliverable data from the off-chain database according to the hash value recorded on the chain and verifies the integrity and consistency of the data by comparing the hash values.

[0119] Through this on-chain and off-chain combined storage strategy, the blockchain storage module 130 not only reduces the storage pressure on the blockchain but also improves the overall performance and scalability of the system.

[0120] Furthermore, during the data writing and block generation process, the blockchain storage module 130 adopts a distributed ledger method based on a consensus algorithm to ensure that all nodes reach an agreement when writing data.

[0121] As a further illustration, when implementing the blockchain storage module 130, a hybrid consensus architecture is adopted, combining the high security of PBFT and the high performance of PoS, and data synchronization and verification are carried out between the permissioned chain and the public chain through a cross-chain interoperability mechanism to achieve high security, high efficiency, and cross-platform collaborative storage of project delivery data, meeting the actual needs of multi-party collaboration in project management.

[0122] Specifically, for the permissioned blockchain environment, the blockchain storage module 130 uses the Practical Byzantine Fault Tolerance (PBFT) algorithm to achieve consensus. The PBFT algorithm can ensure consistency in the presence of up to 1 / 3 malicious nodes and is suitable for scenarios of multi-party collaboration such as engineering projects. The PBFT consensus process includes three stages: pre-prepare, prepare, and commit. Each stage requires the majority agreement of nodes to continue execution, thus ensuring data consistency and security.

[0123] For the public chain environment, the blockchain storage module 130 adopts the PoS (Proof of Stake) consensus algorithm, determines the weights of the nodes through proof of stake, and generates a block after the data is confirmed by randomly selected verification nodes.

[0124] Furthermore, a linkage mechanism between the on-chain smart contract and data storage is established in the blockchain storage module 130.

[0125] Specifically, the blockchain storage module 130 constructs this linkage mechanism based on the event-driven model and the on-chain and off-chain data mapping strategy.

[0126] First, when the status of the delivery node changes (such as task completion, acceptance passed), the blockchain storage module 130 will call the smart contract interface, write key data such as status updates and hash indexes into the blockchain, and trigger the blockchain event listener. This listener asynchronously notifies the off-chain storage module to perform data synchronization based on the message queue (Kafka or RabbitMQ).

[0127] Second, the blockchain storage module 130 adopts a hierarchical storage architecture. Transaction records and hash indexes are stored on the chain, and large files such as BIM models and acceptance documents are stored in IPFS or a distributed database. The on-chain and off-chain data are associated through hash values to ensure data consistency.

[0128] Finally, all data changes are verified through the Merkle tree to achieve the verification of the integrity of the block data, ensuring that the on-chain smart contract can automatically execute the data storage task, and at the same time supporting efficient query and traceability.

[0129] Based on this linkage mechanism between the on-chain smart contract and data storage, the blockchain storage module 130 can cooperate with the automated task trigger module 140. By monitoring the tasks of the status changes of the delivery node through the automated task trigger module 140, the blockchain storage module 130 can, when the status of the delivery node changes, call the smart contract interface and record the status change on the blockchain; at the same time, the automated task trigger module 140 generates relevant events for other modules to subscribe to and process.

[0130] For the sake of easy understanding, a solution for the automated task trigger module 140 to implement the monitoring of the delivery node status change is described here. Specifically, this automated task trigger module 140 is based on the event-driven architecture (EDA, Event-Driven Architecture), which listens to the status of each node in the delivery process in real time, and triggers corresponding events when situations such as task completion, acceptance passing, task failure, or timeout occur; at the same time, this automated task trigger module 140 uses a rule engine (Rule Engine) to parse the preset trigger conditions, and combines a message queue (Kafka or RabbitMQ) to ensure the status change monitoring and asynchronous processing in a high-concurrency environment; in this way, when the status of the delivery node changes, the automated task trigger module 140 will immediately generate a status change event and push this information to other modules that have subscribed to this event.

[0131] On this basis, the blockchain storage module 130 can automatically execute the corresponding smart contract call operation after receiving the status change event pushed by the automated trigger module.

[0132] As a further illustration, this blockchain storage module 130 preferably adopts a smart contract call adaptation layer, and encapsulates compatible interfaces corresponding to different blockchain platforms at this layer, so as to ensure that the called contract methods can be correctly executed.

[0133] Such an event-driven data storage linkage mechanism can ensure the real-time recording and synchronization of status changes, and support multiple parties to view and verify the progress of the delivery process in real time.

[0134] Furthermore, this blockchain storage module 130 uses a Merkle Tree structure for querying and quickly verifying transactions within a block.

[0135] Specifically, this blockchain storage module 130 calculates the transaction data in each block body through a hash function in sequence to generate the leaf nodes of the Merkle tree, and calculates the root hash value (Merkle Root) layer by layer upward. The root hash value of the current block is recorded in the block header. Accordingly, when a user queries a certain transaction, this blockchain storage module 130 quickly locates the transaction according to the position of the block where the transaction is located, and verifies by recalculating the hash value of the Merkle path and comparing it with the root hash value in the block header, so as to judge the integrity and validity of the data.

[0136] This blockchain storage module 130 performs data query and verification based on the Merkle tree method, which has high efficiency and security. The time complexity of query and verification is O(log N), where N is the number of transactions within the block.

[0137] Furthermore, the blockchain storage module 130 also deploys a multi-node blockchain network and uses a replication consistency protocol (such as the Raft protocol) to synchronously manage the replicas of the off-chain distributed database. In this way, each node maintains a complete blockchain replica. When a certain node fails, other nodes can quickly take over its work to ensure the continuous operation of the system and the security of data. This can effectively ensure the high availability and fault tolerance of the blockchain storage module 130.

[0138] Furthermore, a task-driven dynamic storage optimization architecture is also built in the blockchain storage module 130. Through technologies such as cross-chain indexing mechanism, zero-knowledge proof (ZKP) privacy protection, verifiable computing (VC) query optimization, and smart contract-driven data life cycle management, more efficient and secure delivery data storage and management are achieved.

[0139] Compared with the traditional blockchain storage that often faces problems such as storage expansion, inefficient query, and insufficient privacy protection, the blockchain storage module 130 ensures the high security and traceability of the evidence storage data through the intelligent mapping of the permissioned chain (PBFT) and the public chain (PoS), while reducing the data burden on the chain.

[0140] In addition, the blockchain storage module 130 allows the data holder to provide a data validity proof through zero-knowledge proof without disclosing the specific content, improving the privacy protection ability of data access; on this basis, combined with verifiable computing, it can efficiently verify the stored data under lightweight computing, reducing the computing cost of evidence query.

[0141] Accordingly, based on the blockchain storage module 130, it can be ensured that during the life cycle management driven by smart contracts, data is automatically archived or cleared at different stages of delivery, optimizing the storage efficiency.

[0142] The automated trigger module 140 in this system effectively interacts with the blockchain storage module 130 and the smart contract generation module 120, and is used to automatically execute relevant tasks and notify all relevant parties in real time according to the node state changes in the delivery process and preset trigger conditions.

[0143] See Figure 4 , which shows a specific composition example scheme of this automated trigger module 140.

[0144] Based on the illustration, this automated trigger module 140 is mainly composed of an event-driven sub-module 141, a rule engine (RuleEngine) sub-module 142, a task scheduling sub-module 143, a status synchronization sub-module 144, and an exception handling sub-module 145 that cooperate with each other to ensure the efficient automatic operation and accurate triggering of the delivery process in a multi-party collaboration environment.

[0145] The event-driven sub-module 141 in this automated trigger module 140 adopts an event-driven architecture (Event-Driven Architecture), and triggers the corresponding tasks in the smart contract by listening to the state change events of each node in the engineering project digital delivery process stored in the blockchain storage module 130.

[0146] As an example, if the state change event of a certain node in the engineering project digital delivery process stored in the blockchain storage module 130 is listened to, that is, when the state of the node changes (such as task completion, acceptance passing or exception feedback), the event-driven sub-module 141 will automatically generate an event and push it into the message queue (such as Kafka or RabbitMQ), so that other modules (such as the smart contract generation module 120, the blockchain storage module 130, etc.) that have subscribed to this event will automatically receive and process this event, thus realizing asynchronous decoupling and efficient collaboration between modules. Such an event asynchronous processing method based on the message queue can ensure the real-time nature of event triggering and the stability of the system in a high-concurrency environment.

[0147] A trigger condition parser based on a rule engine is configured in the rule engine sub-module 142 of this automated trigger module 140. By cooperating with the event-driven sub-module 141, it can be used to flexibly process different types of tasks and trigger conditions.

[0148] Specifically, as mentioned above, the trigger conditions in this solution usually exist in the form of logical expressions, such as "the construction progress reaches 80% and the quality inspection is qualified" or "all design documents are submitted". This rule engine sub-module 142 adopts a reasoning algorithm based on forward chaining to parse and execute the trigger conditions. That is, when the system receives an event, this rule engine sub-module 142 will match the parameters in the event with the preset trigger conditions, and trigger the corresponding tasks after successful matching.

[0149] As a further illustration, the rule engine sub-module 142 parses and executes the trigger conditions, which can be achieved through the following steps in cooperation:

[0150] First, perform lexical analysis and syntactic analysis on the trigger conditions to generate an abstract syntax tree (AST, Abstract Syntax Tree);

[0151] Then generate condition matching rules by traversing the AST and load them into the rule execution engine; finally, when the event is triggered, the rule engine will match the conditions in real time and execute the corresponding tasks.

[0152] The rule engine sub-module 142, which is a rule engine based on forward chaining inference, can dynamically load and execute trigger conditions, ensuring the flexibility and scalability of the triggering process.

[0153] The task scheduling sub-module 143 in this automated triggering module 140 uses a distributed task scheduling framework (such as Quartz or Celery) to manage and execute triggering tasks.

[0154] Specifically, the task scheduling framework here supports the scheduling of periodic tasks and one-time tasks, and can sort tasks according to task priorities and dependencies.

[0155] On this basis, the task scheduling sub-module 143 uses a method that combines a priority queue and topological sorting to manage and execute triggering tasks, as follows:

[0156] The priority queue ensures that high-priority tasks are executed first, while topological sorting is used to handle dependencies between tasks to ensure that dependent tasks are executed in the correct order.

[0157] Among them, the priority of a task is dynamically calculated by the system according to the urgency and importance of the task. The priority calculation formula can be expressed as:

[0158] Priority = α * Urgency + β * Importance,

[0159] Where α and β are weight coefficients, and users can configure them according to the actual project requirements.

[0160] The state synchronization sub-module 144 in this automated triggering module 140, as a guarantee for the stable operation of the automated triggering module 140, is used to ensure that the states of all nodes in the system are consistent after triggering.

[0161] Specifically, this state synchronization sub-module 144 is set to automatically update the state of the corresponding node when a task is completed, and record the state change on the blockchain by calling the interface of the blockchain storage module. At the same time, this state synchronization sub-module 144 also synchronously generates state change events and broadcasts them to all subscribers to ensure data consistency and process synchronization in multi-party collaboration.

[0162] Furthermore, to improve the reliability of state synchronization, this state synchronization sub-module 144 uses the two-phase commit protocol (2PC) for the submission and confirmation of state changes. That is, before the state change, the system will first send a pre-submission request to all subscribers. If all subscribers confirm successful reception, the system will officially submit the state change; otherwise, the change operation will be rolled back.

[0163] The exception handling sub-module 145 in this automated trigger module 140 processes exception situations by constructing a corresponding exception detection and feedback mechanism.

[0164] Specifically, when an exception occurs during task execution (such as task timeout, trigger failure, etc.), the exception handling sub-module 145 automatically generates an exception event and records the exception information, and at the same time notifies the relevant parties for processing.

[0165] Furthermore, the exception handling strategies of this exception handling sub-module 145 for exception situations include two methods: automatic retry and manual intervention.

[0166] For non-critical exceptions (such as task timeout caused by network latency), this exception handling sub-module 145 will automatically retry the trigger operation. The retry strategy uses the Exponential Backoff Algorithm, that is, the interval time of each retry increases exponentially until the maximum number of retries is reached.

[0167] For critical exceptions (such as data inconsistency or rule parsing failure), this exception handling sub-module 145 will pause the trigger process and notify the user for manual intervention. After the manual intervention is completed, this exception handling sub-module 145 will re-trigger the task and resume the process.

[0168] As a further explanation, when the automated trigger module 140 formed accordingly is running, the event-driven sub-module 141 listens to the node status in the delivery process. When a task is completed, the acceptance is passed, or an exception occurs, an event is immediately generated and pushed to the message queue to trigger subsequent operations.

[0169] Next, the rule engine sub-module 142 parses the trigger event and matches it based on the preset business logic and conditional expressions to determine whether the automatic execution condition is met, such as "start task B after task A is completed and the acceptance is successful", to ensure the intelligent control of the process.

[0170] Next, when the trigger condition is met, the task scheduling sub-module 143 reasonably arranges the task execution order based on the priority queue and topological sorting algorithm, and allocates the tasks to the corresponding execution units. At the same time, the status synchronization sub-module 144 is responsible for data update during task execution to ensure the consistency of the on-chain and off-chain status, and records the status change to the blockchain through the smart contract interface to ensure the immutability of the data; if the task execution fails or an exception occurs, the exception handling sub-module 145 triggers the retry mechanism, controls the retry frequency using the exponential backoff algorithm, and pushes an exception alert to the relevant parties if it fails multiple times to ensure the stability and recoverability of the process.

[0171] In the present automatic trigger module 140, through the organic collaborative operation among the above-mentioned sub-functional modules, it is possible to efficiently and accurately manage the delivery process, and improve the automation degree and reliability of the execution of engineering projects.

[0172] The multi-party collaboration interface module 150 in this system is specifically used to provide a unified interface and interaction platform for different participants (such as design parties, construction parties, supervision parties, owner parties, etc.) in engineering projects, ensuring that all parties can view the status of the delivery process in real time, submit tasks and feedback information, and conduct acceptance confirmation and document management.

[0173] This module involves core technical methods and algorithms such as RESTful API design, identity authentication and permission management mechanisms, multi-party data synchronization and consistency assurance, instant messaging and feedback mechanisms, etc., aiming to achieve the high efficiency, data security and operation transparency of multi-party collaboration.

[0174] Specifically, the multi-party collaboration interface module 150 adopts a RESTful architecture, defines a set of standardized API interfaces, covering functions such as querying the status of the delivery process, submitting tasks, acceptance confirmation, document uploading and downloading, feedback submission, etc. At the same time, each API interface is configured to follow the design rules of the uniform resource identifier (URI), and uses HTTP methods (such as GET, POST, PUT, DELETE) to distinguish different operations, ensuring the standardization and usability of the interfaces. Furthermore, the interface request and response data are in JSON format, which is convenient for the systems of all parties to parse and process.

[0175] As an example, among them, the delivery process status query interface requests the status information of the specified node through the GET method; the task submission interface uploads task data and documents to the specified node through the POST method.

[0176] Furthermore, in the multi-party collaboration interface module 150, there is an identity authentication and permission management mechanism based on JSON Web Token (JWT), thereby ensuring data security and strict control of operation permissions during multi-party collaboration.

[0177] Specifically, based on this identity authentication and permission management mechanism, the multi-party collaboration interface module 150 can verify the user identity information when the user logs in for the first time, and generate a JWT token containing the user role and permissions. The token includes information such as the encrypted user ID, role type, permission scope and validity period, etc. Accordingly, the user needs to carry this token for identity verification in subsequent requests. The multi-party collaboration interface module 150 determines the user's identity and permissions by parsing and verifying the JWT token. If the verification passes, the user is allowed to perform the corresponding operation, otherwise the request is rejected.

[0178] The stateless authentication mechanism based on JWT of this multi-party collaboration interface module 150 can effectively improve the scalability and security of the system and is applicable to scenarios of multi-user concurrent access.

[0179] As a further illustration, in this multi-party collaboration interface module 150, a Role-Based Access Control (RBAC) model is adopted for permission management. Different roles (such as the design party, the construction party, the supervision party, etc.) are granted different permissions. The system determines the resources that can be accessed and the operations that can be executed according to the user's role and permission scope, ensuring the security and rationality of data access.

[0180] Furthermore, an event-driven data synchronization mechanism is also set up in this multi-party collaboration interface module 150 to ensure multi-party data synchronization and consistency.

[0181] Specifically, based on this data synchronization mechanism, this multi-party collaboration interface module 150 listens to the state change events of each node in the delivery process and pushes the latest status information to all participating parties that have subscribed to this node in real time.

[0182] As an example, when a certain task is completed and passes the acceptance, the system will automatically generate a status change event and push it to all relevant parties to notify them to update the local data. This multi-party collaboration interface module 150 realizes asynchronous event transmission through a message queue (such as Kafka or RabbitMQ) based on the data synchronization mechanism, and combines a distributed consistency algorithm based on the CAP theory (such as the Paxos or Raft protocol) to ensure the consistency and correctness of data among all parties. In case of an exception (such as a network interruption of a participating party resulting in untimely data synchronization), a retry strategy and a compensation mechanism will be adopted for exception recovery to ensure eventual consistency.

[0183] Furthermore, an instant messaging and feedback mechanism is also set up in this multi-party collaboration interface module 150 to support real-time communication and feedback among participating parties during the delivery process, thereby improving the real-time performance and communication efficiency of multi-party collaboration.

[0184] Specifically, this multi-party collaboration interface module 150 adopts the WebSocket protocol to achieve two-way communication, enabling real-time communication to be maintained between the client and the server through the establishment of a long connection, ensuring the instant transmission and response of messages.

[0185] The instant messaging mechanism here includes functions such as task progress notification, problem feedback and reply, acceptance result notification, etc. All messages are transmitted and stored in the database asynchronously, and users can view the historical message records at any time.

[0186] Furthermore, a problem feedback and handling interface is also set in the multi-party collaboration interface module 150, which is used for users to submit problem feedback and handling exceptions. Based on this interface, users can submit feedback information and related attachments. The system will automatically record the feedback information in the blockchain and notify the relevant parties for processing and confirmation.

[0187] Furthermore, the multi-party collaboration interface module 150 supports the upload and download of documents in multiple formats, including BIM model files (such as IFC, Revit), PDF format acceptance reports and drawings, etc., which is convenient for document management.

[0188] Among them, the upload interface of the document adopts a block transfer and verification mechanism, that is, when uploading a large file, the file is divided into several small pieces and transferred one by one. The hash value of each file block is calculated by the SHA-256 algorithm before transmission. After the transmission is completed, the system reorganizes and performs hash verification on all file blocks to ensure the integrity and accuracy of the file.

[0189] The download interface supports resume breakpoint and permission verification. Before downloading a document, the user needs to pass identity authentication and permission verification to ensure that only authorized users can access sensitive data.

[0190] For the automated solution of the digital delivery process of engineering projects driven by smart contracts given in the present invention, in specific applications, a corresponding software program can be formed to form a corresponding software system for the automated digital delivery process of engineering projects driven by smart contracts. When this software program runs, it is stored in a corresponding storage medium for the processor to retrieve and execute to implement the above system functions.

[0191] In specific applications, corresponding hardware devices are deployed, such as client computers, servers, switches, etc., thereby building an operating environment for the software system for the automated digital delivery process of engineering projects driven by smart contracts.

[0192] Accordingly, by running this software system for the automated digital delivery process of engineering projects, the automated digital delivery of engineering projects can be achieved, and the corresponding implementation process is as follows:

[0193] (1) Initialization of the delivery process.

[0194] Before the project starts, the delivery node management module defines the key delivery nodes of the project, including design delivery, construction progress confirmation, quality acceptance, and completion delivery. Each node is configured with task content, participants, and acceptance criteria. The system automatically generates a delivery flow chart and generates a corresponding smart contract through the smart contract generation module.

[0195] (2) Task execution and automated trigger.

[0196] After the design unit completes the delivery of the BIM model, the event-driven sub-module in the automated trigger module detects the completion of the task and triggers the rule engine sub-module to match the acceptance rules. The system calls the task scheduling sub-module to arrange the acceptance task for the supervision unit to ensure that the delivered BIM model meets the LOD400 standard. If the conditions are met, the status synchronization sub-module updates the delivery status and calls the blockchain storage module to store the acceptance result in the blockchain to ensure the immutability of the data.

[0197] (3) Construction progress management.

[0198] During the construction stage, the construction progress data is collected in real time through IoT devices and submitted to the system through the multi-party collaboration interface module. After the automated trigger module analyzes the data and confirms that the progress reaches 80% and the quality inspection is qualified, the smart contract automatically triggers the next task, such as arranging the construction of the next stage or equipment installation. All task execution records are stored through the blockchain to ensure traceability and verification by all parties.

[0199] (4) Exception handling.

[0200] If the construction progress does not meet the standard or the quality inspection fails, the exception handling sub-module will trigger an automatic retry or notify the relevant parties for manual intervention. The system uses the exponential backoff algorithm for multiple retries. If it still fails, the abnormal data is recorded and the supervision review process is triggered to ensure that the problem is solved.

[0201] (5) Completion and delivery.

[0202] In the project completion and delivery stage, the system automatically checks whether all delivery nodes have been completed, integrates information such as the final delivery model, acceptance report, and operation and maintenance documents, and uploads them to the database for storage. Relevant parties can query the delivery data at any time through the multi-party collaboration interface module and conduct a final review and confirmation to ensure the integrity and compliance of the completion and delivery.

[0203] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0204] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and modules described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0205] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0206] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0207] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0208] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0209] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0210] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0211] A computer-readable medium includes permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0212] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or apparatus comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising the element.

[0213] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0214] The method of the present invention described above, or a specific system unit, or a part of it, is a pure software architecture and can be distributed through program code on a physical medium such as a hard disk, an optical disc, or any electronic device (such as a smart phone, a computer-readable storage medium). When the machine loads the program code and executes it (such as a smart phone loading and executing), the machine becomes a device for implementing the present invention. The method and device of the present invention described above can also be in the form of program code and be transmitted through some transmission media such as cables, optical fibers, or any transmission type. When the program code is received, loaded and executed by a machine (such as a smart phone), the machine becomes a device for implementing the present invention.

[0215] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. An automated system for the delivery process of engineering projects driven by smart contracts, characterized in that, The engineering project delivery process automation system includes: A delivery node management module, which can define and manage key nodes in the engineering project delivery process, and can define and construct one or more attributes of corresponding delivery tasks, acceptance criteria, and trigger conditions for each node; An intelligent contract generation module, which can interact with the delivery node management module, can generate an intelligent contract that can be executed on the blockchain and can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module. A trigger mechanism is set in the intelligent contract, which can automatically trigger the execution of the delivery task of the corresponding delivery node described in the intelligent contract when the preset trigger condition is met; A blockchain data storage module, which is used to obtain key data generated during the digital delivery process of the engineering project and store it on the blockchain. The key data includes at least one of the delivery node status, acceptance record, and task result; An automated task trigger module, which can interact with the blockchain data storage module and the intelligent contract generation module, can monitor the key data obtained by the blockchain data storage module and stored on the blockchain, and can analyze and judge the status change events of each node in the delivery process through the monitored key data. It can compare and analyze the generated status change events with the trigger conditions in the intelligent contract on the blockchain, and can automatically trigger the execution of the corresponding delivery task in the intelligent contract when the trigger condition is met.

2. The automated engineering project delivery process system driven by a smart contract according to claim 1, characterized in that In the delivery node management module, corresponding dependency trigger start relationships can be set between the defined and constructed key nodes according to the business logic of the engineering project delivery process.

3. The automated system for engineering project delivery process driven by smart contract according to claim 1, wherein The delivery node management module uses a directed acyclic graph to manage the defined and constructed key nodes, configures the vertices in the graph as corresponding key nodes, configures the directed edges in the graph as the dependency relationships between the corresponding key nodes, and configures the direction of the edges as the trigger order between the key nodes.

4. The automated system for engineering project delivery process driven by smart contract according to claim 1, wherein The intelligent contract generation module uses a predefined contract template and dynamically generates an intelligent contract in combination with the attributes of the defined key nodes.

5. The automated system for engineering project delivery process driven by smart contract according to claim 1, characterized in that The intelligent contract generation module uses a parsing algorithm based on reverse Polish notation to parse and configure acceptance criteria and trigger conditions for the generated intelligent contract.

6. The automated system for engineering project delivery process driven by smart contract according to claim 1, wherein, The blockchain data storage module configures the status change of the delivery node as a transaction, generates a transaction for each status change, and records the transaction data in the block after hash processing.

7. The automated system for engineering project delivery process driven by smart contract according to claim 1, wherein After the automated trigger module completes the execution of the corresponding node delivery task, it automatically updates the status of the corresponding delivery node and records the status change on the blockchain by calling the interface of the blockchain data storage module.

8. The automated system for engineering project delivery process driven by smart contract according to claim 1, wherein, The engineering project delivery process automation system further includes a multi-party collaboration interface module, which interacts with the delivery node management module, the intelligent contract generation module, the blockchain storage module, and the automated trigger module, and can perform access permission and interaction management.

9. An automatic delivery method for engineering projects driven by smart contracts, characterized in that, The engineering project automatic delivery method includes: According to the business logic of the engineering project delivery process, define and manage the key nodes in the engineering project delivery process, and define and construct one or more attributes such as corresponding delivery tasks, acceptance criteria, and trigger conditions for each node. Generate a smart contract that can be executed on the blockchain and can describe the business logic of the engineering project delivery process according to the delivery node information defined in the delivery node management module, and a trigger mechanism is set for the smart contract, which can automatically trigger the execution of the delivery tasks of the corresponding delivery nodes described in the smart contract when the preset trigger conditions are met. Used to obtain the key data generated during the digital delivery of the engineering project and store it on the blockchain. The key data includes at least one of the data such as delivery node status, acceptance record, and task result. Monitor the key data obtained by the blockchain data storage module and stored on the blockchain, and analyze and judge the status change events of each node in the delivery process through the monitored key data. It can compare and analyze the generated status change events with the trigger conditions in the smart contract on the blockchain, and automatically trigger the execution of the corresponding delivery tasks in the smart contract when the trigger conditions are met.

10. The method for automatically delivering an engineering project driven by a smart contract according to claim 9, wherein The trigger mechanism of the event-driven model is adopted for the smart contract in the automatic delivery method of the engineering project.

Images