Binary logic organizational structure system based on block chain technology and operation method thereof

Abstract

The invention belongs to the technical field of blockchain technology application, and discloses a binary logic organizational structure system based on a blockchain technology and an operation method thereof.The binary logic organizational structure system comprises a basic element and expansion element double-layer structure, the basic element undertakes compliance supervision and financial overall planning, and the expansion element operates on a chain and is responsible for task execution and autonomous governance; the system introduces a DID, intelligent contract management, a reputation-driven incentive mechanism and a DDI dynamic index model, and constructs an on-chain and off-chain fused organization collaboration architecture. Through multi-dimensional behavior scoring, non-linear incentive distribution, digital twinborn simulation and a community autonomy mechanism, incentive precision, governance transparency and settlement compliance are realized. The method is suitable for decentralized commercial organizations, alliance governance, DAO incubation, cross-border supervision and other scenes.

Description

Technical Field

[0001] This invention belongs to the field of blockchain technology application technology, specifically a binary logic organizational architecture system based on blockchain technology and its operation method. Background Technology

[0002] In the current digital economy and global governance context, traditional centralized organizations are widely used in enterprises, institutions, and social groups, but they generally suffer from the following core problems: First, the decision-making chain is lengthy, and the top-down flow of information leads to slow response and difficulty in responding to market changes and external shocks in a timely manner; second, the lack of transparency and high concentration of power make ordinary members lack a sense of participation and trust, weakening the organization's cohesion and innovation drive; third, cross-border compliance is difficult, and the differences in regulations under different jurisdictions lead to high compliance costs, and financial audits and dispute resolution often rely on cumbersome manpower and offline processes.

[0003] At the same time, while decentralized autonomous organizations (DAOs) have clear advantages in transparency, openness, and democratic governance, they also expose their own technical and practical shortcomings. For example, the scalability and security of blockchain technology are not yet fully mature, and smart contracts have vulnerabilities. The lagging legal and regulatory framework often leaves DAOs in a legal gray area. In addition, high technical barriers make it difficult for ordinary users to participate directly, hindering large-scale popularization and application. More importantly, existing hybrid solutions that attempt to combine traditional organizations with DAOs often have complex operating logic and imperfect coordination mechanisms, making it difficult to truly balance the stability of centralization and the flexibility of decentralization, resulting in resource waste, inefficiency, and governance imbalances. Summary of the Invention

[0004] The purpose of this invention is to provide a binary logic organizational architecture system based on blockchain technology and its operation method, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a binary logic organizational architecture system based on blockchain technology, which consists of a basic module, an extended module, a business incentive module, a digital twin and intelligent early warning module, and a community governance and intelligent agent module;

[0006] The basic module allows legally registered entities to be configured with legal compliance, financial management, and strategic planning units. The Law2Code module generates smart contract code from Chinese and English legal provisions through natural language processing, semantic annotation, and logical transformation. It also simulates compliance effects in multiple jurisdictions in a sandbox environment, including a dual-track dispute resolution interface of on-chain arbitration and off-chain mediation.

[0007] The extended meta-module, based on blockchain-deployed smart contract clusters, includes a constitutional layer (core governance rules), a business layer (dynamic business logic and zero-knowledge proof protection), and an emergency layer (reserved interfaces for off-chain intervention). The cross-chain compliant bridging protocol connects and enables atomic swaps of cross-chain assets through Hash Time Locked Contracts (HTLCs), and is configured with a dual-token mechanism, including a governance token and a fiat-pegged stablecoin;

[0008] The business incentive module is deeply integrated with the extended meta smart contract. Based on DID (decentralized identity) and on-chain behavior event logs, it continuously monitors the participation records of each extended meta node in on-chain governance, proposal review, community consensus voting, and compliance behavior. The system calculates the autonomous contribution of each node by setting an autonomous scoring model (such as the DDI index) and reputation weight function, and dynamically allocates governance tokens or points in a non-linear weighted manner accordingly. The incentive results are bound to the extended meta permission status through smart contracts, realizing permission upgrades, role inheritance, and programmable evolution of organizational structure, ensuring strong coupling between governance incentives and identity reputation.

[0009] The digital twin and intelligent early warning module combines physical organization data collected by the Internet of Things (including meeting minutes, project progress, RWA asset changes) and on-chain business data. It simulates ≥1000 extreme scenarios through Monte Carlo algorithm and sandbox environment, sets deviation thresholds and anomaly detection indicators, triggers on-chain freeze, contract adjustment or governance optimization, and provides risk analysis reports.

[0010] The community governance and intelligent agent module assesses the level of autonomy based on decentralized identity (DID) and dynamic decentralization index (DDI, 0.4 × decision participation rate + 0.3 × token Gini coefficient + 0.3 × contract autonomy ratio), directly driving the intensity of incentives, contract permissions, and voting rights configuration. It combines digital humans, NFT-based virtual avatars, and humanoid robots as auxiliary intelligent agents embedded in the extension module to assist in intelligent promotion, community interaction, and task execution. Their behavioral data can be included in the extension module governance performance evaluation indicators, but do not constitute an independent extension module governance unit.

[0011] Preferably, the basic module includes:

[0012] (1) Modular legal and financial collaboration: To ensure the organization is legally registered and operates efficiently, basic modules are set up, including legal compliance, financial management and strategic planning units; through legal counsel, financial transparency system and strategic evaluation mechanism, a corporate structure that is not for profit but focuses on social value is constructed; combined with the Law2Code module, Chinese and English legal provisions are automatically converted into structured rules and generated smart contract code through natural language processing and semantic annotation; this process is pre-verified in a multi-jurisdictional sandbox environment to reduce the compliance risks of cross-border operations and take into account both flexibility and security;

[0013] (2) A dual-track system of multi-layered governance and dispute resolution: Decentralized governance is achieved by expanding meta-modules, and a smooth transition to DAO governance is achieved by relying on the layered architecture of smart contracts and dynamic weighting algorithms; a dual-track dispute resolution interface is established by combining on-chain arbitration (such as automatic arbitration based on zero-knowledge proofs) and off-chain mediation (connecting to online dispute resolution platforms) to effectively deal with conflicts in multiple scenarios. The digital twin sandbox can simulate extreme situations such as policy changes and sudden technological events, and the intelligent early warning system can promptly remind organizations of compliance deviations, providing organizations with dynamic optimization and multi-dimensional disaster recovery protection to ensure a deep integration of innovation and compliance.

[0014] Preferably, the extended module includes:

[0015] (1) Multi-layer smart contract architecture: The system adopts a blockchain-based smart contract cluster design, which is divided into a constitutional layer, a business layer and an emergency layer. The constitutional layer establishes the core governance rules that cannot be tampered with, the business layer supports dynamic business iteration and privacy protection (such as zero-knowledge proof), and the emergency layer reserves an interface for off-chain legal intervention. This layered design ensures robust governance, flexible business and compliance, and meets the high standard of operation requirements in complex scenarios.

[0016] (2) Cross-chain compliance and dual-token mechanism: The system introduces the ERC-20 and SWIFT cross-chain compliance bridging protocol and ensures the security of cross-chain asset atomic swaps through Hash Time Locked Contracts (HTLC); in the configured dual-token mechanism, the governance token empowers users to participate in decision-making, while the stablecoin pegged to fiat currency ensures the compliance and stability of financial circulation; this design combines the advantages of liquidity, compliance and decentralized governance, providing technical support for global business.

[0017] Preferably, the business incentive module includes:

[0018] (1) After the system is integrated with the Extended Meta smart contract module, a unique identifier is first established for each Extended Meta node through a Decentralized Identifier (DID). The DID is an on-chain identity credential with uniqueness, immutability, and long-term validity, used to bind various governance entities in the smart contract. The system deploys a behavior collection module to monitor the operation events executed by the node on the chain in real time, including:

[0019] Governance proposal submission;

[0020] Community participation (Governance Voting);

[0021] Smart contract review and signing;

[0022] Upload compliance report;

[0023] The above behaviors are recorded as structured behavior logs through an event capture mechanism. The log content includes: DID identifier, behavior type, timestamp, on-chain transaction number (TxID), contract interface call parameters, etc., and is uniformly written into the node behavior file.

[0024] Through this structured log design, the system achieves full-link tracking of governance participation behavior that is authentic, verifiable, and auditable, ensuring that the source of autonomous behavior data is authentic, the subject of the behavior is unique, and the process is reconstructable. This provides a technical foundation for subsequent algorithm-based scoring and incentive mechanisms, and avoids scoring injustice and incentive mismatch caused by missing behaviors or data gaps.

[0025] (2) After completing the collection and structuring of on-chain behavioral data, the system establishes an autonomous scoring model based on multi-dimensional indicators and introduces a non-linear incentive function to achieve a fair and transparent token or points allocation mechanism.

[0026] First, the system sets four core evaluation indicators: proposal participation, voting activity, compliance feedback quality, and governance influence. Proposal participation refers to the number of valid governance proposals initiated and submitted by the meta-nodes per unit of time; voting activity refers to the proportion of community votes actually participated in by a node to the total number of votes it can participate in; compliance feedback quality refers to the percentage of compliance materials submitted by a node that have been confirmed and approved by the auditing system; and governance influence refers to the weighted average of the number and proportion of proposals initiated by a node that are ultimately adopted or implemented.

[0027] The system normalizes the above raw data, converting them into standard values ​​between 0 and 1, denoted as A', B', C', and D' respectively. Correspondingly, to reflect the relative importance of different indicators to the governance effect, the system sets four scoring weight parameters α, β, γ, and δ. The sum of these four weight parameters is always 1, satisfying the formula:

[0028] α+β+γ+δ=1

[0029] Based on this, the system uses a weighted summation function to calculate the autonomous contribution score S, and the calculation formula is as follows:

[0030] S=α·A'+β·B'+γ·C'+δ·D'

[0031] Where S represents the comprehensive autonomy performance score of the extended meta-node. All calculations are automatically executed by on-chain contracts, all parameters are public and transparent, and can be periodically adjusted through community governance voting. To avoid resource concentration issues caused by linear growth of the score results in incentive distribution, the system designs a non-linear mapping function to convert the score value S into the actual distributable governance token quantity T. This incentive function adopts an exponential form, and its calculation formula is as follows:

[0032] T = T max ·(1-e -k·S )

[0033] Where T is the number of governance tokens allocated to the node; T max The maximum allocatable token limit set by the system within the current period; k is a positive real constant used to adjust the incentive growth rate, controlling the sensitivity of score changes to incentive release; e is the base of the natural logarithm, with a value of approximately 2.718; S is the aforementioned autonomous score;

[0034] The function has the following technical characteristics: when S is small, T grows approximately linearly, which is beneficial for early excitation feedback; when S approaches 1, the function enters the saturation range and gradually approaches T. max To prevent high-scoring nodes from acquiring incentive resources without limit, this nonlinear allocation strategy effectively improves the fairness and flexibility of the incentive mechanism and helps avoid the problem of high-scoring nodes dominating resource allocation.

[0035] The final calculation results are output by the system's built-in incentive contract and simultaneously written into the on-chain financial audit contract and permission management contract, enabling the real-time release of governance tokens, the level update of node permissions, and the automatic evolution of organizational structure.

[0036] Preferably, the digital twin and intelligent early warning module includes:

[0037] (1) Dynamic monitoring of physical and on-chain data fusion: The system combines physical organizational data (such as meeting minutes, project progress, RWA asset changes) collected by the Internet of Things with on-chain business data to achieve comprehensive data fusion; with the help of sandbox environment and Monte Carlo algorithm, the system can simulate more than a thousand extreme scenarios, effectively assess potential risks, and provide organizations with real-time, comprehensive operational profiles and monitoring.

[0038] (2) Intelligent early warning and on-chain governance response: The system presets deviation thresholds and anomaly detection indicators. When an over-limit event is detected, it automatically triggers on-chain freezing, smart contract adjustment or governance strategy optimization. Combined with the risk analysis report, the basic element and the extended element can adjust the financial, operational and governance plans accordingly to achieve dynamic response and forward-looking management, and improve the system's resilience and compliance guarantee.

[0039] Preferably, the community governance and intelligent agent module includes:

[0040] (1) Decentralized assessment-driven governance incentives: The system assesses the overall level of autonomy through decentralized identity and dynamic decentralized index. DDI integrates decision-making participation, token distribution and contract autonomy performance. The assessment results directly affect the incentive intensity, contract permissions and voting rights configuration, realize dynamic resource allocation based on governance level, and promote fairer and more efficient operation of the community.

[0041] (2) Based on decentralized identity and dynamic decentralized index, the level of autonomy is evaluated, which directly drives the configuration of incentive intensity, contract permissions and voting rights. Combined with digital human, NFT virtual image and humanoid robot as auxiliary intelligent agent embedded in the extension module, it assists in carrying out intelligent promotion, community interaction and task execution. Its behavior data can be included in the extension module governance performance evaluation indicators, but does not constitute an independent extension module governance unit.

[0042] Preferably, a binary logic organizational architecture operation method based on blockchain technology is provided. This method is based on the aforementioned system, and the specific steps of the method are as follows:

[0043] S1, Dynamic Control and Role Assignment, through a progressive control transfer algorithm T(t)=αe λ (-βt)+γ(1-e λ (-δt)), the system is initiated by the basic element, and business and governance weights are gradually transferred to the extension element;

[0044] S2, driven by business incentives and viral spread, uses basic elements and digital twin modules to collaboratively monitor the daily governance behavior, task execution, and promotional activities of expansion element members. It also calculates incentive scores by combining anomaly detection mechanisms and behavioral weighting models. The final results are synchronously updated to the financial module through smart contracts, achieving compliant allocation and transparent performance auditing driven by governance.

[0045] S3 enables real-time monitoring, evaluation, and adaptive optimization. The digital twin module collects on-chain and off-chain data in real time, tests the system's operating status and business incentive performance through sandbox simulation, and outputs governance and contract optimization suggestions in conjunction with the DDI index to achieve adaptive closed-loop adjustment.

[0046] Preferably, the specific steps of dynamic control and role allocation in S1 are as follows:

[0047] S11, Progressive Weight Transfer: The system employs a progressive control transfer algorithm.

[0048] T(t) = ce ∧ (-βt)+γ(1-e ∧ (-δt))

[0049] Where T(t) is the centralized weight, t is time, and β, γ, and δ are adjustment parameters; initially, the system is started by the basic elements to ensure legal compliance, financial stability, and strategic planning, laying a safe and stable starting point for decentralized operation;

[0050] S12, driving decentralized evolution: As time progresses, the α dominance in the algorithm gradually diminishes, while the γ weight increases, smoothly transitioning business and governance permissions to the extension element; through this dynamic adjustment, the system achieves a natural evolution from centralization to decentralization, preserving both initial regulatory and control capabilities and ensuring later autonomy and innovation vitality, thus optimizing long-term governance effects.

[0051] Preferably, the specific steps of business incentive-driven and viral propagation in S2 are as follows:

[0052] S21. When an extended meta node completes a valid governance action (such as participating in a proposal, voting, or compliant execution) for the first time, the system immediately writes the action event into a dedicated action file through its bound decentralized identity (DID) identifier. This file is uniformly managed by the action recording smart contract deployed on the blockchain. Its recording fields include: DID number, action type, timestamp, action parameter value, calling interface identifier (function ID), and transaction hash (TxHash), etc.

[0053] To enhance data credibility, the system is configured with a behavior verification module. This module uses trusted nodes (compliant nodes authorized by the basic metabase) to review the behavior, including but not limited to verifying that the transaction was indeed executed, the input parameters were not tampered with, and the behavior results were consistent with the contract rules. After the behavior verification is passed, the system inputs the event data into the decentralized scoring engine.

[0054] This scoring engine introduces an autonomous index model to calculate the governance behavior score S using multidimensional parameters. The specific formula is as follows:

[0055] S=α·A'+β·B'+γ·C'+δ·D'

[0056] in,

[0057] S: Autonomous contribution score of the extended meta node in the current cycle;

[0058] A ' : Participation rate in governance proposals (normalized value, ranging from [0,1]);

[0059] B ' Community voting activity (normalized value);

[0060] C ' : Compliance behavior execution confirmation rate (normalized value);

[0061] D ' : Validity of smart contract interactions (normalized value);

[0062] α,β,γ,δ: System-preset dimension weight coefficients, satisfying α+β+γ+δ=1;

[0063] The score S, as a key input parameter before incentive allocation, will be called by the on-chain incentive management contract to determine the amount of allocatable equity for the node in subsequent steps. This score is not only used in the current incentive cycle, but also accumulated into the node's historical score file for reference in long-term reputation and permission management.

[0064] After completing the scoring, the system packages the scoring results with the node DID, governance cycle identifier and timestamp, generates a resource synchronization instruction, submits it to the resource control contract and generates a synchronization transaction, ensuring that the on-chain resource status update is consistent with the subsequent processing of the off-chain financial module;

[0065] S22, at the end of each governance cycle, the system generates an incentive amount T based on the aforementioned scoring result S, specifically using a nonlinear mapping function:

[0066] T = T max ·(1-e -k·S )

[0067] Where: T: The actual number of governance tokens allocated to this node;

[0068] T max The maximum total number of tokens that can be released during the current governance cycle;

[0069] S: Node's autonomous contribution score;

[0070] k: Incentive growth control coefficient (positive real number);

[0071] e: The base of the natural logarithm, approximately equal to 2.718.

[0072] This function satisfies the following incentive characteristics: when S is below the low value range, token growth is slow to encourage continuous governance behavior; when S is close to 1, the function tends to saturate, preventing high-scoring nodes from acquiring resources indefinitely and preventing incentive concentration skew.

[0073] Based on the output of the incentive function, the system automatically generates a compliant incentive allocation proposal, in the format of a structured governance proposal supported by the on-chain governance contract, including the following fields:

[0074] Node DID number;

[0075] Motivation score S;

[0076] Allocation quota T;

[0077] The corresponding behavior is a hash set (TxHashList);

[0078] Resource sourcing module and budget sub-pool;

[0079] Proposal version number and unique motion ID;

[0080] The proposal was submitted to the governance review interface of the extended metacontract, where it was verified and voted on by community nodes. Once the proposal passed, the system immediately synchronized the allocation instructions to the financial compliance module of the basic metacontract. This module deploys an intelligent audit engine, which, in conjunction with the Law2Code structured compliance contract, reviews the following:

[0081] Does the allocation of incentives comply with the authorization of the governance charter?

[0082] Is the amount of tokens used within the budget pool?

[0083] Does the node have any violations or freeze records?

[0084] Does the content of the proposal meet local judicial compliance standards?

[0085] After compliance verification is completed, the finance module sends a confirmation signal to the resource release module through the on-chain contract interface, and the incentive is immediately transferred to the account, while the incentive log and node permission table are updated.

[0086] In addition, to ensure the judicial validity of the entire process, the system synchronously stores all incentive transactions (including scoring, proposals, voting, settlement, and permission updates) in multiple judicial sandbox environments; each transaction is compared with the compliance rules stored in the Law2Code module to form a structured audit report, supporting future cross-border compliance filing, financial and tax disclosure, and dispute mediation.

[0087] This closed-loop mechanism ensures the legality of on-chain incentive behavior, the verifiability of incentive results, and the immutability of node records, thus constructing a trustworthy architecture that integrates on-chain governance, off-chain auditing, and legal domain evidence storage.

[0088] Preferably, the specific steps of real-time monitoring, evaluation, and adaptive optimization in S3 are as follows:

[0089] S31, Real-time Data Collection and Sandbox Simulation: The digital twin module collects data such as on-chain transactions, governance participation, and business incentives in real time, as well as off-chain operation and user interaction information; it conducts system status and incentive mechanism simulation testing in a sandbox environment to identify potential anomalies and operational bottlenecks, providing comprehensive data support and scenario verification for subsequent governance optimization;

[0090] S32, DDI Assessment and Adaptive Optimization: Combining the Dynamic Decentralization Index (DDI) to assess the level of autonomy, the system automatically generates governance and contract optimization suggestions, covering incentive allocation, contract permissions and voting mechanisms; the adjustment suggestions are adaptively fed back to on-chain and off-chain modules to form a real-time closed-loop optimization, continuously improving organizational resilience, efficiency and user participation experience.

[0091] The beneficial effects of this invention are as follows:

[0092] 1. This invention introduces a basic module to legally register an organization as a legal entity that complies with local laws, and configures units such as legal compliance, financial management, and strategic planning. Combined with the Law2Code module, it transforms Chinese and English legal provisions into verifiable smart contract code and rehearses compliance effects in a multi-jurisdictional sandbox, effectively reducing the legal risks of cross-border operations. Through a dual-track dispute resolution mechanism of on-chain arbitration and off-chain mediation, it improves the efficiency of dispute resolution. Compared with traditional organizations, this solution retains the robustness and regulatory advantages of centralized organizations, while also providing technical preparation and compliance support for the future decentralized transition at the underlying level, enhancing the reliability and resilience of overall operations.

[0093] 2. This invention constructs an identity-driven incentive mechanism centered on path-binding through a business incentive module. It no longer relies on traditional sharing path tracing or invitation relationship chains, but instead uses DID identity as a unique identifier. On-chain monitoring technology records the governance participation, task completion, content co-creation, and compliance feedback of extended meta-nodes, and synchronously updates their contribution profiles. The system effectively distinguishes between genuine participation and fraudulent operations by setting segmented payment contracts for initial and final payments, combined with mechanisms such as pseudo-active behavior identification, zombie account detection, and continuous analysis of behavioral trajectories. This enables dynamic release of incentives based on contribution. This mechanism ensures that every reward resource originates from audited contribution behavior, and the payment process is triggered only after approval by the basic meta-audit node through a structured contract proposal. This significantly improves the security, fairness, and traceability of incentive distribution, avoiding incentive abuse or governance imbalance caused by path manipulation.

[0094] 3. This invention utilizes a digital twin and intelligent early warning module, combining physical organizational data collected by the Internet of Things with on-chain governance and business data. Through Monte Carlo simulations of ≥1000 extreme scenarios, it identifies potential risks and abnormal behaviors. Based on a dynamic decentralized index, the system generates optimization suggestions for incentive intensity, contract permissions, and voting rights in real time, and feeds them back to on-chain and off-chain modules to achieve adaptive closed-loop optimization. This mechanism not only improves the organization's agility, stability, and user participation experience, but also provides a replicable and scalable solution for more complex and cross-domain governance scenarios in the future. Attached Figure Description

[0095] Figure 1 This is a flowchart of the binary logic organizational architecture system based on blockchain technology of the present invention;

[0096] Figure 2 This is a flowchart of the binary logic organizational architecture operation method based on blockchain technology of the present invention. Detailed Implementation

[0097] 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.

[0098] like Figures 1 to 2 As shown, this embodiment of the invention provides a binary logic organizational architecture system based on blockchain technology. The system consists of a basic module, an extended module, a business incentive module, a digital twin and intelligent early warning module, and a community governance and intelligent agent module. The basic module allows legally registered entities to be configured with legal compliance, financial management, and strategic planning units. The Law2Code module generates smart contract code from Chinese and English legal provisions through natural language processing, semantic annotation, and logical transformation. It also simulates compliance effects in multiple jurisdictions in a sandbox environment, including a dual-track dispute resolution interface of on-chain arbitration and off-chain mediation. Example of a basic module: Taking a non-profit organization registered in Singapore as an example, the organization has established a dedicated legal compliance team responsible for developing an internal compliance manual in accordance with Singapore company law, data protection regulations (such as PDPA), etc. Through the Law2Code module, the team converts the relevant provisions into machine-readable smart contract code and rehearses it in a sandbox environment, including testing the compliance adaptation in different jurisdictions. In its daily operations, the organization uses on-chain arbitration to handle small contract disputes (such as supplier performance issues). For more complex situations or situations that require human judgment, it connects to an off-chain ODR (Online Dispute Resolution) platform for mediation and arbitration.

[0099] The extended meta-module, based on blockchain-deployed smart contract clusters, includes a constitutional layer (core governance rules), a business layer (dynamic business logic and zero-knowledge proof protection), and an emergency layer (reserved interfaces for off-chain intervention). The cross-chain compliant bridging protocol connects and enables atomic swaps of cross-chain assets through Hash Time Locked Contracts (HTLCs), and is configured with a dual-token mechanism, including a governance token and a fiat-pegged stablecoin; Example of an Extended Meta module: A cross-border e-commerce alliance deployed a smart contract cluster based on the Conflux public chain in Extended Meta, establishing a constitutional layer (the alliance's charter is immutable), a business layer (quarterly updates to cross-border transaction and settlement rules), and an emergency layer (reserving off-chain intervention interfaces); the alliance... The bridging protocol enables the secure conversion between alliance governance tokens and fiat currency funds; alliance members hold tokens at the governance layer and participate in voting, such as on annual budgets and strategic adjustments, while cross-border settlements between merchants use stablecoins pegged to the US dollar to ensure compliant and cost-controllable fund flows.

[0100] The business incentive module is deeply integrated with the extended meta smart contract. Based on DID (decentralized identity) and on-chain behavior event logs, it continuously monitors the participation records of each extended meta node in on-chain governance, proposal review, community consensus voting, and compliance behavior. The system calculates the autonomous contribution of each node by setting an autonomous scoring model (such as the DDI index) and reputation weight function, and dynamically allocates governance tokens or points in a non-linear weighted manner accordingly. The incentive results are bound to the extended meta permission status through smart contracts, realizing permission upgrades, role inheritance, and programmable evolution of organizational structure, ensuring strong coupling between governance incentives and identity reputation.

[0101] Example of Business Incentive Module: During the business launch phase, after the expansion node completes its first participation, the system activates the on-chain behavior tracking mechanism based on its DID identity, records its comprehensive behavioral events in scenarios such as proposal participation, collaborative tasks, and content co-creation, and identifies pseudo-active behavior by combining anti-tampering audit logs; the system generates an incentive score based on the expansion node's continuous governance contribution, behavioral consistency, and verified collaborative results, which is used to drive resource allocation and token release rhythm, rather than relying on traditional invitation paths or transaction propagation links;

[0102] The system automatically generates compliant allocation proposals based on autonomous incentive scores. After on-chain review, the proposals are synchronized to the basic meta-financial compliance module, which verifies the legality of the reward allocation scheme and authorizes its release according to smart audit rules. All incentive transfers, resource releases, and permission change records are compared with Law2Code structured compliance clauses through smart contracts in multiple judicial sandboxes to ensure a solid two-way trust bridge between on-chain incentives and off-chain compliant settlements.

[0103] After a user completes their initial governance action, the system activates their "contribution identity" tag and records their participation path through a behavior graph engine, including events such as task collaboration, community response, and compliance feedback. Each contribution action is automatically updated by the system after being confirmed by the governance verification node. It does not rely on referral behavior, and all incentive releases are based on reputation weight rather than transaction frequency, effectively preventing low-quality referrals and incentive abuse.

[0104] The digital twin and intelligent early warning module combines physical organization data collected by the Internet of Things (including meeting minutes, project progress, RWA asset changes) and on-chain business data. It simulates ≥1000 extreme scenarios through Monte Carlo algorithm and sandbox environment, sets deviation thresholds and anomaly detection indicators, triggers on-chain freeze, contract adjustment or governance optimization, and provides risk analysis reports.

[0105] Example of a digital twin and intelligent early warning module: An organization focused on renewable energy projects uses IoT sensors to collect real-time on-site data (such as power generation and equipment operation status) and upload it to the blockchain. This is combined with on-chain business data (such as fund disbursement and milestone achievement status). The digital twin module simulates more than 1,000 extreme scenarios (such as equipment failure, energy price fluctuations, and policy adjustments) in a sandbox environment and sets thresholds. If power generation in a certain region deviates from the target by 10% or fund usage is abnormal, it will trigger the freezing of related payments on the blockchain, adjustment of contract parameters, or issuance of an early warning report, which will be responded to promptly by the governance team.

[0106] The community governance and intelligent agent module assesses the level of autonomy based on decentralized identity (DID) and dynamic decentralization index (DDI, 0.4 × decision participation rate + 0.3 × token Gini coefficient + 0.3 × contract autonomy ratio), directly driving the intensity of incentives, contract permissions, and voting rights configuration. It combines digital humans, NFT-based virtual avatars, and humanoid robots as auxiliary intelligent agents embedded in the extension module to assist in intelligent promotion, community interaction, and task execution. Their behavioral data can be included in the extension module governance performance evaluation indicators, but do not constitute an independent extension module governance unit.

[0107] Community Governance and Intelligent Agent Module Example: In a decentralized social platform, users participate in community governance through DID (Decentralized Identity) authentication; the platform assesses the degree of community autonomy through DDI (Dynamic Decentralization Index), such as participation rate, token distribution, and contract automation level, and dynamically adjusts user voting rights, reward ratios, etc. accordingly; digital avatars (AIGC-generated virtual images) and NFT-based personal avatars are used for social scenarios and activity participation, while humanoid robots undertake tasks such as content review and FAQ answers in forums, realizing partial automation of community management and providing users with a richer and more immersive interactive experience.

[0108] The foundational modules, designed to ensure legal registration and efficient operation, include legal compliance, financial management, and strategic planning units. Through legal counsel, financial transparency mechanisms, and strategic evaluation, a corporate structure focused on social value rather than profit is constructed. The Law2Code module automatically converts Chinese and English legal provisions into structured rules and generates smart contract code through natural language processing and semantic annotation. This process is pre-verified in a multi-jurisdictional sandbox environment, reducing compliance risks in cross-border operations while balancing flexibility and security. Decentralized governance is achieved through extended modules, smoothly transitioning to DAO governance via a layered smart contract architecture and dynamic weighting algorithms. A dual-track dispute resolution interface is established, combining on-chain arbitration (such as automated arbitration based on zero-knowledge proofs) and off-chain mediation (connecting to online dispute resolution platforms), effectively addressing conflicts in various scenarios. The digital twin sandbox can simulate extreme scenarios such as policy changes and technological emergencies, with an intelligent early warning system promptly alerting to compliance deviations, providing dynamic optimization and multi-dimensional disaster recovery guarantees to ensure a deep integration of innovation and compliance.

[0109] The extended meta-module refers to the system's adoption of a blockchain-based smart contract cluster design, divided into a constitutional layer, a business layer, and an emergency layer. The constitutional layer establishes immutable core governance rules, the business layer supports dynamic business iteration and privacy protection (such as zero-knowledge proofs), and the emergency layer reserves interfaces for off-chain legal intervention. This layered design ensures robust governance, flexible business operations, and compliant resilience, meeting high-standard operational requirements in complex scenarios. The system introduces an ERC-20 and SWIFT cross-chain compliance bridging protocol, using Hash Time Locked Contracts (HTLCs) to ensure the security of atomic swaps of cross-chain assets. In the configured dual-token mechanism, the governance token empowers user participation in decision-making, while the fiat-pegged stablecoin ensures the compliance and robustness of financial circulation. This design combines the advantages of liquidity, compliance, and decentralized governance, providing technical support for global business.

[0110] The business incentive module refers to the process where, after the system integrates with the extended element smart contract module, it first establishes a unique identifier for each extended element node through a decentralized identity (DID). The DID serves as an on-chain identity credential, possessing uniqueness, immutability, and long-term validity, and is used to bind various governance entities within the smart contract. The system deploys a behavior collection module to monitor in real-time the operational events executed by this node on the chain, including:

[0111] Governance proposal submission;

[0112] Community participation (Governance Voting);

[0113] Smart contract review and signing;

[0114] Upload compliance report;

[0115] The above behaviors are recorded as structured behavior logs through an event capture mechanism. The log content includes: DID identifier, behavior type, timestamp, on-chain transaction number (TxID), contract interface call parameters, etc., and is uniformly written into the node behavior file.

[0116] Through this structured log design, the system achieves full-link tracking of governance participation behavior that is authentic, verifiable, and auditable, ensuring that the source of autonomous behavior data is authentic, the subject of the behavior is unique, and the process is reconstructable. This provides a technical foundation for subsequent algorithm-based scoring and incentive mechanisms, and avoids scoring injustice and incentive mismatch caused by missing behaviors or data gaps.

[0117] After completing the collection and structuring of on-chain behavioral data, the system establishes an autonomous scoring model based on multi-dimensional indicators and introduces a non-linear incentive function to achieve a fair and transparent token or points allocation mechanism.

[0118] First, the system sets four core evaluation indicators: proposal participation, voting activity, compliance feedback quality, and governance influence. Proposal participation refers to the number of valid governance proposals initiated and submitted by the meta-nodes per unit of time; voting activity refers to the proportion of community votes actually participated in by a node to the total number of votes it can participate in; compliance feedback quality refers to the percentage of compliance materials submitted by a node that have been confirmed and approved by the auditing system; and governance influence refers to the weighted average of the number and proportion of proposals initiated by a node that are ultimately adopted or implemented.

[0119] The system normalizes the above raw data, converting them into standard values ​​between 0 and 1, denoted as A', B', C', and D' respectively. Correspondingly, to reflect the relative importance of different indicators to the governance effect, the system sets four scoring weight parameters α, β, γ, and δ. The sum of these four weight parameters is always 1, satisfying the formula:

[0120] α+β+γ+δ=1

[0121] Based on this, the system uses a weighted summation function to calculate the autonomous contribution score S, and the calculation formula is as follows:

[0122] S=α·A'+β·B'+γ·C'+δ·D'

[0123] Where S represents the comprehensive autonomy performance score of the extended meta-node. All calculations are automatically executed by on-chain contracts, all parameters are public and transparent, and can be periodically adjusted through community governance voting. To avoid resource concentration issues caused by linear growth of the score results in incentive distribution, the system designs a non-linear mapping function to convert the score value S into the actual distributable governance token quantity T. This incentive function adopts an exponential form, and its calculation formula is as follows:

[0124] T = T max ·(1-e -k·S )

[0125] Where T is the number of governance tokens allocated to the node; T max The maximum allocatable token limit set by the system within the current period; k is a positive real constant used to adjust the incentive growth rate, controlling the sensitivity of score changes to incentive release; e is the base of the natural logarithm, with a value of approximately 2.718; S is the aforementioned autonomous score;

[0126] The function has the following technical characteristics: when S is small, T grows approximately linearly, which is beneficial for early excitation feedback; when S approaches 1, the function enters the saturation range and gradually approaches T. max To prevent high-scoring nodes from acquiring incentive resources without limit, this nonlinear allocation strategy effectively improves the fairness and flexibility of the incentive mechanism and helps avoid the problem of high-scoring nodes dominating resource allocation.

[0127] The final calculation results are output by the system's built-in incentive contract and simultaneously written into the on-chain financial audit contract and permission management contract, enabling the real-time release of governance tokens, the level update of node permissions, and the automatic evolution of organizational structure.

[0128] The digital twin and intelligent early warning module refers to the system's comprehensive data fusion, which combines physical organizational data collected by the Internet of Things (such as meeting minutes, project progress, and RWA asset changes) with on-chain business data. Leveraging a sandbox environment and Monte Carlo algorithms, the system can simulate over a thousand extreme scenarios, effectively assessing potential risks and providing organizations with real-time, comprehensive operational profiles and monitoring. The system presets deviation thresholds and anomaly detection indicators; when an out-of-limit event is detected, it automatically triggers on-chain freezes, smart contract adjustments, or governance strategy optimizations. Combined with risk analysis reports, the basic and extended components can adjust financial, operational, and governance plans accordingly, achieving dynamic response and forward-looking management, and enhancing system resilience and compliance assurance.

[0129] The community governance and intelligent agent module refers to the system's assessment of overall autonomy level through decentralized identity and dynamic decentralized index, DDI comprehensive decision-making participation, token distribution, and contract autonomy performance. The assessment results directly affect incentive intensity, contract permissions, and voting rights configuration, realizing dynamic resource allocation based on governance level and promoting fairer and more efficient community operation. The autonomous level assessment based on decentralized identity and dynamic decentralized index directly drives incentive intensity, contract permissions, and voting rights configuration. Combined with digital humans, NFT-based virtual avatars, and humanoid robots as auxiliary intelligent agents embedded in the extension module, they assist in carrying out intelligent promotion, community interaction, and task execution. Their behavioral data can be included in the extension module governance performance evaluation indicators, but do not constitute an independent extension module governance unit.

[0130] This embodiment provides a method for operating a binary logic organizational architecture based on blockchain technology. The specific steps are as follows:

[0131] S1, Dynamic Control and Role Assignment, through a progressive control transfer algorithm T(t)=αe λ (-βt)+γ(1-e λ (-δt)), the system is initiated by the basic element, and business and governance weights are gradually transferred to the extension element;

[0132] S2, driven by business incentives and viral spread, uses basic elements and digital twin modules to collaboratively monitor the daily governance behavior, task execution, and promotional activities of expansion element members. It also calculates incentive scores by combining anomaly detection mechanisms and behavioral weighting models. The final results are synchronously updated to the financial module through smart contracts, achieving compliant allocation and transparent performance auditing driven by governance.

[0133] S3 enables real-time monitoring, evaluation, and adaptive optimization. The digital twin module collects on-chain and off-chain data in real time, tests the system's operating status and business incentive performance through sandbox simulation, and outputs governance and contract optimization suggestions in conjunction with the DDI index to achieve adaptive closed-loop adjustment.

[0134] In S1, dynamic control and role allocation refer to the system employing a progressive control transfer algorithm.

[0135] T(t) = ce ∧ (-βt)+γ(1-e ∧ (-δt))

[0136] Where T(t) is the centralization weight, t is time, and β, γ, and δ are adjustment parameters. Initially, the system is started by the basic element to ensure legal compliance, financial stability, and strategic planning, laying a safe and stable starting point for decentralized operation. As time progresses, the dominance of α in the algorithm gradually decreases, while the weight of γ increases, smoothly transitioning business and governance authority to the extension element. Through this dynamic adjustment, the system achieves a natural evolution from centralization to decentralization, retaining both initial supervision and control, ensuring later autonomy and innovation vitality, and optimizing long-term governance effects.

[0137] In S2, business incentive-driven and viral propagation refers to the fact that when an extended meta node completes an effective governance action for the first time (such as participating in a proposal, voting, or compliant execution), the system immediately writes the action event into a dedicated action file through its bound decentralized identity (DID) identifier. This file is uniformly managed by a smart contract for action recording deployed on the blockchain, and its recording fields include: DID number, action type, timestamp, action parameter value, call interface identifier (function ID), and transaction hash (TxHash), etc.

[0138] To enhance data credibility, the system is configured with a behavior verification module. This module uses trusted nodes (compliant nodes authorized by the basic metabase) to review the behavior, including but not limited to verifying that the transaction was indeed executed, the input parameters were not tampered with, and the behavior results were consistent with the contract rules. After the behavior verification is passed, the system inputs the event data into the decentralized scoring engine.

[0139] This scoring engine introduces an autonomous index model to calculate the governance behavior score S using multidimensional parameters. The specific formula is as follows:

[0140] S=α·A'+β·B'+γ·C'+δ·D'

[0141] in,

[0142] S: Autonomous contribution score of the extended meta node in the current cycle;

[0143] A ' : Participation rate in governance proposals (normalized value, ranging from [0,1]);

[0144] B ' Community voting activity (normalized value);

[0145] C ' : Compliance behavior execution confirmation rate (normalized value);

[0146] D ' : Validity of smart contract interactions (normalized value);

[0147] α,β,γ,δ: System-preset dimension weight coefficients, satisfying α+β+γ+δ=1;

[0148] The score S, as a key input parameter before incentive allocation, will be called by the on-chain incentive management contract to determine the amount of allocatable equity for the node in subsequent steps. This score is not only used in the current incentive cycle, but also accumulated into the node's historical score file for reference in long-term reputation and permission management.

[0149] After completing the scoring, the system packages the scoring results with the node DID, governance cycle identifier and timestamp, generates a resource synchronization instruction, submits it to the resource control contract and generates a synchronization transaction, ensuring that the on-chain resource status update is consistent with the subsequent processing of the off-chain financial module;

[0150] At the end of each governance cycle, the system generates an incentive amount T based on the aforementioned scoring result S, specifically using a nonlinear mapping function:

[0151] T = T max ·(1-e -k·S )

[0152] Where: T: The actual number of governance tokens allocated to this node;

[0153] T max The maximum total number of tokens that can be released during the current governance cycle;

[0154] S: Node's autonomous contribution score;

[0155] k: Incentive growth control coefficient (positive real number);

[0156] e: The base of the natural logarithm, approximately equal to 2.718.

[0157] This function satisfies the following incentive characteristics: when S is below the low value range, token growth is slow to encourage continuous governance behavior; when S is close to 1, the function tends to saturate, preventing high-scoring nodes from acquiring resources indefinitely and preventing incentive concentration skew.

[0158] Based on the output of the incentive function, the system automatically generates a compliant incentive allocation proposal, in the format of a structured governance proposal supported by the on-chain governance contract, including the following fields:

[0159] Node DID number;

[0160] Motivation score S;

[0161] Allocation quota T;

[0162] The corresponding behavior is a hash set (TxHashList);

[0163] Resource sourcing module and budget sub-pool;

[0164] Proposal version number and unique motion ID;

[0165] The proposal was submitted to the governance review interface of the extended metacontract, where it was verified and voted on by community nodes. Once the proposal passed, the system immediately synchronized the allocation instructions to the financial compliance module of the basic metacontract. This module deploys an intelligent audit engine, which, in conjunction with the Law2Code structured compliance contract, reviews the following:

[0166] Does the allocation of incentives comply with the authorization of the governance charter?

[0167] Is the amount of tokens used within the budget pool?

[0168] Does the node have any violations or freeze records?

[0169] Does the content of the proposal meet local judicial compliance standards?

[0170] After compliance verification is completed, the finance module sends a confirmation signal to the resource release module through the on-chain contract interface, and the incentive is immediately transferred to the account, while the incentive log and node permission table are updated.

[0171] In addition, to ensure the judicial validity of the entire process, the system synchronously stores all incentive transactions (including scoring, proposals, voting, settlement, and permission updates) in multiple judicial sandbox environments; each transaction is compared with the compliance rules stored in the Law2Code module to form a structured audit report, supporting future cross-border compliance filing, financial and tax disclosure, and dispute mediation.

[0172] This closed-loop mechanism ensures the legality of on-chain incentive behavior, the verifiability of incentive results, and the immutability of node records, thus constructing a trustworthy architecture that integrates on-chain governance, off-chain auditing, and legal domain evidence storage.

[0173] In S3, real-time monitoring, evaluation, and adaptive optimization refer to the digital twin module's real-time collection of data on on-chain transactions, governance participation, and business incentives, as well as off-chain operational and user interaction information. Through sandbox environment simulation testing of system status and incentive mechanisms, potential anomalies and operational bottlenecks are identified, providing comprehensive data support and scenario verification for subsequent governance optimization. Combined with the Dynamic Decentralization Index (DDI) to assess autonomy levels, the system automatically generates governance and contract optimization suggestions, covering incentive allocation, contract permissions, and voting mechanisms. These suggestions are adaptively fed back to on-chain and off-chain modules, forming a real-time closed-loop optimization that continuously improves organizational resilience, efficiency, and user experience.

[0174] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0175] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A binary logic organizational architecture system based on blockchain technology, characterized in that: The system is composed of basic meta-modules, expansion meta-modules, business incentive modules, digital twins and intelligent early warning modules, and community governance and intelligent agent modules; The basic meta-module is a legally registered entity organization, which configures legal compliance, financial management, and strategic planning units. Through the Law2Code module, Chinese and English legal provisions are processed by natural language processing, semantic annotation, and logical conversion to generate smart contract code. The system simulates compliance effects in multiple jurisdictions in a sandbox environment, including on-chain arbitration and off-chain mediation dispute resolution interfaces. Expansion meta-module, based on blockchain deployment of smart contract cluster, including constitution layer, business layer, emergency layer, and Cross-chain compliance bridge protocol interconnection, cross-chain asset atomic exchange is realized through hash time lock contract, and double token mechanism is configured, including governance Token and stable currency anchored by legal tender; The business incentive module is deeply integrated with the expansion meta-intelligent contract. Based on DID and on-chain behavior event logs, the system continuously monitors the participation records of each expansion meta-node in on-chain governance, proposal review, community consensus voting, and compliance behavior dimensions. The system sets an autonomous scoring model and a reputation weight function to calculate the autonomous contribution of each node and dynamically allocate governance tokens or points in a non-linear weighted manner. The digital twin and intelligent early warning module combines physical organization data collected by the Internet of Things and on-chain business data. Through Monte Carlo algorithm and sandbox environment, ≥1000 extreme scenarios are simulated. The system sets deviation thresholds and anomaly detection indicators to trigger on-chain freezing, contract adjustment or governance optimization, and provides risk analysis reports. The community governance and intelligent agent module assesses autonomy level based on decentralized identity and dynamic decentralized index. It directly drives incentive intensity, contract permissions, and voting rights configuration. It provides intelligent promotion, community interaction, and task automation services through digital people, NFT virtual avatars, and humanoid robots. 2.The binary logic organization architecture system based on blockchain technology according to claim 1, characterized in that: The basic meta-module includes: (1) Modular legal and financial collaboration: To ensure that the organization is registered in accordance with the law and operates efficiently, the basic meta-module includes legal compliance, financial management, and strategic planning units. Through legal consultants, financial transparency systems, and strategic assessment mechanisms, a legal structure is established that is not profit-driven but focuses on social value. Combined with the Law2Code module, Chinese and English legal provisions are automatically processed by natural language processing and semantic annotation, converted into structured rules, and generated into smart contract code. This process is pre-verified in a multi-jurisdiction sandbox environment to reduce compliance risks in cross-border operations, balancing flexibility and security. (2) Multi-layer governance and dispute resolution dual-track system: Decentralized governance is achieved through the expansion meta-module, relying on a hierarchical smart contract architecture and dynamic weight algorithm to smoothly transition to DAO governance. Combined with on-chain arbitration and off-chain mediation, a dual-track dispute resolution interface is established. The digital twin sandbox can simulate policy changes, technology emergencies, and other extreme scenarios, and the intelligent early warning system can promptly alert compliance deviations. 3.The binary logic organization architecture system based on blockchain technology according to claim 2, characterized in that: The expansion meta-module includes: (1) Multi-layer smart contract architecture: The system uses a blockchain-based smart contract cluster design, divided into a constitution layer, a business layer, and an emergency layer. The constitution layer establishes immutable core governance rules, the business layer supports dynamic business iteration and privacy protection, and the emergency layer reserves interfaces for off-chain legal intervention. This hierarchical design ensures stable governance, flexible business, and compliance flexibility, meeting the high-standard operation requirements in complex scenarios. (2), Cross-chain compliance and dual-token mechanism: The system introduces an ERC-20 and SWIFT cross-chain compliance bridge protocol, and guarantees the atomic exchange safety of cross-chain assets through a hash time lock contract. In the configured dual-token mechanism, governance tokens empower users to participate in decision-making, and stablecoins anchored to fiat currencies ensure compliance and stability in financial circulation. 4.The binary logical organization architecture based on blockchain technology according to claim 3, wherein: The commercial incentive module comprises: (1), After the system is integrated with the extended meta-intelligent contract module, the unique extended meta-node is identified through DID first, and the behavior event data of its governance operation, proposal submission, community voting and compliance execution on the chain are collected in real time. These behavior events are recorded as structured logs, which constitute the original basis for autonomous behavior; (2), The system establishes an autonomous scoring model and introduces a reputation weight function. The collected various on-chain behaviors are standardized according to the indicators, and different dimensions are given score weights. Then, the autonomous contribution of the extended meta-node is calculated through a nonlinear weighting formula, and the number of governance tokens or the integral amount that it should obtain is dynamically determined according to the governance cycle and the contract configuration results. 5.The binary logical organization architecture system based on blockchain technology according to claim 4, characterized in that: The digital twin and intelligent early warning module comprises: (1), Dynamic monitoring of physical and on-chain data fusion: The system combines physical organization data collected by the Internet of Things and on-chain business data to achieve comprehensive data fusion. With the help of sandbox environment and Monte Carlo algorithm, the system can simulate more than a thousand extreme scenarios, effectively evaluate potential risks, and provide real-time, all-round operation profiling and monitoring for organizations; (2), Intelligent early warning and on-chain governance response: The system presets deviation thresholds and abnormal detection indicators. When an out-of-limit event is detected, it automatically triggers on-chain freezing, intelligent contract adjustment or governance strategy optimization. Combined with the risk analysis report, the basic meta and the extended meta can adjust the financial, operational and governance schemes accordingly, realize dynamic response and forward-looking management, and improve the system resilience and compliance guarantee. 6.The binary logic organization architecture system based on blockchain technology according to claim 5, characterized in that: The community governance and intelligent agent module comprises: (1), Decentralized evaluation-driven governance incentive: The system evaluates the overall autonomy level through decentralized identity and dynamic decentralized index. DDI integrates decision-making participation, token distribution and contract autonomy performance. The evaluation results directly affect the incentive intensity, contract authority and voting right configuration, realizing dynamic resource allocation based on governance level, and promoting the community to operate more fairly and efficiently; (2), Based on the decentralized identity and dynamic decentralized index evaluation of the autonomy level, the incentive intensity, contract authority and voting right configuration are directly driven. Combined with digital people, NFT virtual avatars and humanoid robots as auxiliary intelligent agents embedded in the extended meta module, they assist in intelligent promotion, community interaction and task execution. Their behavior data can be included in the extended meta governance performance evaluation indicators, but do not independently constitute the extended meta governance unit. 7.A method for running a binary logic organization architecture based on a blockchain technology, characterized in that: The binary logic organizational architecture operation method based on blockchain technology is based on the system of claim 6, and the specific steps of the method are as follows: S1, Dynamic control and role allocation, through the gradual control right migration algorithm, the system is started by the basic meta, and the business and governance weight is gradually transferred to the extended meta; S2, business incentive drive and fission spread, through the basic element and digital twin module to monitor the daily governance behavior, task execution and promotion activities of the expansion element members, and combine the abnormal detection mechanism and behavior weight model to calculate the incentive score; S3, real-time monitoring, evaluation and adaptive optimization, the digital twin module collects real-time on-chain and off-chain data, detects system state and business incentive performance through sandbox simulation, combines DDI index to output governance and contract optimization suggestions, and realizes adaptive closed-loop adjustment. 8.The method of claim 7, wherein the method further comprises: receiving a request for a blockchain-based binary logic organization framework; and providing the blockchain-based binary logic organization framework to the requestor. The specific steps of dynamic control and role allocation in S1 are as follows: S11, gradual weight migration: the system uses a gradual control weight migration algorithm: T(t)=ce^(-βt)+γ(1-e^(-δt)), Where T(t) is the centralization weight, t is the time, β, γ, δ are adjustment parameters; S12, drive decentralized evolution: with the passage of time, the algorithm gradually decays the alpha dominant right and increases the gamma weight, which will smoothly transition the business and governance rights to the expansion element.

9. The binary logic organizational structure operation method based on blockchain technology according to claim 8, characterized in that: The specific steps of business incentive drive and fission spread in S2 are as follows: S21, after the user completes the first governance participation, the smart contract of the expansion element automatically records the behavior event based on its DID identity; the system combines the abnormal detection mechanism and trusted node confirmation process to update the user's governance behavior score in real time; before incentive distribution, the system calculates the user's deserved rights and interests based on the decentralized index model, and completes the on-chain resource synchronization and financial authorization process; S22, the system automatically generates a compliance distribution proposal based on the autonomous incentive score, which is synchronized to the basic element financial module after being reviewed on the chain, and the legal verification and authorization release of the reward distribution scheme are completed by the smart audit rules; all incentive transfers, resource releases and permission changes are recorded in the multi-jurisdiction sandbox and compared through smart contracts and Law2Code structured compliance provisions to ensure the construction of a stable two-way trust bridge between on-chain incentives and off-chain compliance settlement. 10.The method of claim 9, wherein the method further comprises: receiving a request for a blockchain-based binary logic organization framework; and providing the blockchain-based binary logic organization framework to the requestor. The specific steps of real-time monitoring, evaluation and adaptive optimization in S3 are as follows: S31, real-time data collection and sandbox simulation: the digital twin module collects real-time on-chain transaction, governance participation, business incentive data, and off-chain operation and user interaction information; through sandbox environment, system state and incentive mechanism simulation detection are carried out to identify potential abnormalities and running bottlenecks, and provide comprehensive data support and scene verification for subsequent governance optimization; S32, DDI evaluation and adaptive optimization: combine dynamic decentralized index to evaluate autonomy, the system automatically generates governance and contract optimization suggestions, covering incentive distribution, contract permissions and voting mechanism; adjustment suggestions are fed back to on-chain and off-chain modules in an adaptive manner to form a real-time closed-loop optimization, continuously improving organizational resilience, efficiency and user participation experience.

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