A commodity full-link trust management method and system based on a deterministic rule field and a medium

Abstract

The application discloses a kind of commodity full-link credible management method, system and medium based on deterministic rule field.The method is executed in the deterministic program execution environment driven by steady-state rule kernel, comprising: configuring physical identification for commodity unit and establishing the digital identity of cryptography level binding;In key node, execute sweep-away-transmit asynchronous storage certificate, collect image containing space-time data, immediately release physical after local signature and asynchronously upload, form time sequence evidence chain and programmed tracking;Passively respond to external traceability request, after preposition quality evaluation, call multidimensional automatic check rule set in steady-state rule kernel to carry out logical falsification to time sequence evidence chain, according to which hierarchical programmed decision and constraint response are executed by system.The present application realizes the paradigm reconstruction of commodity credible management from artificial verification to deterministic rule automatic execution, and systematically solves the fundamental contradiction of scalability, cooperativity and governance certainty.

Description

Technical Field

[0001] This invention belongs to the field of digital trust infrastructure and end-to-end trusted management technology for goods, specifically relating to a method, system and computer-readable storage medium for end-to-end trusted management of goods based on deterministic rule fields. Background Technology

[0002] In the context of commodity circulation, building a highly deterministic and scalable comprehensive trustworthy management system has long been a fundamental technical challenge in this field. Existing mainstream technical architectures have diverged into two major evolutionary paths: one is the "technical countermeasure" path relying on physical anti-counterfeiting, and the other is the "process-based" path relying on digital code queries. These two paths are mutually restrictive and incompatible in terms of cost models and governance effectiveness, and share common underlying architectural flaws: they are generally constrained by centralized data silos and manual verification and adjudication. This invention defines this traditional architectural paradigm as a "manually dependent architecture." The inherent systemic contradictions of this paradigm have kept the effectiveness of commodity trustworthy governance at a long-term technical bottleneck, preventing a fundamental breakthrough at the architectural level.

[0003] One approach is the high-cost, weakly scalable "technology-based countermeasure." This type of solution relies on continuously raising the barrier to counterfeiting as its core protection logic, falling into a vicious cycle of technological iteration and rising costs. The high cost per product inherently conflicts with the cost-sensitive nature of the massive circulation of low-value goods, making large-scale adoption economically impossible. Furthermore, the accurate determination of physical anti-counterfeiting status largely depends on specialized testing equipment or subjective human experience, failing to translate into standardized, deterministic signals that can be autonomously and logically determined by a digital system. This fundamentally hinders the automation of the entire business chain.

[0004] Secondly, there is the low-constraint, low-efficiency "process-based" approach. While this type of solution can control implementation costs, it shifts the responsibility for authenticity verification to the end consumer, resulting in extremely low actual proactive verification coverage, rendering the anti-counterfeiting defenses ineffective. Conventional labels lack physical anti-transfer characteristics, failing to provide long-term, automated, and rigid constraints against illegal swapping, unpacking, and cross-selling during the logistics process. Essentially, it relegates trust management to a reactive, post-event consumer inquiry model, failing to establish a procedural and proactive governance capability covering the entire product lifecycle.

[0005] The two existing paths differ significantly in their external implementation, yet their underlying architectures both rely on manual judgment and intervention at key nodes. This unified paradigm has given rise to three sets of interdependent, fundamental flaws in the industrial ecosystem that cannot be eradicated at the engineering level. This application defines these flaws as "meta-problems": Scalability issues: Verification and traceability, anomaly identification, and violation handling all rely on independent manual operation or high single-point technical investment. The overall system cost increases rigidly and linearly with the scale of business, making it impossible to achieve a scale effect where marginal cost approaches zero. This hinders the full-domain implementation and popularization of the trustworthy system from the perspective of economic model.

[0006] The fundamental problem of collaboration: cross-entity data trust and business process collaboration rely on point-to-point customized development. The complexity of system integration increases superlinearly with the number of participating entities, forming a structural barrier that cannot be overcome for the large-scale expansion of the industrial ecosystem.

[0007] The fundamental problem of determinism is that the discovery of violations relies on random sampling, the verification of the authenticity of facts relies on human experience and deduction, and the handling of commercial disputes relies on case-by-case negotiation and game theory. The overall governance process is characterized by probabilistic, lagging, and high friction, making it impossible to build a rule-driven deterministic governance closed loop.

[0008] The three types of problems are interconnected and deeply coupled, and are not local defects at a single technical point, but rather a concentrated externalization of the inherent contradictions in the engineering economic model and system topology of the "human-dependent architecture". This leads to prominent industry pain points: even if process traceability is achieved by relying on basic data records, the identification of violations, logical falsification, and execution of rulings still heavily rely on human intervention, and it is always impossible to establish a fully automated and procedural governance link from "conclusive evidence" to "ruling implementation".

[0009] The existing technological system exposes a core architectural dilemma: a systemic disconnect exists between the evidence production layer and the adjudication enforcement layer. Even with highly credible and tamper-proof technical evidence, the existing system lacks an underlying operational mechanism for automated identification, low-cost acceptance, and procedural execution, leaving the industry generally trapped in a perennial predicament of "conclusive evidence, but uneconomical rights protection." This situation indicates that the shortcomings of existing technologies are not limited to single-point anti-counterfeiting and traceability processes or algorithms themselves, but also lack a top-level trust governance architecture that can transform objective and conclusive evidence into deterministic enforcement effectiveness.

[0010] Therefore, the industry urgently needs to build a new digital trust infrastructure that can automatically analyze highly deterministic evidence and transform it into low-cost, highly deterministic, and programmable responses. This would reconstruct the paradigm of trustworthy product management from an architectural perspective and systematically resolve the inherent technical contradiction that makes it impossible to balance scalability, cross-domain collaboration, and governance certainty. Summary of the Invention

[0011] I. Purpose of the Invention This invention aims to overcome the systemic defects of existing "manually dependent architectures," bridge the architectural gap between "conclusive evidence" and "implementation of rulings," and resolve the fundamental structural contradiction of the incompatibility between scalability, collaboration, and governance certainty in traditional trust systems. The defects in existing architectures directly hinder the large-scale engineering implementation of high-level trust management systems, leaving the commodity circulation industry perpetually trapped in an industrial predicament of "conclusive evidence, but uneconomical rights protection."

[0012] To this end, this invention provides a method, system, and computer-readable storage medium for end-to-end trusted management of goods based on a deterministic rule field. Its core lies in constructing a "deterministic rule field" defined by coded deterministic business rules, i.e., a "steady-state rule kernel." The design goal of this invention is to build a standardized deterministic rule field by defining and implementing standardized trusted interaction protocols and automated logical adjudication rules; and to reconstruct the traditional trust-building model, which relies on high-cost, highly uncertain manual operation and maintenance, subjective screening, and commercial game theory, into a standardized technology flow process that is autonomously driven by deterministic code rules, automatically executed, and with marginal costs approaching zero.

[0013] This invention systematically breaks through the inherent bottlenecks of traditional systems in terms of scalability, cross-entity collaboration, and governance certainty from the engineering architecture level, realizing a technological paradigm leap from "manually dependent architecture" to "deterministic rule field system", and providing a complete technical solution for end-to-end trusted management that can be implemented in engineering and scaled up in the ecosystem.

[0014] The aforementioned deterministic rule field possesses clear technical boundaries, positioned as the factual production layer and logical adjudication layer for commodity circulation business. Its core function is to implement high-confidence logical falsification and structured solidification of evidence for the entire chain of commodity business activities incorporated into the system, outputting legally evidentiary results for status confirmation and automated structured credit marking. The system outputs immutable objective technical evidence, providing an authoritative and neutral factual basis for upper-level commercial contract performance and cross-entity commercial dispute resolution. The system does not directly intervene in physical-level performance behavior, but only ensures the certainty and operational efficiency of subsequent commercial negotiations, contract performance, and legal remedies by outputting irrefutable objective facts.

[0015] II. Technical Solution This invention discloses a method, system, and computer-readable storage medium for trusted management of the entire product supply chain based on deterministic rule fields.

[0016] The deterministic rule field is essentially a passively triggered, programmable deterministic program execution environment. All state transitions, logical decisions, and factual confirmation actions within the field are passively triggered by authenticated external compliant business requests, and are uniformly driven and globally arbitrated by the underlying core primitives of the architecture (i.e., the steady-state rule kernel). The steady-state rule kernel encapsulates all core business logic and decision rules, maintains a globally unique digital identity fact state machine, and sets up an unavoidable standardized logical decision gate for each business request accessing the system. This accurately maps physical space commodity circulation operations to unique, unambiguous, and tamper-proof objective fact records and standardized decision results in the digital space, reconstructing the trust and collaboration foundation for commodity circulation across organizations and entities from the underlying technical level.

[0017] The core innovation of this invention lies in building an independent, closed-loop deterministic rule field. Following the architectural design principles of "rule pre-positioning, condition triggering, and automatic execution," it fundamentally resolves the systemic disconnect between "conclusive evidence" and "final ruling" in the background technology. Relying on embedded deterministic rules uniformly parsed and scheduled by a steady-state rule kernel, it upgrades core capabilities such as high-credibility anti-counterfeiting verification, end-to-end traceability, and rigid constraints on violations from the traditional manual case-by-case handling model to an automated, standardized business process that responds unambiguously to compliant inputs without human intervention.

[0018] The system of this invention ultimately achieves the following: when objective technical evidence matches the preset rule conditions, the corresponding business processing rules are triggered autonomously and unambiguously by the system and executed in a closed loop, realizing a certain, automated and seamless transmission from evidence solidification and logical falsification to the final decision.

[0019] To achieve the above objectives, the technical solution of the present invention is composed of two logical layers working together.

[0020] (a) Pre-adaptation layer: a deterministic signal filter for the physical world To ensure the input quality and determinism of the core processing closed loop, this system establishes a front-end adaptation layer at the input end. Its core function is to transform unstructured, multi-source heterogeneous original evidence (such as images) submitted from the outside into standardized technical events that can be processed by the steady-state rule kernel and have clear traceability through standardized technology verification based on physical identifiers.

[0021] The processing of this evidence image will be performed by the corresponding pluggable implementation components (i.e., physical identifiers and sensing components) called by the steady-state rule kernel. This includes locating, decoding, and analyzing the state of the physical identifiers to quickly determine whether they constitute a technically admissible traceability request. Its technical positioning is as a strict filter and machine-readable interface, aiming to intercept low-quality and invalid inputs at the source and achieve deterministic automated triage based on preset rules.

[0022] (II) Core Processing Layer: The Three Major Technical Pillars of Deterministic Rule Fields For admissible evidence screened through the pre-processing interface, the system enters the core processing layer, driven by a steady-state rule kernel, where three technical pillars work collaboratively. These three pillars are independent yet mutually supportive, jointly constructing the foundation for credible adjudication across the entire process. They are listed below: First, the identity anchoring pillar: This pillar is used to achieve unique identity and hierarchical trusted binding. It assigns physical identifiers to each level of product unit and creates unique digital identities with preset lifecycle states for them in a trusted evidence storage system. Then, based on cryptographic methods, it establishes deterministic binding relationships between digital identities at different levels. Through this deterministic binding relationship, a compliant operation on a high-level aggregate unit can automatically and unambiguously cover all bound sub-units below it.

[0023] Second, the behavioral constraint pillar: This pillar is used to implement procedural constraints for traceable behavior and asynchronous evidence storage. At key handover nodes in the supply chain, asynchronous evidence storage operations of scanning, sending, and transmitting are executed according to the steady-state rule kernel, and the evidence storage process is tracked procedurally according to preset rules. Once the system determines that the corresponding evidence data packet has not been successfully received and verified within a preset time limit, an evidence chain interruption marker with a unique hash identifier is automatically generated and recorded as a deterministic fact in the trusted evidence storage system. This marker will be periodically anchored with each batch of evidence storage, thereby achieving immutable finality.

[0024] Third, the enforcement pillar: This pillar ensures that violations are investigated and that procedural decisions are made. When an external tracing request, deemed acceptable by the pre-adaptation layer, is triggered, the relevant temporal evidence chain is automatically retrieved, and logical falsification is performed based on the multi-dimensional automated verification rule set within the steady-state rule kernel. This system is configured for a passive response principle; all adjudication actions are strictly triggered by certified external requests. Based on the verification conclusion, for violations that fail verification, a constraint loop encompassing the enforcement of the ruling and a procedural response is automatically triggered; for complex events where the responsible party raises objections, a pre-set procedural review channel is initiated.

[0025] (III) Architecture Implementation and Deployment: Steady-state rule kernel + pluggable implementation component paradigm The system adopts a decoupling paradigm of "centralized adjudication by a stable rule kernel and pluggable implementation component protocol adaptation". This paradigm, through the physical separation of interfaces and implementations, enables the independent deployment and evolution of technical components while ensuring the consistency of global business logic.

[0026] Steady-state rule core: Closed-loop deterministic adjudication core The steady-state rule kernel is a deterministic adjudication engine that encapsulates all core business rules, state logic, and verification criteria, serving as the unified technical consensus source for the ecosystem. Logically, it includes a unified business rule base, a global fact state machine, and a rule interpreter, forming a complete rule execution closed loop. The kernel's internal computation units (rule base, state machine) are not directly exposed externally, but only provide arbitration services through preset, standardized programmatic adjudication interfaces.

[0027] Pluggable Component Implementation: Standard Protocol Adapters and Actuators The pluggable implementation component is an independent software module that strictly adheres to the programmatic adjudication interface specification provided by the kernel, which governs the steady-state rules. Its technical essence is that of a kernel protocol adapter and function executor, responsible for receiving heterogeneous external requests and converting them into standard calls to the kernel interface, thereby obtaining the kernel's adjudication conclusion and formatting it for external output. The pluggable implementation component itself does not encapsulate or interpret any core business rules; its effective output must entirely originate from the formatted forwarding of the kernel's adjudication conclusion. In this system, different functional categories, such as the physical identification and sensing component and the scan-walk-transfer evidence storage engine, all serve as specific implementations of the pluggable implementation component, following the same adaptation pattern. This design allows each component to be independently selected and replaced according to scenario requirements.

[0028] Paradigm Synergy Effect The kernel, as an immutable rule interpretation layer, ensures the final consistency of the rulings; the pluggable implementation components, as standardized protocol adaptation layers, support the diversity and openness of technical implementations. Together, they collaborate through a programmatic adjudication interface, forming the engineering foundation for the reliable operation of deterministic rule fields.

[0029] This architecture supports various deployment models, including enterprise private deployment, Software as a Service (SaaS) deployment, and industry or regional consortium blockchain deployment. As long as different deployment instances strictly follow the same steady-state rule kernel, the generated time-series evidence chain will have underlying consistency, thereby achieving cross-instance, machine-automatically verifiable native data mutual recognition and trust transfer. Beneficial effects

[0030] (I) Overcoming the fundamental problem of collaboration: Achieving native cross-domain mutual recognition of data and trust Based on the single consensus source of the steady-state rule kernel, data credentials generated by different deployment instances have underlying consistency. Each credential itself is proof of conformity to the kernel rules and can be independently verified in other instances. This reconstructs the complexity of trust integration in ecosystem collaboration from the superlinear growth of O(N²) in traditional point-to-point customization to a linear expansion of O(N) based on the consensus source. This is not merely a technical improvement, but a fundamental reconstruction of the trust transmission network topology.

[0031] (II) Overcoming the fundamental problem of determinism: transforming governance from a probabilistic game to a deterministic technical process Driven by a steady-state rule kernel, programmatic tracking and multi-dimensional concurrent verification transform violation determination from probabilistic manual checks to deterministic falsification based on a full chain of evidence and real-time logical calculations. This systematically eliminates the potential for concealment of violations and achieves a paradigm shift from probabilistic responses to deterministic rulings.

[0032] (III) Overcoming the Scalability Issue: Unifying Judicial Effectiveness and Economies of Scale with a Hybrid Storage Architecture By adopting a decoupled architecture of on-chain cryptographic anchoring and off-chain economic storage, at the engineering and economic level, it simultaneously meets the verifiability requirements of judicial-grade evidence preservation and the cost-effectiveness requirements of massive business data storage, breaking the binary opposition between trustworthiness and scalability in traditional architectures, and laying a feasible economic foundation for the unlimited expansion of the system.

[0033] (iv) Constructing a trusted digital twin network through cryptographic hierarchical binding to achieve an asymmetric advantage in verification efficiency and anti-counterfeiting strength. By establishing cryptographic hierarchical bindings between digital identities of goods, a trusted digital twin network with embedded business logic is constructed. This structure achieves a dual asymmetric effect in engineering. In terms of defense, attacking any node will cause the global binding to fail, leading to a non-linear increase in the cost of systematic forgery. In terms of efficiency, a single compliant operation on the root node automatically covers all child nodes, enabling batch verification efficiency to jump from linear complexity O(N) to constant complexity O(1). This structure provides a scalable trusted data structure with both ultra-high security and ultra-high efficiency for the circulation of massive amounts of goods.

[0034] (v) Develop the adaptive evolutionary capability from handling violations to systemic immunity. The system executes hierarchical procedural adjudication based on deterministic falsification conclusions. For boundary cases, it initiates deep tracing through preset protocols and transforms the disposal conclusions into inputs that drive the iteration of the core rules of steady-state rules. This enables the system's defense capabilities to continuously evolve based on adversarial examples, achieving iterative enhancement of the system's immunity while maintaining the steady state of core business rules.

[0035] (vi) Laying the engineering foundation for an open and trust ecosystem with a kernel-component decoupled architecture The steady-state rule kernel, serving as the architectural primitive and the sole source of consensus, encapsulates all core rules, allowing pluggable components to implement specific technical functions through standard interfaces. This architectural decoupling, while ensuring the determinism of global rules, grants ultimate flexibility to technical implementation, resolving the fundamental contradiction between rule uniformity and flexible implementation, and providing foundational support for building an open ecosystem.

[0036] (vii) Establish a two-way checks and balances framework between business logic execution and ecosystem consensus governance. When dealing with extreme cases such as root-cause conflicts, the system links technical evidence, offline tracing conclusions, and external ecosystem governance decisions to form a procedural two-way closed loop of rule execution, event governance, consensus decision-making, and rule optimization. For the first time, it realizes the linkage and checks and balances between the business logic layer and the governance consensus layer within the technical system, providing a governance foundation for the distributed digital ecosystem that has both operational stability and rule evolution capabilities.

[0037] (viii) Establish a new paradigm of precision governance based on the “state credential chain” to drive the focus of governance forward. This invention's inherent programmatic tracking, multi-dimensional verification, and adjudication execution collectively generate a digital status credential chain that spans the entire product lifecycle and can be independently verified. This credential chain shifts the governance focus from reactive, reactive responses to discrete violations to a systematic, proactive approach of continuously producing and ensuring the integrity and compliance of the entire distribution process. This not only significantly improves the certainty and efficiency of violation tracing but also reconstructs the "credible status" of a product itself into a core digital asset that can be audited in real time and used for risk pricing and process optimization, thus defining a new paradigm of precise governance from "violation accountability" to "status verification." Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall architecture of the product end-to-end trusted management system, which defines a layered technical system based on the kernel-component decoupling paradigm.

[0039] Figure 2 It is a schematic diagram of the cryptographic binding and hierarchical hash aggregation between physical entities and digital identities, demonstrating the core mechanism for achieving unique identity and hierarchical trusted binding.

[0040] Figure 3 It is a flowchart of the asynchronous evidence storage operation of scanning-walking-transfer and programmatic status tracking, which reveals the collaborative path between logistics efficiency and data credibility in the behavioral constraint pillar.

[0041] Figure 4 It is a diagram illustrating the closed-loop workflow of procedural adjudication and constraints, which clarifies the hierarchical procedural adjudication framework of screening evidence, falsifying evidence, constraints, and case closure.

[0042] Figure 5 It is a schematic diagram of a five-layer collaborative trust and intrinsic security architecture, depicting an intrinsic security system that extends from physical data sources to consensus on ecological governance.

[0043] Figure 6 It is a diagram illustrating the synergistic relationship between the steady-state rule kernel, the full-link business scenario, and the trusted digital evidence chain, explaining the core autonomous cycle of "rules driving business, business accumulating evidence, and evidence feedback evolution". Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer, a detailed description is provided below in conjunction with the accompanying drawings and specific embodiments; the following embodiments are only used to illustrate the present invention and are not intended to limit the scope of protection.

[0045] I. System Implementation Overview The following series of interconnected embodiments provides a complete description of a product end-to-end trusted management system based on deterministic rule fields. Each embodiment follows a progressive logic from physical interaction to data foundation, from rule operation to governance closed loop, and then to architectural support and paradigm validation, collectively constructing a complete deterministic rule field technology system: (I) Construction of physical interface and trusted data foundation (Examples 1, 2, and 3): First, define the standardized interface and implementation example for interacting with the physical world (Example 1), then explain how to transform commodity circulation operations into a key mechanism with source trust and real-time locking of time-series evidence chain (Example 2), and ensure the intrinsic guarantee of data trustworthiness through programmatic tracking (Example 3).

[0046] (II) Evidence-Based Deterministic Governance Closed Loop (Examples 4, 5, and 6): Building upon the aforementioned data foundation, this demonstrates how the system responds to external tracing, performs automated, multi-dimensional logical verification and falsification of evidence across the entire chain (Example 4), and triggers tiered, procedural adjudication and constraint responses based on the determined conclusions (Example 5). In extreme scenarios where digital records conflict with physical authority verification, the system completes root cause tracing and rule evolution according to a preset protocol (Example 6).

[0047] (III) Engineering Architecture and Paradigm Value (Examples 7 and 8): Finally, the decoupled architecture and deployment form of the core engineering paradigm "steady-state rule kernel + pluggable implementation components" that supports all the above capabilities are explained (Example 7), and the necessity and paradigm breakthrough of this solution in solving meta-problems such as synergy, scalability, and determinism are demonstrated from the system level (Example 8).

[0048] The following will describe each embodiment in detail in this order.

[0049] II. Explanation of Core Terms To ensure a clear and consistent understanding of the present invention, the core terms that are used throughout the text and have specific technical meanings are defined as follows.

[0050] The deterministic rule field is a deterministic program execution environment that is uniquely driven by a steady-state rule kernel and instantiated through pluggable components. In this environment, any commodity circulation event is mapped as a temporal evidence chain and used as input to generate deterministic adjudication instructions that can be directly executed by programmatic processes through the pre-set multi-dimensional rules in the kernel. This establishes a fully automated and programmatic processing paradigm from event triggering to adjudication execution.

[0051] The steady-state rule kernel is a pre-encapsulated code-based rule execution core that provides final, deterministic rulings for the migration of digital identity states of goods and all business events. Its core characteristic lies in its steady-state attribute. The set of rules already in effect constitutes the system's trust baseline. Any changes to this baseline must be implemented through a pre-defined governance process with consensus constraints and cannot be unilaterally imposed. All compliant business events must and can only be adjudicated by this kernel to drive changes in the global fact state machine. This kernel is the sole source of rule interpretation and state consensus within the deterministic rule field, and its steady-state attribute is the ultimate technological foundation of system trust.

[0052] A trusted evidence storage system refers to a functional entity that realizes the complete functions of trusted data storage and management, and is responsible for verifying signature data, maintaining the status of digital identity, and storing and querying evidence chains.

[0053] Trusted evidence storage components specifically refer to pluggable software modules that implement the above functions in the kernel-component architecture. The trusted evidence storage system is the functional entity, and the trusted evidence storage components are the specific implementation forms of this entity under the architecture.

[0054] The scan-go-transmit asynchronous mode refers to a data collection and evidence storage process executed at pre-defined key handover nodes in the supply chain. Its core lies in decoupling evidence preservation from network transmission in time. This mode typically includes three core operations: scanning involves collecting data locally at the terminal and completing a digital signature; going involves immediately releasing the physical goods based on successful signature; and transmitting involves asynchronously uploading the signed data packet in the background. Through these operations, this mode achieves a synergy between the immediacy of logistics flow and the verifiability of data evidence storage at the engineering level.

[0055] The digital identity lifecycle state machine is a deterministic engine encapsulated in the steady-state rule kernel, which predefines all legal states of a product's digital identity (such as inactive, in transit, in stock, etc.) and their migration rules. The system uses this state machine to arbitrate any state change request for compliance, rejecting all operations that violate the preset migration path, thus forming the core cornerstone of automated state migration and business compliance.

[0056] Example 1: Optimal Structure of Physical Identifier and its Cooperative Relationship with the System This embodiment combines Figure 1 , Figure 5As shown, this paper defines a standardized physical sensing interface specification required for a "deterministic rule field" and describes a preferred implementation method for physical identifiers that conforms to this specification. Its core lies in transforming the verification of physical integrity into deterministic, machine-readable physical state evidence that can be provided to the backend steady-state rule kernel. This specification does not limit specific materials and processes, but rather stipulates the physical behavior and signal output requirements needed for the access system.

[0057] Its core design lies in leveraging pre-defined cohesion-breaking characteristics and the resulting morphological evidence that can be visually determined. This transforms the verification of physical integrity into highly deterministic evidence of physical state changes that can be captured by machine vision systems and directly serve automated backend adjudication. The technical essence of this interface is to encode complex physical world states into deterministic machine inputs consisting of two standardized Boolean signals: "identity readability" and "feature manifestation state." These two signals are generated strictly according to pre-defined physical rules, providing deterministic computational input for subsequent automated verification and programmed adjudication. This design aligns with the system's core operating principle of passive triggering and on-demand verification.

[0058] 1. Design Overview To meet the system's collaborative requirements, the physical sensing interface addresses three key needs: efficient workflow, without increasing the execution latency of the scan-walk-transfer protocol; low false alarm rate, achieved through fault-tolerant coding design and deterministic judgment based on physical evidence; and high evidentiary validity, relying on its anti-transfer characteristics and deterministic destruction mechanism to provide the system with directly credible physical fact input. These three needs collectively define the technical baseline for physical identifiers as the physical sensing interface for deterministic rule fields.

[0059] 2. Example of physical implementation of the interface A physical identifier that can be adapted to the system can be constructed with a functionally layered composite structure, the core of which lies in having a cohesive destruction mechanism and a separate design for evidence output.

[0060] 2.1 Positioning Auxiliary Layer This layer, located at the outermost layer of the identification, is used for rapid processing in machine vision. It can be configured with high-contrast geometric markers (such as diagonal double L-shapes) as positioning references. Additionally, a backup identification code (such as Code 128) can preferably be provided to offer redundant identification channels in case the primary code fails, aiming to improve system robustness. This backup channel does not participate in the core physical state decision-making logic.

[0061] 2.2 Fragile visible layer This layer is the main body for achieving the anti-transfer function and outputting key evidence. It is composed of composite materials with cohesive destructive properties and specifically includes two functional parts.

[0062] The first is the data carrier, which carries the identity code carrier (such as a QR code) that is bound to the digital identity of the product, and is used to link the digital identity and the evidence chain in the background.

[0063] The second part is the decisive evidence section, which includes a pre-defined physical feature region. This region is configured such that, upon unlawful peeling and cohesive failure, cracks propagate along a pre-defined path, causing irreversible morphological changes in the region. Normally, these changes are visually concealed, but after damage, they manifest as a high-contrast, regular pattern. This "pre-defined path" is the common basis for both damage guidance and morphological manifestation. This change can be detected by machine vision, and this manifest change corresponds to the "change in the state of the pre-defined microscopic feature region" claimed in claim 10.

[0064] 2.3 Stress Control Layer This is an adhesive layer, located at the innermost layer. Its peel strength is greater than the cohesive strength of the fragile visible layer. This mechanical gradient causes the stress from unauthorized removal to preferentially trigger cohesive failure of the fragile layer, thus preserving crucial evidence while avoiding accidental triggering under normal material flow vibrations.

[0065] 2.4 Functional Coordination Logic The aforementioned structures work together to form a progressive verification chain of "location → association → verification". When an illegal operation occurs, the readability anomaly in the data carrier section and the explicit change in the decisive evidence section serve as coupled representations of the same cohesive breach event, constituting a physically coupled and logically interlocked evidence combination. The two signals in this combination originate from different regions of the same physical event, are spatially separated by mechanically isolated areas, and logically corroborate each other, jointly constituting a high-confidence, deterministic fact input, providing physical fact input for the system's subsequent multi-dimensional automated verification process.

[0066] 3. Synergistic mechanical properties To achieve reliable triggering, the 90° cohesive strength of the fragile exposed layer can be selected within the range of 0.6 N / cm to 2.0 N / cm (inclusive of the endpoints). The 90° peel strength of the stress control layer is greater than that of the former, with the difference ranging from 0.5 N / cm to 1.3 N / cm (inclusive of the endpoints). This gradient relationship is the mechanical basis for illegal peeling to preferentially trigger cohesive failure of the fragile layer and preserve evidence of the predetermined morphology. The given peel strength parameter range represents a balance between the triple engineering constraints of resisting normal material stress, preventing accidental triggering by environmental vibration, and ensuring that malicious peeling will inevitably trigger the event.

[0067] 4. Examples of collaboration with system processes When the system receives a tracing request with an accompanying image of physical identification, the physical identification and sensing component integrated into the system's processing pipeline will be automatically invoked within the standardized interface framework defined by the steady-state rule kernel. This component is configured to perform fully automated processing on the identification image, including rapid localization, encoding / decoding, and physical state analysis, to extract two preset standardized Boolean signals: identity readability and feature visibility state, thereby completing the deterministic conversion from physical evidence to machine-readable signals.

[0068] The system, based on the signal mapping rules preset by the steady-state rule kernel, adjudicates the four complete combination states formed by the two Boolean signals and directly guides them to differentiated processing paths. The specific mapping rules are as follows: When the identity is readable and the characteristics are revealed, the mapping is determined as "the identifier has suffered cohesion destruction, and the evidence of violation is complete and valid"; When the identity is unreadable and the characteristics have been revealed, the mapping is determined as "the identifier has suffered cohesion failure and the data carrier has been damaged simultaneously"; When the identity is readable but the characteristics are not apparent, the mapping is determined as "the physical state of the identifier is complete and there is no illegal or destructive behavior"; When the identity is unreadable and the features are not apparent, the mapping is determined as "the identifier status is abnormal and cannot pass the regular verification, and will be automatically transferred to the preset exception handling process".

[0069] In the aforementioned combined states, the "feature revealed" state is direct core evidence based on the inherent structural characteristics of the physical identifier, determining the existence of illegal stripping or other violations. The combination of readable identity and revealed features, however, is a highly specific evidentiary state achieved through a unique cohesive destruction mechanism and targeted mechanical layering design, distinct from all conventional physical identifiers, specific to this embodiment's physical structure. When a conventional physical identifier suffers equivalent illegal damage, its data carrier will fail and be destroyed simultaneously with the overall damage, rendering the identity code readable. In this embodiment, the physical structure, through a cohesive destruction mechanism and mechanical gradient layering design, fully preserves the identity code carrier while triggering irreversible destruction, simultaneously confirming the two key facts of "the illegal destruction has objectively occurred" and "the product identity can be accurately traced" at the physical level. This provides the system with strong, unforgeable, uniquely targeted, and directly credible physical evidence for subsequent automated adjudication.

[0070] The collaborative operation of physical identifiers and the system essentially constructs a deterministic trust conversion chain that is unambiguous and free from subjective bias, from physical intervention to system-wide procedural adjudication. This chain is driven by a closed loop of dual pre-set technical rules: the first layer is the physical layer technical rules, where physical identifiers, relying on their unique material properties and mechanical gradient structure design, encode external illegal interventions and other physical behaviors into regular morphological evidence that is irreversible, unforgeable, and free from random bias, eliminating the randomness and ambiguity in physical world state determination; the second layer is the system layer technical rules, where the steady-state rule kernel, through physical identifiers, sensing components, and standardized logic algorithms, decodes the aforementioned physical morphological evidence into a unified Boolean signal, and completes automated verification and deterministic adjudication according to pre-set mapping rules, achieving a seamless and precise connection between physical evidence and system computational input.

[0071] The entire collaborative architecture employs a two-layer technical transformation logic: "physical layer structural rules constraining morphological changes and system layer algorithm rules extracting state signals." This completely breaks down the trust transmission barriers between physical entities and digital systems, providing a deterministic factual basis—free from human intervention and subjective bias, and based on objective physical facts—for the fully automated processing of steady-state rule kernels. This solution, based on physical structure and system collaboration, is a specific technical solution, not simply an abstract algorithm or rule for intellectual activities.

[0072] 5. Technical Effects and Positioning Based on the aforementioned design, the physical identifier implemented in this embodiment achieves the following core technical effects: Firstly, in terms of process efficiency, the independent physical verification process, which previously required specialized equipment or manual intervention, has been restructured into a process that is naturally synchronized with the scanning of product identity codes. This achieves near-zero marginal cost and full-process automation of anti-counterfeiting verification, fundamentally breaking the dilemma of traditional physical anti-counterfeiting being difficult to scale due to excessively high costs.

[0073] Secondly, regarding evidentiary value, its output, a standardized Boolean signal based on physical structure, provides the backend steady-state rule kernel with highly deterministic machine fact input that can directly drive automated logical adjudication. The combination of these two signals unambiguously defines the complete state of the physical identifier, providing a deterministic factual basis for upper-level procedural governance without human intervention.

[0074] Based on the aforementioned technical effects, this embodiment essentially establishes the standardized physical sensing interface specification defined by the "deterministic rule field". The core of this specification is that any physical identifier, as long as it can deterministically and unambiguously encode its integrity state into a standardized machine-readable Boolean signal through a preset physical mechanism, meets the access conditions and can be used as the physical origin for system trust transmission.

[0075] Example 2: Implementation of Trusted Data Generation, Real-time Locking, and Hybrid Storage This embodiment specifically illustrates the implementation of the data acquisition, signing, verification, storage, and source locking mechanism in step S2 of claim 1, and provides corresponding specific implementation methods for all the technical features recorded in claims 6, 7, 8, 10, and 12.

[0076] Combination Figure 3 and Figure 5 As shown, this embodiment focuses on the core mechanism for constructing a credible foundation for deterministic rule field data. This mechanism ensures that the temporal evidence chain possesses authenticity, integrity, temporality, verifiability, and cryptographic finality from the source through deterministic fact generation on the terminal side, instant cryptographic finality locking on the source side, and cloud-based protocol-based verification and layered processing.

[0077] 2.1 Terminal Side: Trusted Data Generation, Source Commitment, and Real-Time Locking The data acquisition and signing functions are implemented by a client module deployed on a mobile terminal (such as a barcode scanner or mobile phone). Under the security protection of a local trusted execution environment (TEE) or secure element (SE), this module completes data acquisition and digital signing, generating an unforgeable "source commitment".

[0078] 2.1.1 Data Acquisition and Signature The implementation process follows an asynchronous scan-walk-pass pattern. For example... Figure 3 As shown, after the terminal triggers the identifier scan, the client calls upon sensors such as cameras and Global Navigation Satellite System (GNSS) to simultaneously collect raw data packets containing physical identifier images, millisecond-level timestamps, and high-precision geographic coordinates. The timestamps and geographic coordinates, as key spatiotemporal metadata, are generated synchronously with the on-site images and strongly bound together, forming the logical foundation for high-precision spatiotemporal traceability.

[0079] Subsequently, within the security boundary of the TEE or SE, the client encapsulates the aforementioned original data containing spatiotemporal stamps and the operator's identity information, and digitally signs the complete evidence storage data packet using a private key stored in a secure environment (corresponding to claim 6). This signing operation is atomically bound to the data acquisition, ensuring that the data and its spatiotemporal context form an inseparable cryptographic binding from the moment of its generation, possessing verifiable source and data integrity.

[0080] 2.1.2 Immediate Locking and Pre-Anchoring of Source Commitments To establish the cryptographic final state of digital identity the instant the physical operation is completed, and to eliminate the theoretical risk window between "data generation" and "on-chain final anchoring", the system atomically triggers the following finality locking protocol after local signing is completed.

[0081] First, a pre-anchoring request is generated. The terminal sends the signed evidence storage data packet and its cryptographic hash as a "pre-anchoring request" to the trusted evidence storage system.

[0082] Next, a pre-anchored credential is issued. After the trusted evidence storage system verifies the validity of the terminal signature, it digitally signs the hash using the system-level private key with a millisecond-level response speed, generating a structured "pre-anchored credential." This credential is an irrevocable credential signed with the system private key. Its core cryptographic semantics are: the system has verified and irrevocably promised to include the source evidence corresponding to the hash in the Nth future global state notarization batch, and ultimately anchor it to the distributed ledger.

[0083] Finally, after finalization and process release, and once the system signature on the terminal verification certificate is valid, a "release" command is immediately generated. At this point, the initial state of the product's digital identity is definitively locked with the source system's private key endorsement and possesses instant cryptographic finality. All subsequent physical transfers and digital evidence storage are based on this locked initial state.

[0084] Once the signing and locking are complete, the terminal immediately generates a "release" command. This command atomically binds the acquisition of cryptographic finality with the granting of logistics release rights, transforming high security requirements into a spontaneous efficiency incentive for the operator. The signed evidence data packet and pre-anchored credentials are temporarily stored in the terminal's local secure cache and are asynchronously uploaded by a background service thread, completing the closed loop of the scan-go-transmit asynchronous mode.

[0085] 2.2 Layered Processing and Protocol-Based Verification of Trusted Evidence Storage Systems The trusted evidence storage system processes the signed data packets and pre-anchored credentials submitted asynchronously by the terminal in a layered and asynchronous manner. The overall architecture adheres to the core principle of separating "real-time protocol verification" from "on-demand in-depth analysis".

[0086] 2.2.1 Real-time Protocol Access and Credential Verification Layer This layer performs a series of atomic and decisive compliance decisions on each received data packet, constituting the technical entry threshold for data storage in the system. Specifically, this includes: cryptographic credential verification, confirming the authenticity of the terminal's digital signature and the signature of the pre-anchored credential system; replay protection and freshness verification, verifying the freshness of the data packet's timestamp and rejecting requests from future times or exceeding a reasonable time window; business state transition compliance verification, confirming whether the state transition triggered by this operation conforms to the global commodity digital identity state machine rules defined by the steady-state rule kernel; and credential consistency verification, confirming that the data packet hash is completely consistent with the hash promised by the pre-anchored credential.

[0087] Only after the data packet passes the above four compliance checks can the system recognize it as valid protocol evidence and accept it. The system then performs two atomic operations: updating the digital identity status of the product to the target status, and storing the cryptographic digest of this evidence (including the pre-anchored credential) into the database, forming an incremental record of the evidence chain. This pre-anchored credential is the core trust atom for subsequently building a cryptographic layer binding.

[0088] 2.3 Hybrid Storage and Definitive Notarization of the Chain of Evidence To balance data trustworthiness, auditability, and storage economy, the system adopts a hybrid storage architecture (corresponding to claim 12), which is specifically divided into two layers.

[0089] The first layer is the off-chain raw data storage layer, where complete evidence data packages (including digital signatures, on-site images, spatiotemporal metadata, etc.) and pre-anchored credentials are stored in a highly available cloud object storage service, enabling complete retention and rapid retrieval of raw data.

[0090] The second layer is the on-chain deterministic notarization layer. The system processes pre-anchored commitments in fixed-time batches, aggregating a batch of verified "pre-anchored credential" records to generate a Merkel root hash, and submitting this root hash to a distributed ledger (such as a blockchain) with a consensus mechanism for notarization. This operation provides public and time-sequential batch notarization of previously effective, cryptographically final pre-anchored commitments, giving the system excellent audit resistance and cross-institutional mutual recognition capabilities.

[0091] 2.4 Technical Effects This embodiment systematically constructs a data trust foundation for a deterministic rule field through a collaborative architecture of terminal trusted generation, real-time source locking, cloud-based layered verification, and hybrid storage. The core technical effects are as follows.

[0092] By establishing a source-end state, the timing of trust establishment is reshaped. Through a pre-anchored credential mechanism, an irrevocable cryptographic final state is assigned to the digital identity of a product the instant the physical operation is completed, completely eliminating the theoretical risk window before data is asynchronously uploaded to the blockchain. This marks a revolutionary shift in the trust establishment node from the cloud server receiving stage to the instant the physical event occurs, achieving the highest level of security: "trustworthy from the source" and "authorization confirmed upon operation."

[0093] Anchoring atomic foundations enables lossless aggregation of trust. Pre-anchored credentials provide a globally unique and verifiable trust anchor for each product, allowing subsequent hierarchical aggregation operations such as packing and palletizing to build efficient and verifiable cryptographic binding relationships on this basis, achieving lossless transfer and exponential aggregation of trust from atomic units to arbitrary aggregation units.

[0094] Unifying security and efficiency, and reconstructing the incentive and collaboration mechanism. The final locking process is completed in milliseconds within the scan-go-transfer protocol, with no additional awareness from the operator. The system binds the right to release logistics with the atomicity of cryptographic final locking, transforming high security requirements into self-driven behavior of participants at the engineering level, achieving a fundamental incentive reconstruction for security and operational efficiency.

[0095] Balancing effectiveness and scale, an economical evidence preservation model is created. The hybrid storage architecture integrates instant cryptographic commitments with final on-chain batch notarization, generating a time-series evidence chain that meets the most stringent judicial requirements for electronic evidence in terms of integrity, immutability, and timeliness, while supporting the storage and processing of massive amounts of data in an economically feasible manner.

[0096] Therefore, this embodiment constructs a complete trust generation and solidification protocol, realizing lossless mapping from physical events to deterministic and credible evidence in the digital world, laying an independently verifiable "original fact" foundation for the entire deterministic rule field.

[0097] Example 3: Programmatic Tracking and Evidence Chain Status Marking Mechanism This embodiment combines Figure 1 , Figure 3 and Figure 5 The illustration specifically describes the implementation methods for the features described in claims 8 and 9. Its core lies in constructing an automated mechanism driven by deterministic timing rules. This mechanism programmatically tracks asynchronous evidence storage failures and generates evidence chain interruption markers with unique hash identifiers.

[0098] 3.1 Mechanism Overview, Time Rule Design and Configurability This mechanism constitutes an inherent and deterministic reliability guarantee and procedural audit layer in the scan-walk-transfer asynchronous evidence storage operation. Its design concept is to transform the timeliness requirement that traditionally relies on subjective judgment into an automated state machine triggered by preset and precise time nodes, thereby transforming process compliance into calculable and verifiable objective facts.

[0099] This mechanism is entirely driven by preset rules in the steady-state rule kernel, and its operation is based on the deterministic definition of the following three core time elements.

[0100] The compliance verification deadline (T1) is a definite time that arrives after a preset time offset (e.g., 3 hours or 6 hours) since the evidence storage data packet is generated locally on the terminal. This time is the core node for the system to determine the final compliance of this evidence storage. If a valid data packet is received and verified before T1, the evidence storage process is considered compliant and terminated. If no valid data packet is received by this time, the system will immediately and automatically start the subsequent programmatic tracking process. This is also the only technical boundary that distinguishes conventional asynchronous evidence storage processing from abnormal tracking and handling.

[0101] The programmatic tracing and handling period (duration defined as parameter T) is the first stage of the programmatic tracing process, which starts immediately after time T1 and lasts for a preset duration (e.g., T=9 hours). This stage provides a forgiving tracing window for data packet uploads after the compliance verification period has expired. During this period, a valid upload can still complete the evidence preservation process, and the upload time attribute will be fully recorded and retained for subsequent audit traceability. The end time of this stage is the sole basis for the system to trigger the pending evidence preservation status determination.

[0102] The final observation waiting period (T2) is the final tolerance determination phase that the system automatically enters when the procedural tracking and handling period expires and no valid data packet has been received (e.g., T2 = 24 hours). This phase provides a last chance for evidence preservation operations, and the end of the phase is the only trigger condition for the system to make a final status decision and complete evidence anchoring.

[0103] Configurability and Execution Rigidity: The aforementioned time parameters (T1 offset, processing period T, waiting period T2) are managed by the steady-state rule kernel and can be adjusted through pluggable configuration components to adapt to different operational scenarios. The time parameters applicable to any specific business flow must be configured and locked before the process starts. Once the parameters take effect, the resulting sequence of time rules is transformed into immutable and unavoidable deterministic execution logic. The system will strictly drive state transitions according to this logic, eliminating any possibility of manual intervention during runtime. The aforementioned design of "configurable before deployment and mandatory during operation" constitutes the absolute rigidity of process constraints.

[0104] 3.2 Deterministic State Transition and Evidence Generation Process like Figure 3 As shown, the entire mechanism constitutes a state machine driven entirely by time rules, specifically divided into two execution paths.

[0105] Path 1 is the compliant completion path: If the evidence data packet is successfully received and verified by the cloud system before time T1, the system determines it to be compliant, and the process ends normally.

[0106] Path two is to trigger and execute the programmatic tracing path: if no valid data packet is received by time T1, this mechanism is immediately triggered and the preset programmatic tracing process is entered. This path further includes the following steps.

[0107] First, the system enters the tracking and processing period, where it begins to focus on tracking the evidence storage task. This processing period is... Figure 3 The process is initiated within a preset time limit T. If the data packet is successfully uploaded within this period, the process can be completed normally, and this completion status will be associated with and recorded with the time attribute of "completed within the programmatic tracking and handling period".

[0108] This triggers the "Pending Evidence" state. If the data packet is not successfully uploaded by the expiration of the programmatic tracking period, the system immediately marks the corresponding commodity circulation status as "Pending Evidence" using atomic operations and simultaneously starts the timing of the final observation waiting period T2. The setting of the "Pending Evidence" state marks the transition of the system from the tolerant delay stage to the deterministic programmatic state of the final adjudication preparation stage.

[0109] Finally, a final judgment and evidence consolidation are performed. If the data packet is successfully uploaded during T2, the system removes the "Pending Evidence" mark, and the process ends with a successful remediation. If the upload is not successful by the end of T2, the system performs the following atomic operations in sequence: performs a final status judgment, changing the status from "Pending Evidence" to "Evidence Abnormal"; completes evidence consolidation, automatically generating an "Evidence Chain Interruption Mark" with a unique hash identifier, which is stored in the trusted evidence storage system as a definitive fact record. This mark will be periodically anchored with each batch of evidence storage, thus forming an immutable final record.

[0110] 3.3 The technical role of record generation The "chain of evidence interruption marker" ultimately formed by the procedural tracking mechanism is a key structured fact encapsulation carrier in the deterministic rule field, and its technical role is mainly reflected in two aspects.

[0111] On the one hand, this marker can serve as a deterministic input condition for continuity verification. When the adjudication process of Embodiment 5 is triggered by an external request, the steady-state rule kernel will call the multi-dimensional automated verification rule set of Embodiment 4. In the evidence chain continuity verification dimension, the presence or absence of this marker will serve as a preset Boolean condition, directly used to determine whether there is an interruption in the evidence chain due to the eventual loss of data packets, providing a highly deterministic machine criterion for logical falsification.

[0112] On the other hand, this marker can serve as a structured basis for procedural judgment and traceability. Its structured encapsulation of the complete time context from T1 to T2 constitutes a deterministic technical testimony that "the data acquisition result is ultimately invalid." Thus, "ensuring successful data upload" is transformed from a general operational expectation into a technical constraint with clear procedural consequences. Essentially, this mechanism deterministically transforms potentially hidden technical upload failures into permanent, auditable interruption status credentials, fundamentally driving participants to optimize their operations to avoid such deterministic adverse records.

[0113] 3.4 Technical Effects The procedural tracking and status marking mechanism constructed in this embodiment achieves the following technical effects through the coding of time rules, the automation of state transitions, and the permanent setting of failure evidence.

[0114] First, it achieves a leap in governance precision. The vague management concept of "timeliness" is broken down into a series of time-point events that can be precisely measured and programmatically judged, such as compliance determination at time T1, tracking during the disposal period, and final adjudication at time T2, thereby fundamentally improving governance precision.

[0115] Second, it transforms hidden operational risks into auditable technical evidence. By mandating upgrades to track and solidify records on the blockchain, the difficult-to-quantify operational risk of "silent data loss" is transformed into a system-mandated and permanently retained evidence chain interruption marker, making data integrity a quantifiable and traceable core management indicator.

[0116] Third, a rigid compliance baseline is established using coded time rules. This mechanism ensures that any data upload failure exceeding the time limit will inevitably trigger and generate a standardized, auditable, and verifiable record of the anomaly. This certainty of "leaving a trace of any violation" eliminates the possibility of violations being concealed, ensuring that any violation will be objectively recorded and traceable by the system.

[0117] Fourth, it drives participants to adhere to operational timelines from the outset, thereby avoiding violations that can be definitively recorded by the system. This mechanism transforms the temporal compliance of evidence storage operations from a management expectation into a technical fact that can be independently verified and possesses millisecond-level timestamp certainty. This fact constitutes key proof of the process integrity during the transfer of digital identities for goods and is the underlying core factual foundation upon which the upper layer builds real-time, auditable "digital status credentials."

[0118] Example 4: A Programmatic Validation Method Based on Multi-Dimensional Automated Verification Rules This embodiment combines Figure 1 , Figure 4 , Figure 5 and Figure 6 The diagram illustrates the implementation methods of step S3 of claim 1, and the features described in claim 9 and claim 10. Figure 4 As shown, multi-dimensional automated verification is the core verification step in the intelligent adjudication process, taking a chronological chain of evidence as input. The deterministic logic of this verification stems from... Figure 6 The set of predefined verification rules in the steady-state rule kernel. For example... Figure 5 As shown, this verification is performed at the business rules and state security layer, and its output verification result directly drives... Figure 4 Subsequent tiered procedural adjudication. The entire process is handled by... Figure 1 The core processing layer architecture is defined and executed in a unified manner.

[0119] 4.1 Multi-dimensional rule set for automated verification When the traceability process is triggered, the system automatically retrieves the complete temporal evidence chain, which is then driven by the rule interpreter in the steady-state rule kernel to perform preset, deterministic, multi-dimensional concurrent verification. The rule interpreter first obtains the current authoritative state of the traceable product's digital identity from the fact state machine as the initial factual benchmark for verification. Subsequently, based on the preset deterministic rule set, the system performs automated verification in parallel across the following four dimensions.

[0120] First, physical identifier state consistency verification. This verification automatically analyzes the sequence images of the same physical identifier in the temporal evidence chain to verify whether irreversible physical state degradation based on a preset technical standard, as defined in claim 4, has occurred. The core of the verification is to analyze the state changes of the preset micro-feature region described in claim 10, and to perform temporal and logical correlation analysis between the detected state change events and the compliant operations recorded by the system (such as "unsealing" and "unpacking"). If state degradation is detected and there is no corresponding compliant operation record, it is determined to be a logical contradiction and an alarm is triggered; if the state degradation and the compliant operation record are consistent in temporal and logical terms, it is determined to be a compliant state change.

[0121] Second, the spatiotemporal logic rationality verification. This verification checks whether the time interval and geographical displacement between any two adjacent evidence storage operation records are within a reasonable threshold preset based on the target commodity logistics format. Any spatiotemporal jump that violates the preset physical law threshold and constitutes a logical contradiction (e.g., records showing that the commodity completed a physically impossible long-distance displacement in a very short time) will trigger an alarm. The threshold can be statically pre-configured in the system according to different commodity types and logistics methods, or it can be dynamically optimized and adjusted based on statistical analysis of historical compliant evidence storage data. This mechanism ensures the determinism of the verification rules while also giving it configurability to adapt to diverse business scenarios.

[0122] Third, compliance verification of operation source and hierarchical binding. This dimension performs two key verifications in parallel. The first is operation source compliance verification, which verifies whether the geographical coordinates of key operations such as initial activation (i.e., digital identity creation) are within a pre-defined compliant geographic fence (e.g., a production plant area). The second is hierarchical binding state consistency verification, which verifies whether a trusted hierarchical binding relationship has been established through cryptography (e.g., ...). Figure 2 For the product unit (as described in Example 1), verify whether the operation records for the parent unit and child unit violate the preset business state transition logic. For example, before the digital identity of the whole box (parent unit) is recorded as "unpacked", the digital identity status of any individual item (child unit) in the box should not be updated to "in transit" or "sold".

[0123] Fourth, the continuity verification of the evidence chain. This verification is used to check whether there is an "evidence chain interruption marker" in the chronological evidence chain that was ultimately produced by the procedural tracking mechanism of Example 3. As a standardized encapsulation of deterministic facts, the existence of this marker itself constitutes a machine-readable proof that "the evidence chain is interrupted due to the eventual loss of the evidence data package", providing binary factual input for continuity judgment.

[0124] The above four dimensions together constitute a rigorous logical constraint network.

[0125] 4.2 Generation and Output of Verification Conclusions After the above four dimensions of verification are executed in parallel, the system aggregates the verification results from each dimension. The conclusion of this multi-dimensional verification serves as the deterministic starting point for all subsequent adjudication actions and directly determines... Figure 4 The branches of the process shown.

[0126] If all dimensions pass the verification, the system generates a deterministic technical conclusion that the "chain of evidence is logically consistent." This conclusion is the direct technical basis for triggering the process described in Implementation Example 5 and generating the "declaration of the completeness of the adjudication logic."

[0127] If any dimension fails the verification, the system automatically generates a structured "Violation Conclusion and Evidence Summary," clearly indicating the specific verification dimension that failed, the triggering rule, and the associated key evidence points. This summary will serve as deterministic input, driving the subsequent hierarchical adjudication and procedural constraint process described in Example 5.

[0128] 4.3 Technical Effects The multi-dimensional automated verification method implemented in this embodiment establishes its technical value as the core logic of the "business rules and state security layer" on three levels.

[0129] First, it automates and objectifies the violation verification process. It transforms violation determination from relying on human experience to parallel rule verification driven by a steady-state rule kernel and based on deterministic code execution, thus eliminating the subjectivity and contingency of the conclusions from a mechanism perspective.

[0130] Secondly, a rigorous logical falsification network is constructed. Through concurrent cross-verification across four dimensions—physical identifier state, spatiotemporal logic, operational source and hierarchical binding, and evidence chain continuity—a robust logical falsification network is formed. This concurrent design ensures that each verification dimension is logically equal and independent, fundamentally eliminating the possibility of attackers creating a "partial compliance illusion" by satisfying rules in a single or partial dimension, thereby systematically bypassing verification. Any operation attempting to circumvent the system will expose logical contradictions that can be deterministically captured by the algorithm due to violations of at least one preset rule in any dimension. This systematically blocks the path of creating a compliance illusion by satisfying partial rules at the logical level.

[0131] Third, it provides deterministic facts to drive subsequent adjudication. The "verification passed" or "violation summary" conclusion output by this method is a direct result of automated logical operations, providing deterministic factual input for the hierarchical adjudication process in Example 5. This is precisely the concentrated embodiment of the core capability of deterministic rule fields.

[0132] Example 5: Implementation of Hierarchical Procedural Adjudication This embodiment combines Figure 4 and Figure 5 The diagram illustrates specific methods for implementing the features described in step S3 of claim 1, claim 9, and claim 11. For example... Figure 4 As shown, the system constructs a four-stage adjudication architecture of "screening evidence, falsifying evidence, binding rules, and closing the case," following the principle of passive response. All adjudication actions are triggered by external requests and processed through predetermined deterministic rules in the steady-state rule kernel, ultimately outputting a structured adjudication result with clear legal and technical implications. This drives actual performance or accountability, forming an autonomous, evidence-driven closed loop of technical governance.

[0133] 5.1 Overview of the Triggering and Stages of the Adjudication Process The system's adjudication process strictly follows the passive triggering principle defined in claim 1, meaning that all adjudication actions are in response to traceability requests submitted by certified external entities that conform to the protocol specifications. The triggering sources for such requests mainly fall into two categories: The first is the incident reporting request, which is a request for evidence submitted by consumers, brand owners, or regulatory agencies when they discover an anomaly. The second is a procedural audit request, which is a request initiated by authorized entities such as regulatory agencies to verify the status of specific goods and invoke the system's adjudication process.

[0134] Both types of requests are equivalent in terms of compliance in triggering a ruling, and their actions and conclusions are subject to the same rules.

[0135] The system kernel itself does not initiate any proactive audits, probes, or investigations. This design ensures the objectivity and neutrality of its core: every ruling necessarily corresponds to a clear external input, thereby eliminating the possibility of the system itself becoming a source of dispute in the architecture, and keeping it in the position of a "technical arbitrator" that provides definitive judgments based on rules.

[0136] Once triggered, the process proceeds according to the deterministic logic preset in the steady-state rule kernel, sequentially entering four standard stages: screening (section 5.2), falsification (section 5.3), constraint (section 5.4), and case closure (section 5.5).

[0137] 5.2 Phase 1: Automated Quality Assessment and Triage of Input Evidence This stage corresponds to the "Input Quality Control Interface," which aims to quickly filter out low-quality and counterfeit inputs based on the deterministic anti-counterfeiting signals provided by physical identifiers, and to standardize valid evidence.

[0138] 5.2.1 Evaluation Mechanism and Event Encapsulation This stage is performed by the physical identification and perception component in the pluggable implementation component deployed in the front-end adaptation layer. In this embodiment, this component is implemented as an intelligent evidence preprocessing component.

[0139] This component performs automated analysis of input evidence, completes quality filtering and preliminary event structuring, and encapsulates valid inputs into standardized event objects that can be processed by subsequent core processes.

[0140] The core output of this component is a structured preliminary event summary, which must contain two types of procedurally generated, independent decision information: Evidence Quality Confidence: This is a comprehensive score automatically calculated by the component according to preset rules. The criteria include weighted analysis and rule-based judgment of multiple dimensions such as evidence source attributes, metadata of the collection scene, carrier technology quality, and abnormal performance of physical identification areas. When the input includes a third-party authoritative appraisal report, the independent credibility score declared in that report can also be used as input for this item.

[0141] Physical anti-counterfeiting status signal parsing result: This is a structured signal generated after deterministically extracting and determining the preset anti-counterfeiting feature status of the physical identifier in the input evidence. Its determination logic strictly follows the physical identifier structure defined in Example 1 and must simultaneously output the following two basic, unambiguous Boolean signal determination results: * Readability status of the primary identifier carrier: determines whether the unique identity code carried by the physical identifier can be successfully decoded; * Preset Destructive Feature Triggering State: Detects whether a pre-set microstructural feature (e.g., a specific pattern composed of pre-marked lines as shown in Example 1) has been definitively revealed due to illegal stripping.

[0142] 5.2.2 Triage Decision The system compares the preliminary event summary with the preset admission rules in the steady-state rule kernel, and performs traffic splitting according to the following preset, deterministic logic: * Feature triggering path: If the confidence level of the evidence quality is not lower than the preset threshold, and the judgment result of the preset destruction feature triggering state in the physical anti-counterfeiting status signal analysis result is "feature has been revealed", then it is judged as an "acceptable event" and the structured summary is sent to the core falsification stage (Section 5.3).

[0143] * External Authority Path: If a third-party authoritative appraisal report is submitted, and the system assesses its evidence quality confidence level as high, it will be determined as a "root cause conflict pending verification event" and will be transferred to the subsequent digital evidence completeness special verification process.

[0144] * Low-quality / invalid path: If none of the above conditions are met, it is judged as "low-quality / invalid input", the process will be terminated immediately and feedback will be provided.

[0145] 5.2.3 Technical Positioning This stage acts as a "physical anti-counterfeiting signal filter" and an "evidence quality grader" in the adjudication process, specializing in standardized physical state assessment, evidence credibility grading, and triage decisions. Its core logic strictly follows the physical identification structure defined in Example 1, determining the physical state of the identification by detecting whether preset anti-counterfeiting features (such as the appearance of a pre-etched five-pointed star) undergo a deterministic change; simultaneously, it conducts independent confidence assessments of external authoritative evidence such as third-party authentication reports, providing preliminary evidence for subsequent root cause conflict verification.

[0146] Therefore, this component anchors highly reliable physical fact inputs and highly confident supplementary evidence inputs at the forefront of the system architecture for the adjudication process. This enables all subsequent stages to build upon this solid foundation of evidentiary certainty and automatically generate enforceable adjudications through procedural rules, achieving a procedural closed loop from "conclusive evidence" to "conclusive enforcement" at the technical level.

[0147] 5.3 Second Phase: Retrieval of Temporal Evidence Chains and Multi-Dimensional Automated Verification The system proceeds to the corresponding verification process based on the event type: for "acceptable events," it performs falsification and logical verification; for "root cause conflict pending verification events" triggered by high-confidence third-party reports, it performs digital evidence completeness verification.

[0148] 5.3.1 Collection of Evidence Chain The system uses the digital identity of the product parsed from the input event as a global index to automatically retrieve the complete temporal evidence chain associated with that identity.

[0149] 5.3.2 Multi-dimensional Concurrency Verification The system invokes the multi-dimensional automated verification rule set encapsulated in the steady-state rule kernel to perform rigorous concurrent logical analysis and rule matching on the aforementioned time-series evidence chain. This concurrent design ensures the logical independence and equality of each verification dimension, with the core verification covering the following four dimensions.

[0150] First, physical identifier state consistency verification. Based on the physical state signal analysis results extracted in the first stage, the sequence images of the same physical identifier in the time-series evidence chain are analyzed to verify whether the preset micro-feature regions have undergone irreversible physical state changes that conform to preset destruction characteristics, and to verify whether the changes are consistent with the digital records in terms of time and logic.

[0151] Second, verify the rationality of spatiotemporal logic. Based on the timestamps and geographical coordinates in the evidence records, verify whether the operation occurred within the preset compliant geographical fence, and verify whether the spatiotemporal displacement between consecutive operations meets the reasonable threshold of the logistics scenario.

[0152] Third, verify the consistency of hierarchical binding states. Using cryptographic methods, verify the hierarchical binding relationships of product units and check whether the state transitions of operation records for parent and child units with binding relationships conform to the preset, globally consistent business logic.

[0153] Fourth, verify the continuity of the evidence chain. Verify whether the asynchronous evidence storage process of the goods circulation is continuous and uninterrupted, and focus on checking whether there is an "evidence chain interruption mark" generated due to asynchronous evidence storage timeout or failure (this mark is generated by the programmatic tracking mechanism in Implementation Example 3).

[0154] 5.3.3 Deterministic Verification Conclusion Based on the above multi-dimensional concurrent verification results, the system generates deterministic technical conclusions.

[0155] If all verification rules are met, the system determines that the temporal evidence chain is logically consistent and generates a deterministic technical conclusion of "logical consistency of the evidence chain." This conclusion is the deterministic output of the system after performing full-link verification of the target product's status, and can be directly used as a "status verification certificate" for programmatic auditing. For events triggered by high-confidence third-party appraisal reports, the system automatically generates a "declaration of the completeness of the adjudication logic," which directly serves as a technical prerequisite for triggering the "root cause conflict" handling protocol described in Example Six.

[0156] If any verification rule is triggered, the system determines that there is a logical contradiction in the time-series evidence chain and automatically generates a structured "violation conclusion and evidence summary," clearly indicating the specific verification dimension that failed, the triggered rule, and the associated key evidence points. This summary will serve as deterministic input to drive the subsequent hierarchical adjudication and procedural constraint process described in this embodiment.

[0157] 5.4 Phase Three: Deterministic Decisions and Procedural Responses For events that fail verification, the system automatically generates a definitive, structured "Enforcement Ruling" based on the "Violation Conclusion and Evidence Summary" and initiates subsequent procedures. This ruling is the sole technical conclusion generated by the steady-state rule kernel based on all evidence and established rules. All subsequent behavioral forks in the system stem from the different responses of the responsible parties to this definitive conclusion.

[0158] 5.4.1 Deterministic Decision Output and Grace Period Initiation The system first generates an "Enforcement Ruling" data object, clearly defining the responsible party, the recommended enforcement method, and the preset grace period for response, and then pushes it through a messaging service. Simultaneously, the system starts a timer for the case state machine instance associated with this case, marking the formal commencement of the procedural response process.

[0159] 5.4.2 Programmatic Forking Based on Responsible Party Response Based on the responsible party's behavior during the grace period, the system will automatically enter one of the following three preset deterministic response paths.

[0160] Path A (Acceptance and Compliance): The responsible party accepts the ruling and completes the compliance. After system verification, the case status is updated to "Compliance Completed and Closed in Compliance", a neutral case closure record is generated, the process ends and no negative credit mark is generated.

[0161] Path B (Raise an objection and initiate the procedural review channel): The responsible party raises an objection to the ruling and submits supplementary materials. After the system verifies the validity of the materials, the case is transferred to the procedural review channel. This channel processes cases according to the following preset certainty rules: One is the automated adjudication mode: the system calls the built-in automated adjudication engine to perform a second automated comparison between the new evidence and the existing evidence chain, and directly generates a review adjudication opinion (this adjudication is the system's final technical conclusion on the case), and drives the automated constraint response process to return to path A or enter path C to re-execute; The second is the procedural review mode: If the responsible party explicitly indicates the need for review in the objection request, the system will push the review ruling opinion generated by the automated adjudication mode and its associated evidence package to the review node protected by the system's preset program through an authenticated external interface (this node is reviewed by authorized personnel in a dedicated interface, and all operations are recorded in real time and immutably); after the review is completed, the node outputs the "Review Confirmation Opinion", and the system adopts the opinion according to the preset rules, forms the final review ruling opinion, and drives the procedural constraint response process back to path A or enters path C for re-execution.

[0162] Regardless of the mode used, the generated review ruling is the system's final technical conclusion on the case.

[0163] Path C (No Response or Invalid Rejection): If the responsible party does not respond within the grace period, or if the reason for its rejection is deemed invalid by the system, the system will automatically perform the following operations: generate a procedural status flag of "Ruling Not Fulfilled" and enter it into the reputation status factor database, which is associated with the responsible party's digital identity and uniformly managed by the steady-state rule kernel; trigger the generation of a "Procedural Breach of Contract Evidence Package", which is a cryptographically anchored structured data packet that encapsulates a summary of the complete chain of evidence on which this ruling depends, the enforcement ruling, the conclusion of the violation, and the current status; and mark the case status as "Evidence Complete and Can Be Legally Obtained".

[0164] 5.4.3 Programmatic Output and Termination of Autonomous Process For path C, the system generates a "procedural breach evidence package." The generation of this evidence package signifies the termination of the autonomous adjudication process based on deterministic rules within the system, and the case enters a state awaiting external handling. This evidence package serves as the system's final technical statement regarding this breach, providing a complete and verifiable cryptographic evidentiary basis for subsequent external handling.

[0165] 5.5 Fourth Stage: Case Closure and Status Synchronization This phase assigns a definitive final technical status to all events that have entered the adjudication process and synchronizes them with external handling results. Based on the different handling paths of the events, the system provides the following three definitive case closure types.

[0166] Compliance-based case closure after performance: Applicable to events processed through path A. After verifying the performance result, the system updates the case status to "closed - performance completed".

[0167] Review ruling closure: Applicable to events processed through the procedural review channel. Based on the generated review ruling opinion, the system will treat the ruling as the final technical conclusion and directly drive the event into the "Compliance Closure after Performance" or "Breach of Contract Disposal Closure" path below.

[0168] Default handling closure: Applicable to events handled through path C. Under this path, the system can complete the closure based on two types of external feedback: The first is the settlement of compensation. After verifying the valid proof that the responsible party has completed the compensation, the status is updated to "Case closed - Proactive compensation completed"; The second is judicial closure. After verifying the validity of the judicial or arbitration award, the status is updated to "Case Closed - External Award Completed".

[0169] The final status of all events, related rulings, and procedural breach evidence packages are all cryptographically linked to permanent technical records to ensure auditability and traceability throughout the entire lifecycle.

[0170] 5.6 Technical Effects The four-stage architecture of "screening evidence, falsifying evidence, constraining judgments, and closing cases" implemented in this embodiment is not a simple automation of the traditional adjudication process, but rather a systematic reconstruction of the governance paradigm at the technical level. Through automated quality filtering driven by a steady-state rule kernel, multi-dimensional logical falsification, hierarchical procedural response, and external state synchronization, it achieves a fully automated, evidence-driven, and auditable governance closed loop. The "enforcement ruling," "procedural status marker," and "procedural breach of contract evidence package" generated by this closed loop constitute a deterministic governance tool that can be enforced at the procedural level and verified and accepted at the legal level.

[0171] The procedural review channel transforms the factual ambiguity in complex objection scenarios into a definitive technical conclusion with procedural rigidity and auditability, thereby ensuring the finality, fairness, and acceptability of the system's rulings through its mechanism.

[0172] Thus, at the adjudication level, this embodiment systematically achieves a paradigm shift from a "manually dependent architecture" that relies on individual case-by-case human intervention to a "deterministic rule-based system" driven by deterministic code rules and executed procedurally throughout the entire process. It reconstructs "highly deterministic event tracing" and "verifiable procedural auditing" into two standardized procedural outputs based on the same fact-producing kernel, ultimately establishing a procedural governance system with code rules as the sole criterion, system-generated facts as the sole driver, and deterministic participation of all parties within a pre-defined procedure.

[0173] Example 6: Attribution, Tracing, and System Evolution Protocols for Root Cause State Conflicts This embodiment combines Figure 5 , Figure 6 As shown, this illustrates a pre-defined, automated handling protocol that is activated when a self-consistent digital record within a deterministic rule field fundamentally conflicts with the physical world state verified by external authorities. This protocol is a pre-defined, mandatory, self-evolving technical loop designed by the deterministic rule field to address this theoretically extreme scenario.

[0174] 6.1 Protocol Triggering and Root Cause State Marking The triggering of this agreement depends on the simultaneous satisfaction of the following two deterministic technical prerequisites: Internal final decision: The system has completed the procedural decision process described in claim 1 for the product’s chronological evidence chain, and has generated a “declaration of the completeness of the decision logic” accordingly. This declaration indicates that the chronological evidence chain has definitively passed all the verification items defined in claim 9.

[0175] External authoritative counter-evidence: The system receives a valid authoritative verification report issued by a legally qualified verification body through a certified interface, the conclusion of which is fundamentally contrary to the aforementioned internal ruling.

[0176] When both of the above premises are met simultaneously, a deterministic conflict is constituted between digital records and physical reality. Given that the immutability and logical consistency of the aforementioned chronological evidence chain in the circulation process have been definitively confirmed, the system, through deterministic logical deduction, converges the root cause of the conflict to the initial generation stage of the commodity's digital identity (i.e., the production end).

[0177] This convergence conclusion represents a deterministic technical state marked within the system, named "Root Cause State Conflict." This state marker serves only as the technical factual input to trigger subsequent automated processes and does not presuppose any subjective attribution.

[0178] 6.2 Automated Technology Process for Protocol Execution 6.2.1 State Synchronization and Response Initialization The system updates the digital identity status of the relevant products to "root cause conflict" and opens a standardized "conflict response and traceability initiation interface" to the responsible party (i.e., the creator of the product's digital identity). If the responsible party (brand) triggers the pre-set programmatic compensation process of the steady-state rule kernel through this interface, the system calls the integrated payment component to complete the automatic transfer of the corresponding security deposit account and generates an "advance compensation completion certificate" with a unique hash identifier. This certificate is the technical key to activate subsequent advanced traceability permissions.

[0179] 6.2.2 Support for Voucher-Driven Deep Traceability Once the "Advance Compensation Completion Certificate" is generated, the system automatically grants the brand full access to the "In-Depth Root Cause Traceability Support Package" and automatically aggregates and generates the support package in real time. This support package adheres to the principle of technological neutrality and aims to provide a high-fidelity, structured root cause diagnostic report, offering precise guidance for offline investigations. Its specific contents include: a fully correlated evidence set and a penetrating analysis report of the production process.

[0180] After completing the investigation based on the support package, the brand can submit the verified conclusions through the system's "Traceability Conclusion Archiving Interface". The conclusions must clearly point to specific anomalies in the production process and be accompanied by verifiable supporting materials hashes.

[0181] 6.2.3 System response triggered by verified traceability conclusions After verifying the traceability conclusion, the system automatically executes the following preset response.

[0182] First, the defense rules are urgently iterated. Any specific vulnerability characteristics revealed in the conclusions (such as the affected device, geographical location, operating mode, and new attack characteristics) will be used as the highest priority input to drive the controlled emergency update of the corresponding verification rules and risk control strategies in the steady-state rule kernel (Example 7) in order to achieve technical blocking of this specific attack path.

[0183] Second, the system generates counter-evidence. If the investigation results contain strong evidence that the conflict stems from a fraudulent verification report provided by the whistleblower, the system will automatically generate a "Technical Analysis Report on Conflict Points in System Records." This report will present a structured view of the verifiable contradictions between the system's credible internal records and the provided report, providing core electronic evidence for potential judicial counter-evidence proceedings.

[0184] 6.3 Technical Effects The value of this agreement transcends the handling of individual conflict events; it lies in establishing ultimate resilience, self-evolutionary capability, and due process of governance for deterministic rule-based systems, enabling them to cope with theoretically extreme scenarios. This is specifically manifested in three indispensable systemic pillars: First, it establishes a rigid procedure for conflict resolution, ensuring comprehensive governance. Addressing the theoretical blind spot of "complete digital records but conflicting physical states," this agreement uses pre-defined automated procedures to transform this unresolvable dilemma into a deterministic and executable technical process. This ensures that the system's governance scope covers all scenarios, from routine operations to extreme challenges, eliminating the risk of systemic trust collapse due to inability to resolve conflicts.

[0185] Second, it builds a technological bridge to transform online certainty into verifiable offline facts. Through the mandatory association of "advance compensation - evidence-driven - in-depth tracing," this agreement transforms the cryptographic certainty of the online evidence chain into a high-fidelity, structured root cause diagnosis report that can guide offline investigations. This breaks down the barrier between digital governance and physical world investigations, enabling the tracing of root causes of conflicts to leap from broad-spectrum screening to precise verification under strong technological guidance.

[0186] Third, a mandatory evolutionary mechanism is established to drive system immune upgrades through security incidents. The core closed loop of this protocol lies in the principle that "event handling inevitably drives rule iteration." The conclusion of any conflict handled by this protocol is used as the highest priority input, forcibly driving controlled updates to the steady-state rule kernel. This transforms a single security incident into a deterministic upgrade of the system's defense capabilities, thereby forming a continuously enhanced adaptive immune capability at the system level.

[0187] In summary, this protocol is not a passive response module, but rather a proactive and evolutionary architectural cornerstone that ensures the long-term stable operation of a deterministic rule-based system. Through procedural means, it transforms the handling of extreme conflicts into a strategic process of strengthening the system's credibility, uncovering root causes of hidden dangers, and iterating defense rules, thus achieving a fundamental leap from "static completeness" to "dynamic evolution" in the digital trust system.

[0188] Example 7: Architectural Implementation of Open Trust Infrastructure This embodiment combines Figure 1 , Figure 5 and Figure 6As shown, the system elaborates on how to engineer the methodologies and mechanisms defined in the preceding embodiments into an interoperable and long-term evolving open trust infrastructure. Its core lies in establishing the steady-state rule kernel as the sole source of consensus for the entire digital trust ecosystem. Through decoupling design with pluggable implementation components, it maximizes ecological innovation and collaborative network effects while ensuring the authority, consistency, and immutability of the core rules, thus resolving the fundamental contradiction between "unified rules" and "flexible implementation" from an engineering perspective.

[0189] 7.1 Steady-state rule kernel: the core of encapsulation and execution of deterministic rule sets like Figure 6 As shown, the steady-state rule kernel is a deterministic execution module that encapsulates all the core business rules, state logic, and verification criteria necessary for implementing this invention in programmatic code. As a specific engineering implementation, it can be instantiated as a deterministic, event-driven rule execution engine, logically comprising three core components.

[0190] First, a unified business rule library is established to encapsulate all state transition, logic verification, and conflict handling rules in code.

[0191] Second, a global fact state machine is used to maintain the exact state of all digital identities in real time.

[0192] Third, the rule interpreter is used to call the rule base to perform logical calculations based on the input events and the current state, and output deterministic adjudication events (such as state update instructions, evidence chain interruption markers, and enforcement rulings).

[0193] The three components described above work collaboratively based on an event-driven model to form a complete deterministic rule execution closed loop. The rule interpreter responds to external input, obtains the current fact baseline from the fact state machine, calls the corresponding rules in the rule base for calculation, and drives the fact state machine to update its state and trigger programmatic responses. This closed loop ensures that the system's response to any compliant input can be uniquely traced back to a specific rule, state, or event.

[0194] Therefore, the steady-state rule kernel essentially constitutes the core architectural cornerstone of the entire digital trust ecosystem, and its operating mechanism establishes three unshakable underlying technical constraints.

[0195] First, the core business logic must be immutable by one party, meaning that any addition, deletion, or modification of rules must be completed through a pre-defined governance process agreed upon by consensus, as described in Example 6.

[0196] Secondly, the non-repudiation of the ruling means that any output can be uniquely traced back to the coded rules and on-chain state.

[0197] Third, the indivisibility of the state, that is, as the sole maintainer of global facts, it ensures the global consistency of the system state.

[0198] The three technical constraints mentioned above together form the trust foundation for the system's operation.

[0199] Once deployed, the rules encapsulated within the kernel are executed deterministically through technical mechanisms. Any modification to these rules must be completed through the pre-defined governance process described in Example 6, thereby ensuring the long-term stability of the business logic. This stability, guaranteed by technology and tamper-proof, constitutes the ultimate technological foundation for the entire system's trust. Simultaneously, the overall architecture operates according to a design pattern where external business requests drive system responses, and core verification and adjudication rules are solidified and encapsulated within the kernel. The entire logical chain and state changes are traceable, eliminating uncertainties caused by subjective human intervention.

[0200] 7.2 Pluggable Components: Modular, replaceable technical functional units The system's specific technical functions are implemented by a series of independent modules that strictly adhere to the interface specifications defined by the steady-state kernel. These pluggable implementation components are adaptable executors of the deterministic rules defined by the kernel in specific software and hardware environments.

[0201] As a specific implementation example, the pluggable implementation components may include functional categories such as physical identification and sensing components, a scan-walk-transfer asynchronous evidence storage engine, a programmatic adjudication engine, and a trusted evidence storage component. Specifically, the physical identification and sensing component is used to implement interaction with physical identifiers; for example, it can be implemented as an intelligent evidence preprocessing component for initial screening of evidence quality. The scan-walk-transfer asynchronous evidence storage engine is used to execute asynchronous evidence storage protocols. The programmatic adjudication engine is used to implement multi-dimensional automated verification and programmatic adjudication. The trusted evidence storage component is used to achieve trusted storage and verification of data. Those skilled in the art should understand that the above examples are merely illustrative, and the specific form, type, function, and quantity of the pluggable implementation components can be flexibly configured and expanded according to actual deployment needs, and are not limited to the above examples.

[0202] This kernel-component decoupled architecture fundamentally resolves the engineering implementation contradiction between the fundamental issues of "coordination" and "scalability" in the background technology: it solves the coordination problem through a stable rule kernel as the sole source of consensus, while solving the scalability problem by enabling the diversity and independent evolution of component support technologies through pluggability. Its specific strategic value is reflected in three aspects.

[0203] First, break the technology stack lock-in and avoid dependence on a single technology from the root.

[0204] Second, it lowers the barriers to participation in the ecosystem, forms an open technology market based on the core, fosters diversified innovation around the core, and constitutes an innovative design model with defined rules and freedom of choice.

[0205] Third, it enables the system to respond quickly to differentiated compliance requirements in different industries or regions by configuring or replacing specific components, without touching the core rules.

[0206] 7.3 Multi-deployment and Native Interoperability Based on a Unified Kernel Based on the decoupled architecture described above, this system supports multiple deployment models: enterprise private deployment, Software as a Service (SaaS) deployment, and industry or regional consortium blockchain deployment. These deployment models share the same technical premise: all instances strictly adhere to the same set of stable-state rule kernels and their interface specifications.

[0207] The key technological effect of this is that data credentials and chains of evidence generated by different instances, because they all originate from the adjudication of the same steady-state rule kernel, possess inherent consistency in cryptographic proof, data semantics, and verification logic. Therefore, any credential itself is proof conforming to the kernel rules and can be independently and automatically verified in any other instance. This trust interconnection based on a unified consensus source will trigger a powerful network effect: with each new deployment instance, the trusted collaborative value of all existing instances within the ecosystem leaps, laying the engineering foundation for building a decentralized global trust network. This decoupled architecture of the kernel and pluggable components enables the entire trust system to have standardized engineering deployment capabilities and cross-scenario ecosystem expansion capabilities, allowing different deployment instances to natively recognize and interoperate with each other.

[0208] 7.4 Privacy-enhanced cross-domain collaboration support While complying with data sovereignty and privacy protection regulations, this architecture can be scaled to support broader cross-domain collaboration. Each compliant deployment instance can be authorized to synchronize the cryptographic digests of the evidence chains it manages to a global index service governed by consensus, enabling efficient and compliant credential verification.

[0209] Furthermore, privacy-enhancing computing technology can be integrated as a pluggable core component, supporting cross-domain joint statistics and risk analysis without the raw data leaving its respective managed nodes. This collaborative design pattern of "data remains stationary while value moves" enables the architecture to achieve the trusted flow of data value while respecting data sovereignty and privacy.

[0210] Example 8: Meta-problem Restructuring and Architectural Necessity Analysis 8.0 Demonstration Methods and Core Design Constraints This embodiment, based on the technical solutions defined in claims 1 to 17, clarifies, through systematic engineering and topology analysis, the fundamental paradigmatic differences between deterministic rule fields and existing technologies. This technical system is defined by two interdependent core design constraints that constitute its architectural axioms.

[0211] 8.0.1 Core Design Constraint 1: Global Passive Response All system state changes, logic checks, and adjudication executions are strictly triggered only by compliance requests submitted by certified external parties (including operators, regulators, and consumers). The system itself does not contain any proactive detection, inspection, or discretionary logic. This constraint ensures, architecturally, absolute determinism of system behavior (any output can be uniquely traced back to a specific input and fixed rules), clarity of operational technology boundaries (the system acts as an arbitration layer and does not intervene in business processes), and inherent simplicity of the architecture (no need to reserve redundancy for unpredictable proactive behaviors).

[0212] 8.0.2 Core Design Constraint Two: Globally Auditable and Verifiable All core business logic is encapsulated in a steady-state rule kernel using programmatic code, satisfying the following requirements: rules are publicly auditable (versioned storage, any participant can view any version); the chain of evidence is independently verifiable (including digital signatures, state hashes, and rule version identifiers, allowing third parties to verify compliance without relying on the system's private state); and the process is reproducible and simulable (given the same initial state and input events, behavior can be deduced from the publicly available rules). Therefore, constraint two is a prerequisite for constraint one to hold in engineering terms. Together, they form a recursive trust loop: passivity eliminates the possibility of proactive malicious actions by the system, and verifiability ensures that each step of passive behavior can be independently audited.

[0213] The two core design constraints mentioned above drove a fundamental restructuring of the technical architecture in three dimensions: First, the integration topology is reconstructed (corresponding to the meta-problem of synergy): the integration cost of the defender is reconstructed from O(N²) to a star topology with a steady-state rule kernel as the consensus source and an integration complexity of O(N) linearized.

[0214] Second, the decoupling of evidence storage economy (corresponding to the scalability meta-problem): from the engineering economic opposition of "credibility-scalability", it is reconstructed into a hybrid architecture that decouples on-chain anchored judicial proof from off-chain economic storage.

[0215] Third, a paradigm shift in governance (corresponding to the fundamental problem of determinism): from probabilistic governance that relies on human experience and case-by-case negotiations, to deterministic technological governance driven by a core of steady-state rules, with full coverage of the evidence chain and procedural execution.

[0216] Building upon this foundation, a strategically significant paradigm shift in anti-counterfeiting effectiveness has emerged: the linear efficiency bottleneck of traditional single-item independent verification has been broken, replaced by a networked verification structure based on cryptographic hierarchical binding and state consistency verification. This not only achieves an order-of-magnitude improvement in verification efficiency from O(N) to O(1), but also fundamentally reconstructs the economic model of the anti-counterfeiting game: attackers pay a superlinear cost of O(N²) for systematic counterfeiting, while the defender's verification cost remains constant. Anti-counterfeiting governance has shifted from reactive post-event verification to proactive risk mitigation based on architectural game constraints.

[0217] 8.1 Explicit Formation and Topological Reconstruction Solving of Cooperative Meta-Problems 8.1.1 The Meta-Problem Emerges: The Superlinear Growth of Defender Integration Costs In the traditional “manually dependent architecture”, trusted collaboration among N organizations requires the establishment of N×(N-1) / 2 pairs of bidirectional trust channels. Each pair of channels requires customized connection, permission negotiation and continuous manual maintenance. The total cost of ecosystem integration increases by O(N²), which constitutes a mathematical barrier to ecosystem expansion.

[0218] 8.1.2 New System Solution: Star Topology Reconstruction Based on Unified Consensus Source This invention establishes a steady-state rule kernel as the unified technical consensus source for the digital trust ecosystem. It encapsulates deterministic behavioral guidelines that all participants must adhere to using programmatic code, ensuring the finality of rulings within the ecosystem. All participants only need to connect to this kernel through a standardized interface (Example 7), reducing the complexity of new party integration from O(N) to O(1). Any system that does not adopt such a globally unique, tamper-proof, and auditable rule kernel as the basis for its rulings will not receive native mutual recognition within this ecosystem.

[0219] 8.1.3 Structural Changes and Scalability The complexity of ecosystem integration has been restructured from O(N²) to linearly increasing O(N), stemming from the "unified technology consensus source" architecture combined with standardized interfaces and pluggable components, enabling seamless access for participants with different technology stacks. This architecture has no theoretical upper limit on the number of participants or the choice of technology stack, and the linear growth model ensures the engineering feasibility and economic sustainability of ecosystem expansion. This change directly supports the beneficial effects of (i) "overcoming the meta-problem of collaboration" and (vi) "laying the foundation for open ecosystem engineering."

[0220] 8.2 Explicit and Hybrid Storage Solutions to the Scalability Meta-Problem 8.2.1 The Meta-Problem Emerges: The Engineering Conflict Between Judicial Effectiveness and Massive Storage Costs In scenarios involving the daily circulation of millions of goods, traditional evidence preservation faces a "two-way paradox": putting all data on the blockchain ensures judicial validity but the cost is unsustainable; off-chain storage has controllable costs but the integrity and temporal reliability of the data are difficult to prove to third parties. This contradiction is a fundamental manifestation of the difficulty in reconciling "reliability" and "scalability" from an engineering and economic perspective.

[0221] 8.2.2 New System Solution: Decoupling Architecture of On-Chain Integrity Anchoring and Off-Chain Economic Storage This invention employs a hybrid storage architecture: cryptographic digests of key evidence records are periodically aggregated to generate a Merkle root hash and anchored to a distributed ledger, while complete original business data is stored in a cost-effective cloud storage service. Only lightweight integrity proofs of a constant size are stored on-chain, while massive amounts of horizontally scalable business data are hosted off-chain, with an immutable link established between the two through cryptographic mechanisms.

[0222] 8.2.3 Structural Changes and Scalability On-chain anchoring operations are infrequent, fixed, and have low marginal costs, perfectly meeting the "integrity proof" requirements of judicial evidence preservation; off-chain storage achieves high capacity, elastic expansion, and low unit price. The combination of these two features reduces the total system storage cost by orders of magnitude under the same judicial validity requirements. Any tampering with the original off-chain data will cause its hash to fail to match the on-chain anchor value. This architecture allows off-chain storage capacity to expand almost infinitely with business volume, and on-chain anchoring costs are decoupled from the total amount of data, providing a predictable and manageable economic model for the reliable preservation of massive amounts of data. This change directly supports the beneficial effect (III) "Breaking the trustworthiness-scalability paradox."

[0223] 8.3 Explicit and Procedural Problem Solving of Deterministic Element Problems 8.3.1 The Emergence of the Meta-Problem: The Systemic Disadvantages of Probabilistic Manual Governance Traditional governance relies on manual spot checks, empirical reasoning, and case-by-case consultations, resulting in accidental discovery of violations, lengthy response cycles, and highly probabilistic outcomes. The defending party is at a systemic disadvantage in terms of information, response speed, and consistency of decisions.

[0224] 8.3.2 New System Solution: End-to-End Programmatic Tracking, Deterministic Falsification, and Closed-Loop Adjudication This invention constructs three interconnected technical closed loops.

[0225] First, the tracking-discovery closed loop: Based on the programmatic tracking mechanism, all preset compliance nodes are automatically tracked by time rules. Any process interruption is forcibly and indisputably recorded as an "evidence chain interruption marker", and violation discovery is transformed from accidental sampling reconstruction to systematic automatic recording.

[0226] Second, the falsification-adjudication closed loop: When the traceability is triggered, the time-series evidence chain is automatically analyzed based on a multi-dimensional concurrent verification rule set. Any violation will inevitably expose at least one dimension of logical contradiction. Based on the deterministic falsification conclusion, the corresponding business rules are automatically and unambiguously triggered and executed by the system to generate an enforcement ruling, and enter the corresponding path according to the procedural response of the responsible party.

[0227] Third, the evolution-enhancement closed loop: For theoretical boundary cases such as "root state conflict", a pre-set deep tracing and rule iteration protocol is initiated. The handling conclusion directly drives the controlled update of the corresponding rules in the steady-state rule kernel, thereby enhancing the system's immunity.

[0228] 8.3.3 Structural Changes and Scalability The governance structure has undergone a fundamental transformation: the scope of governance has expanded from limited sampling to global coverage, response time has been compressed from days / weeks to seconds / minutes, and adjudication conclusions have shifted from subjective negotiation to the deterministic output of coded rules. Tracking, falsification, adjudication, and evolution constitute an autonomous technical governance loop, marking a fundamental leap in commodity circulation governance from case-by-case games under a "manually dependent architecture" to procedural governance continuously driven by a "digital state credential chain" under a "deterministic rule field system." The focus of governance has shifted from responding to discrete violations to the continuous production and assurance of verifiable facts regarding the integrity of the entire circulation process. Procedural governance capabilities are not diluted by business expansion, the marginal cost of automated processes approaches zero, and the built-in rule iteration mechanism ensures the long-term adaptability and deterrent effect of the governance system. This change directly supports the beneficial effect (II) "Overcoming the meta-problem of determinism."

[0229] 8.4 Strategic Emergence of System Capabilities: From Verification Efficiency Bottlenecks to Eliminating Attack Motivations 8.4.1 The Structural Dilemma of Traditional Anti-counterfeiting Paradigms Under the traditional "manually dependent architecture," anti-counterfeiting systems face a double dilemma: First, the linear bottleneck of verification efficiency means that verifying N products one by one results in O(N) costs, which is unsustainable in high-volume circulation scenarios. Second, there is an asymmetry between the costs of attack and defense: the cost for an attacker to forge an aggregate unit (such as a whole box) is O(1), while the cost for the defender to verify all individual items in the box is O(N). This structural disadvantage forces actual operations to rely on low-probability sampling, creating a systemic defense gap.

[0230] 8.4.2 Strategic Deconstruction of the New System: From Efficiency Optimization to Game Theory Restructuring Based on the systematic solution of the three major problems, this system realizes the structural reconstruction of the anti-counterfeiting verification paradigm of commodities through cryptographic hierarchical binding and state consistency verification network, that is, the paradigm shift from post-event verification to pre-event suppression.

[0231] 8.4.3 Structural Observation: The Dual Effect of Asymmetric Gain and Motivation Elimination This design produces a definite dual effect.

[0232] First, a constant-level improvement in verification efficiency: the compliance party's verification of the root node (such as the whole box) automatically and unambiguously covers all child nodes through cryptographic binding, enabling the batch verification efficiency to jump from O(N) to O(1).

[0233] Second, there is an asymmetry in the costs of attack and defense: if an attacker wants to forge an aggregated unit evidence chain containing N nodes, they must overcome cryptographic and logical consistency constraints, and their attack cost increases superlinearly with N on the order of O(N²); the defender's verification cost remains constant. This inherent asymmetric game structure in engineering economics renders large-scale systematic forgery attacks against this system economically infeasible.

[0234] 8.4.4 Scale adaptability of system capabilities This mechanism possesses unique scalability. As the scale and complexity of the managed product system increase, the compliance party's verification efficiency advantage O(1) remains constant, while the attacker's cost disadvantage O(N²) intensifies simultaneously. This inherent asymmetry in the architecture ensures that the system's defense capabilities are not diluted with scale, but rather enhanced, forming a positive correlation between defense effectiveness and system size growth.

[0235] 8.5 Summary of Architectural Paradigms: From "Active Opacity" to "Reactive Verifiability" 8.5.1 The fundamental opposition between the two technological systems The traditional "manually dependent architecture" and the deterministic rule-based field system defined in this invention are fundamentally opposed in their core philosophy and architectural dimensions: the former is based on a trust model that relies on the authority and reputation of the operator, and the system behavior is characterized by proactivity, probing, and discretion. The decision-making process is closed and opaque, and the evidence is internalized and difficult to verify independently, ultimately leading to a probabilistic and high-friction governance model. The latter completely reconstructs this paradigm. The trust foundation is entirely and exclusively based on public, verifiable coded rules and cryptographic evidence. The system follows the principle of passive response, all behaviors are determined by preset rules, the decision-making logic is open, auditable, and reproducible, and the evidence has independent and verifiable legal force, achieving deterministic, procedural, and automated technical governance.

[0236] 8.5.2 The Engineering Inevitability of Paradigm Shift Based on the aforementioned core constraints, the following architectural necessity arises in this system.

[0237] First, scalability constraints: If a unified steady-state rule kernel is not used as the consensus source for star-shaped mutual recognition, the integration complexity of the N-party ecosystem cannot be lower than O(N²), and large-scale expansion faces insurmountable mathematical barriers.

[0238] Second, economic constraints: If a hybrid architecture that decouples on-chain anchored proofs from off-chain economic storage is not adopted, there is an irreconcilable binary opposition between the guarantee of judicial effectiveness and the cost of massive data storage.

[0239] Third, deterministic constraints: Without the introduction of pre-defined procedural tracking and multi-dimensional concurrent verification, the discovery and handling of violations will inevitably remain at a probabilistic and high-latency manual level, making deterministic governance impossible.

[0240] Therefore, in the field of end-to-end trusted management of goods, which requires simultaneous satisfaction of determinism, scalability, verifiability, high reliability, and low marginal cost, the "passive verifiability" architecture and its inherent "state credentialization" governance paradigm established by this invention are the inevitable architectural form that matches the constraints under the combined effect of the aforementioned multiple stringent engineering constraints. Conversely, any system with proactive behavior, due to the unpredictability of the timing and scope of its behavior, constitutes a source of uncertainty itself and cannot meet the necessary condition for a deterministic decision-making benchmark: its output must be completely and solely determined by external inputs and publicly available rules.

[0241] 8.5.4 Industrial Positioning of the New Paradigm The deterministic rule field and its steady-state rule kernel defined in this invention play a role in the digital trust layer that can be compared to the role of the TCP / IP protocol in the data transmission layer: it does not specify the specific business applications at the upper layer, but defines the basic interaction paradigm for achieving mutual trust recognition, evidence verification and adjudication execution between cross-domain entities.

[0242] 8.6 Conclusion In summary, this invention achieves three fundamental breakthroughs.

[0243] First, it systematically resolves structural contradictions: through the three major technical pillars of topology reconstruction, hybrid storage, and programmatic governance, it completely solves the structural engineering contradictions represented by the three meta-problems of synergy, scalability, and determinism; on this basis, it achieves a paradigm reconstruction of anti-counterfeiting effectiveness through cryptographic hierarchical binding. This reconstruction is reflected in the verification efficiency jumping from O(N) to O(1), fundamentally reversing the cost game between attack and defense, making large-scale systematic forgery infeasible both in engineering and economics, and curbing violations at the motivation level.

[0244] Second, it has completed a fundamental leap in governance paradigms: it has achieved a systemic paradigm shift from "relying on the reliability of people" to "relying on the certainty of rules", from "probabilistic correctness" to "certain correctness", and from "customized for each case" to "defined once, operated everywhere".

[0245] Third, it provides a complete infrastructure paradigm: it provides complete technical elements from rule primitives, verification protocols, evidence standards to governance processes, and defines clear architectural boundaries and feasible evolution paths.

[0246] Based on a deep understanding of the limitations of "manually dependent architectures," this invention fundamentally reconstructs and fully defines a new paradigm for trustworthy product management by defining two core architectural constraints: "global passive response" and "global auditability and verifiability." The deterministic rule field is a complete and logically self-consistent new paradigm. The synergy of all its technical features achieves a synergistic effect in solving the aforementioned three fundamental problems, and gives rise to the strategic capability of paradigm reconstruction in anti-counterfeiting effectiveness. Thus, it comprehensively surpasses existing technical architectures in terms of scalability, synergy, determinism, and anti-counterfeiting efficiency, constituting a systematic reconstruction of the existing technical architecture in this field. This invention provides a complete, self-consistent technical architecture based on deterministic code and passive response principles to resolve long-standing structural contradictions in this field. This architecture defines a new paradigm for trustworthy interaction in this field.

Claims

1. A method for end-to-end trusted management of goods based on deterministic rule fields, characterized in that, The deterministic rule field is a deterministic program execution environment driven by a steady-state rule kernel, which makes deterministic decisions on commodity circulation events; the method includes the following steps: S1. Identity Binding Steps: Configure physical identifiers for each level of product unit, and create a unique digital identity with a preset lifecycle state for each physical identifier in the trusted evidence storage system; establish a trusted binding relationship between digital identities at different levels based on cryptographic methods; S2. Asynchronous Evidence Preservation and Programmatic Tracking Steps: At preset key handover nodes in the supply chain, an asynchronous evidence preservation operation is performed via a terminal, namely: scanning the physical identifier to collect data containing the identifier image, timestamp, and geographic coordinates; generating a digitally signed evidence preservation data packet locally on the terminal; immediately releasing the physical goods; and asynchronously uploading the data packet to the trusted evidence preservation system to form a time-series evidence chain of goods circulation; the system automatically tracks the continuity of the time-series evidence chain according to the preset rules in the steady-state rule kernel; S3. Triggering and Programmatic Decision-Making Steps: In response to a request initiated by an external traceability party or an operator in the commodity circulation process, the system performs a preliminary quality assessment of the request; for requests that pass the assessment, the decision-making process is triggered, the time-series evidence chain is automatically retrieved, and logical falsification is performed based on the multi-dimensional automated verification rule set in the steady-state rule kernel. Based on the verification conclusion, the hierarchical programmatic decision-making and constraint response defined by the steady-state rule kernel are triggered.

2. The method according to claim 1, characterized in that, The steady-state rule kernel is implemented as a deterministic rule execution engine, which includes: a rule base that encapsulates all core business logic, a fact state machine that maintains the state of all digital identities, and a rule interpreter that serves as the sole adjudication entry point; wherein, the rule interpreter is configured to receive external requests and perform logical calculations based on the rule base and the fact state machine, and the rule base and the fact state machine do not directly expose access interfaces to external systems.

3. The method according to claim 1, characterized in that, In step S1, the trusted binding relationship is implemented through a hierarchical hash structure constructed using cryptographic methods, which enables a compliant operation on the digital identity of a high-level aggregation unit to automatically and unambiguously cover the digital identities of all bound sub-units based on the binding relationship.

4. The method according to claim 1, characterized in that, The physical identifier has anti-transfer properties, and its structure is configured to cause cohesive failure and produce a visually detectable, irreversible physical state change when subjected to unauthorized stripping.

5. The method according to claim 1, characterized in that, In step S1, the preset lifecycle states of the unique digital identity include "inactive", "in transit", "in stock", "sold", "consumed", and "cancelled". The method also includes: arbitrating according to globally consistent digital identity lifecycle state machine rules defined by the steady-state rule kernel, and rejecting any operation requests that violate the preset state transition path.

6. The method according to claim 1, characterized in that, In step S2, the digitally signed evidence data packet includes at least the following signed object data: physical identifier encoding, cryptographic hash value of the identifier image, timestamp and geographic coordinates when the image was acquired, and identity information of the operator.

7. The method according to claim 1, characterized in that, In step S2, the scan-go-transmit asynchronous evidence storage operation is as follows: after scanning and data collection are completed, the terminal completes the digital signature of the data packet locally and then sends out a release instruction to allow the physical goods to leave the current node; the signed evidence storage data packet is asynchronously uploaded by the terminal to the trusted evidence storage system in the background.

8. The method according to claim 1, characterized in that, In step S2, the programmatic tracking includes: for each scan-go-transmit asynchronous evidence storage operation, starting from the time it completes the local signature on the terminal, if the trusted evidence storage system fails to successfully receive and verify the corresponding evidence storage data packet within a preset time limit, the system enters an observation and waiting period; if the system still fails to successfully receive and verify the evidence storage data packet within the observation and waiting period, an evidence chain interruption marker with a unique hash identifier is automatically generated and recorded in the trusted evidence storage system; this marker will be periodically anchored to the distributed ledger with each batch of evidence storage.

9. The method according to claim 8, characterized in that, In step S3, the multi-dimensional automated verification rule set is used to concurrently perform automated verification of the following dimensions on the time-series evidence chain: (1) Physical identifier state consistency verification: Based on machine vision algorithm, analyze the sequence image of the same physical identifier in the time-series evidence chain to verify whether its physical state has undergone irreversible degradation; (2) Spatiotemporal logic rationality verification: Verify the relationship between the time interval and geographical location displacement between any two evidence storage operations and whether it is within the reasonable threshold range preset according to the logistics scenario; (3) Hierarchical binding state consistency verification: Verify whether the operation record of the commodity unit with cryptographic binding relationship conforms to the preset hierarchical state transition logic; (4) Evidence chain continuity verification: Verify whether there is an evidence chain interruption mark of the type described in claim 8 in the time-series evidence chain.

10. The method according to claim 9, characterized in that, In the physical identifier state consistency verification, the physical identifier has a preset micro-feature region to indicate its integrity; the verification determines whether the preset micro-feature region has undergone irreversible physical state change by analyzing the state changes of the preset micro-feature region in the sequence image.

11. The method according to claim 9, characterized in that, In step S3, the hierarchical procedural adjudication and constraint response includes: the system generating a performance ruling with procedural binding force based on the verification conclusion; automatically executing a procedural constraint response for events where the responsible party accepts the ruling; and initiating a procedural review channel for events where the responsible party or the requesting party objects to the ruling result, and generating a performance ruling based on the review conclusion.

12. The method according to claim 1, characterized in that, In step S2, the time-series evidence chain is formed using a hybrid storage architecture: the complete evidence data package is stored in an off-chain storage system; at the same time, the cryptographic digests of the key evidence data are periodically calculated and aggregated to generate a Merkle root hash, which is then written into a distributed ledger for deterministic anchoring.

13. The method according to claim 1, characterized in that, The method further includes: when an external authoritative institution verifies that there is a fundamental conflict between the physical state of the goods and the time-series evidence chain recorded by the system, the system drives the controlled update of the relevant rules in the steady-state rule kernel based on the verification conclusion.

14. A trusted management system for the entire product supply chain, used to implement the method according to any one of claims 1-13, characterized in that, The system is a deterministic rule field system, comprising: an identity binding and verification module, used to execute the identity binding step (S1), managing the mapping and hierarchical binding relationship between physical identifiers and digital identities; a trusted evidence storage and status tracking module, used to execute the asynchronous evidence storage and programmatic tracking step (S2), realizing data collection, signing, asynchronous uploading, and continuous tracking of the evidence chain; and a programmatic adjudication and execution module, used to execute the triggering and programmatic adjudication step (S3), performing logical falsification and programmatic response based on the temporal evidence chain and a preset rule set.

15. The system according to claim 14, characterized in that, The core architecture of the system includes a steady-state rule kernel and pluggable implementation components; wherein, the steady-state rule kernel is a deterministic rule interpretation and state arbitration core formed by encapsulating the business rules, data models, state machines and verification logic defined by any one of the methods in claims 1-13 into code.

16. The system according to claim 15, characterized in that, The pluggable implementation component is a software functional module that is implemented based on the standardized interface specifications provided by the steady-state rule kernel and can be deployed and replaced independently.

17. The system according to any one of claims 14 to 16, characterized in that, The system supports at least one of the following deployment methods: enterprise private deployment, industry or regional consortium blockchain deployment, or Software as a Service (SaaS) deployment.

18. A non-volatile computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the product end-to-end trusted management method as described in any one of claims 1-13.

19. A computing device, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the end-to-end trusted management method for goods as described in any one of claims 1-13.

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