An internet commodity supply chain whole-process information tracing method and system

Abstract

The application relates to the technical field of supply chain information tracing, in particular to a full-process information tracing method and system for an internet commodity supply chain, which comprises the following steps: when a node in a supply chain network is in a network outage state, a window commitment certificate with a node signature is generated after each node determines the coding of data collected according to a time window for a target single commodity; when the commodity is handed over from a node to a next node, a handover proof digest is generated; when tracing and inquiring, the abnormality degree of each hop is calculated along the path to screen out a responsible node; and an auditable evidence package is output. The application aims to generate an interpretable tracing result when a node in a supply chain network is in a network outage state.

Description

Technical Field

[0001] This application relates to the field of supply chain information traceability technology, specifically to a method and system for full-process information traceability of internet commodity supply chains. Background Technology

[0002] The internet-based goods supply chain is a network value chain that dynamically decouples the flow of commerce, logistics, capital, and information throughout the entire process from raw material procurement, warehousing and transportation, platform distribution to last-mile delivery and ultimately to the consumer. It achieves collaborative orchestration through online means. Leveraging digital components such as e-commerce platforms, SaaS ERP, IoT devices, logistics cloud platforms, payment systems, and data algorithms, order, inventory, transportation capacity, payment, and after-sales data, originally scattered across factories, warehouses, customs, carriers, express delivery stations, and consumers, is abstracted and modeled into shareable, computable, and interactive digital twin objects. This replaces the traditional linear supply chain's reliance on bulk stockpiling and forecasting-driven operations with a cloud-based intelligent scheduling mechanism. During the supply chain operation, each product must be assigned a unique digital identity (i.e., a data passport), and an immutable chain of evidence must be built through a trusted mechanism to achieve end-to-end information traceability and precise accountability.

[0003] Traditional supply chain traceability methods generate hash digests of key events at each stage of the supply chain periodically or in batches, writing them into public or consortium blockchains for traceability through on-chain timestamps and immutability. This process is typically handled by a single responsible entity, with regulators and consumers querying data by scanning product QR codes. However, this method relies on a persistent network. When containers are offline for extended periods at sea or at high altitudes, sensors can only cache data locally, forcing the batch-based on-chain process to be interrupted, potentially leading to data gaps. Furthermore, handover between nodes relies solely on manual scanning, making it impossible to determine whether the problem lies with the previous node or the handover process. This results in batch hashes not being accurately linked to individual products, making it difficult to accurately pinpoint responsible nodes and time points during the entire traceability process.

[0004] Therefore, this application aims to solve the following technical problem: how to accurately locate abnormal nodes in the entire process of information traceability of Internet commodity supply chain, even in the event of network interruption, by relying on the time window commitment mechanism with node signature, combined with the two-way digital commitment and physical evidence verification in the handover process. Summary of the Invention

[0005] To address the aforementioned technical problems, this application provides a method and system for tracing the entire process of internet-based commodity supply chain information. The specific technical solution adopted is as follows:

[0006] In a first aspect, one embodiment of this application provides a method for tracing the entire process of an internet-based goods supply chain, the method comprising the following steps:

[0007] When a node in the supply chain network is offline, sensor samples, node metadata, and individual item identifiers are collected for the target single item at each node according to a time window. After deterministic encoding of all collected data, a window commitment certificate with node signature is generated by hashing.

[0008] When goods are handed over from one node to the next, a handover proof digest is generated by hashing based on the window commitment credentials of both nodes and the immediate evidence set at the time of handover.

[0009] During the traceability query, hash consistency, signature validity, time consistency, and temperature consistency are verified hop by hop along the path. The anomaly degree of each hop is calculated to filter out the responsible node. An auditable evidence package containing the responsible node, credibility, hop-by-hop verification results, commitment certificate, handover proof summary, and temperature time sequence is output.

[0010] Preferably, the method for generating the window commitment certificate is further expressed as follows:

[0011] ,in This indicates that node j generates a commitment certificate for a single item n within a time window. This indicates the collected product information, where This represents the sensor samples collected within window T. Represents node metadata, A unique identifier for a single item; This represents a deterministic coding function. This represents a collision-resistant cryptographic hash. This represents the digital signature of the node's private key on the same CAN byte stream. This represents a simple byte concatenation symbol.

[0012] Preferably, the deterministic encoding steps include: arranging sensor samples, node metadata, and individual identifiers in ascending alphabetical order by field, unifying the time to UTC ISO-8601 format, retaining three decimal places for floating-point numbers and removing trailing zeros, filling missing values ​​with null, and outputting a UTF-8 JSON or CBOR byte stream.

[0013] Preferably, the method for generating the handover proof digest is further expressed as follows:

[0014] ,in This represents the handover proof summary generated when a single item n is transferred from node j to node k. This represents node j's commitment certificate for product n in the last time window before the handover. This represents the commitment certificate of node k for the same product n within the first time window after the handover. This represents the immediate evidence set when node j transfers item n to node k.

[0015] Preferably, the formula for calculating the anomaly degree is:

[0016] ,in This represents the anomaly degree of the h-th hop on the tracing path. To indicate hash consistency, the window commitment certificate and handover proof digest of a single item n at the two handover nodes in the h-th hop are recalculated and compared with the stored value in the system. If they are completely consistent, the value is 1; otherwise, the value is 0, indicating that the data has been tampered with or lost. Indicates the validity of the signature. It is verified by the public key in the node certificate to verify the window commitment certificate and the temporary signature of both parties in the handover proof instant evidence set of the two handover nodes at the h-th hop. The value is 1 when all are verified and the certificate has not been revoked; otherwise, the value is 0. To indicate time consistency, calculate the interval between the handover timestamp of the h-th hop and the time window of its adjacent previous hop. If the interval is less than a preset time, the value is 1; otherwise, the time consistency score is exponentially decayed by exp(). Temperature consistency is represented by the moving average of thermodynamic consistency scores over different time windows.

[0017] Preferably, the method for screening the responsible nodes is as follows: the two handover nodes with the highest anomaly degree in a single hop are identified as suspected responsible nodes; the responsible nodes among the suspected responsible nodes are judged based on hash consistency, signature validity, time consistency, and temperature consistency.

[0018] Preferably, the formula for calculating the thermodynamic consistency score is: ,in This represents the average relative deviation between the observed temperature and the desired temperature within the window.

[0019] Preferably, ,in This represents a time window for the handover node j. This represents the length of a time window for the handover node j. This indicates the half-width of the tolerance range for temperature changes. This indicates the actual measured temperature of the sensor. This represents the desired temperature in the first-order heat transfer model.

[0020] Preferably, the trust level is determined by averaging the hash consistency, signature validity, time consistency, and temperature consistency across all hops.

[0021] Secondly, another embodiment of this application provides a full-process information traceability system for an internet-based commodity supply chain, implementing the aforementioned method for full-process information traceability of an internet-based commodity supply chain. The system includes:

[0022] The edge acquisition and commitment module is used to collect sensor samples, node metadata and individual item identifiers of individual items at each node according to time windows, perform deterministic coding and generate window commitment credentials with node signatures;

[0023] The handover verification module is used to generate a handover verification summary based on the window commitment credentials of both parties and the real-time evidence set at the time of handover when nodes are handed over.

[0024] The verification and location module is used to perform hash, signature, time, and temperature consistency verification on hop-by-hop proofs during traceability queries, calculate the anomaly degree of each hop, and output the responsible node and evidence package;

[0025] The storage and indexing module is used to store or index window commitment credentials, handover proof summaries, and original codes, and supports offline caching, batch reporting, and third-party anchoring.

[0026] This application has at least the following beneficial effects:

[0027] This application deterministically encodes a single product's time-window sensor data, node identity, and unique identifier at the node entry point during a network outage, and generates a signed partial commitment using the node's private key. During handover between two nodes, the commitments of both parties, along with immediate evidence, are hashed together to form a two-way endorsement. In the query phase, the hash, signature, time sequence, and temperature factors of the entire chain are multiplied and inverted to amplify single-point anomalies, locate the most likely responsible node, and output an auditable evidence package. Its advantages include generating commitment certificates even during network outages, eliminating the time window vacuum and evidentiary blind spots caused by batch arrivals on the chain in traditional methods; during handover, both parties jointly hash and sign, ensuring that any subsequent unilateral tampering is exposed due to the lack of the other party's private key, thus identifying the responsible node; the four-factor multiplication amplifies single-point failures, outputting interpretable traceable results and avoiding disputes. Attached Figure Description

[0028] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1This is a flowchart illustrating a method for tracing the entire process of an internet-based goods supply chain, as provided in one embodiment of this application. Detailed Implementation

[0030] Example 1

[0031] One embodiment of this application provides a method for tracing the entire process of an internet-based goods supply chain; see details below. Figure 1 The method includes the following steps:

[0032] S1: When a node in the supply chain network is offline, sensor samples, node metadata, and individual item identifiers are collected for the target single item at each node according to a time window. After deterministic encoding of all collected data, a window commitment certificate with node signature is generated.

[0033] This application takes cross-border cold chain fresh goods as an example. Cold chain containers may be offline for a long time in the open sea, at high altitude or in remote warehouses, and the hash cannot be written to the chain in time, which may be tampered with. If the traditional method of putting the entire batch on the chain after arriving at the port is used, the abnormal temperature of the goods can only be discovered when unloading, and it is impossible to prove which node and time the abnormality occurred. Therefore, the time window vacuum caused by the network outage will break the evidence chain.

[0034] In a supply chain network, any entity that can legally operate goods and complete the transfer of ownership and responsibility, whether it is a factory workshop, cold storage, container, customs inspection area, air cargo terminal, express distribution center or third-party quality inspection laboratory, is considered a node; the node has an independent ID, can collect environmental data, and can issue digital signatures.

[0035] Once a product enters a node, product information is collected according to a time window, and a window commitment certificate is generated. This can be represented as follows: ,in This represents the commitment certificate generated by node j for a single item n within a time window.

[0036] This indicates the collected product information, where This represents the sensor samples collected within window T. In one embodiment, T is set to 30 minutes or 200 data points. Each sensor sample includes a timestamp, temperature, humidity, and light intensity. The collection time interval is 5 minutes. This represents node metadata, including node ID, device certificate fingerprint, public key reference or certificate serial number, geographic coordinates, operator ID, and shipping order number. A unique identifier for a single item can be a QR code, an RFID tag EPC, or an encrypted chip UID.

[0037] This represents a deterministic encoding function that ensures the same byte stream is obtained across different hardware and software implementations. Fields are arranged in ascending alphabetical order, and time is uniformly in UTC ISO-8601 format. Missing values ​​are filled with null and field names are retained. Floating-point numbers are uniformly retained to 3 decimal places and trailing zeros are removed. The output is UTF-8 JSON or CBOR, ensuring that the same data yields the same byte sequence.

[0038] This represents a collision-resistant cryptographic hash, which can be SHA-3-256 or SM3. It is calculated on a CAN byte stream to generate a 32-bit digest. Any bit change will cause the digest to change, which is used for fast integrity verification. This represents a digital signature of the node's private key on the same CAN byte stream. It can be ECDSA-P256, Ed25519, or the national cryptographic standard SM2, and is used to prove that the window data was indeed confirmed by the node at that time. This represents a simple byte concatenation symbol that concatenates the hash digest and signature bytes in a fixed order to form a window commitment credential, which is easy to interpret by splitting it by length.

[0039] After obtaining the window commitment certificate, it is first written to local trusted storage while offline. After connecting to the network, it is uploaded to the cloud traceability platform or consortium blockchain order service. After the platform verifies that the signature is correct, it writes the summary of the window commitment certificate to the blockchain and updates the world state synchronously. The complete certificate is stored in object storage and a secondary index is established with the single product ID and window number as the primary key. This ensures that the commitment generated offline has evidentiary effect. This is for subsequent handover between nodes, customs inspection, and real-time retrieval by consumers for scanning codes, and completes on-chain and off-chain consistency verification, thereby ensuring that the commitment generated offline has evidentiary effect.

[0040] Compared to the traditional method of batch on-chaining, the edge segmented commitment mechanism of this application performs deterministic encoding at each node entry point and generates a digital signature by combining the node's private key, forming local evidence with unforgeability and non-repudiation. At the physical level, it binds specific commodities and specific time periods, and at the logical level, it relies on the strong security assumptions of collision-resistant hash functions and public-key cryptography. This ensures that any tampering with the original data or metadata will lead to the failure of digest value and signature verification, thereby achieving data integrity and source verifiability in offline state, and thus increasing the tamper-proof capability of the traceability chain.

[0041] S2: When goods are handed over from one node to the next, a handover proof summary is generated based on the window commitment credentials of both nodes and the real-time evidence set at the time of handover.

[0042] Traditional methods rely solely on the previous node unilaterally uploading hashes to the blockchain, failing to provide the recipient with endorsement of the goods' condition and the transfer of responsibility at the time. This could lead to subsequent disputes about whether anomalies occurred during transit. This application addresses this by hashing the window commitment credentials of both nodes together at the handover site to generate a handover proof digest, with each node retaining its own window commitment credential hash. Consequently, any subsequent alterations to temperature records or handover times will be exposed due to the lack of the other party's private key signature, thus pinpointing the time period of the anomaly and the responsible party.

[0043] When goods are transferred from the previous node j to the next node k, the transfer proof summary is calculated based on the window commitment credentials of both parties and the immediate evidence set, which can be represented as follows: ,in This represents the handover proof digest generated when a single item n is handed over from node j to node k. It is a 32-byte string (SHA-3-256 / SM3, depending on the selected hash function).

[0044] This represents the commitment certificate of node j for product n in the last time window before handover. If a window has not been fully collected at the time of handover, a window commitment certificate is generated for the collected portion. This represents the commitment credential of node k for the same product n in the first time window after the handover. Since the node has not yet started monitoring the product, this commitment only contains node metadata and the single item identifier, and the rest is left empty.

[0045] This represents the immediate evidence set when node j delivers item n to node k, used to prove that the delivery actually occurred and was completed under specific spatiotemporal conditions. Its fields include, but are not limited to: delivery timestamp; geofencing assertion, GPS coordinates, GeoHash, or area codes for ports and airports; and temporary signatures from both parties, where node j and node k each use their private keys to create short signatures for the item ID, timestamp, and geohash. All fields are deterministically encoded in a fixed order (using the same rules as CAN), generating a single byte stream.

[0046] S3: During the trace query, verify hash consistency, signature validity, time consistency, and temperature consistency hop by hop along the path, calculate the anomaly degree of each hop, and use the anomaly degree to filter out the responsible node; and output an auditable evidence package containing the responsible node, credibility, hop by hop verification results, commitment certificate, handover proof summary, and temperature time sequence.

[0047] Traditional traceability can only provide the static fact that a certain record exists on the chain, and cannot directly quantify which hop of the handover process, which time period, or what caused the cold chain failure. This application verifies the digest and signature of the window commitment certificate and handover proof hop by hop, and then conducts a comprehensive analysis in combination with time misalignment, temperature mutation, and signature failure. It uses hash consistency, signature validity, time consistency, and temperature consistency as four compliance factors, and multiplies and inverts the four compliance factors to amplify the contribution of single-point failure to the anomaly score. This transforms the credible record into an explainable responsibility score, so that the platform only needs to traverse the evidence to find the responsible node after receiving a dispute notification.

[0048] Single-hop anomaly can be expressed as ,in This represents the anomaly degree of the h-th hop on the tracing path. To indicate hash consistency, the window commitment certificate and handover proof digest of a single item n at the two handover nodes in the h-th hop are recalculated and compared with the stored value in the system. If they are completely consistent, the value is 1; otherwise, the value is 0, indicating that the data has been tampered with or lost. Indicates the validity of the signature. It is verified by using the public key in the node certificate to verify the window commitment credentials and the temporary signatures of both parties in the handover proof instant evidence set of the two handover nodes at the h-th hop. The value is 1 if all are verified and the certificate has not been revoked, otherwise the value is 0. To indicate time consistency, the interval between the handover timestamp of the h-th hop and the time window of its adjacent previous hop is calculated. If the interval is less than a preset time, the value is 1; otherwise, the time consistency score is exponentially decayed by exp(). In this embodiment, the preset time is 5 minutes.

[0049] In scenarios involving prolonged network outages, if the temperature of goods becomes abnormal, a simple moving average alone is insufficient to determine whether the change is abnormal. Under normal refrigeration unit operation, due to heat transfer effects, the container's temperature curve will fluctuate slightly around the set temperature in a sawtooth pattern, a natural cycle caused by the compressor's start-stop cycle. If the container is manually opened, the temperature curve will rise slowly with a small slope, and then slowly fall back with an approximately equal slope after the door is closed and refrigeration resumes. Temperature consistency is represented by the moving average of thermodynamic consistency scores over different time windows.

[0050] By comparing the measured temperature curves with the heat transfer model, it is possible to distinguish between normal heat transfer rise and human error such as opening the box or a refrigeration failure, thereby obtaining a more accurate determination of the responsible point. ,in Thermodynamic consistency score is represented by, where This represents the average relative deviation between the observed temperature and the desired temperature within the window.

[0051] ,in This represents a time window for the handover node j. This represents the length of a time window for the handover node j. This represents the half-width of the tolerance range for temperature changes (the value used in this embodiment). ), used for normalization, This represents the measured temperature of the sensor. The presence of unexpected thermal disturbances under network outage conditions is quantified by normalized average deviation.

[0052] ,in Let represent the desired temperature of the first-order heat transfer model, where This represents the reference temperature, i.e., the temperature set for the container, where e is the natural constant. Indicates the window start time. The value represents the ambient temperature outside the container, and k represents a preset thermal decay constant. In one embodiment, the thermal decay constant of the refrigerated container is set to a value of [value missing]. This model simplifies the container into a single-node heat capacity and uniform thermal resistance, assuming that heat flux is proportional to the internal and external temperature difference, with respect to the time constant. Differentiating the equation yields a first-order differential equation, which can be solved. It is used to quickly estimate the temperature decay or increase over time.

[0053] Because the time window is very short, the compressor of the refrigeration unit may not start within the window, so most windows conform to the first-order heat transfer model. Perform a moving average over ten windows. The closer the value is to 1, the more the measured temperature curve matches the temperature predicted by the first-order heat transfer model, indicating that the container is more likely to be in a normal state and the temperature change is due to normal heat conduction. Conversely, a value closer to 1 indicates an unexpected thermal disturbance. If the current location is identified as the responsible node, then... The largest window is the responsibility window.

[0054] The above four compliance factors are multiplied together and then inverted. When any one of them equals 0 or approaches 0, the single-hop anomaly score approaches 1, amplifying the anomaly and used to accurately locate the most suspicious link in the chain of responsibility. For a single product n, the two junction nodes of the hop with the highest single-hop anomaly score are taken as suspected responsibility nodes, representing the abnormal link. Based on the four compliance factors, the specific node responsible is determined, thus identifying the responsible node. For example, when hash consistency is zero, the node whose hash verification fails is considered the responsible node.

[0055] Finally, the overall traceability credibility is calculated by averaging the four compliance factors across all hops to provide a global perspective. A higher value indicates high credibility throughout the entire chain, while a lower value closer to zero indicates multiple consecutive failures, requiring overall rejection or a full batch recall. The final output is an auditable evidence package containing the responsible node, credibility, hop-by-hop verification results, commitment credentials, handover proof summary, and temperature timing.

[0056] Example 2

[0057] Another embodiment of this application provides a full-process information traceability system for an internet-based commodity supply chain. This system has the same inventive concept as the aforementioned full-process information traceability method for an internet-based commodity supply chain. The system includes:

[0058] The edge acquisition and commitment module is used to collect sensor samples, node metadata and individual item identifiers of individual items at each node according to time windows, perform deterministic coding and generate window commitment credentials with node signatures;

[0059] The handover verification module is used to generate a handover verification summary based on the window commitment credentials of both parties and the real-time evidence set at the time of handover when nodes are handed over.

[0060] The verification and location module is used to perform hash, signature, time, and temperature consistency verification on hop-by-hop proofs during traceability queries, calculate the anomaly degree of each hop, and output the responsible node and evidence package;

[0061] The storage and indexing module is used to store or index window commitment credentials, handover proof summaries, and original codes, and supports offline caching, batch reporting, and third-party anchoring.

[0062] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not invented in this application.

[0063] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for full-process information traceability in the internet commodity supply chain, characterized in that, The method includes the following steps: When a node in the supply chain network is offline, sensor samples, node metadata, and individual item identifiers are collected for the target single item at each node according to a time window. After deterministic encoding of all collected data, a window commitment certificate with node signature is generated by hashing. When goods are transferred from one node to the next, a transfer proof digest is generated by hashing based on the window commitment credentials of both nodes and the immediate evidence set at the time of transfer; the method for generating the transfer proof digest is further expressed as follows: ,in This represents the handover proof summary generated when a single item n is transferred from node j to node k. This represents node j's commitment certificate for product n in the last time window before the handover. This represents the commitment certificate of node k for the same product n within the first time window after the handover. This represents the immediate evidence set when node j transfers item n to node k. During the traceability query, hash consistency, signature validity, time consistency, and temperature consistency are verified hop by hop along the path. The anomaly degree of each hop is calculated to filter out the responsible nodes. An auditable evidence package containing the responsible node, credibility, hop-by-hop verification results, commitment certificate, handover proof summary, and temperature time sequence is output. The method for generating window commitment vouchers is further expressed as follows: ,in This indicates that node j generates a commitment certificate for a single item n within a time window. This indicates the collected product information, where This represents the sensor samples collected within window T. Represents node metadata, A unique identifier for a single item; This represents a deterministic coding function. This represents a collision-resistant cryptographic hash. This represents the digital signature of the node's private key on the same CAN byte stream. This represents a simple byte concatenation symbol.

2. The method for full-process information traceability of an internet commodity supply chain as described in claim 1, characterized in that, The deterministic encoding steps include: arranging sensor samples, node metadata, and individual identifiers in ascending alphabetical order by field, unifying the time to UTC ISO-8601 format, retaining three decimal places for floating-point numbers and removing trailing zeros, filling missing values ​​with null, and outputting a UTF-8 JSON or CBOR byte stream.

3. The method for full-process information traceability of an internet-based commodity supply chain as described in claim 1, characterized in that, The formula for calculating the anomaly degree is: ,in This represents the anomaly degree of the h-th hop on the tracing path. To indicate hash consistency, the window commitment certificate and handover proof digest of a single item n at the two handover nodes in the h-th hop are recalculated and compared with the stored value in the system. If they are completely consistent, the value is 1; otherwise, the value is 0, indicating that the data has been tampered with or lost. Indicates the validity of the signature. It is verified by the public key in the node certificate to verify the window commitment certificate and the temporary signature of both parties in the handover proof instant evidence set of the two handover nodes at the h-th hop. The value is 1 when all are verified and the certificate has not been revoked; otherwise, the value is 0. To indicate time consistency, calculate the interval between the handover timestamp of the h-th hop and the time window of its adjacent previous hop. If the interval is less than a preset time, the value is 1; otherwise, the time consistency score is exponentially decayed by exp(). Temperature consistency is represented by the moving average of thermodynamic consistency scores over different time windows.

4. The method for full-process information traceability of an internet commodity supply chain as described in claim 3, characterized in that, The method for selecting the responsible nodes is as follows: the two handover nodes with the highest anomaly rate in a single hop are identified as suspected responsible nodes; the responsible nodes among the suspected responsible nodes are determined based on hash consistency, signature validity, time consistency, and temperature consistency.

5. The method for full-process information traceability of an internet-based commodity supply chain as described in claim 3, characterized in that, The formula for calculating the thermodynamic consistency score is as follows: ,in Indicates the thermodynamic consistency score. This represents the average relative deviation between the observed temperature and the desired temperature within the window.

6. The method for full-process information traceability of an internet-based commodity supply chain as described in claim 5, characterized in that, ,in This represents a time window for the handover node j. This represents the length of a time window for the handover node j. This indicates the half-width of the tolerance range for temperature changes. This indicates the actual measured temperature of the sensor. This represents the desired temperature in the first-order heat transfer model.

7. A full-process information traceability system for internet-based commodity supply chains, characterized in that, This system implements a method for full-process information traceability of an internet-based commodity supply chain as described in any one of claims 1-6. The system includes: The edge acquisition and commitment module is used to collect sensor samples, node metadata and individual item identifiers of individual items at each node according to time windows, perform deterministic coding and generate window commitment credentials with node signatures; The handover verification module is used to generate a handover verification summary based on the window commitment credentials of both parties and the real-time evidence set at the time of handover when nodes are handed over. The verification and location module is used to perform hash, signature, time, and temperature consistency verification on hop-by-hop proofs during traceability queries, calculate the anomaly degree of each hop, and output the responsible node and evidence package; The storage and indexing module is used to store or index window commitment credentials, handover proof summaries, and original codes, and supports offline caching, batch reporting, and third-party anchoring.

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