A product traceability method and system based on space-time codes and dynamic key derivation chain, a terminal and a storage medium

Abstract

The present application belongs to the technical field of data processing of traceability and information security of Internet of Things, and discloses a product traceability method, system, terminal and storage medium based on space-time code and dynamic key derivation chain, comprising: acquiring source space-time data of a physical entity, and generating multi-dimensional space-time continuous coding; generating a source root key based on a source enterprise digital identity and the multi-dimensional space-time continuous coding; appending a space-time state parameter in the source root key, and constructing a supply chain key derivation chain; generating a composite traceability identifier based on the derived key, and binding it with the current physical product; when the composite traceability identifier is scanned, performing traceability identifier analysis and key chain reverse backtracking verification; restoring and outputting the structured space-time data corresponding to the current physical product through reverse analysis and feature reconstruction; the present application only needs to analyze lightweight coding to trace back along the key derivation chain, and has high space-time expression accuracy, cross-platform decoding universality and tamper-proof security.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) traceability and information security data processing technology, and in particular to a product traceability method, system, terminal, and storage medium based on spatiotemporal codes and dynamic key derivation chains. Background Technology

[0002] With the deepening expansion of global supply chains, the production and distribution processes of high value-added products (such as agricultural products with geographical indications, rare earth resources, and precision components) are becoming increasingly complex. Existing product identification systems (such as one-dimensional barcodes or conventional QR codes) only have static indexing functions and essentially rely on information mapping from centralized databases. Therefore, they suffer from the following significant technical shortcomings: First, there is a lack of information in the spatiotemporal dimension: existing coding lacks an endogenous structured expression of the precise three-dimensional spatial coordinates and time span of the product's initial source, making it difficult to adapt to the accurate traceability of complex three-dimensional spaces (e.g., underground deep well mining areas, multi-layered three-dimensional factories).

[0003] Second, the data chain is at risk of breakage and tampering: traditional centralized storage is vulnerable to single-point attacks, and the data at each transfer node is isolated, making it impossible to form a continuous chain of evidence that can resist repudiation. Third, poor cross-domain interoperability: the encoding rules between heterogeneous systems are fragmented, making it impossible to achieve rapid self-parsing of source information on offline or lightweight terminals.

[0004] Therefore, existing technologies still need improvement. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a product traceability method, system, terminal and storage medium based on spatiotemporal code and dynamic key derivation chain, in order to solve the problems of information loss, low chain security and poor cross-domain interoperability of existing product traceability technologies.

[0006] The technical solution adopted by this invention to solve the technical problem is as follows: In a first aspect, the present invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including: Obtain the source spatiotemporal data of physical entities, and generate multidimensional spatiotemporal continuous codes based on the source spatiotemporal data; The source root key is generated based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding. A decentralized dynamic key derivation mechanism is used to append spatiotemporal state parameters to the source root key to construct a supply chain key derivation chain; A composite traceability identifier is generated based on the derived key in the supply chain key derivation chain, and the composite traceability identifier is bound to the current physical product; When the composite traceability identifier is scanned, traceability identifier parsing and key chain reverse backtracking verification are performed; The structured spatiotemporal data corresponding to the current physical product is restored and output through reverse analysis and feature reconstruction.

[0007] In one implementation, the step of acquiring the source spatiotemporal data of the physical entity and generating a multidimensional spatiotemporal continuous code based on the source spatiotemporal data includes: Real-time acquisition of the source spatiotemporal data of the physical entity; Based on the source spatiotemporal data, a reverse analysis is performed using a preset geographic information system spatial mapping model to obtain regional feature codes; Based on the aforementioned source spatiotemporal data, a grid dimensionality reduction coding algorithm based on spatial filling curves is used to discretize continuous longitude and latitude into grid index vectors, and a nonlinear quantization function is used to compress the elevation values. The grid indices of the three dimensions are interwoven with binary bits to generate spatial compression codes. Based on the source spatiotemporal data, a starting time anchor point is extracted and generated, and a dynamic time interval code is generated according to the starting time anchor point and the duration increment. Based on the source spatiotemporal data, the resolution level of the current spatial division is dynamically configured and recorded; The region feature encoding, the spatial compression encoding, the dynamic time interval encoding, and the resolution level are combined to obtain the multidimensional spatiotemporal continuous encoding.

[0008] In one implementation, the generation of the source root key based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding includes: Obtain the source enterprise's digital identity, trusted timestamp, and hardware anti-counterfeiting salt value to obtain the security factor of the physical entity under the current operation; The security factor and the multidimensional spatiotemporal continuous code are sequentially serialized and concatenated, and then input into a collision-resistant one-way hash algorithm or key derivation function to generate a unique source root key. The generated source root key is signed using asymmetric cryptography and then encapsulated according to the data structure of the genesis certificate to obtain the encapsulated source root key.

[0009] In one implementation, the decentralized dynamic key derivation mechanism appends spatiotemporal state parameters to the source root key to construct a supply chain key derivation chain, including: Collect the dynamic spatiotemporal and material state parameters of the current physical entity and construct the current spatiotemporal evolution vector; wherein, the current spatiotemporal evolution vector includes: the identifier of the currently processed entity, the process or morphological evolution description, the real-time timestamp, and the local spatial change coordinates; Based on the derived key from the previous step and the current spatiotemporal evolution vector, an avalanche-style key calculation model is constructed, and the derived key of the current node is calculated according to the signature confirmation mechanism of asymmetric cryptography. The supply chain key derivation chain is obtained based on the derived keys of all nodes.

[0010] In one implementation, generating a composite traceability identifier based on a derived key in the supply chain key derivation chain and binding the composite traceability identifier to the current physical product includes: Extract the attribute data of the current physical product and the associated derived key index from the supply chain key derivation chain, and generate a composite traceability identifier that includes routing header, production payload, key chain anchor and message authentication code. The composite traceability identifier is converted into the corresponding machine-readable carrier format, and the converted composite traceability identifier is bound to the current physical product.

[0011] In one implementation, the step of performing traceability identifier parsing and key chain reverse backtracking verification when the composite traceability identifier is scanned includes: When the composite traceability identifier is scanned, the message authentication code or the verification bit in the composite traceability identifier is extracted, and the structural integrity of the message authentication code or the verification bit is verified. After the verification is passed, the terminal derived key index is extracted from it. Starting from the terminal-derived key index, a backtracking query is initiated to the database or distributed ledger, and node query and signature verification are performed based on the key chain reverse traversal algorithm. Based on the results of node query and signature verification, all verified node records on the traceability path are spliced ​​together to restore the complete supply chain topology path of the current physical product from source to end, and intermediate circulation records and multi-dimensional spatiotemporal continuous codes of the source are extracted.

[0012] In one implementation, the step of restoring and outputting the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction includes: Based on the source extraction of multidimensional spatiotemporal continuous coding, resolution level, regional feature coding, spatial compression coding and dynamic time interval coding are extracted; The extracted resolution level is restored using a preset resolution mapping table to obtain the resolution level corresponding to the current code, and the extracted regional feature code is matched with the basic geographic information database to obtain the corresponding administrative division boundary attribute. The extracted spatial compressed code is reverse decoded, and the corresponding reverse space filling curve algorithm is called to perform bit separation and de-aggregation operation. Based on the three-dimensional spatial grid index value obtained by de-aggregation, inverse decoding and inverse quantization are performed to obtain the three-dimensional spatial position. The extracted dynamic time interval code is split into a starting anchor point and a continuous increment; The obtained resolution level, administrative division boundary attributes, three-dimensional spatial location, starting anchor point and continuous increment are structurally encapsulated, and the structured spatiotemporal data corresponding to the current physical product is output.

[0013] Secondly, the present invention provides a product traceability system based on spatiotemporal codes and dynamic key derivation chains, comprising: A multidimensional spatiotemporal continuous coding module is used to acquire source spatiotemporal data of physical entities and generate multidimensional spatiotemporal continuous codes based on the source spatiotemporal data. The source root key module is used to generate a source root key based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding. The supply chain key derivation module is used to append spatiotemporal state parameters to the source root key using a decentralized dynamic key derivation mechanism to construct a supply chain key derivation chain. The composite traceability identifier module is used to generate a composite traceability identifier based on the derived key in the supply chain key derivation chain, and bind the composite traceability identifier to the current physical product; The key chain reverse backtracking module is used to perform traceability identifier parsing and key chain reverse backtracking verification when the composite traceability identifier is scanned. The reverse parsing and feature reconstruction module is used to restore and output the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction.

[0014] Thirdly, the present invention provides a terminal, comprising: a processor and a memory, wherein the memory stores a product traceability program based on spatiotemporal codes and dynamic key derivation chains, and the product traceability program based on spatiotemporal codes and dynamic key derivation chains, when executed by the processor, is used to implement the operation of the product traceability method based on spatiotemporal codes and dynamic key derivation chains as described in the first aspect.

[0015] Fourthly, the present invention also provides a computer-readable storage medium storing a product traceability program based on spatiotemporal codes and dynamic key derivation chains. When executed by a processor, the product traceability program based on spatiotemporal codes and dynamic key derivation chains is used to implement the operation of the product traceability method based on spatiotemporal codes and dynamic key derivation chains as described in the first aspect.

[0016] The present invention, by employing the above technical solution, has the following effects: This invention generates a highly cohesive four-dimensional spatiotemporal code (G4D) at the source of resource supply, performing multi-level compression encoding of administrative regions, three-dimensional spatial grids, time intervals, and resolution levels. Using G4D as the root seed, an initial node key is generated. At each node in the product supply chain, current process characteristics and timestamp-triggered hash mappings are integrated to construct an irreversible dynamic key derivation chain. This invention achieves a strong binding between physical entities and spatiotemporal digital information, breaking the traditional paradigm of relying on a massive central database. Terminal devices only need to parse the lightweight code to trace back along the key derivation chain, possessing both extremely high spatiotemporal expression accuracy, cross-platform decoding universality, and tamper-proof security. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the product traceability method based on spatiotemporal codes and dynamic key derivation chains in this invention.

[0019] Figure 2 This is the overall architecture diagram of the product traceability system based on spatiotemporal codes and dynamic key derivation chains in this invention.

[0020] Figure 3 This is a flowchart of the G4D generation process in this invention.

[0021] Figure 4 This is a schematic diagram of the evolution of the directed acyclic graph key chain in this invention.

[0022] Figure 5 This is a flowchart of the source tracing reverse analysis and G4D solution process in this invention.

[0023] Figure 6 This is a complete flowchart of the process of obtaining source G4D information through key chain backtracking in this invention.

[0024] Figure 7 This is a functional schematic diagram of the terminal in one implementation of the present invention.

[0025] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0027] Exemplary methods Existing product identification systems (e.g., one-dimensional barcodes or conventional QR codes) only have static indexing capabilities. They essentially rely on information mapping from a centralized database, thus exhibiting the following significant technical shortcomings: First, there is a lack of information in the spatiotemporal dimension: existing coding lacks an endogenous structured expression of the precise three-dimensional spatial coordinates and time span of the product's initial source, making it difficult to adapt to the accurate traceability of complex three-dimensional spaces (e.g., underground deep well mining areas, multi-layered three-dimensional factories).

[0028] Second, the data chain is at risk of breakage and tampering: traditional centralized storage is vulnerable to single-point attacks, and the data at each transfer node is isolated, making it impossible to form a continuous chain of evidence that can resist repudiation. Third, poor cross-domain interoperability: the encoding rules between heterogeneous systems are fragmented, making it impossible to achieve rapid self-parsing of source information on offline or lightweight terminals.

[0029] To address the above technical issues, this invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, comprising: acquiring source spatiotemporal data of physical entities and generating multidimensional spatiotemporal continuous codes; generating source root keys based on source enterprise digital identity identifiers and multidimensional spatiotemporal continuous codes; appending spatiotemporal state parameters to the source root keys to construct a supply chain key derivation chain; generating composite traceability identifiers based on the derivation keys and binding them to the current physical product; when the composite traceability identifier is scanned, performing traceability identifier parsing and key chain reverse backtracking verification; and restoring and outputting the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction.

[0030] This invention generates a highly cohesive four-dimensional spatiotemporal code (G4D) at the source of resource supply, performing multi-level compression encoding of administrative regions, three-dimensional spatial grids, time intervals, and resolution levels. Using G4D as the root seed, an initial node key is generated. At each node in the product supply chain, current process characteristics and timestamp-triggered hash mappings are integrated to construct an irreversible dynamic key derivation chain. This invention achieves a strong binding between physical entities and spatiotemporal digital information, breaking the traditional paradigm of relying on a large central database. Terminal devices only need to parse the lightweight encoding to trace back along the key derivation chain, possessing both extremely high spatiotemporal expression accuracy, cross-platform decoding universality, and tamper-proof security.

[0031] like Figure 1As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S100: Obtain the source spatiotemporal data of the physical entity, and generate a multidimensional spatiotemporal continuous code based on the source spatiotemporal data.

[0032] In this embodiment, to implement the method, a product traceability system based on spatiotemporal codes and dynamic key derivation chains is provided, such as... Figure 2 As shown, the overall system architecture includes: a physical acquisition layer, a supply chain flow layer, and an application backtracking layer.

[0033] Based on the physical acquisition layer, supply chain flow layer, and application traceability layer, the following core stages are used to achieve end-to-end reliable traceability from the source of resources to the end consumer: Step 1: Multidimensional spatiotemporal continuous encoding G4D generation; Step 2: Generating the source root key based on digital identity and spatiotemporal information; Step 3: Constructing the supply chain key derivation chain; Step 4: Generation and coding of composite traceability identifiers; Step 5: Source identification parsing and key chain reverse backtracking verification; Step Six: Reverse analysis and feature reconstruction of multidimensional spatiotemporal continuous encoding G4D.

[0034] This embodiment takes the rare earth resource traceability of electric vehicles purchased by users as an example to specifically explain the core stage of the product traceability method based on spatiotemporal codes and dynamic key derivation chains.

[0035] In the process of generating Four-Dimensional Geospatial Data (G4D), IoT sensing devices deployed at the product source (such as mining equipment or agricultural product harvesting terminals) acquire real-time source spatiotemporal data of physical entities and trigger the generation of G4D. The G4D encoding adopts a hierarchical spatiotemporal manifold structure, which is dynamically aggregated from four dimensions of data: regional feature encoding R, three-dimensional spatial grid encoding S3, dynamic time interval encoding T, and resolution level L. Its standard structure is: G4D = [R][S3]-[T]-[L].

[0036] Specifically, in one implementation of this embodiment, step S100 includes the following steps: Step S101: Real-time acquisition of the source spatiotemporal data of the physical entity; Step S102: Based on the source spatiotemporal data, reverse analysis is performed using a preset geographic information system spatial mapping model to obtain regional feature codes.

[0037] In this embodiment, as Figure 3 As shown, the specific encoding generation rules and algorithms of G4D are as follows: (1) Generation of region feature encoding R: The data acquisition terminal sends its current location's global positioning data (such as BeiDou / GPS latitude and longitude) to the edge gateway. The gateway uses a pre-built Geographic Information System (GIS) spatial mapping model to reverse-parse the corresponding country, province, and prefecture-level administrative division, and generates the corresponding hierarchical regional code (e.g., the regional feature code for a certain city is CN3707). This prefix is ​​used to achieve fast routing and retrieval of top-level data in the global traceability network.

[0038] Specifically, in one implementation of this embodiment, step S100 further includes the following steps: Step S103: Based on the source spatiotemporal data, the continuous longitude and latitude are discretized into grid index vectors using a grid dimensionality reduction coding algorithm based on space filling curves, and the elevation values ​​are compressed using a nonlinear quantization function. The grid indices of the three dimensions are interwoven with binary bits to generate spatial compression codes.

[0039] In this embodiment, after the region feature code R is generated, the following steps are performed: (2) Generation of 3D spatial mesh encoding S3: To achieve efficient identification of complex three-dimensional spaces (including surface and underground / high-altitude work areas), this embodiment abandons the traditional discrete coordinate recording method and proposes a grid dimensionality reduction encoding algorithm based on space-filling curves. Its spatial structure is expressed as follows: .

[0040] Horizontal latitude and longitude gridding: Let the grid side length corresponding to the current resolution level be... The system will continuously measure longitude. and latitude Discretize into grid index vector The calculation formula is as follows: .

[0041] Absolute Elevation Nonlinear Quantization (GZ): For underground mining areas or multi-story factory buildings, this method obtains absolute elevation values ​​based on a unified elevation datum (such as the national elevation datum). To reduce the code length, a non-linear quantization function is used. The elevation values ​​are compressed and converted to Base32 encoding. .

[0042] 3D spatial dimensionality reduction and fusion: acquisition Then, using Z-order curves (a type of space-filling curve that maps points in multidimensional space to a one-dimensional linear order) or Hilbert curves (a type of continuous fractal space-filling curve), the three-dimensional grid indices are interwoven with binary bits, reducing the dimensionality of the three-dimensional spatial coordinates to a one-dimensional string sequence. The final output is Base32 encoded S3 data (example: 8F2A91C33K). This algorithm significantly compresses the encoding volume while ensuring that spatial proximity features are not lost, greatly improving the storage efficiency of chips or QR codes.

[0043] Specifically, in one implementation of this embodiment, step S100 further includes the following steps: Step S104: Based on the source spatiotemporal data, extract and generate a starting time anchor point, and generate a dynamic time interval code according to the starting time anchor point and the duration increment.

[0044] In this embodiment, after the three-dimensional spatial mesh encoding S3 is generated, the following steps are performed: (3) Generation of dynamic time interval encoding T: The production process at its source is not instantaneous but continuous. This embodiment uses a model of "start and end anchor points + continuous increments" to represent the time dimension, defining the dynamic time interval encoding as... .

[0045] Start Time Anchor (TS): Extract the standard Unix timestamp of the start time of the production job and compress it into a compact string using the Base36 algorithm (e.g., timestamp 1750224000 compressed into 19C8).

[0046] Duration Increment D: Records the duration of resource extraction or processing for this batch (e.g., 6 months as 6M, 12 hours as 12H). Finally, this is concatenated into a dynamic time interval code. (Example: 19C8-6M).

[0047] In this embodiment, the start time anchor point TS is concatenated with the duration increment D to obtain the dynamic time interval code. (Example: 19C8-6M).

[0048] Specifically, in one implementation of this embodiment, step S100 further includes the following steps: Step S105: Based on the source spatiotemporal data, dynamically configure and record the resolution level of the current spatial division; Step S106: The region feature encoding, the spatial compression encoding, the dynamic time interval encoding, and the resolution level are synthesized to obtain the multidimensional spatiotemporal continuous encoding.

[0049] In this embodiment, after the dynamic time interval code T is generated, the following steps are performed: (4) Resolution level L label: To accommodate the traceability needs of products with different value densities, the system dynamically configures and records the resolution level of the current spatial division. Preferably, multiple levels of spatial resolution are set: when The grid size is 10 km. The time is 1 km. The time is 100 m. The time is 10 m. The time is 1 m.

[0050] (5) G4D bus encoding synthesis: The system generates a source-tracing seed code from the data across the four dimensions mentioned above, possessing physical coordinate attributes, time period attributes, and machine-readable characteristics. For example, the generated complete G4D code is: CN3607-8F2A91C33K-19C8-6M-3. This code will then serve as the random source for the cryptographic system, inputting it into the next stage of key chain generation.

[0051] This embodiment abandons the existing approach of relying solely on a central database to generate meaningless serial numbers or simply recording planar latitude and longitude, and proposes a highly cohesive spatiotemporal manifold data structure. It uses a spatial filling curve algorithm (such as a Z-order curve or Hilbert curve) to reduce the dimensionality of three-dimensional spatial coordinates through cross-weaving, and performs nonlinear quantization compression on absolute elevations, ultimately dynamically aggregating them with time intervals, administrative regions, and accuracy levels. By employing the multidimensional spatiotemporal continuous coding G4D technology that integrates spatial dimensionality reduction and nonlinear quantization, it achieves centimeter-level structured representation of complex three-dimensional physical spaces (including underground / high-altitude) within a limited character length; significantly improving the storage efficiency of chips or QR codes; and endowing terminals with the ability to self-parse source spatiotemporal data in offline or weak network environments.

[0052] like Figure 1 As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S200: Generate a source root key based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding.

[0053] In this embodiment, after obtaining the source G4D code of the physical entity, to ensure that the starting point of the product's digital lifecycle is immutable and the entity's responsibility is traceable, the system performs root key generation and on-chain / database operations at the source of the supply chain for the "genesis node," that is, it performs the step of generating the source root key based on digital identity and spatiotemporal information. This step breaks away from the traditional recording method that relies solely on plaintext data, and cryptographically binds the source enterprise's digital identity, spatiotemporal code, and the hardware characteristics of the physical device.

[0054] Specifically, in one implementation of this embodiment, step S200 includes the following steps: Step S201: Obtain the source enterprise's digital identity identifier, trusted timestamp, and hardware anti-counterfeiting salt value to obtain the security factor of the physical entity under the current operation.

[0055] In this embodiment, the specific method for generating the source root key based on digital identity and spatiotemporal information is as follows: (1) Construction of multi-source security context vectors: While acquiring G4D data, the source IoT edge gateway simultaneously collects contextual security factors for the current operation, constructing an input vector set. These security factors include at least: Resource Ownership Entity Identifier The unique decentralized digital identity (DID) or public key certificate registered by the source enterprise (such as mining company A or farm owner) in the traceability system.

[0056] Trusted timestamps Absolute timestamps provided by national time service centers or blockchain oracles are used to prevent replay attacks on historical data.

[0057] Hardware anti-counterfeiting salt value Extract the Physical Unclonable Feature (PUF) response value or encrypted device MAC address from the source information input device (such as an industrial IoT gateway or barcode scanner) and use it as a hardware-level random salt value.

[0058] Specifically, in one implementation of this embodiment, step S200 further includes the following steps: Step S202: The security factor and the multidimensional spatiotemporal continuous code are sequentially serialized and concatenated, and then input into a collision-resistant one-way hash algorithm or key derivation function to generate a unique source root key; Step S203: Perform asymmetric cryptographic signature on the generated source root key and encapsulate it according to the data structure of the genesis certificate to obtain the encapsulated source root key.

[0059] In this embodiment, after constructing the multi-source security context vector, the following steps are performed: (2) Source root key Derived from: The aforementioned security factors and the four-dimensional spatiotemporal code G4D generated in step one are sequentially serialized and concatenated, and then input into a collision-resistant one-way hash algorithm (preferably the national cryptographic SM3 algorithm or the SHA-256 high-security hash algorithm) or a key derivation function (KDF) to calculate and generate a unique source root key: ; in, . Represents a hash function; Should It not only includes the absolute spatiotemporal origin of the product, G4D, but also internalizes the producer's identity and physical operating environment, serving as the "genesis seed" for all key derivation chains in the subsequent supply chain traceability network.

[0060] (3) Non-repudiation signature and registration of genesis certificate: To meet the non-repudiation requirements for legal tracing, the source enterprise's client accesses the private key stored in its local secure element (SE) or encryption machine. For the generated source root key Perform asymmetric cryptographic signatures (such as using the Chinese national cryptographic standard SM2 or ECDSA algorithm): .

[0061] Subsequently, the system packages the source root key and its associated plaintext traceability information into a "Genesis Record Credential" and synchronizes it to a distributed ledger or a highly available centralized database. The data structure of this Genesis Record Credential is encapsulated as follows: Unique index of a node: ; Owner: Company A (including its public key and digital signature) (used for identity verification) Multidimensional Spatiotemporal Coding G4D: CN3607-8F2A91C33K-19C8-6M-3; Trusted entry time: 2025-06-15 10:23:45 (UTC+8); At this point, the origin point for tracing, characterized by strong identity authentication and extremely high spatiotemporal recognizability, has been established. Any attempt to deviate from this source enterprise's private key and forge the source root key will be thwarted. Actions that attempt to tamper with G4D information or otherwise fail to pass the system's signature verification and hash comparison will not be accepted.

[0062] like Figure 1As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S300: A decentralized dynamic key derivation mechanism is used to append spatiotemporal state parameters to the source root key to construct a supply chain key derivation chain.

[0063] In this embodiment, after the source root key is generated, a supply chain key derivation chain is constructed. Specifically, during the product's journey through procurement, logistics, and multi-level processing, this system employs a decentralized dynamic key derivation mechanism, continuously adding spatiotemporal state parameters as the physical form evolves and geographical location changes. This process not only forms a linear tracking chain but also adaptively solves the topological backtracking problem of "one-to-many (material distribution)" and "many-to-one (component assembly)" in complex supply chains.

[0064] Specifically, in one implementation of this embodiment, step S300 includes the following steps: Step S301: Collect the dynamic spatiotemporal and material state parameters of the current physical entity and construct the current spatiotemporal evolution vector; wherein, the current spatiotemporal evolution vector includes: the current processing entity identifier, process or morphological evolution description, real-time timestamp, and local spatial change coordinates.

[0065] In this embodiment, as Figure 4 As shown, the specific method for constructing the supply chain key derivation chain is as follows: (1) Extraction of dynamic spatiotemporal evolution vector (State Vector): In the At each level of the supply chain flow node (i.e., the current processor or receiver), the system gateway not only records processing behavior but also forcibly collects the dynamic spatiotemporal and material status parameters of the current entity to construct a spatiotemporal evolution vector. The vector contains: Current entity identifier : The public key certificate identifier of the currently participating enterprise (such as the DID of enterprise B or enterprise C).

[0066] Description of process or form evolution This field describes the type of physical processing (e.g., purification, forging, assembly) or material transfer action. For processes involving changes in material form, this field embeds the form feature code of the current batch of materials.

[0067] Real-time handover / processing timestamp : The absolute time record of the node operation.

[0068] Local spatial transformation coordinates Real-time geographic location data of the current processing plant or warehousing logistics node (such as latitude and longitude parsed through the gateway or new local G4D encoding) is used to depict the geographical transfer trajectory of the product on a macro scale.

[0069] Specifically, in one implementation of this embodiment, step S300 further includes the following steps: Step S302: Construct an avalanche key calculation model based on the derived key from the previous step and the current spatiotemporal evolution vector, and calculate the derived key of the current node according to the signature confirmation mechanism of asymmetric cryptography. Step S303: Obtain the supply chain key derivation chain based on the derived keys of all nodes.

[0070] In this embodiment, after the dynamic spatiotemporal evolution vector is extracted, the following steps are performed: (2) Topology-adaptive derived key computation and “digital handshake”: To achieve immutable inheritance of supply chain relationships, this embodiment designs a system based on the previous node. Derived key With the current spatiotemporal evolution vector A combined avalanche key computation model is used. Simultaneously, to clarify the boundaries of upstream and downstream responsibility, asymmetric cryptography's signature verification mechanism (i.e., the "digital handshake") is introduced.

[0071] Current node Derived key The calculation formula is: ; in, A safe hash function; This indicates that the current entity is using its own private key. For the received previous node Derived key Perform digital signatures to confirm receipt and state inheritance.

[0072] in, The choice depends on the supply chain topology: Linear flow / one-to-many distribution (e.g., bulk mineral unpacking and distribution): directly using the key passed from the previous level. As input.

[0073] Many-to-one convergence assembly (e.g., motor assembly): When multiple sub-components (e.g., magnets) carry independent traceability keys... coil When assembling the entire system, the Directed Acyclic Graph (DAG) fusion algorithm is first used to link all the child node keys of the previous level in sequence and hash them to generate a new root node digest. Then, the key is substituted into the above formula to generate a unified cascade key for the assembled product. This mechanism ensures that complex assembled products can be traced back to the independent source of all sub-parts indefinitely.

[0074] (3) Example of supply chain circulation scenario: Through the above mechanism, a directed key chain network with a strong topological structure is formed: .

[0075] 1) First-level circulation (material procurement and refining): Refining company B (e.g., a factory in Guangdong) purchases raw ore from mining area A. The gateway captures company B's identity, refining process, current time, and spatial coordinates in Guangdong. .

[0076] Generate the derived key for the first level of circulation: .

[0077] The system records the derived credentials of this node, and Derived key anchored to parent node .

[0078] 2) Second-level circulation (deep processing and manufacturing): Magnetic material company C (e.g., a factory in Zhejiang) purchases neodymium oxide from company B to manufacture magnets. The gateway also captures C's spatiotemporal state vector (including the spatial coordinates of Zhejiang). ).

[0079] Generate the derived key for the second-level circulation: .

[0080] At this point, the magnet packaging is assigned an embedded index, key_id = K2_C.

[0081] 3) Third-level flow (terminal component assembly): Motor manufacturer D purchases magnets from supplier C and may also source coils from other suppliers. During the assembly process, a terminal-derived key for the finished product is generated. This key not only inherits the processing state of C, but also locks down multiple parallel supply chain paths through DAG fusion.

[0082] As another example, such as Figure 2 As shown, for parallel machining methods, local spatial coordinates are injected at the first-level machining nodes. Obtain the corresponding derived key 1. Injecting local spatial coordinates into parallel assembly nodes. x, obtain the corresponding derived key x, after performing a many-to-one assembly, injects the assembly process to generate a terminal key. 3. Forming a chain-like derived structure of parallel assembly.

[0083] The aforementioned chain-derived structure ensures that any information tampering or bypass forgery in the supply chain (such as attempting to replace the supply from Company C with counterfeit magnets) will break the continuity of the hash chain, causing all subsequent derived keys to become invalid, thus achieving full-chain anti-counterfeiting and solidification without relying on a central trust institution.

[0084] This embodiment upgrades a simple, linear hash chain into a dynamic evolutionary derivation model that combines a directed acyclic graph (DAG) with asymmetric signatures. In the key derivation formula, the "local spatial transition coordinates" and "processing form" of the current node are forcibly injected, and a DAG convergence algorithm is introduced in the many-to-one assembly process; at the same time, upstream and downstream handover is subject to a "digital handshake" based on private key signatures.

[0085] The DAG key derivation network and digital handshake authorization mechanism that drive the evolution of physical states in this embodiment are perfectly adapted to the real material topology networks of "one-to-many (distribution)" and "many-to-one (assembly)" in complex industrial manufacturing; the addition of "local spatial coordinates" enables the traceability chain to truly have spatial trajectory continuity; the "digital handshake" mechanism completely eliminates the risk of forgery injected by the supply chain bypass, and realizes the non-repudiation of the responsibilities of each node.

[0086] like Figure 1 As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S400: Generate a composite traceability identifier based on the derived key in the supply chain key derivation chain, and bind the composite traceability identifier to the current physical product.

[0087] In this embodiment, after constructing the supply chain key derivation chain, a composite traceability identifier is generated. Specifically, after completing the processing or assembly of the current circulation node and generating the corresponding hierarchical derivation key (such as the terminal derivation key), the system generates a composite traceability identifier (PCODE) based on the derivation key and binds the identifier to the physical product.

[0088] Specifically, in one implementation of this embodiment, step S400 includes the following steps: Step S401: Extract the attribute data of the current physical product and the associated derived key index from the supply chain key derivation chain, and generate a composite traceability identifier that includes the routing header, production payload, key chain anchor and message authentication code. Step S402: Convert the composite traceability identifier into the corresponding machine-readable carrier format, and bind the converted composite traceability identifier to the current physical product.

[0089] In this embodiment, the specific process of generating a composite traceability identifier based on the derived key is as follows: (1) Construct a composite traceability identifier data structure: Extract product attribute data and associated derived key indexes The data structure of PCODE consists of: a routing header, a production payload, a key chain anchor, and a message authentication code (MAC).

[0090] Route header: contains industry code, company identifier, and product category; Production load: includes production batch number and individual item serial number; Keychain anchor: Write the generated derived key index ; Message authentication code: generated by the current node entity using its private key (or a preset hash algorithm) to calculate the above fields, used to verify the data integrity of the encoded structure.

[0091] (2) Identifier carrier mapping: The system converts the PCODE string into the corresponding machine-readable carrier format. Depending on the product form, the machine-readable carrier includes, but is not limited to, the storage sequence of optical QR codes, data matrices, or radio frequency identification (RFID / NFC) tags.

[0092] (3) Physical bonding and anti-transfer packaging: The machine-readable carrier carrying the PCODE is attached to the surface of a physical product or its packaging. Preferably, this attachment process employs a transfer-resistant encapsulation structure (such as a fragile paper substrate or a disposable RFID inlay). When the machine-readable carrier is physically peeled off, its internal microstructure or antenna suffers irreversible damage, preventing the reading device from fully extracting the derived key index. This ensures a unique correspondence between the traceability identifier and the physical entity.

[0093] In this embodiment, during the source creation stage, hardware anti-counterfeiting salt values ​​(such as PUF / MAC), decentralized identity (DID), and G4D are forcibly bound to generate the source root key. During the terminal coding stage, a message authentication code (MAC) is introduced and combined with an anti-transfer encapsulation physical carrier to generate a composite traceability identifier. Through strong anchoring anti-counterfeiting and composite identifier (PCODE) technology that crosses the physical and digital boundaries, the fatal shortcoming of traditional traceability—"anti-tampering but not anti-transfer"—is overcome. This completely eliminates the vulnerabilities of source data replay attacks and terminal "genuine code on counterfeit goods," achieving a unique, mandatory, and irreversible anchoring between the physical entity and the digital spatiotemporal key chain.

[0094] like Figure 1 As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S500: When the composite traceability identifier is scanned, traceability identifier parsing and key chain reverse backtracking verification are performed.

[0095] In this embodiment, after generating the composite traceability identifier, traceability identifier parsing and key chain reverse backtracking verification are performed; specifically, when the reading device (such as the end user's smartphone or enterprise-level barcode scanner) obtains the traceability identifier on the product, the system executes a reverse backtracking and verification procedure from the terminal link to the source link.

[0096] Specifically, in one implementation of this embodiment, step S500 includes the following steps: Step S501: When the composite traceability identifier is scanned, the message authentication code or verification bit in the composite traceability identifier is extracted, and the structural integrity of the message authentication code or verification bit is verified. After the verification is passed, the terminal derived key index is extracted from it. Step S502: Using the terminal derived key index as the starting point for retrieval, initiate a backtracking query to the database or distributed ledger, and perform node query and signature verification based on the key chain reverse traversal algorithm. Step S503: Based on the results of node query and verification, all verified node records on the traceability path are spliced ​​together to restore the complete supply chain topology path of the current physical product from source to end, and intermediate circulation records and multi-dimensional spatiotemporal continuous codes of the source are extracted.

[0097] In this embodiment, as Figure 5 As shown, the specific methods for reverse backtracking and verification from the terminal stage to the source stage are as follows: (1) Identifier reading and local verification: The terminal reads the machine-readable carrier and obtains the Composite Origin Derivative (PCODE). The system first extracts the Message Authentication Code (MAC) or checksum from the PCODE for structural integrity calculation to confirm that the encoding has not been tampered with. After successful verification, the terminal's derived key index is extracted from it. ).

[0098] (2) Directed key chain graph traversal and signature verification: Extracted Starting from the retrieval point, the system initiates a backtracking query to the database or distributed ledger, executing a key chain reverse traversal algorithm. The backtracking logic is as follows: Node query and signature verification: Retrieves the data record associated with the current key node, and the system calls the public key of the corresponding entity to digitally sign it. Perform cryptographic verification to ensure that the node data was submitted by a legitimate entity and has not been forged.

[0099] Branch traversal: Get the index of the parent key of the current node record ( If the current node belongs to a many-to-one aggregation assembly process (i.e., there are multiple parent node key aggregations), the traversal algorithm will derive multiple concurrent query branches, which will backtrack upstream along the paths of each sub-component.

[0100] Recursion Termination: Repeat the above query and signature verification operations, tracing the source step by step along the directed acyclic graph (DAG) until a non-existent node is reached. Extract the corresponding source root key from the genealogy root node (i.e., the origin). .

[0101] (3) Spatiotemporal link reconstruction and data extraction: Based on the above traversal process, the system splices together all verified node records on the traceability path to reconstruct the complete supply chain topology path of the product from the source to the end.

[0102] The system extracts and outputs: Intermediate flow records: Entity ID, processing procedure, handover timestamp, and local spatial change coordinates (Loc) for each level of node; Source Spatiotemporal Anchor Point: Extraction of the Source Root Key The strongly bound source four-dimensional spatiotemporal code G4D serves as the final spatiotemporal tracing reference data.

[0103] like Figure 1 As shown, this embodiment of the invention provides a product traceability method based on spatiotemporal codes and dynamic key derivation chains, including the following steps: Step S600: Restore and output the structured spatiotemporal data corresponding to the current physical product through reverse analysis and feature reconstruction.

[0104] In this embodiment, after source identification parsing and key chain reverse backtracking verification, reverse parsing and feature reconstruction of multidimensional spatiotemporal continuous coding G4D are performed; specifically, after extracting the multidimensional spatiotemporal continuous coding G4D associated with the root node, the system executes the reverse parsing algorithm to restore the compressed coding payload into machine-readable structured geographic and temporal state data.

[0105] Specifically, in one implementation of this embodiment, step S600 includes the following steps: Step S601: Based on the multidimensional spatiotemporal continuous coding extracted from the source, extract the resolution level, regional feature coding, spatial compression coding, and dynamic time interval coding. Step S602: Use a preset resolution mapping table to restore the extracted resolution level to obtain the resolution level corresponding to the current code, and match the extracted regional feature code with the basic geographic information database to obtain the corresponding administrative division boundary attribute. Step S603: Reverse decode the extracted spatial compression code, and call the corresponding reverse space filling curve algorithm to perform bit separation and de-aggregation operation. Based on the three-dimensional spatial grid index value obtained by de-aggregation, perform inverse decoding and inverse quantization to obtain the three-dimensional spatial position. Step S604: The extracted dynamic time interval code is split into a starting anchor point and a continuous increment; Step S605: The restored resolution level, administrative division boundary attributes, three-dimensional spatial location, starting anchor point and continuous increment are structurally encapsulated, and the structured spatiotemporal data corresponding to the current physical product is output.

[0106] In this embodiment, for the encoding structure G4D = [R][S3]-[T]-[L], the specific parsing and reconstruction steps are as follows: (1) Resolution level and region boundary restoration: The system first extracts the resolution level at the tail. Query the system's preset resolution mapping table to obtain the basic grid side length corresponding to the current encoding. ,like correspond ; Subsequently, the region feature encoding of the head is extracted. The data is input into the basic geographic information database and matched with the corresponding macro-administrative division boundary attributes (e.g., CN3607 is mapped to City A), which are then used as the macro-verification boundary for subsequent coordinate calculations.

[0107] (2) Three-dimensional spatial grid encoding S3 de-aggregation: Extract the three-dimensional spatial grid code S3, perform Base32 reverse decoding on it, and restore it to a one-dimensional binary bit string sequence.

[0108] For this sequence, the system calls the corresponding inverse space-filling curve algorithm (such as Inverse Z-order or Inverse Hilbert mapping) to perform bit-separation and de-aggregation operations on the bit string, restoring it to independent three-dimensional spatial grid index values. , With elevation quantification value .

[0109] Based on the index value obtained from de-aggregation and the grid side length The system reconstructs the three-dimensional coordinate range of the physical space: Inverse latitude and longitude solution: Calculate the coordinates of the center point of the target spatial grid. The calculation formula is: ; ; Elevation inverse quantization: converting elevation values ​​into quantized values. Substitute into the inverse nonlinear quantization function To restore the absolute elevation value of the target under a unified elevation datum. .

[0110] (3) Dynamic time interval mapping: The system extracts dynamic time interval codes based on delimiters. Split into starting anchor points With continuous increment .

[0111] Will The Base36 decoding algorithm is used to restore the data to a standard Unix timestamp integer, which is then converted into a structured date and time format for the system's default time zone to establish the start time limit.

[0112] Analysis The units and values ​​in the time (e.g., 6M maps to 6 months) are added to the starting time to calculate the closed-loop time interval for tracing the source of the problem.

[0113] (4) Structured spatiotemporal data aggregation and output: After completing the inverse calculations of the above dimensions, the system will encapsulate the reconstructed discrete data in a structured manner, generating a set of records containing complete spatiotemporal traceability features. The structure definition of this output object includes at least: Macro-level location: Administrative division text description; Microscopic space: Coordinates of the center point of the physical grid Its 3D bounding box parameters, and positioning accuracy is indicated as follows: .

[0114] Time status: Absolute start time and operation cycle.

[0115] Ultimately, the system renders this structured information onto the end-user's query interface or outputs it to a third-party regulatory platform via API.

[0116] like Figure 6 As shown, in a practical application scenario, the complete process of obtaining source G4D information through key chain backtracking is as follows: S11, user scans QR code; S12, read the key_id from the product code; S13, query the key chain database to obtain the current node information; S14, determine if a parent key exists; if yes, proceed to S5; if no, proceed to S6. S15, jump to the parent key node to continue the query, return to execute S13; S16, Reach the source root key to obtain the associated G4D encoding; S17, analyzing G4D to reconstruct the complete supply chain path; S18 displays traceability information (company, time, location, G4D).

[0117] In summary, the above-described scheme in this embodiment only requires parsing the lightweight code to trace back along the key derivation chain, and has extremely high spatiotemporal expression accuracy, cross-platform decoding universality, and tamper-proof security.

[0118] This embodiment achieves the following technical effects through the above technical solution: This embodiment generates a highly cohesive four-dimensional spatiotemporal code (G4D) at the source of resource supply, performing multi-level compression encoding of administrative regions, three-dimensional spatial grids, time intervals, and resolution levels. Using G4D as the root seed, an initial node key is generated. At each node in the product supply chain, current process characteristics and timestamp-triggered hash mappings are integrated to construct an irreversible dynamic key derivation chain. This embodiment achieves a strong binding between physical entities and spatiotemporal digital information, breaking the traditional paradigm of relying on a massive central database. Terminal devices only need to parse the lightweight code to trace back along the key derivation chain, possessing both extremely high spatiotemporal expression accuracy, cross-platform decoding universality, and tamper-proof security.

[0119] Exemplary device Based on the above embodiments, the present invention also provides a product traceability system based on spatiotemporal codes and dynamic key derivation chains, comprising: A multidimensional spatiotemporal continuous coding module is used to acquire source spatiotemporal data of physical entities and generate multidimensional spatiotemporal continuous codes based on the source spatiotemporal data. The source root key module is used to generate a source root key based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding. The supply chain key derivation module is used to append spatiotemporal state parameters to the source root key using a decentralized dynamic key derivation mechanism to construct a supply chain key derivation chain. The composite traceability identifier module is used to generate a composite traceability identifier based on the derived key in the supply chain key derivation chain, and bind the composite traceability identifier to the current physical product; The key chain reverse backtracking module is used to perform traceability identifier parsing and key chain reverse backtracking verification when the composite traceability identifier is scanned. The reverse parsing and feature reconstruction module is used to restore and output the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction.

[0120] Based on the above embodiments, the present invention also provides a terminal, the principle block diagram of which can be as follows: Figure 7 As shown.

[0121] The terminal includes: a processor, a memory, an interface, a display screen, and a communication module connected via a system bus; wherein, the processor of the terminal provides computing and control capabilities; the memory of the terminal includes a computer-readable storage medium and internal memory; the computer-readable storage medium stores an operating system and computer programs; the internal memory provides an environment for the operation of the operating system and computer programs in the computer-readable storage medium; the interface is used to connect to external devices; the display screen is used to display relevant information; and the communication module is used to communicate with a cloud server or other devices.

[0122] When executed by a processor, this computer program is used to implement a product traceability method based on spatiotemporal codes and dynamic key derivation chains.

[0123] It will be understood by those skilled in the art that Figure 7 The schematic diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the terminal to which the present invention is applied. A specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0124] In one embodiment, a terminal is provided, comprising: a processor and a memory, the memory storing a product traceability program based on spatiotemporal codes and dynamic key derivation chains, the product traceability program based on spatiotemporal codes and dynamic key derivation chains being executed by the processor to implement the above-described product traceability method based on spatiotemporal codes and dynamic key derivation chains.

[0125] In one embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a product traceability program based on spatiotemporal codes and dynamic key derivation chains, which, when executed by a processor, is used to implement the above-described product traceability method based on spatiotemporal codes and dynamic key derivation chains.

[0126] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, database, or other media used in the embodiments provided by this invention can include both non-volatile and volatile memory.

[0127] In summary, this invention provides a product traceability method, system, terminal, and storage medium based on spatiotemporal codes and dynamic key derivation chains, including: acquiring source spatiotemporal data of physical entities and generating multidimensional spatiotemporal continuous codes; generating source root keys based on source enterprise digital identity identifiers and multidimensional spatiotemporal continuous codes; appending spatiotemporal state parameters to the source root keys to construct a supply chain key derivation chain; generating composite traceability identifiers based on the derivation keys and binding them to the current physical product; when the composite traceability identifier is scanned, performing traceability identifier parsing and key chain reverse backtracking verification; restoring and outputting the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction; this invention only needs to parse lightweight codes to trace back along the key derivation chain, possessing both extremely high spatiotemporal expression accuracy, cross-platform decoding universality, and tamper-proof security.

[0128] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A product traceability method based on spatiotemporal codes and dynamic key derivation chains, characterized in that, include: Obtain the source spatiotemporal data of physical entities, and generate multidimensional spatiotemporal continuous codes based on the source spatiotemporal data; The process of generating a source root key based on the source enterprise's digital identity and the multidimensional spatiotemporal continuous encoding of the physical entity includes: obtaining the source enterprise's digital identity, a trusted timestamp, and a hardware anti-counterfeiting salt value to obtain the security factor of the physical entity under the current operation; sequentially concatenating the security factor and the multidimensional spatiotemporal continuous encoding in sequence, and inputting them into a collision-resistant one-way hash algorithm or key derivation function to generate a unique source root key; performing asymmetric cryptographic signature on the generated source root key, and encapsulating it according to the data structure of the genesis certificate to obtain the encapsulated source root key. A decentralized dynamic key derivation mechanism is used to append spatiotemporal state parameters to the source root key to construct a supply chain key derivation chain; A composite traceability identifier is generated based on the derived key in the supply chain key derivation chain, and the composite traceability identifier is bound to the current physical product; When the composite traceability identifier is scanned, traceability identifier parsing and key chain reverse backtracking verification are performed; The structured spatiotemporal data corresponding to the current physical product is restored and output through reverse analysis and feature reconstruction.

2. The product traceability method based on spatiotemporal codes and dynamic key derivation chains according to claim 1, characterized in that, The step of acquiring the source spatiotemporal data of physical entities and generating multidimensional spatiotemporal continuous codes based on the source spatiotemporal data includes: Real-time acquisition of the source spatiotemporal data of the physical entity; Based on the source spatiotemporal data, a reverse analysis is performed using a preset geographic information system spatial mapping model to obtain regional feature codes; Based on the aforementioned source spatiotemporal data, a grid dimensionality reduction coding algorithm based on spatial filling curves is used to discretize continuous longitude and latitude into grid index vectors, and a nonlinear quantization function is used to compress the elevation values. The grid indices of the three dimensions are interwoven with binary bits to generate spatial compression codes. Based on the source spatiotemporal data, a starting time anchor point is extracted and generated, and a dynamic time interval code is generated according to the starting time anchor point and the duration increment. Based on the source spatiotemporal data, the resolution level of the current spatial division is dynamically configured and recorded; The region feature encoding, the spatial compression encoding, the dynamic time interval encoding, and the resolution level are combined to obtain the multidimensional spatiotemporal continuous encoding.

3. The product traceability method based on spatiotemporal codes and dynamic key derivation chains according to claim 1, characterized in that, The decentralized dynamic key derivation mechanism appends spatiotemporal state parameters to the source root key to construct a supply chain key derivation chain, including: Collect the dynamic spatiotemporal and material state parameters of the current physical entity and construct the current spatiotemporal evolution vector; wherein, the current spatiotemporal evolution vector includes: the identifier of the currently processed entity, the process or morphological evolution description, the real-time timestamp, and the local spatial change coordinates; Based on the derived key from the previous step and the current spatiotemporal evolution vector, an avalanche-style key calculation model is constructed, and the derived key of the current node is calculated according to the signature confirmation mechanism of asymmetric cryptography. The supply chain key derivation chain is obtained based on the derived keys of all nodes.

4. The product traceability method based on spatiotemporal codes and dynamic key derivation chains according to claim 1, characterized in that, The step of generating a composite traceability identifier based on the derived key in the supply chain key derivation chain and binding the composite traceability identifier to the current physical product includes: Extract the attribute data of the current physical product and the associated derived key index from the supply chain key derivation chain, and generate a composite traceability identifier that includes routing header, production payload, key chain anchor and message authentication code. The composite traceability identifier is converted into the corresponding machine-readable carrier format, and the converted composite traceability identifier is bound to the current physical product.

5. The product traceability method based on spatiotemporal codes and dynamic key derivation chains according to claim 1, characterized in that, When the composite traceability identifier is scanned, the process of parsing the traceability identifier and performing reverse key chain backtracking verification includes: When the composite traceability identifier is scanned, the message authentication code or the verification bit in the composite traceability identifier is extracted, and the structural integrity of the message authentication code or the verification bit is verified. After the verification is passed, the terminal derived key index is extracted from it. Starting from the terminal-derived key index, a backtracking query is initiated to the database or distributed ledger, and node query and signature verification are performed based on the key chain reverse traversal algorithm. Based on the results of node query and signature verification, all verified node records on the traceability path are spliced ​​together to restore the complete supply chain topology path of the current physical product from source to end, and intermediate circulation records and multi-dimensional spatiotemporal continuous codes of the source are extracted.

6. The product traceability method based on spatiotemporal codes and dynamic key derivation chains according to claim 1, characterized in that, The process of restoring and outputting the structured spatiotemporal data corresponding to the current physical product through reverse analysis and feature reconstruction includes: Based on the source extraction of multidimensional spatiotemporal continuous coding, resolution level, regional feature coding, spatial compression coding and dynamic time interval coding are extracted; The extracted resolution level is restored using a preset resolution mapping table to obtain the resolution level corresponding to the current code, and the extracted regional feature code is matched with the basic geographic information database to obtain the corresponding administrative division boundary attribute. The extracted spatial compressed code is reverse decoded, and the corresponding reverse space filling curve algorithm is called to perform bit separation and de-aggregation operation. Based on the three-dimensional spatial grid index value obtained by de-aggregation, inverse decoding and inverse quantization are performed to obtain the three-dimensional spatial position. The extracted dynamic time interval code is split into a starting anchor point and a continuous increment; The obtained resolution level, administrative division boundary attributes, three-dimensional spatial location, starting anchor point and continuous increment are structurally encapsulated, and the structured spatiotemporal data corresponding to the current physical product is output.

7. A product traceability system based on spatiotemporal codes and dynamic key derivation chains, used to implement the product traceability method based on spatiotemporal codes and dynamic key derivation chains as described in any one of claims 1-6, characterized in that, include: A multidimensional spatiotemporal continuous coding module is used to acquire source spatiotemporal data of physical entities and generate multidimensional spatiotemporal continuous codes based on the source spatiotemporal data. The source root key module is used to generate a source root key based on the source enterprise digital identity of the physical entity and the multidimensional spatiotemporal continuous encoding. The supply chain key derivation module is used to append spatiotemporal state parameters to the source root key using a decentralized dynamic key derivation mechanism to construct a supply chain key derivation chain. The composite traceability identifier module is used to generate a composite traceability identifier based on the derived key in the supply chain key derivation chain, and bind the composite traceability identifier to the current physical product; The key chain reverse backtracking module is used to perform traceability identifier parsing and key chain reverse backtracking verification when the composite traceability identifier is scanned. The reverse parsing and feature reconstruction module is used to restore and output the structured spatiotemporal data corresponding to the current physical product through reverse parsing and feature reconstruction.

8. A terminal, characterized in that, include: The processor and memory, wherein the memory stores a product traceability program based on spatiotemporal codes and dynamic key derivation chains, and the product traceability program based on spatiotemporal codes and dynamic key derivation chains, when executed by the processor, is used to implement the operation of the product traceability method based on spatiotemporal codes and dynamic key derivation chains as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a product traceability program based on spatiotemporal codes and dynamic key derivation chains. When executed by a processor, the product traceability program based on spatiotemporal codes and dynamic key derivation chains is used to implement the operation of the product traceability method based on spatiotemporal codes and dynamic key derivation chains as described in any one of claims 1-6.

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