A product whole-link logistics fidelity tracing method, system, device and medium

Abstract

The application relates to a product full-link logistics fidelity tracing method, system, device and medium, and relates to the product anti-fake technical field.The method comprises the following steps: based on delivery location information, receipt location information and transfer node information, generating an anti-fake label and a geographic fence of each logistics node, and anti-fake data of each logistics node; in response to a shooting operation of a scanning terminal of the anti-fake label in the geographic fence where the logistics node is located, obtaining verification data; comparing and judging whether the verification data is consistent with the anti-fake data of the current logistics node; if the verification data is consistent with the anti-fake data of the current logistics node, the signing process is completed. The application can effectively prevent package switching in the logistics link through strong binding of the logistics location and the information of the person who signs, and provide reliable evidence for product tracing.

Description

Technical Field

[0001] This application relates to the field of product anti-counterfeiting technology, and in particular to a method, system, equipment and medium for tracing and verifying the authenticity of products across the entire logistics chain. Background Technology

[0002] As the market volume of high-end products continues to increase, consumers are paying more and more attention to the authenticity and safety of products during the logistics process. A reliable logistics traceability system can enhance consumer trust in products, maintain brand reputation, and promote the healthy development of the high-end product market. At the same time, for businesses, an effective traceability system helps reduce problems such as product tampering in the logistics process, minimize economic losses, and improve logistics efficiency.

[0003] In existing technologies, a common approach to addressing the authenticity and traceability issues in the logistics of high-end products is to use physical anti-counterfeiting labels. These tamper-evident labels prevent easy damage and transfer, thus ensuring the physical integrity of the product to some extent. Another method is to use designated recipients and authorized signatories for identity protection, ensuring goods are delivered to the correct person. Additionally, some systems employ electronic fences for geographic protection, restricting the delivery location within a preset geographical area. For digital anti-counterfeiting, some systems use static anti-counterfeiting codes for verification.

[0004] However, existing technologies have significant drawbacks. Conventional physical anti-counterfeiting labels are easily counterfeited, and identity verification and geofencing verification methods are relatively simple, lacking dynamism and flexibility. Static anti-counterfeiting codes are easily cracked and copied, making it difficult to effectively prevent product tampering during logistics. Consequently, they cannot achieve end-to-end, tamper-proof, and multi-dimensional verification for authenticating high-end products from production to consumption. Summary of the Invention

[0005] The purpose of this application is to provide a method for authenticating and tracing the entire product logistics chain, which can effectively prevent product tampering in the logistics process by strongly binding the logistics location with the recipient's information, and provide conclusive evidence for product traceability.

[0006] Firstly, this application provides a product end-to-end logistics traceability method, which adopts the following technical solution: A method for tracing and verifying the authenticity of products across the entire logistics chain includes: Based on the origin of shipment, destination of shipment, and transit node information, anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, are generated. In response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, verification data is obtained. The verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule. Compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node; If they match, the signing process is complete.

[0007] By adopting the above technical solutions, the information of the place of shipment, the place of receipt and the transit node are integrated to generate a unique geofence and anti-counterfeiting data for each logistics node, realizing the digital locking of the logistics path and ensuring that the location of the product at each link in the circulation process can be verified. Combined with the physical identification of the anti-counterfeiting label, it provides a spatial dimension framework for full-chain traceability, effectively binding the logistics location with the product identity and preventing the product from being swapped from the source.

[0008] In a preferred embodiment, this application can be further configured as follows: the step of generating anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, based on the shipping location information, receiving location information, and transit node information, includes: Configure the location information of each logistics node, which includes the location information of each logistics node and the location information of the mobile phone number of the scanning terminal; Based on the location information of each logistics node, geofencing is divided according to risk level; The location information and the mobile phone number's place of origin information are converted using preset conversion rules to generate anti-counterfeiting data.

[0009] By adopting the above technical solutions, location and mobile phone number attribution information are configured for logistics nodes, and geofences are divided based on risk levels. This achieves a preliminary association between the recipient's identity and the logistics location, providing a structured data foundation for subsequent verification. It enables the anti-counterfeiting data generation process to integrate geographical location and identity information, enhances the transparency of the logistics process, and builds a multi-dimensional anti-counterfeiting system for traceability.

[0010] In a preferred embodiment, this application may be further configured such that, prior to the step of obtaining verification data in response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, the method further includes: Determine whether the real-time location information of the scanning terminal is within the same address fence as the delivery address information; If they are within the same address fence, the scanning terminal is allowed to open the signature interface and activate the consistency judgment process between the verification data and the anti-counterfeiting data. If they are not in the same address fence, the scanning terminal will stop opening the signature interface, and the risk level of the geofence corresponding to the scanning terminal will be adjusted based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence.

[0011] By adopting the above technical solution and setting up a pre-set location verification, the forced signing operation must be carried out within the preset geofence; otherwise, the process is terminated and the risk level is dynamically adjusted. This strengthens the binding between logistics location and signing behavior, preventing malicious signing or tampering at unauthorized locations. At the same time, cross-verification based on the mobile phone number's location enhances the dual authentication of identity and location, providing real-time risk monitoring and intervention capabilities for traceability.

[0012] In a preferred embodiment, this application can be further configured as follows: the step of terminating the opening of the signature interface on the scanning terminal if the address fences are not the same, and adjusting the risk level of the geofence corresponding to the scanning terminal based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence, includes: Obtain the location information of the mobile phone number of the scanning terminal, and obtain the list of authorized regions pre-bound to the current geofence; Determine whether the location of the mobile phone number exists in the authorized region list; If it exists, maintain the current geofence level and trigger the first risk management strategy; If it does not exist, the risk level of the current geofence will be increased, and the second risk management strategy will be triggered.

[0013] By adopting the above technical solution, the risk assessment of the association between the recipient's identity and geographical location is realized based on the comparison between the mobile phone number's location and the geofence authorization list. When the location is abnormal, the risk level of untrusted locations is increased and corresponding strategies are triggered through tiered handling, which ensures a strong binding between location and identity in the logistics process, timely warning of potential package tampering, and strengthens the resilience and response speed of the traceability chain.

[0014] In a preferred embodiment, this application can be further configured such that the step of determining whether the real-time location information of the scanning terminal and the delivery address information are within the same address fence includes: Obtain the authorization information of the scanning terminal, the authorization information including the main authorization feature and the authorized feature; In response to obtaining the authorized feature of the scanning terminal, the location of the authorized scanning terminal's mobile phone number is obtained; Determine whether the location of the mobile phone number exists in the authorized region list; If present, maintain the geofence level of the authorized scanning terminal and trigger the third risk handling strategy; If it does not exist, the risk level of the geofence where the authorized scanning terminal is located will be increased, and the fourth risk handling strategy will be triggered.

[0015] By adopting the above technical solution, the characteristics of the main authorizer and the authorized recipient are distinguished, thereby refining the permission management of different signatories. For the authorized signatories, cross-verification of the mobile phone number's location and geofence is also performed to ensure the integrity of the authorization chain. This achieves accurate binding of logistics location and multi-level signatory information, prevents authorization abuse, provides hierarchical confirmation evidence for product traceability, and enhances the overall anti-tampering capability and traceability accuracy.

[0016] In a preferred embodiment, this application can be further configured as follows: the step of comparing and determining whether the verification data is consistent with the anti-counterfeiting data of the current logistics node includes: Obtain the image feature similarity between the verification data and the anti-counterfeiting data; If the similarity of the image features exceeds a preset threshold, they are judged to be identical.

[0017] By adopting the above technical solution, based on the image feature similarity comparison of anti-counterfeiting information and verification information, accurate verification of digital information of anti-counterfeiting labels is achieved, ensuring that the verification data collected at each logistics node is highly matched with the pre-stored anti-counterfeiting data, thereby verifying the authenticity of the product and the consistency of its circulation. This strengthens the binding between logistics location and product anti-counterfeiting information, provides technical verification means for preventing tampering, and improves the credibility and automation level of traceability evidence.

[0018] In a preferred embodiment, this application can be further configured as follows: the step of generating anti-counterfeiting data by converting the location information and the mobile phone number's location information according to a preset conversion rule includes: The longitude and latitude values ​​in the location information are converted into integer sequences respectively; Based on the integer sequence and the sequential index of the current logistics node in the flow path, a first value and a second value are generated using a preset hash function. The first value, the second value, and the size of the anti-counterfeiting label reference image are moduloed, and the results are used as the x and y coordinates of the cutting start point, respectively. Based on the sequential index, the corresponding size is selected from the preset size set as the cutting size of the cutting area, and the cutting size is configured as anti-counterfeiting data.

[0019] By adopting the above technical solution, the geographical location and mobile phone number location information are converted into unique image segmentation parameters, generating anti-counterfeiting data that is strongly correlated with logistics nodes. Furthermore, the preset conversion rules can ensure that the anti-counterfeiting data of each node is dynamically generated and unpredictable based on its specific location and order. This binds the logistics location with the physical presentation of the anti-counterfeiting label, making it difficult for tampering to replicate the node's exclusive verification information, and providing encrypted spatial evidence and algorithmic protection for traceability.

[0020] In a preferred embodiment, this application can be further configured as follows: the step of obtaining verification data in response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located includes: The received verification data is obtained by cutting and converting the image of the anti-counterfeiting label after obtaining the abscissa and ordinate of the cutting starting point by using the longitude and latitude values ​​of the logistics node corresponding to the geofence where the scanning terminal was located when it took the picture, through a preset conversion rule.

[0021] By adopting the above technical solution, image segmentation driven by real-time geolocation enables verification data to strictly correspond to the current logistics node location; the scanning terminal photographs the anti-counterfeiting label within the fence and generates segmentation coordinates based on the location, realizing the real-time conversion of location information to image information, strengthening the real-time binding between the logistics site location and verification data, preventing offline forgery, ensuring that the verification of each node is based on the real geographical context, and providing dynamic evidence and real-time protection against tampering.

[0022] In a preferred embodiment, this application can be further configured such that: the step of obtaining verification data in response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located further includes: Obtain a planar image of the side of the product bearing the anti-counterfeiting label; The planar image is preprocessed to obtain the relative position of the anti-counterfeiting label in the planar image; Based on the relative position, it is matched with the relative position of the pre-entered anti-counterfeiting code of the product in a standard planar image; If the match is successful, the signing process is allowed to be completed; if the match is unsuccessful, the scanning terminal is activated to re-verify the process.

[0023] By adopting the above technical solution, the relative position of the anti-counterfeiting label on the packaging is matched, which increases the verification dimension of physical packaging integrity; it detects whether the anti-counterfeiting label is in the standard position of the product packaging, preventing the label from being transferred or re-pasted, and realizes the triple binding of logistics location, product packaging status and anti-counterfeiting label, further avoiding the possibility of package tampering, and providing conclusive evidence of physical packaging consistency and integrity verification for product traceability.

[0024] In a preferred embodiment, this application can be further configured such that, before the step of generating anti-counterfeiting labels and geofences for each logistics node based on the shipping location information, receiving location information, and transit node information, and the anti-counterfeiting data for each logistics node, the following additional steps are included: Receive product production information and obtain the location information of the scanning terminal that uploaded the production information; If the geofence of the location information is inconsistent with the production scanning node associated with the production information, the third risk handling strategy is triggered. If the number of times the production information of the product is received is equal to the preset number of production scanning nodes, then a shipping key is generated based on the serial number of all scanning terminals that scan the product through a preset conversion algorithm. The shipping key is used to activate the shipping interface of the scanning terminal that performs the shipping operation. The shipping key is distributed to the scanning terminal authorized to perform the shipping operation.

[0025] By adopting the above technical solutions, the location of uploaded production information is compared with the geofence of production nodes, which can effectively identify abnormal production behavior. The dynamic delivery key generated based on multi-terminal serial numbers not only realizes the fine-grained control of delivery permissions, but also improves the system's anti-attack capability through the distributed key generation mechanism. Before the product is shipped, a dual security verification mechanism is built at the production end and the logistics end, forming a full-link security closed loop from the source of production to the logistics node, which further reduces the risk of products being tampered with or switched in the circulation process.

[0026] Secondly, this application provides a product end-to-end logistics traceability system, which adopts the following technical solution: A product end-to-end logistics traceability system includes: Anti-counterfeiting data generation module: used to generate anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, based on shipping location information, receiving location information, and transit node information. Verification data receiving module: used to respond to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, and to obtain verification data. The verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule. Anti-counterfeiting verification module: used to compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node; The "Acceptance Completed" module is used to complete the acceptance process if the items match.

[0027] Thirdly, this application provides an electronic device that adopts the following technical solution: An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described product end-to-end logistics traceability method.

[0028] Fourthly, this application provides a computer storage medium, as follows: A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described product end-to-end logistics traceability method.

[0029] Fifthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer implements any of the above-described product end-to-end logistics traceability methods.

[0030] In summary, this application has the following beneficial technical effects: This application can construct a dynamically perceived anti-counterfeiting status based on the fusion and real-time verification of multi-source information such as logistics node location, recipient identity, and anti-counterfeiting images, thereby improving the real-time performance and reliability of traceability verification. By dynamically dividing and adjusting electronic fences according to geographical location and risk level, it can achieve refined management of verification scenarios and improve the adaptability and proactivity of anti-counterfeiting decisions. Furthermore, it can dynamically match dedicated image segmentation algorithms and verification strategies based on different nodes and scenarios to improve the accuracy and tamper resistance of anti-counterfeiting verification. Ultimately, it solves the problems of opaque information flow and difficulty in tracing package swapping behavior in complex logistics links for high-end products, and realizes the authenticity control from single-point anti-counterfeiting to full-link closed-loop traceability. Attached Figure Description

[0031] Figure 1 This is a flowchart of a product end-to-end logistics authenticity traceability method in one embodiment of this application.

[0032] Figure 2 This is a flowchart of the step S4 for obtaining attendance information in one embodiment of this application.

[0033] Figure 3 This is a flowchart of the steps for obtaining construction information in step S4 of one embodiment of this application.

[0034] Figure 4 This is a flowchart of the steps added after step S6 in one embodiment of this application.

[0035] Figure 5 This is a flowchart of a sub-step of step S62 in one embodiment of this application.

[0036] Figure 6 This is a flowchart of a sub-step of step S22 in one embodiment of this application.

[0037] Figure 7This is a flowchart of a sub-step of step S8 in one embodiment of this application.

[0038] Figure 8 This is a flowchart of a sub-step of step S22 in one embodiment of this application.

[0039] Figure 9 This is a flowchart of a sub-step of step S8 in one embodiment of this application.

[0040] Figure 10 This is a flowchart of the steps added before step S1 in one embodiment of this application.

[0041] Figure 11 This is a schematic diagram of the structure of a product end-to-end logistics authenticity traceability system according to one embodiment of this application.

[0042] Figure 12 This is a schematic block diagram of an electronic device in one embodiment of this application.

[0043] Attached labels: 1. Anti-counterfeiting data generation module; 2. Verification data receiving module; 3. Anti-counterfeiting verification module; 4. Signature completion module. Detailed Implementation

[0044] The following is in conjunction with the appendix Figure 1-12 This application will be described in further detail.

[0045] It should be noted that, in the embodiments of this invention, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this invention involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0046] refer to Figure 1 A method for tracing and verifying the authenticity of products across the entire logistics chain, specifically including: S1. Based on the shipping location information, receiving location information, and transit node information, generate anti-counterfeiting labels, geofences for each logistics node, and anti-counterfeiting data for each logistics node.

[0047] Specifically, the process begins by collecting and structuring precise location information for the shipping and receiving locations, as well as the preset location information for all planned transit nodes, as logistics node information. Based on this location data, a unique electronic geofence is dynamically generated for each node on the logistics path, including the central warehouse, distribution center, and delivery station. This electronic geofence is a virtual geographical boundary area centered on the preset location of the node, set according to business rules and security levels. Simultaneously, a unique anti-counterfeiting label is generated or bound to the product, carrying information that can be scanned and identified by devices.

[0048] Ultimately, each logistics node pre-generates a unique set of anti-counterfeiting data. This means that the physical logistics path and node location are pre-anchored through digital means, giving the product a digital identity credential that is consistent throughout the entire process and bound to its spatial location. Initially, it is strongly associated with the node and its geofence. The generation logic of the anti-counterfeiting data integrates the spatial attributes of the nodes, ensuring that every spatial transfer of the product must be verified by the pre-set nodes. This provides an immutable initial data benchmark for subsequent real-time verification and also ensures the difference and uniqueness of data from different nodes.

[0049] S2. In response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, the verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule.

[0050] Specifically, when a product is transferred to a certain logistics node, the operator needs to use an authorized scanning terminal to take a picture of the anti-counterfeiting label on the product within the geofence preset by that node.

[0051] In response to the shooting operation, the system does not simply read the static information on the label, but initiates a conversion process. The scanning terminal acquires its own precise location information in real time and uploads this location information along with the captured anti-counterfeiting label image. The conversion rules map the spatial parameter of the logistics node's location information into instructions for specific processing of the anti-counterfeiting label image. Through these conversion rules, the system uses the uploaded real-time location information to extract unique image feature fragments from the captured complete label image; these feature fragments serve as verification data.

[0052] In this way, each verification action is strongly linked to the precise geographical location at the time of verification. Therefore, the verification data is no longer fixed but dynamically changes with the scanning location, effectively preventing fraudulent activities such as pre-copying scan results and replaying attacks in unauthorized locations. This ensures that only operations performed within the correct geofence of the node can generate verifiable verification data.

[0053] S3. Compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node.

[0054] Specifically, upon receiving the generated verification data bound to a specific geographical location, the system immediately retrieves the anti-counterfeiting data pre-generated and stored for the current logistics node from the database. By defining a custom security threshold, the two data points are only considered identical if the calculated similarity exceeds the threshold.

[0055] S4. If they match, the signing process is complete.

[0056] Specifically, the system will only trigger the subsequent steps of the signing process if and only if the verification data matches the anti-counterfeiting data of the current logistics node, marking the successful completion of the verification task for that logistics node.

[0057] For transit nodes, a successful verification signal will update the product status to "safely arrived at a certain node" and authorize the product to flow to the next stage; for the final receiving node, it means that the consumer's signature is legal and valid, the system will complete the order verification and record the successful full-link verification history.

[0058] The above integrates the information of the place of origin, the place of receipt, and the transit node, and generates a unique geofence and anti-counterfeiting data for each logistics node. This avoids the loophole of forcibly completing logistics operations without passing the location binding verification, so that any successful receipt naturally becomes conclusive electronic evidence that the product has a clear origin, a reliable circulation path, and has not been tampered with. Ultimately, it achieves a deep integration of anti-counterfeiting goals and business processes.

[0059] refer to Figure 2 Furthermore, in one embodiment, step S1 is refined into the following sub-steps: S10. Configure the location information of each logistics node. The location information includes the location information of each logistics node and the location information of the mobile phone number of the scanning terminal.

[0060] Specifically, during initialization, the system precisely configures the geographical location information for each node on the logistics path, such as the central warehouse, regional distribution center, or last-mile delivery station. This includes the node's latitude and longitude coordinates and a descriptive address text. Simultaneously, the system pre-associates the mobile phone number location information of one or more authorized scanning terminals for each node. This location information represents the permanent geographic location of the personnel allowed to operate at that node. This structured binding of physical location and operator geographic information at the data source of logistics traceability establishes a whitelist foundation for subsequent verification.

[0061] S11. Based on the location information of each logistics node, geofencing is divided according to the risk level.

[0062] Specifically, the system classifies geofencing into risk levels based on pre-configured location information for each logistics node, combined with historical security data, regional business characteristics, and the node's importance in the logistics chain. For example, nodes located in core hubs or strictly regulated areas are classified as low-risk geofencing, with a more precise scope; while nodes located in transportation hubs, areas with complex populations, or temporary delivery points are classified as medium- to high-risk geofencing, with a slightly broader scope but more stringent monitoring strategies. The classification criteria include, but are not limited to, regional crime rate statistics, past abnormal delivery records, and the value density of goods at each node.

[0063] Furthermore, the size of the geofence varies depending on the risk level. The system will dynamically adjust the radius or coverage area of ​​the geofence based on the real-time risk level. Specifically, the higher the risk level, the smaller the radius or coverage area of ​​the geofence.

[0064] In summary, by matching geofences of different security levels to different nodes, the system can implement differentiated verification strengths and monitoring strategies, thereby enabling key defenses and resource allocation for high-risk areas.

[0065] S12. The location information and the mobile phone number's place of origin information are converted using preset conversion rules to generate anti-counterfeiting data.

[0066] Specifically, the system inputs the latitude and longitude coordinates from the configured logistics node location information, along with the associated mobile phone number's location information, such as the city code, into a set of preset, irreversible conversion rules. These conversion rules, through a specific algorithm, generate a set of highly discrete and uniquely corresponding output data, which constitutes the node's unique anti-counterfeiting data. In this embodiment, the anti-counterfeiting data is a feature template used for image comparison.

[0067] In summary, the anti-counterfeiting data generation process integrates geographical location and identity information, making the data at each node unique. This enhances the transparency of the logistics process and builds a multi-dimensional anti-counterfeiting system for traceability.

[0068] In addition, refer to Figure 3 Furthermore, in one embodiment, steps S20, S21, and S22 are added before step S2: S20. Determine whether the real-time location information of the scanning terminal is within the same address fence as the delivery address information.

[0069] Specifically, the system acquires and parses the precise geographic coordinates reported by the scanning terminal through its built-in positioning module in real time. Simultaneously, it calls upon a predefined precise address fence data model corresponding to the final delivery address. This data model is set as a polygonal or circular area constructed based on a geographic information system. Subsequently, the system determines in real time whether the scanning terminal's current coordinates fall within the range of this address fence.

[0070] The above-mentioned method of matching the real-time location information of the scanning terminal with the geofence of the delivery location information forces that the intention to sign for the package must be initiated within the target geographical area of ​​the final delivery. From the very beginning of the interaction, it eliminates the possibility of malicious signing for the package remotely or attempting to intercept the package at a non-destination location during transportation. It hardens and locks the binding relationship between the logistics location and the signing behavior at the starting point of the operation, laying a spatial authenticity foundation for the entire anti-tampering process.

[0071] S21. If they are within the same address fence, the scanning terminal is allowed to open the signature interface and activate the consistency judgment process between the verification data and the anti-counterfeiting data.

[0072] Specifically, when the system determines that the scanning terminal is within the correct address fence, it immediately authorizes the terminal, unlocks it, and presents a dedicated signature operation interface. This includes the terminal devices of the operators at each logistics node conducting the acceptance, as well as the terminal device of the consumer signing for the package. Simultaneously, the backend logic formally activates the response steps for the shooting operation, and the subsequent verification data and anti-counterfeiting data consistency judgment process. Once activated, it means that the system will establish a formal verification context for this session, prepare to receive and process the data generated by subsequent shooting operations, and allow the process to proceed to the key verification stage.

[0073] The above ensures that users can only see and enter the signing process in the correct location, making subsequent complex anti-counterfeiting verification necessarily take place in a secure environment confirmed by the space. This not only improves the continuity of the user experience, but more importantly, it ensures from the process logic that the execution scenario of the core anti-counterfeiting verification steps is controlled and reliable, preventing the security risks that may be caused by forcibly performing data comparison under abnormal location conditions.

[0074] S22. If they are not in the same address fence, stop the scanning terminal from opening the signing interface, and adjust the risk level of the geofence corresponding to the scanning terminal based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence.

[0075] Specifically, when the location of the scanning terminal is determined to be outside the target address fence, the system immediately performs forced interception, refusing to provide any signing operation interface, thereby terminating the current signing attempt; at the same time, the system automatically starts the analysis mechanism, that is, to obtain the location information of the scanning terminal's mobile phone number, and to perform cross-correlation analysis with the geofence identifier that is currently trying to access but being rejected, and to adjust the risk level, realizing an upgrade from passive interception to proactive early warning and adaptive protection.

[0076] In addition, refer to Figure 4 Furthermore, in one embodiment, step S22 is refined into the following sub-steps: S220. Obtain the location information of the mobile phone number of the scanning terminal, and obtain the list of authorized regions pre-bound to the current geofence.

[0077] Specifically, the system first queries the operator's interface or local database to accurately obtain the location information of the mobile phone number corresponding to the scanning terminal that initiated the abnormal location access, usually accurate to the city level. At the same time, the system retrieves a list of authorized regions pre-bound to the currently triggered target geofence from the security policy library. This list defines the geographic origin of legitimate personnel who are allowed or are usually expected to operate within this geofence, and may be generated based on business logic such as the recipient's place of residence, the place of shipment, and the logistics company's service network, in order to establish a direct association channel between identity geographic attributes and spatial access policies.

[0078] S221. Determine if the location of the mobile phone number exists in the authorized region list.

[0079] Specifically, the system will match the obtained mobile phone number location information with the authorized region list of geofences. The matching process is based on standardized regional codes for precise comparison, aiming to quickly distinguish operators appearing in abnormal locations and determine whether the regional source is in line with normal expectations and is a possible reasonable occasional situation, or a significantly different situation from expectations and is a highly suspicious abnormal situation.

[0080] S222. If it exists, maintain the current geofence level and trigger the first risk management strategy.

[0081] Specifically, when the location information of a mobile phone number is confirmed to exist in the authorized region list, the system determines that the current abnormal location access event may have been caused by legitimate personnel within the authorized region due to temporary reasons such as GPS drift or temporary change of delivery point, and is considered a low-threat or accidental anomaly. Therefore, the system decides to maintain the current geofence risk level to avoid unnecessary global alerts or policy tightening caused by accidental events.

[0082] At the same time, the system will trigger the first risk handling strategy, including but not limited to recording detailed abnormal event logs, performing short-term minor enhanced monitoring of subsequent operations on the terminal, or sending a low-priority notification message to the backend system for the administrator to be aware of.

[0083] S223. If it does not exist, the risk level of the current geofence will be increased, and the second risk management strategy will be triggered.

[0084] Specifically, when the location information of a mobile phone number is confirmed not to exist in the authorized region list, the current abnormal location access event is determined to be accompanied by an abnormal identity region, constituting a suspicious event with a high threat level. At this time, the system will immediately and dynamically increase the real-time risk level of the target geofence. The increase can be dynamically calculated based on the degree of deviation between the location and the authorized list, historical risk patterns, etc.

[0085] At the same time, the system triggers a second risk handling strategy, including but not limited to immediately sending a high-risk real-time alert to the security administrator, automatically locking the account or terminal permissions associated with the mobile phone number, requiring the initiation of a manual review process, or marking the event pattern as a risk.

[0086] In addition, refer to Figure 5 Furthermore, in one embodiment, step S20 is refined into the following sub-steps: S200. Obtain the authorization information of the scanning terminal. The authorization information includes the main authorization feature and the authorized feature.

[0087] Specifically, in the verification process, the system first actively acquires and parses the authorization information carried by the current scanning terminal. The acquired authorization information is clearly distinguished into primary authorization features and authorized features: primary authorization features are usually directly bound to the identity of the original recipient specified at the time of shipment, such as real-name authentication information or a dedicated device identifier; while authorized features are the authorization credentials for the recipient granted in advance by the original recipient through system functions, such as a time-limited digital authorization code or an associated mobile phone number identifier for the recipient. The system identifies these features to determine the specific permission level of the current operator.

[0088] S201. In response to obtaining the authorized characteristics of the scanning terminal, obtain the location of the mobile phone number of the authorized scanning terminal.

[0089] Specifically, when the system identifies that the current scanning terminal holds an authorized feature, the system then registers a mobile phone number for the authorized person pre-stored in this embodiment based on the information associated with the authorized feature. Then, it initiates a query to the operator or internal database to accurately obtain the location information of the mobile phone number currently used by the authorized terminal. This ensures that even if the operation is performed by an agent, the geographical attribute corresponding to their identity can be accurately captured and included in the risk assessment system. The geographical identity of the authorized agent is included in the scope of spatial security verification, thus realizing the effective acquisition of information of participants at the end of the authorization chain.

[0090] S202. Determine if the location of the mobile phone number exists in the authorized region list.

[0091] Specifically, after obtaining the location of the authorized scanning terminal's mobile phone number, the location of the mobile phone number is compared and analyzed with the pre-configured list of authorized regions of the geofence currently being accessed to determine whether the location is allowed by the list.

[0092] S203. If it exists, maintain the geofence level of the authorized scanning terminal and trigger the third risk handling strategy.

[0093] Specifically, when the location of the authorized terminal's mobile phone number is confirmed to exist in the authorized region list, it indicates that the geographical attribute of this collection behavior meets security expectations. At this time, the system therefore determines that the risk is low and decides to maintain the current risk level of the geofence, without triggering an escalation due to the proxy behavior itself.

[0094] At the same time, the system will trigger a third risk handling strategy specifically designed for compliant agency scenarios, including but not limited to recording detailed agency receipt logs for traceability, sending an agency receipt initiation notification to the original consignee, or conducting standard-level process monitoring of this agency receipt process.

[0095] S204. If not, the risk level of the geofence where the authorized scanning terminal is located will be increased, and the fourth risk handling strategy will be triggered.

[0096] Specifically, when the location of the authorized terminal's mobile phone number is confirmed not to exist in the authorized region list, it indicates that the proxy behavior is accompanied by abnormal regional signals, significantly increasing the risk. At this time, the system will immediately and dynamically adjust the geofence risk level of the authorized terminal's current attempted operation upwards, with the increase potentially exceeding that of ordinary abnormal events.

[0097] At the same time, the system triggers a fourth risk management strategy specifically for suspicious agency behavior, including but not limited to immediately freezing the current collection authorization, forcing the original consignee to conduct real-time secondary manual confirmation, sending high-risk warnings to both parties, or marking this abnormal agency event as a high-risk case for key analysis and investigation.

[0098] In addition, refer to Figure 6 Furthermore, in one embodiment, step S3 is refined into the following sub-steps: S30. Obtain the image feature similarity between the verification data and the anti-counterfeiting data.

[0099] Specifically, firstly, the system performs a preprocessing procedure on the original images captured by the scanning terminal to eliminate or mitigate the impact of unavoidable interference factors in the actual logistics environment on image quality, laying the foundation for subsequent accurate feature extraction.

[0100] Preprocessing mainly includes: First, image enhancement and filtering are performed to correct brightness differences and noise caused by uneven lighting, shadows, or reflections, ensuring clear contrast and a clean background in the QR code area. Next, geometric correction and perspective transformation are performed. By detecting the positioning pattern of the anti-counterfeiting label, image tilt, distortion, or perspective deformation caused by a non-frontal shooting angle is automatically corrected, restoring the anti-counterfeiting label area to a standard frontal view image. Then, precise positioning and cropping are performed. Based on the corrected image, the effective area of ​​the QR code is identified and selected, eliminating interference from other irrelevant patterns or backgrounds on the packaging, ensuring that the image input to the feature extraction module is a normalized, complete QR code graphic. Furthermore, the system uses the same preprocessing standard for the pre-stored anti-counterfeiting data benchmark image to ensure consistency in the comparison benchmark.

[0101] Subsequently, the system performs in-depth analysis and comparison of the inherent physical morphological features of the anti-counterfeiting code, determined by its encoded information and graphic structure, to calculate the image feature similarity between the verification data and the anti-counterfeiting data. For example, when the anti-counterfeiting code is a QR code, the extracted features include, but are not limited to: the dot matrix distribution formed by the precise geometric center positions of each black or white code element module; the edge contour features between adjacent code elements and their relative positional relationships; the unique texture pattern formed by the arrangement of code elements in a specific local area; and the spatial configuration of stable corner points or feature regions composed of multiple code elements. The system obtains two datasets representing their respective code structures by performing feature extraction on pre-stored anti-counterfeiting data images and on-site captured verification data images using the same algorithm, and then calculates the matching degree or similarity of the two datasets in terms of spatial distribution and morphology.

[0102] S31. If the image feature similarity exceeds the preset threshold, it is judged as consistent.

[0103] Specifically, the calculated image feature similarity score is directly compared with a pre-set safety threshold based on extensive experiments and data analysis to ensure that while allowing reasonable differences in image acquisition, forgery, tampering, or mismatch can be effectively identified.

[0104] If the similarity score is higher than the preset threshold, the system will automatically determine that the verification data collected at the current logistics node is consistent with the pre-stored anti-counterfeiting data, indicating that the verification of the geographical location binding has passed, and the consumer can complete the final signing operation.

[0105] In addition, refer to Figure 7 Furthermore, in one embodiment, step S12 is refined into the following sub-steps: S120. Convert the longitude and latitude values ​​in the location information into integer sequences respectively.

[0106] Specifically, the system first obtains the latitude and longitude coordinates of the logistics nodes. These coordinates are usually floating-point numbers with decimals, and the longitude and latitude values ​​need to be converted into a set of integer sequences. In this embodiment, the coordinate values ​​are multiplied by a sufficiently large fixed multiple and then rounded; in another embodiment, the numerical bits are directly truncated and reassembled to form the sequence according to a specific precision.

[0107] S121. Based on the integer sequence and the sequential index of the current logistics node in the flow path, generate the first value and the second value through a preset hash function.

[0108] Specifically, the system takes the obtained sequence of location integers, along with the unique sequential index of the current logistics node in the overall flow path, as input. This input is fed into a pre-defined cryptographic hash function with good discreteness and collision resistance, and the output is a long string of fixed-length pseudo-random hash values. Subsequently, the system extracts two independent values ​​from a specific position of this hash value or derives them through specific rules, naming them the first value and the second value, respectively. Due to the sensitivity of the hash function, any slight change in the input information will lead to drastically different outputs. Therefore, each node generates a unique pair of values ​​based on its unique position and order.

[0109] S122. Perform a modulo operation on the first value, the second value, and the dimensions of the anti-counterfeiting label reference image, and use the results as the horizontal and vertical coordinates of the cutting starting point, respectively.

[0110] Specifically, the system pre-stores the total pixel width and total pixel height of the anti-counterfeiting label reference image. Then, it performs a modulo operation between the first value and the image width, and a modulo operation between the second value and the image height. The results of the modulo operations are constrained to the effective coordinate range of zero to the image width minus one and zero to the image height minus one. These two result values ​​are set as the x and y coordinates of the starting point for the cutting operation from the reference image, respectively. This ensures that no matter how large the input key value is, the calculated starting point always falls within the effective area of ​​the image. Furthermore, due to the randomness of the input key, the starting point coordinates exhibit a uniform and dispersed distribution on the image plane, ultimately achieving the conversion of the abstract key to a specific physical image medium.

[0111] S123. Based on the sequential index, select the corresponding size from the preset size set as the cutting size of the cutting area, and configure the cutting size as anti-counterfeiting data.

[0112] Specifically, the system predefines a set of dimensions containing various width and height combinations, with each dimension corresponding to an index number. Based on the sequential index of the current logistics node in the flow path, the system uses this index to search for and select the corresponding dimension combination from the predefined set of dimensions. This combination specifies the width and height pixel values ​​of the cutting area.

[0113] The selected cutting size, along with the generated cutting start coordinates, together define a rectangular region on the reference image. Furthermore, this cutting size parameter is formally configured and stored by the system as one of the anti-counterfeiting data for this node, further increasing the complexity of the anti-counterfeiting mode.

[0114] In addition, refer to Figure 8 Furthermore, in one embodiment, step S2 is refined into the following sub-steps: S23. The received verification data is obtained by cutting and converting the image of the anti-counterfeiting label after obtaining the abscissa and ordinate of the cutting starting point by using the longitude and latitude values ​​of the logistics node corresponding to the geofence where the scanning terminal was located when it took the picture, through a preset conversion rule.

[0115] Specifically, when the scanning terminal performs a shooting operation within the authorized geofence, the built-in positioning module captures and reports the precise longitude and latitude values ​​of the terminal in real time. Subsequently, the real-time location coordinate data is immediately sent to a preset conversion rule that is completely isomorphic to the one used when generating the pre-stored anti-counterfeiting data for calculation. The conversion rule uses these real-time coordinates to calculate two values ​​using the same algorithm, and then combines them with the known reference image size of the anti-counterfeiting label to finally determine a unique cutting starting point with horizontal and vertical coordinates located in the image plane through modulo operations.

[0116] Then, the scanning terminal or its collaborating cloud service, based on the cutting coordinates, crops a rectangular image region defined by the starting point and the cutting size determined by preset rules from the complete anti-counterfeiting label image captured within the preset verification time window. The feature data extracted from the cropped local image fragment becomes the verification data generated in this operation, ensuring that each verification request is geographically authentic and recent, thus providing an immediate, dynamic, and spatially reliable evidence origin for the entire anti-tampering traceability system.

[0117] In addition, refer to Figure 9 Furthermore, in one embodiment, step S2 is refined into the following sub-steps: S24. Obtain a flat image of the side of the product with the anti-counterfeiting label.

[0118] Specifically, the system guides or instructs operators to use a scanning terminal to take a complete photograph of the side of the product packaging bearing the anti-counterfeiting label from a specific angle, obtaining a clear planar image that includes the label and sufficient surrounding packaging background. The photographing process must ensure the image is clear and accurately focused so that the details of the anti-counterfeiting label and the texture, pattern, or structural features of the packaging surface can be identified simultaneously. The resulting image not only includes the anti-counterfeiting label itself but also records the physical coexistence and spatial context between the label and the packaging carrier it is attached to.

[0119] S25. Preprocess the planar image to obtain the relative position of the anti-counterfeiting label in the planar image.

[0120] Specifically, the system performs preprocessing operations on the acquired planar images, including but not limited to image denoising to improve clarity, geometric correction to eliminate perspective distortion, and color space conversion to optimize feature recognition. Subsequently, the system accurately locates the outline boundary of the anti-counterfeiting label in the preprocessed image and calculates its geometric center point or key locations such as feature corners. Simultaneously, the system identifies fixed reference features of the packaging itself in the image, such as packaging edges, fixed patterns, or specific structural points. By calculating the pixel distance and orientation angle between the label's key points and these packaging reference features, the system ultimately determines the normalized relative position coordinates of the anti-counterfeiting label relative to the surface of its packaging.

[0121] S26. Based on relative position, match the relative position of the pre-entered product's anti-counterfeiting code to the standard planar image.

[0122] Specifically, the system will match and compare the real-time calculated relative position data of the anti-counterfeiting label with the standard position data pre-entered and stored in the database during the product's manufacturing or shipping process. The pre-entered standard position data is the correct relative position of the anti-counterfeiting label affixed to the genuine product packaging, determined under controlled conditions through the same process.

[0123] The comparison process calculates the deviations between real-time location data and standard location data in multiple dimensions, such as the coordinate offset of the center point and the difference in rotation angle. The system will determine whether all these deviations fall within the preset, allowable reasonable tolerance range.

[0124] S27. If the match is successful, the signing process is allowed to be completed; if the match is unsuccessful, the scanning terminal re-verification process is activated.

[0125] Specifically, if the matching result is successful, meaning the positional deviation is within the allowable tolerance, the system determines that the product packaging integrity verification has passed and the physical packaging state is reliable. At this point, the system records this as a necessary condition and allows the signing process to continue, or it can be used together with other verification results as the basis for final release.

[0126] If the matching fails, meaning the positional deviation exceeds the tolerance, the system immediately determines that the physical packaging integrity verification has failed, indicating a high risk of package swapping or tampering. In this case, the system will not directly complete the acceptance, but will proactively activate a re-verification or anomaly handling process, including but not limited to sending a command to the current scanning terminal to re-acquire images, triggering an audible and visual alarm to alert the operator, automatically locking the acceptance operation and generating an anomaly event report to notify the security administrator, or even requesting a higher-level manual review. Upon detecting an anomaly, the process is immediately interrupted and alarms and handling are triggered, achieving real-time interception and proactive response to physical package swapping.

[0127] In addition, refer to Figure 10 Furthermore, in one embodiment, steps S13, S14, S15, and S16 are added before step S1: S13. Receive product production information and obtain the location information of the scanning terminal that uploaded the production information.

[0128] Specifically, after product production is completed, dedicated scanning terminals, either on the production line or handheld by workers, collect product information and upload it to the system. While receiving this production information, the system simultaneously obtains the current location information of the scanning terminal. This location information can be obtained through the scanning terminal's built-in GPS module, BeiDou positioning module, or positioning technology based on the factory's wireless network, ensuring accuracy down to the specific production workshop, production line, or even workstation.

[0129] For example, when a product is assembled and passes quality inspection on production line 3 in workshop A, the terminal responsible for scanning the product information will upload production information such as the batch number, production date, and production team. At the same time, the system will record the terminal's location coordinates at this moment, such as latitude XX degrees XX minutes XX seconds north and longitude XX degrees XX minutes XX seconds east, or a specific location marker such as "Workshop A - Production line 3 - Workstation 5" on the corresponding factory map.

[0130] S14. If the geofence of the production scanning node associated with the location information is inconsistent with that of the production information, the third risk handling strategy will be triggered.

[0131] Specifically, the system pre-sets a corresponding geofence range for each production scanning node, such as a specific production workshop, production line, quality inspection station, or coding equipment. An anomaly is determined when the acquired scanning terminal location information is not within the geofence of the production scanning node associated with the uploaded production information.

[0132] For example, if the production information of a product shows that it should be produced on production line 2 in workshop B, but the location of the scanning terminal when uploading the production information is in the area of ​​workshop C, or exceeds the preset geofence boundary of production line 2 in workshop B, the system will immediately trigger the third risk handling strategy.

[0133] The third risk handling strategy includes, but is not limited to, immediately sending an alarm message to the production management system, indicating an anomaly in the uploaded production information for the product; suspending the subsequent logistics flow of the product until the anomaly is investigated; and automatically recording detailed information about the anomaly, including the identifier of the abnormal product, the information of the uploading terminal, the location deviation data, and the time of the anomaly, to facilitate subsequent source tracing analysis and responsibility determination by management personnel. For example, it might be that the scanning terminal was mistakenly taken to another area for operation, or that the production information does not match the actual production location. By triggering the third risk handling strategy, information entry errors or operational violations in the production process can be detected and corrected in a timely manner, ensuring the accuracy and reliability of product production information from the source.

[0134] S15. If the number of times product production information is received is equal to the preset number of production scanning nodes, then a delivery key is generated based on the serial number of the scanning terminal that scans all products through a preset conversion algorithm. The delivery key is used to activate the delivery interface of the scanning terminal that performs the delivery operation.

[0135] Specifically, the system pre-sets the number of production scanning nodes that a product needs to pass through in the production process. For example, if a certain type of product needs to go through four production scanning nodes in sequence: component assembly, semi-finished product inspection, finished product packaging, and final quality inspection, then the preset number of production scanning nodes is 4. When the system receives the product's production information four times, it means that the product has completed the information collection for all preset production stages.

[0136] At this point, the system extracts the unique serial numbers of all scanning terminals that have scanned the product. These serial numbers are unique identifiers for the scanning terminals. Subsequently, the system uses these serial numbers as input parameters, processes them in a preset conversion algorithm, and generates a specific shipping key.

[0137] In this embodiment, the conversion algorithm used is a hash algorithm, which combines a specific key and a terminal serial number for irreversible operation to ensure that the generated delivery key is uniquely bound to the product and the related scanning terminal.

[0138] The generated shipping key is used to activate the shipping interface of the scanning terminal responsible for shipping operations. If the correct shipping key is not entered, the shipping interface of the scanning terminal will be locked, and operations such as entering shipping information and generating shipping orders will not be possible. This strictly controls the operation permissions in the shipping process and prevents unauthorized shipping behavior.

[0139] S16. Distribute the shipping key to the scanning terminal authorized to perform the shipping operation.

[0140] Specifically, after generating the shipping key, it is sent via an internal secure communication channel to a pre-configured scanning terminal authorized for shipping operations. The information of the authorized terminals is pre-configured in the system to ensure that the key can only be received by designated terminals with shipping permissions. During the transmission process, the system encrypts the transmitted data, for example, using encryption protocols such as SSL / TLS, to prevent the key from being stolen or tampered with during transmission.

[0141] After receiving the shipping key, the authorized scanning terminal will perform local verification. Once the verification is successful, the terminal's shipping interface will be activated and unlocked, allowing operators to enter subsequent shipping information, such as recipient information, tracking number, and quantity, and ultimately generate a shipping order with a unique identifier.

[0142] Even if an unauthorized scanning terminal obtains the delivery key through other means, it will not be able to activate the delivery interface through verification because its terminal serial number is not in the system's authorized list, thus further ensuring the security and controllability of the delivery process.

[0143] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0144] This application also provides a product end-to-end logistics authenticity traceability system, which corresponds one-to-one with the product end-to-end logistics authenticity traceability method in the embodiments.

[0145] refer to Figure 8 A product end-to-end logistics authenticity traceability system includes: anti-counterfeiting data generation module 1, verification data receiving module 2, anti-counterfeiting verification module 3, and receipt completion module 4. Detailed descriptions of each functional module are as follows: Anti-counterfeiting data generation module 1: Used to generate anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, based on the shipping location information, receiving location information, and transit node information. Verification data receiving module 2: Used to respond to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, and to obtain verification data. The verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule. Anti-counterfeiting verification module 3: Used to compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node; Module 4 for signing completion: If the items match, the signing process is completed.

[0146] The system comprises several modules: Anti-counterfeiting data generation module 1 integrates shipping, receiving, and transit node information to generate a uniquely bound geofence and anti-counterfeiting data for each logistics node, establishing a geolocation-based anti-counterfeiting initialization system; Verification data receiving module 2 receives and converts anti-counterfeiting label images captured by scanning terminals within the geofence in real time, dynamically mapping node locations to image verification information to ensure spatial real-time verification for each instance; Anti-counterfeiting verification module 3 compares the image feature similarity between real-time verification data and pre-stored anti-counterfeiting data to achieve accurate automated anti-counterfeiting verification, preventing duplication and forgery; and Sign-off completion module 4 completes the signing process after verification, forming a closed-loop verification system to ensure that only products passing multiple verifications can be delivered. Through the combined action of these modules, a strong binding and dynamic verification of logistics location, identity permissions, and product image information is achieved, effectively preventing logistics tampering and providing a complete and reliable chain of evidence for product traceability.

[0147] Specific limitations regarding the product end-to-end logistics traceability system can be found in the context of the limitations on the product end-to-end logistics traceability method, and will not be repeated here. Each module in the aforementioned product end-to-end logistics traceability system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in an electronic device, or stored in the memory of the electronic device as software, so that the processor can call and execute the corresponding operations of each module. In one embodiment, an electronic device is provided, which is a user terminal. (Reference) Figure 9 The electronic device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores detection data tables. The network interface allows communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for end-to-end product logistics traceability.

[0148] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: S1. Based on the shipping location information, receiving location information, and transit node information, generate anti-counterfeiting labels, geofences for each logistics node, and anti-counterfeiting data for each logistics node.

[0149] S2. In response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, the verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule.

[0150] S3. Compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node.

[0151] S4. If they match, the signing process is complete.

[0152] In one embodiment, the refined sub-steps of step S1 include: S10. Configure the location information of each logistics node. The location information includes the location information of each logistics node and the location information of the mobile phone number of the scanning terminal.

[0153] S11. Based on the location information of each logistics node, geofencing is divided according to the risk level.

[0154] S12. The location information and the mobile phone number's place of origin information are converted using preset conversion rules to generate anti-counterfeiting data.

[0155] In one embodiment, the additional step before step S2 includes: S20. Determine whether the real-time location information of the scanning terminal is within the same address fence as the delivery address information.

[0156] S21. If they are within the same address fence, the scanning terminal is allowed to open the signature interface and activate the consistency judgment process between the verification data and the anti-counterfeiting data.

[0157] S22. If they are not in the same address fence, stop the scanning terminal from opening the signing interface, and adjust the risk level of the geofence corresponding to the scanning terminal based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence.

[0158] In one embodiment, the refined sub-steps of step S22 include: S220. Obtain the location information of the mobile phone number of the scanning terminal, and obtain the list of authorized regions pre-bound to the current geofence.

[0159] S221. Determine if the location of the mobile phone number exists in the authorized region list.

[0160] S222. If it exists, maintain the current geofence level and trigger the first risk management strategy.

[0161] S223. If it does not exist, the risk level of the current geofence will be increased, and the second risk management strategy will be triggered.

[0162] In one embodiment, the refined sub-steps of step S20 include: S200. Obtain the authorization information of the scanning terminal. The authorization information includes the main authorization feature and the authorized feature.

[0163] S201. In response to obtaining the authorized characteristics of the scanning terminal, obtain the location of the mobile phone number of the authorized scanning terminal.

[0164] S202. Determine if the location of the mobile phone number exists in the authorized region list.

[0165] S203. If it exists, maintain the geofence level of the authorized scanning terminal and trigger the third risk handling strategy.

[0166] S204. If not, the risk level of the geofence where the authorized scanning terminal is located will be increased, and the fourth risk handling strategy will be triggered.

[0167] In one embodiment, the sub-steps of step S3 refinement include: S30. Obtain the image feature similarity between the verification data and the anti-counterfeiting data.

[0168] S31. If the image feature similarity exceeds the preset threshold, it is judged as consistent.

[0169] In one embodiment, the sub-steps of step S12 are further refined as follows: S120. Convert the longitude and latitude values ​​in the location information into integer sequences respectively.

[0170] S121. Based on the integer sequence and the sequential index of the current logistics node in the flow path, generate the first value and the second value through a preset hash function.

[0171] S122. Perform a modulo operation on the first value, the second value, and the size of the anti-counterfeiting label reference image, and use the results as the horizontal and vertical coordinates of the cutting starting point, respectively.

[0172] S123. Based on the sequential index, select the corresponding size from the preset size set as the cutting size of the cutting area, and configure the cutting size as anti-counterfeiting data.

[0173] In one embodiment, the sub-steps of step S2 refinement include: S23. The received verification data is obtained by cutting and converting the image of the anti-counterfeiting label after obtaining the abscissa and ordinate of the cutting starting point by using the longitude and latitude values ​​of the logistics node corresponding to the geofence where the scanning terminal was located when it took the picture, through a preset conversion rule.

[0174] In one embodiment, the sub-steps of step S2 refinement include: S24. Obtain a flat image of the side of the product with the anti-counterfeiting label.

[0175] S25. Preprocess the planar image to obtain the relative position of the anti-counterfeiting label in the planar image.

[0176] S26. Based on relative position, match the relative position of the pre-entered product's anti-counterfeiting code to the standard planar image.

[0177] S27. If the match is successful, the signing process is allowed to be completed; if the match is unsuccessful, the scanning terminal re-verification process is activated.

[0178] In one embodiment, the sub-step added before step S1 includes: S13. Receive product production information and obtain the location information of the scanning terminal that uploaded the production information.

[0179] S14. If the geofence of the production scanning node associated with the location information is inconsistent with that of the production information, the third risk handling strategy will be triggered.

[0180] S15. If the number of times product production information is received is equal to the preset number of production scanning nodes, then a delivery key is generated based on the serial number of the scanning terminal that scans all products through a preset conversion algorithm. The delivery key is used to activate the delivery interface of the scanning terminal that performs the delivery operation.

[0181] S16. Distribute the shipping key to the scanning terminal authorized to perform the shipping operation.

[0182] 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 computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0183] Furthermore, embodiments of the present invention provide a computer program product, including a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer executes the product end-to-end logistics traceability method of any of the above embodiments.

[0184] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0185] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A method for authenticating and tracing the entire product logistics chain, characterized in that, include: Based on the origin of shipment, destination of shipment, and transit node information, anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, are generated. In response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, verification data is obtained. The verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule. Compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node; If they match, the receipt process is complete.

2. The method according to claim 1, characterized in that, The steps of generating anti-counterfeiting labels, geofences for each logistics node, and anti-counterfeiting data for each logistics node based on the shipping location information, receiving location information, and transit node information include: Configure the location information of each logistics node, which includes the location information of each logistics node and the location information of the mobile phone number of the scanning terminal; Based on the location information of each logistics node, geofencing is divided according to risk level; The location information and the mobile phone number's place of origin information are converted using preset conversion rules to generate anti-counterfeiting data.

3. The method according to claim 2, characterized in that, Before the step of obtaining verification data by scanning the anti-counterfeiting label with a terminal in response to the geofence where the logistics node is located, the method further includes: Determine whether the real-time location information of the scanning terminal is within the same address fence as the delivery address information; If they are within the same address fence, the scanning terminal is allowed to open the signature interface and activate the consistency judgment process between the verification data and the anti-counterfeiting data. If they are not in the same address fence, the scanning terminal will stop opening the signature interface, and the risk level of the geofence corresponding to the scanning terminal will be adjusted based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence.

4. The method according to claim 3, characterized in that, The steps of terminating the opening of the signature interface on the scanning terminal if the addresses are not within the same address fence, and adjusting the risk level of the geofence corresponding to the scanning terminal based on the intersection information of the scanning terminal's mobile phone number location and the corresponding geofence, include: Obtain the location information of the mobile phone number of the scanning terminal, and obtain the list of authorized regions pre-bound to the current geofence; Determine whether the location of the mobile phone number exists in the authorized region list; If it exists, maintain the current geofence level and trigger the first risk management strategy; If it does not exist, the risk level of the current geofence will be increased, and the second risk management strategy will be triggered.

5. The method according to claim 4, characterized in that, The step of determining whether the real-time location information of the scanning terminal is within the same address fence as the delivery address information includes: Obtain the authorization information of the scanning terminal, the authorization information including the main authorization feature and the authorized feature; In response to obtaining the authorized feature of the scanning terminal, the location of the authorized scanning terminal's mobile phone number is obtained; Determine whether the location of the mobile phone number exists in the authorized region list; If present, maintain the geofence level of the authorized scanning terminal and trigger the third risk handling strategy; If it does not exist, the risk level of the geofence where the authorized scanning terminal is located will be increased, and the fourth risk handling strategy will be triggered.

6. The method according to claim 2, characterized in that, The step of comparing and determining whether the verification data is consistent with the anti-counterfeiting data of the current logistics node includes: Obtain the image feature similarity between the verification data and the anti-counterfeiting data; If the similarity of the image features exceeds a preset threshold, they are judged to be identical.

7. The method according to claim 6, characterized in that, The step of generating anti-counterfeiting data by converting the location information and the mobile phone number's location information according to a preset conversion rule includes: The longitude and latitude values ​​in the location information are converted into integer sequences respectively; Based on the integer sequence and the sequential index of the current logistics node in the flow path, a first value and a second value are generated using a preset hash function. The first value, the second value, and the size of the anti-counterfeiting label reference image are moduloed, and the results are used as the x and y coordinates of the cutting start point, respectively. Based on the sequential index, the corresponding size is selected from the preset size set as the cutting size of the cutting area, and the cutting size is configured as anti-counterfeiting data.

8. The method according to claim 7, characterized in that, The step of obtaining verification data in response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located includes: The received verification data is obtained by cutting and converting the image of the anti-counterfeiting label after obtaining the abscissa and ordinate of the cutting starting point by using the longitude and latitude values ​​of the logistics node corresponding to the geofence where the scanning terminal was located when it took the picture, through a preset conversion rule.

9. The method according to claim 1, characterized in that, The step of obtaining verification data in response to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located further includes: Obtain a planar image of the side of the product bearing the anti-counterfeiting label; The planar image is preprocessed to obtain the relative position of the anti-counterfeiting label in the planar image; Based on the relative position, it is matched with the relative position of the pre-entered anti-counterfeiting code of the product in a standard planar image; If the match is successful, the signing process is allowed to be completed; if the match is unsuccessful, the scanning terminal is activated to re-verify the process.

10. The method according to claim 1, characterized in that, Before the step of generating anti-counterfeiting labels, geofences for each logistics node, and anti-counterfeiting data for each logistics node based on the shipping location information, receiving location information, and transit node information, the method further includes: Receive product production information and obtain the location information of the scanning terminal that uploaded the production information; If the geofence of the location information is inconsistent with the production scanning node associated with the production information, the third risk handling strategy is triggered. If the number of times the production information of the product is received is equal to the preset number of production scanning nodes, then a shipping key is generated based on the serial number of all scanning terminals that scan the product through a preset conversion algorithm. The shipping key is used to activate the shipping interface of the scanning terminal that performs the shipping operation. The shipping key is distributed to the scanning terminal authorized to perform the shipping operation.

11. A product end-to-end logistics traceability system, characterized in that, include: Anti-counterfeiting data generation module: used to generate anti-counterfeiting labels and geofences for each logistics node, as well as anti-counterfeiting data for each logistics node, based on shipping location information, receiving location information, and transit node information. Verification data receiving module: used to respond to the scanning operation of the anti-counterfeiting label scanning terminal at the geofence where the logistics node is located, and to obtain verification data. The verification data is obtained by converting the location information of the logistics node into the image information of the anti-counterfeiting label through a preset conversion rule. Anti-counterfeiting verification module: used to compare and determine whether the verification data is consistent with the anti-counterfeiting data of the current logistics node; The "Acceptance Completed" module is used to complete the acceptance process if the items match.

12. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as any one of the product end-to-end logistics traceability methods as claimed in claims 1 to 10.

13. A computer-readable storage medium, characterized in that, It stores a computer program capable of being loaded by a processor and executed as any one of the product end-to-end logistics traceability methods as claimed in claims 1 to 10.

14. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the product end-to-end logistics authenticity traceability method as described in any one of claims 1-10.

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