Blockchain-based warehouse receipt pledging method, device and medium

Abstract

The application discloses a warehouse receipt pledge method and device based on a blockchain, and a medium, relates to the field of warehouse receipt information management, and comprises the following steps: a warehouse node generates corresponding warehouse receipt information based on received warehouse goods; a first multi-signature address and a second multi-signature address are generated through a public key of a pledge-out node and a public key of a pledge-right node; the warehouse receipt information is written into a blockchain through the second multi-signature address; storage location information of the warehouse goods is determined, and corresponding image acquisition devices are selected according to the storage location information to monitor the warehouse goods and generate goods monitoring information; and the goods monitoring information is written into the blockchain in a corresponding manner selected from the first multi-signature address or the second multi-signature address according to the information level of different information in the goods monitoring information. The warehouse receipt generation process is simplified, and the warehouse receipt pledge business processing efficiency is improved. The tampering difficulty is increased, and the authenticity and integrity of the warehouse receipt information are ensured. Flexible and reasonable data writing and management are realized.

Description

Technical Field

[0001] This application relates to the field of warehouse receipt information management, specifically to a blockchain-based warehouse receipt pledging method, equipment, and medium. Background Technology

[0002] Warehouse receipt pledge refers to a pledge established with warehouse receipts (warehouse receipts are certificates issued by warehousing nodes to storage nodes to acknowledge receipt of stored goods) as the subject matter. It means that the pledgor delivers its warehouse receipts to the pledgee as collateral for the debt.

[0003] In traditional solutions, some aspects of warehouse receipt pledging rely on manual offline processing (for example, when a warehouse receipt is generated, various goods and pledge node information usually need to be filled in manually), which leads to complex processes, low efficiency, and the risk of tampering.

[0004] For the parts that can be processed online, the independence of the systems used by different nodes leads to data being stored in different systems. If problems occur in the warehouse receipt pledging process, it is difficult to quickly trace the data. Summary of the Invention

[0005] To address the aforementioned issues, this application proposes a blockchain-based warehouse receipt pledging method, comprising:

[0006] Based on the received stored goods, the warehousing node generates corresponding warehouse receipt information and determines the corresponding pledge node and pledgee node according to the warehouse receipt information;

[0007] A first multisignature address and a second multisignature address are generated using the public key of the pledge node and the public key of the pledgee node; wherein the first multisignature address is in 1-of-2 mode and the second multisignature address is in 2-of-2 mode.

[0008] The warehouse receipt information is written into the blockchain using the second multi-signature address;

[0009] The storage location information of the stored goods is determined, and based on the storage location information, a corresponding image acquisition device is selected to monitor the stored goods and generate goods monitoring information.

[0010] Based on the information level of different information in the cargo monitoring information, the corresponding method is selected at the first multi-signature address or the second multi-signature address to write the cargo monitoring information into the blockchain.

[0011] In one example, the warehousing node generates corresponding warehouse receipt information based on the received warehouse goods, and determines the corresponding pledge node and pledgee node based on the warehouse receipt information, specifically including:

[0012] Based on the inbound and outbound information uploaded by the inbound and outbound equipment, the warehousing node determines the received warehousing goods and the corresponding goods information.

[0013] Based on the cargo information, generate warehouse receipt information;

[0014] Determine the ownership node of the stored goods and use the ownership node as the corresponding pledge node;

[0015] Among all the preset pledge nodes, the corresponding pledge node is determined based on the feedback from the pledge node.

[0016] In one example, the warehouse receipt information is written into the blockchain via the second multi-signature address, specifically including:

[0017] Using the second multi-signature address as the target address, a write request for the warehouse receipt information is sent to the blockchain.

[0018] Using the private keys of the pledge node and the pledgee node, corresponding digital signatures are generated respectively, and the write request is signed using the digital signatures respectively.

[0019] The write request, with the digital signature attached, is broadcast and, after verification by the consensus mechanism, is written into the blockchain.

[0020] In one example, selecting a corresponding image acquisition device based on the storage location information specifically includes:

[0021] Based on the storage location information, a selection is made among all the pre-set image acquisition devices to determine the designated image acquisition device that is located in the vicinity of the storage location information and is not obstructed by the storage location information.

[0022] If a specified image acquisition device is not currently performing a monitoring task, then the specified image acquisition device will be selected as the corresponding image acquisition device.

[0023] If all specified image acquisition devices are currently performing monitoring tasks, then determine the current shooting range for each specified image acquisition device;

[0024] The simulation adjustment is performed based on the current shooting range until the task area corresponding to the monitoring task and the storage location information can be monitored simultaneously, and the corresponding simulation adjustment result is determined.

[0025] Based on the simulation adjustment results, a corresponding designated image acquisition device is selected as the image acquisition device corresponding to the storage location information.

[0026] In one example, simulation adjustments are made based on the current shooting range until the task area corresponding to the monitoring task and the storage location information can be monitored simultaneously, and the corresponding simulation adjustment result is determined. Specifically, this includes:

[0027] Based on the current shooting range, the task area corresponding to the monitoring task is marked;

[0028] The designated image acquisition device is calibrated, and the image position relationship between the stored location information and the current shooting range is determined based on the calibration results.

[0029] Based on the image position relationship, the current shooting range is simulated and adjusted by shifting the current shooting range. When the task area reaches the critical boundary of the current shooting range, the current shooting range is magnified by adjusting the focal length until the task area corresponding to the monitoring task and the storage location information are both inside the critical boundary of the current shooting range.

[0030] Determine the focal length after the simulated adjustment, as well as the translation distance during the adjustment process, as the corresponding degree of simulated adjustment.

[0031] In one example, based on the simulation adjustment results, a corresponding designated image acquisition device is selected as the image acquisition device corresponding to the storage location information, specifically including:

[0032] Among all the specified image acquisition devices, select the several specified image acquisition devices with the longest simulated focal length to form a set of undetermined devices;

[0033] In the set of pending devices, for each specified image acquisition device, a score is given based on its corresponding translation distance and the task area of ​​the currently executed monitoring task; wherein, the greater the translation distance, the more task areas, and the larger the total image area of ​​the task areas, the lower the score.

[0034] The image acquisition device with the highest score is selected as the image acquisition device corresponding to the storage location information.

[0035] In one example, monitoring the stored goods and generating goods monitoring information specifically includes:

[0036] The stored goods are monitored in real time to obtain corresponding video information;

[0037] The video information is analyzed to determine whether the status of the stored goods has changed;

[0038] If any changes occur, the video information is recorded and corresponding anomaly information is generated.

[0039] Cargo monitoring information is generated based on the video information and the anomaly information.

[0040] In one example, based on the information levels of different information in the cargo monitoring information, a corresponding method is selected at either the first multi-signature address or the second multi-signature address to write the cargo monitoring information into the blockchain, specifically including:

[0041] The video information and the abnormal information included in the cargo monitoring information are determined; wherein the abnormal information and the video information have different information levels.

[0042] Regarding the video information, during each preset monitoring period, the video information is periodically written into the blockchain via the first multi-signature address;

[0043] In response to the aforementioned abnormal information, immediately after generating the abnormal information, the abnormal information is written into the blockchain via the second multi-signature address.

[0044] On the other hand, this application also proposes a blockchain-based warehouse receipt pledging device, comprising:

[0045] At least one processor; and,

[0046] A memory communicatively connected to the at least one processor; wherein,

[0047] The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform a blockchain-based warehouse receipt pledging method as described in any of the above examples.

[0048] On the other hand, this application also proposes a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured as: the blockchain-based warehouse receipt pledging method described in any of the above examples.

[0049] The blockchain-based warehouse receipt pledging method proposed in this application can bring the following beneficial effects:

[0050] 1. Based on the received warehouse goods, warehouse receipt information is automatically generated and relevant nodes are determined, reducing manual intervention, simplifying the warehouse receipt generation process, and improving the efficiency of warehouse receipt pledge business processing.

[0051] 2. The warehouse receipt information is written to the blockchain via a second multi-signature address. The distributed ledger nature and encryption technology of the blockchain make the data difficult to tamper with once recorded. The multi-signature address mechanism requires multiple private key signatures for verification, further increasing the difficulty of tampering and ensuring the authenticity and integrity of the warehouse receipt information.

[0052] 3. By writing warehouse receipt information and cargo monitoring information into the blockchain, the blockchain's chain structure and timestamp characteristics provide complete and traceable data records. In the event of any problems, relevant information can be quickly located and retrieved through the blockchain, tracing the entire warehouse receipt pledging process.

[0053] 4. Based on the information level of the cargo monitoring information, select the corresponding method to write it to the blockchain at either the first multi-signature address or the second multi-signature address. For low-level information, the 1-of-2 mode is relatively efficient and can quickly record information; for high-level information, the 2-of-2 mode provides higher security, ensuring the reliability and integrity of important information, and enabling flexible and reasonable data writing and management. Attached Figure Description

[0054] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0055] Figure 1 This is a flowchart illustrating the blockchain-based warehouse receipt pledging method in the embodiments of this application;

[0056] Figure 2 This is a schematic diagram of a blockchain-based warehouse receipt pledging device in an embodiment of this application. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0058] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0059] like Figure 1 As shown in the embodiments of this application, a warehouse receipt pledging method based on blockchain is provided, including:

[0060] S101: Based on the received stored goods, the storage node generates corresponding warehouse receipt information and determines the corresponding pledge node and pledgee node according to the warehouse receipt information.

[0061] Storage nodes, pledge nodes, and pledgee nodes all apply for and are granted access in advance (pledgee nodes must pass KYC / AML verification and upload an electronic copy of their financial license to the blockchain for evidence storage; node access uses zero-knowledge proofs to verify the authenticity of their qualifications, protecting business privacy while meeting regulatory requirements). As nodes in the blockchain, they have the authority to write data to the blockchain. The blockchain consensus mechanism can be configured based on different needs, including Proof of Work (PoW) and Proof of Stake (PoS). Disaster recovery mechanisms can also be configured (e.g., deploying an IPFS cluster to store raw surveillance video data, with the blockchain only storing content-addressed hashes; a Byzantine Fault Tolerance (BFT) backup chain can also be configured to maintain basic services in the event of a main chain failure) and a user interaction layer (e.g., designing a zero-knowledge proof query interface to allow nodes to verify the validity of warehouse receipts without exposing detailed information).

[0062] A warehouse receipt is a certificate issued by a warehousing node to a pledgor node certifying receipt of stored goods. The warehouse receipt information includes details such as the stored goods, the pledgor node, the pledgee node, and timestamp information. It should also include a unique digital fingerprint (e.g., SHA-256 hash value), a smart contract address association field, and a legal validity declaration field. The warehouse receipt can be time-anchored using the RFC 3161 timestamp protocol to ensure the legal validity of the electronic evidence. The pledgor node, as the owner of the stored goods, pledges the warehouse receipt to the pledgee node (usually a bank node) for business needs. Based on the agreement between the pledgor and pledgee nodes, one or more parties meeting the agreement's stipulations can use the warehouse receipt to collect the stored goods from the warehousing node.

[0063] Specifically, the warehouse of the storage node is equipped with inbound and outbound equipment. When stored goods enter or leave the warehouse, they need to be scanned through the inbound and outbound equipment. The scan obtains the inbound and outbound information (including outbound information and inbound information), which is then uploaded to the server corresponding to the storage node, or directly uploaded to the blockchain.

[0064] The warehousing node determines the received warehouse goods based on the inbound / outbound information, and determines the corresponding goods information based on the content contained in the inbound / outbound information.

[0065] Based on the cargo information, warehouse receipt information is generated. The warehouse receipt information must at least contain cargo information, and it is also necessary to determine the ownership node of the stored cargo. This information is usually also included in the inbound and outbound information, and the ownership node is used as the corresponding pledge node.

[0066] Because pledge nodes need to possess certain qualifications, several pledge nodes are pre-set and admitted to the blockchain, or they are confirmed by the storage node. In this case, the storage node, based on feedback from the pledgor node (e.g., confirmation from the pledgor node of which node is the target of its current pledge), determines the corresponding pledge node from among all the pre-set pledge nodes, thereby perfecting the warehouse receipt information and obtaining complete warehouse receipt information.

[0067] S102: Generate a first multi-signature address and a second multi-signature address using the public key of the pledge node and the public key of the pledgee node; wherein the first multi-signature address is in 1-of-2 mode and the second multi-signature address is in 2-of-2 mode.

[0068] A multisignature address is an address associated with multisignature technology, generated from multiple public keys using a specific algorithm. A multisignature address is bound to multiple public keys and defined signature rules to implement transactions or operations requiring multiple signatures or partial signatures. For example, a deterministic multisignature address can be generated using a corresponding key sorting standard (e.g., BIP-67). Simultaneously, the Gnosis Safe smart contract model can be used to set up multisignature verification logic, and the Shamir secret sharing scheme can be used to segment private key fragments and store them in an HSM hardware security module for key management.

[0069] After a multi-signature address is written into the blockchain, if the initiating node wants to perform operations related to the multi-signature address, such as reading data, it can first construct a request containing detailed operation information and specify the multi-signature address as the sender of the request or the key address involved.

[0070] Then, according to the signature rules set for the multi-signature address, the node needs to collect a sufficient number of private key signatures. The signature rule is m-of-n mode, meaning that among n nodes generating the multi-signature address, at least m nodes' private key signatures are required to execute the corresponding operation. 1-of-2 mode means that for a multi-signature address generated by 2 nodes, at least one node's private key signature is required to execute the corresponding operation. 2-of-2 mode means that for a multi-signature address generated by 2 nodes, both nodes' private key signatures are required to execute the corresponding operation. Compared to 1-of-2 mode, 2-of-2 mode has stricter verification of the request.

[0071] After the initiating node verifies the signature of the private key, it broadcasts the request. Once consensus is reached, the smart contract automatically executes the operation corresponding to this request.

[0072] S103: The warehouse receipt information is written into the blockchain using the second multi-signature address.

[0073] For warehouse receipt information, it involves the pledge rights of both the pledging node and the pledgee node, which is important to both parties. Therefore, a second multi-signature address with stricter verification is chosen. Only after both nodes have no objection to the warehouse receipt information will the warehouse receipt information be written into the blockchain for storage.

[0074] Specifically, during the write operation, the second multi-signature address is used as the target address to send a write request for warehouse receipt information to the blockchain. Digital signatures (i.e., the private key signatures mentioned above) are generated using the private keys of the pledgor and pledgee nodes, and the write request is then signed using these digital signatures. The write request with the attached digital signature is broadcast, and after verification by the consensus mechanism, it is written into the blockchain.

[0075] In addition, a verification mechanism can be set in the blockchain. After a transaction is broadcast (that is, a request to write warehouse receipt information is broadcast), it must wait for at least 6 blocks to confirm to ensure irreversibility. A rollback mechanism can also be set in the smart contract. When the double signature verification fails, the Oracle service will be automatically triggered to conduct off-chain arbitration.

[0076] S104: Determine the storage location information of the stored goods, and select a corresponding image acquisition device based on the storage location information to monitor the stored goods and generate goods monitoring information.

[0077] As a storage node, it may simultaneously store goods issued by multiple different pawning nodes, thus requiring the determination of the storage location information of the goods. This storage location information can include which warehouse the goods belong to and their specific location within that warehouse.

[0078] The warehouse node is equipped with multiple image acquisition devices in the storage area. These devices are equipped with a TEE (Trusted Execution Environment) that provides real-time encrypted video streams (AES-256-GCM) and uses a Merkle Patricia Trie structure to store monitoring data hashes, enabling rapid tamper detection and ensuring the security of the monitoring data. Different image acquisition devices monitor different storage locations, generating cargo monitoring information (which may include monitored video information and anomaly information obtained from video analysis) to prevent abnormal situations from occurring during storage (e.g., human damage, movement). Selecting appropriate image acquisition devices ensures more accurate monitoring of the stored goods.

[0079] Specifically, when selecting an image acquisition device, the device is first selected from all pre-set image acquisition devices based on the storage location information.

[0080] As mentioned above, multiple image acquisition devices are installed in the storage area. The location coordinates of these devices can be pre-stored to determine which image acquisition devices are located within a pre-set distance (e.g., 5 meters) of the storage location information (determined based on the location coordinates of the inbound / outbound equipment). It is also necessary to ensure that no image acquisition devices obstruct the storage location information to prevent occlusion during monitoring. This occlusion determination can be achieved through LiDAR point cloud analysis, constructing a 3D spatial topology model to determine the straight-line path between the image acquisition device and the storage location information, and then checking for any other stored goods along that path to identify any obstructions.

[0081] For ease of description, the image acquisition device selected at this time will be referred to as the designated image acquisition device.

[0082] If a specified image acquisition device is not currently performing a monitoring task, it can be directly selected as the corresponding image acquisition device for monitoring the current warehouse goods.

[0083] If all specified image acquisition devices are currently performing monitoring tasks, then for each specified image acquisition device, determine the current shooting range. The shooting range can be determined based on the shooting direction (which can be determined based on the pan-tilt angle) and focal length of the current specified image acquisition device.

[0084] During the process of adjusting the shooting range (e.g., by adjusting the pan-tilt angle or the focal length range), the image acquisition device may cause image blurring or over-adjustment, which may negatively impact the monitoring of warehouse goods that have already been monitored.

[0085] Therefore, when selecting an image acquisition device, simulation adjustments are made based on the current shooting range of the designated image acquisition device until it is possible to simultaneously monitor the task area and storage location information corresponding to the monitoring task. In other words, it is possible to monitor the warehouse goods in the current new monitoring task while simultaneously monitoring the already executed monitoring task, thus completing the simulation adjustment. At this point, the corresponding simulation adjustment result is determined.

[0086] Based on the simulation adjustment results, select the corresponding designated image acquisition device as the image acquisition device for storing the location information. When selecting, try to choose the designated image acquisition device with the smallest adjustment degree in the simulation results to reduce the negative impact of the adjustment process on the already executed monitoring tasks.

[0087] Furthermore, during the simulation adjustment, the task area corresponding to the monitoring task is first marked according to the current shooting range. That is, in the two-dimensional image obtained by monitoring, the task area of ​​the currently executed monitoring task (obtained by the location area of ​​the warehouse goods of the monitoring task in the two-dimensional image) is marked.

[0088] Camera calibration is the process of determining the geometric and optical parameters (including intrinsic and extrinsic parameters) and distortion coefficients of a camera (i.e., the image acquisition device). Through camera calibration, the relationship between camera image pixel coordinates and three-dimensional world coordinates can be established.

[0089] The image position relationship between the stored location information and the current shooting range is determined based on the calibration results. In other words, the coordinates corresponding to the stored location information in the actual space can be transformed into coordinates in the two-dimensional image. The stored location information is then mapped to the two-dimensional image to obtain the corresponding image position relationship, which in turn gives the image position information of the stored location information in the two-dimensional image.

[0090] Based on the image positional relationships, the current shooting range is simulated and adjusted. Generally, a shorter focal length is considered to result in a larger shooting range, but lower shooting accuracy, which is not conducive to monitoring. Therefore, during the simulation adjustment, the current shooting range is first shifted to test whether it is possible to simultaneously monitor the already executed monitoring tasks and the newly added warehouse goods.

[0091] Simulated adjustment refers to not actually adjusting the image, but rather creating a virtual two-dimensional space. Within this space, coordinates such as the current shooting range and storage location information are mapped, and adjustments are then made within this virtual space. Translation adjustment involves shifting the current shooting range, while focal length adjustment keeps the center of the current shooting range constant and enlarges or reduces the current shooting range accordingly based on the magnitude of the focal length adjustment.

[0092] If the attempt is successful, no further adjustments are needed. If it fails, that is, when the task area reaches the critical boundary of the current shooting range (which is the current shooting range), it is no longer possible to adjust the current shooting range by translation. At this time, the current shooting range is magnified by adjusting the focal length (by shortening the focal length, the shooting range is increased, which also increases the current shooting range) until the task area corresponding to the monitoring task and the storage location information are both within the critical boundary of the current shooting range.

[0093] The panning-zooming process can be repeated multiple times. For example, each time the panning reaches a critical boundary, the current shooting range is zoomed in by a fixed degree, and then the panning is repeated to determine if simultaneous monitoring can be achieved through panning. If this is still not possible, the zooming-panning process is repeated.

[0094] At this point, the simulated adjusted focal length and the translation distance during the adjustment process are determined as the corresponding degree of simulation adjustment, so as to facilitate the subsequent selection of the corresponding designated image acquisition device.

[0095] Specifically, among all the designated image acquisition devices, several devices with the longest simulated adjusted focal lengths are selected to form a set of devices to be determined. The longer the focal length, the smaller the corresponding shooting range, which in turn results in a smaller monitoring range, a relatively clearer image, and less noise during image analysis.

[0096] Within the set of pending devices, each designated image acquisition device is scored based on its corresponding translation distance and the task area of ​​the currently executed monitoring task. Weights are pre-assigned to the translation distance, the number of task areas, and the total image area of ​​the task areas. A greater translation distance increases the probability of image blurring and the negative impact on monitoring, resulting in a lower score. Similarly, a larger number of task areas and a larger total image area mean more content needs to be monitored simultaneously, placing a higher load on the designated image acquisition device and potentially affecting the analysis of anomalies during monitoring, thus also resulting in a lower score.

[0097] At this point, selecting the designated image acquisition device with the highest score as the image acquisition device corresponding to the storage location information can minimize the negative impact of adjusting the current shooting range while ensuring the shooting quality after adjustment.

[0098] S105: Based on the information level of different information in the cargo monitoring information, select the corresponding method at the first multi-signature address or the second multi-signature address to write the cargo monitoring information into the blockchain.

[0099] Compared to warehouse receipt information, cargo monitoring information has a lower level of strictness. Therefore, when writing cargo monitoring information, it can be written in a hierarchical manner to appropriately reduce the workload of the corresponding nodes.

[0100] Specifically, real-time monitoring of stored goods is conducted to obtain corresponding video information, which can then be used as part of the goods monitoring information.

[0101] Video information is analyzed to determine whether the condition of stored goods has changed. The video analysis process can be implemented using methods such as inter-frame difference (calculating the difference between two frames) and deep learning models (training models through deep learning networks such as convolutional neural networks and recurrent neural networks for recognition).

[0102] If any changes occur, the video information will be recorded and corresponding abnormal information will be generated. This abnormal information will be used as part of the cargo monitoring information, and an alarm will be triggered through the alarm devices installed in the warehouse.

[0103] At this point, when writing cargo monitoring information to the blockchain, the video information and anomaly information included in the cargo monitoring information are determined; among them, anomaly information and video information have different information levels. Generally speaking, anomaly information refers to the alarm information generated after the detection of warehouse goods being moved, so it is relatively more important and has a higher information level, while video information has a lower video level. For example, a CNN-LSTM hybrid model can be built to classify the anomaly level (level 1-5) through time series analysis.

[0104] At this point, for video information, in each preset monitoring period (for example, the basic period is 24 hours, which is automatically shortened to 1 hour when abnormal information is detected), the video information is periodically written into the blockchain through the first multi-signature address. That is, when writing, the video information can be written as long as one party agrees, and when reading, any party can read it at any time.

[0105] Regarding anomalous information, upon its generation, due to its higher information priority, it is immediately written into the blockchain via a second multi-signature address. This writing requires mutual authentication by both parties, ensuring the timeliness of both parties' access to the anomalous information and their acceptance of it. The anomalous information can be a text description or a screenshot of video information.

[0106] 1. Based on the received warehouse goods, warehouse receipt information is automatically generated and relevant nodes are determined, reducing manual intervention, simplifying the warehouse receipt generation process, and improving the efficiency of warehouse receipt pledge business processing.

[0107] 2. The warehouse receipt information is written to the blockchain via a second multi-signature address. The distributed ledger nature and encryption technology of the blockchain make the data difficult to tamper with once recorded. The multi-signature address mechanism requires multiple private key signatures for verification, further increasing the difficulty of tampering and ensuring the authenticity and integrity of the warehouse receipt information.

[0108] 3. By writing warehouse receipt information and cargo monitoring information into the blockchain, the blockchain's chain structure and timestamp characteristics provide complete and traceable data records. In the event of any problems, relevant information can be quickly located and retrieved through the blockchain, tracing the entire warehouse receipt pledging process.

[0109] 4. Based on the information level of the cargo monitoring information, select the corresponding method to write it to the blockchain at either the first multi-signature address or the second multi-signature address. For low-level information, the 1-of-2 mode is relatively efficient and can quickly record information; for high-level information, the 2-of-2 mode provides higher security, ensuring the reliability and integrity of important information, and enabling flexible and reasonable data writing and management.

[0110] like Figure 2 As shown in the embodiments of this application, a blockchain-based warehouse receipt pledging device is also provided, including:

[0111] At least one processor; and,

[0112] A memory communicatively connected to the at least one processor; wherein,

[0113] The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform a blockchain-based warehouse receipt pledging method as described in any of the above embodiments.

[0114] This application also provides a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured as: the blockchain-based warehouse receipt pledging method described in any of the above embodiments.

[0115] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device and medium embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the description of the method embodiments.

[0116] The devices and media provided in this application are one-to-one with the methods. Therefore, the devices and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0117] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A blockchain-based warehouse receipt pledging method, characterized in that, include: Based on the received stored goods, the warehousing node generates corresponding warehouse receipt information and determines the corresponding pledge node and pledgee node according to the warehouse receipt information; A first multisignature address and a second multisignature address are generated using the public key of the pledge node and the public key of the pledgee node; wherein the first multisignature address is in 1-of-2 mode and the second multisignature address is in 2-of-2 mode. The warehouse receipt information is written into the blockchain using the second multi-signature address; The storage location information of the stored goods is determined, and based on the storage location information, a corresponding image acquisition device is selected to monitor the stored goods and generate goods monitoring information. Based on the information level of different information in the cargo monitoring information, the corresponding method is selected from the first multi-signature address or the second multi-signature address to write the cargo monitoring information into the blockchain. Based on the information levels of different information in the cargo monitoring information, a corresponding method is selected from the first multi-signature address or the second multi-signature address to write the cargo monitoring information into the blockchain, specifically including: The video information and abnormal information included in the cargo monitoring information are determined; wherein the abnormal information and the video information have different information levels. Regarding the video information, during each preset monitoring period, the video information is periodically written into the blockchain via the first multi-signature address; In response to the aforementioned abnormal information, immediately after generating the abnormal information, the abnormal information is written into the blockchain via the second multi-signature address.

2. The method according to claim 1, characterized in that, Based on the received goods, the warehousing node generates corresponding warehouse receipt information and determines the corresponding pledge node and pledgee node according to the warehouse receipt information, specifically including: Based on the inbound and outbound information uploaded by the inbound and outbound equipment, the warehousing node determines the received warehousing goods and the corresponding goods information. Based on the cargo information, generate warehouse receipt information; Determine the ownership node of the stored goods and use the ownership node as the corresponding pledge node; Among all the preset pledge nodes, the corresponding pledge node is determined based on the feedback from the pledge node.

3. The method according to claim 1, characterized in that, The warehouse receipt information is written into the blockchain via the second multi-signature address, specifically including: Using the second multi-signature address as the target address, a write request for the warehouse receipt information is sent to the blockchain. Using the private keys of the pledge node and the pledgee node, corresponding digital signatures are generated respectively, and the write request is signed using the digital signatures respectively. The write request, with the digital signature attached, is broadcast and, after verification by the consensus mechanism, is written into the blockchain.

4. The method according to claim 1, characterized in that, Based on the storage location information, a corresponding image acquisition device is selected, specifically including: Based on the storage location information, a selection is made among all the pre-set image acquisition devices to determine the designated image acquisition device that is located in the vicinity of the storage location information and is not obstructed by the storage location information. If a specified image acquisition device is not currently performing a monitoring task, then the specified image acquisition device will be selected as the corresponding image acquisition device. If all specified image acquisition devices are currently performing monitoring tasks, then determine the current shooting range for each specified image acquisition device; The simulation adjustment is performed based on the current shooting range until the task area corresponding to the monitoring task and the storage location information can be monitored simultaneously, and the corresponding simulation adjustment result is determined. Based on the simulation adjustment results, a corresponding designated image acquisition device is selected as the image acquisition device corresponding to the storage location information.

5. The method according to claim 4, characterized in that, The simulation is adjusted based on the current shooting range until the task area corresponding to the monitoring task and the storage location information can be monitored simultaneously, and the corresponding simulation adjustment result is determined, specifically including: Based on the current shooting range, the task area corresponding to the monitoring task is marked; The designated image acquisition device is calibrated, and the image position relationship between the stored location information and the current shooting range is determined based on the calibration results. Based on the image position relationship, the current shooting range is simulated and adjusted by shifting the current shooting range. When the task area reaches the critical boundary of the current shooting range, the current shooting range is magnified by adjusting the focal length until the task area corresponding to the monitoring task and the storage location information are both inside the critical boundary of the current shooting range. Determine the focal length after the simulated adjustment, as well as the translation distance during the adjustment process, as the corresponding degree of simulated adjustment.

6. The method according to claim 5, characterized in that, Based on the simulation adjustment results, a corresponding designated image acquisition device is selected as the image acquisition device corresponding to the storage location information, specifically including: Among all the specified image acquisition devices, select the several specified image acquisition devices with the longest simulated focal length to form a set of undetermined devices; In the set of pending devices, for each specified image acquisition device, a score is given based on its corresponding translation distance and the task area of ​​the currently executed monitoring task; wherein, the greater the translation distance, the more task areas, and the larger the total image area of ​​the task areas, the lower the score. The image acquisition device with the highest score is selected as the image acquisition device corresponding to the storage location information.

7. The method according to claim 1, characterized in that, The stored goods are monitored to generate goods monitoring information, specifically including: The stored goods are monitored in real time to obtain corresponding video information; The video information is analyzed to determine whether the status of the stored goods has changed; If any changes occur, the video information is recorded and corresponding anomaly information is generated. Cargo monitoring information is generated based on the video information and the anomaly information.

8. A blockchain-based warehouse receipt pledging device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform: the blockchain-based warehouse receipt pledging method according to any one of claims 1 to 7.

9. A non-volatile computer storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are set as follows: the blockchain-based warehouse receipt pledging method as described in any one of claims 1 to 7.

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