Unmanned aerial vehicle cargo transportation identification method, system and computer device

Abstract

The application relates to a UAV cargo transportation identification method, system and computer device. The method comprises the following steps: obtaining initial label information of cargo by triggering an in-cabin reader first, laying a foundation for subsequent authentication and monitoring; authenticating label password area data and monitoring the state of in-transit cargo, so as to guarantee the safety of the cargo in transportation; then authenticating the UAV label anti-fake through a ground reader, so as to ensure the reliability of the transportation subject; finally, target label information is obtained to determine the delivery situation, forming a perfect closed loop of initial loading-in-transit monitoring-remote verification-delivery confirmation, and improving the safety and efficiency of low-altitude logistics.

Description

Technical Field

[0001] This application relates to the fields of Internet of Things and smart logistics technology, and in particular to a method, system and computer equipment for identifying unmanned aerial vehicle (UAV) cargo transportation. Background Technology

[0002] Drone delivery, with its advantage of overcoming the limitations of ground transportation, is increasingly being used in last-mile urban areas, remote regions, and the transport of emergency supplies. Electronic tagging (RFID) technology, due to its contactless identification characteristics, has become a potential solution for low-altitude logistics tracking; however, simple labeling methods are difficult to adapt to the complexity of scenarios, making technological upgrades urgently needed.

[0003] Currently, basic applications are facing multiple bottlenecks: the association between cargo and drones relies on manual data entry on the ground, and the lack of a real-time verification mechanism easily leads to information mismatches; after the cabin doors are closed, traditional labeling cannot achieve real-time monitoring of cargo movement, falling, and other in-cabin status; inspection requires drone landing operations, which severely restricts logistics efficiency. Meanwhile, low-altitude logistics has extremely high requirements for data real-time performance and reliability, but existing RFID applications lack sufficient coordination with intelligent scheduling, air-to-ground communication, and other systems, making it difficult to support the needs of large-scale operations. Therefore, upgrading RFID technology towards dynamic binding and rapid aerial reading has become a key support for the industry's development. Summary of the Invention

[0004] Based on this, the purpose of this application is to provide a method for real-time monitoring and anti-theft / swapping inspection of drone logistics that enables full traceability, status awareness, and early warning of anomalies from loading to delivery, in order to solve the aforementioned technical problems.

[0005] Firstly, this application provides a method for identifying cargo transported by unmanned aerial vehicles (UAVs). This includes:

[0006] The in-cabin reader is triggered to obtain the initial tag information of the loaded cargo; the initial tag information includes password area data;

[0007] The data in the password area is tagged and authenticated, and the status of the cargo is monitored during the transport by the drone.

[0008] The ground reader is triggered to acquire the drone tag information and perform anti-counterfeiting authentication on the drone tag information;

[0009] The in-cabin reader is triggered to retrieve the target tag information of the cargo again to determine the delivery status of the cargo.

[0010] In one embodiment, the initial tag information further includes key storage area data; the key storage area data includes anti-counterfeiting ciphertext and a first random number; the anti-counterfeiting ciphertext is determined based on the key storage area data and the first random number; the tag authentication of the key storage area data includes: decrypting the anti-counterfeiting ciphertext to obtain plaintext including a second random number; and performing tag authentication based on the first random number and the second random number.

[0011] In one embodiment, monitoring the cargo status of a drone during transit includes: obtaining a list of actually loaded cargo when tag authentication is successful, and triggering the drone to perform transit when the list of actually loaded cargo matches a preset task list; triggering the in-cabin reader to obtain candidate tag information of the cargo during transit according to a preset cycle; and determining the cargo status based on the candidate tag information under different cycles.

[0012] In one embodiment, the cargo status includes loss status and attitude status; determining the cargo status based on candidate tag information under different periods includes: comparing the actual loaded cargo list with the candidate tag information under different periods to determine the loss status of cargo in transit; determining the signal strength changes of candidate tag information under different periods, and determining the attitude status of cargo in transit based on the signal strength changes.

[0013] In one embodiment, the drone tag information includes identification area data; anti-counterfeiting authentication of the drone tag information includes: generating a query request and obtaining drone waybill information; identifying the encrypted identifier in the identification area data through a preset encoding rule; and performing anti-counterfeiting authentication on the password area data in the drone tag information based on the drone waybill information and the encrypted identifier.

[0014] In one embodiment, both the initial label information and the target label information include coded area data; the method further includes: determining the target coding rule corresponding to the coded area data, and verifying the coded area data through the target coding rule; when the verification is successful, changing the shipping information in the database according to the preset task list; and verifying the status of the goods data in the coded area data through the shipping information.

[0015] Secondly, this application also provides a drone cargo transportation identification system. The system includes a cargo subsystem, a drone subsystem, a ground base station subsystem, and an anti-counterfeiting verification platform, wherein:

[0016] The cargo subsystem is used to trigger the in-cabin reader to obtain the initial tag information of the loaded cargo; the initial tag information includes password area data;

[0017] The drone subsystem is used to monitor the status of cargo during drone transport.

[0018] The ground base station subsystem is used to trigger the ground reader to obtain the UAV tag information;

[0019] The anti-counterfeiting verification platform is used to perform tag authentication on the password area data and anti-counterfeiting authentication on the drone tag information;

[0020] The cargo subsystem is used to trigger the in-cabin reader to retrieve the target tag information of the cargo again and determine the cargo delivery status.

[0021] In one embodiment, the cargo subsystem includes a cargo electronic tag and a wireless communication module; the drone subsystem includes a drone electronic tag, a tag reader / writer mounted on the drone, and an airborne control unit, wherein the tag reader / writer collects information from the cargo electronic tag and controls the airborne control unit; and the ground base station subsystem includes a ground reader / writer and a backend server.

[0022] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described UAV cargo transportation identification method.

[0023] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-described UAV cargo transportation identification method.

[0024] The aforementioned drone cargo transportation identification method, system, computer equipment, and readable storage medium first trigger the in-cabin reader to obtain the initial cargo tag information, laying the foundation for subsequent authentication and monitoring; then authenticate the tag password area data and monitor the cargo status en route to ensure cargo safety during transportation; next, authenticate the drone tag anti-counterfeiting through the ground reader to ensure the reliability of the transport entity; finally, obtain the target tag information to determine the delivery status, forming a perfect closed loop of initial loading - en route monitoring - remote verification - delivery confirmation, improving the safety and efficiency of low-altitude logistics. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the structure of a drone cargo transportation identification system in one embodiment;

[0026] Figure 2 This is a flowchart illustrating a drone cargo transportation identification method in one embodiment;

[0027] Figure 3 This is a schematic diagram of the principle of a drone cargo transportation identification system in one embodiment;

[0028] Figure 4This is a schematic diagram of the data area of ​​an electronic tag for goods in one embodiment;

[0029] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0031] This application aims to address the technical challenges of drone cargo transportation identification during drone transport, including drone identification, real-time monitoring of cargo loading status, dynamic verification during drone flight, and remote inspection and supervision of transported goods in conjunction with customs procedures, through a drone cargo transportation identification system based on UHF RFID technology. Therefore, this application designs a drone cargo transportation identification system, which includes a cargo subsystem, a drone subsystem, a ground base station subsystem, and an anti-counterfeiting verification platform.

[0032] The system comprises: a cargo subsystem, used to trigger the in-cabin reader to obtain the initial tag information of the loaded cargo; the initial tag information includes the password area data; a drone subsystem, used to monitor the cargo status of the drone during transit; a ground base station subsystem, used to trigger the ground reader to obtain the drone tag information; an anti-counterfeiting verification platform, used to perform tag authentication on the password area data and anti-counterfeiting authentication on the drone tag information; and a cargo subsystem, used to trigger the in-cabin reader to obtain the target tag information of the cargo again to determine the cargo delivery status.

[0033] like Figure 1 As shown, Figure 1 This is a schematic diagram of a drone cargo transportation identification system in one embodiment. Cargo management is achieved through a cargo subsystem, where an electronic tag serves as the unique identifier for each cargo. Automatic tag scanning ensures efficient and convenient customs clearance. Drone management is achieved through a drone subsystem, where an electronic tag serves as the drone's identifier, and onboard tag readers monitor cargo information in transit. Once the identification and verification results are uploaded to the management platform, the system can achieve cargo and drone identity authentication and tracking, flight safety management and monitoring, privacy protection and data security, automated inventory management, and improved supply chain transparency.

[0034] Therefore, this system realizes a low-altitude digital management and service platform that integrates RFID and drone systems, enabling automatic drone identification, real-time cargo status monitoring, and seamless inspection throughout the entire process. Based on RFID, a virtual port is constructed as the core of intelligent supervision for cross-border logistics, creating an efficient cross-border logistics model of "one declaration, one inspection, and one release." The sensing technology is integrated into the business process, incorporating RFID technology into the entire "loading-transportation-inspection-delivery" business process of drone logistics, and defining specific methods and steps for each step based on RFID scanning, forming a complete and automated management method, rather than fragmented technology applications.

[0035] In one embodiment, the cargo subsystem includes a cargo electronic tag and a wireless communication module; the drone subsystem includes a drone electronic tag, a tag reader / writer mounted on the drone, and an airborne control unit, wherein the tag reader / writer collects information from the cargo electronic tag and controls the airborne control unit; and the ground base station subsystem includes a ground reader / writer and a backend server.

[0036] Specifically, the drone subsystem includes an anti-counterfeiting and encrypted electronic tag installed on the drone's shell as an electronic license plate, an integrated tag reader / writer mounted on the bottom of the drone, and an onboard control unit connected to the flight control system. During flight missions, the unique code tags of the drone and cargo are automatically and dynamically bound and verified, ensuring that "the cargo matches the manifest." The cargo subsystem affixes or embeds anti-counterfeiting and encrypted electronic tags to each piece of cargo. The tag reader / writer mounted on the drone triggers an in-cabin reader / writer to scan the cargo tags in real time during flight, collecting information from the cargo tags. Cargo tag data and status information are reported to the ground-based server in real time via a wireless communication module. This provides unprecedented transparency regarding the status of cargo in transit.

[0037] The ground base station subsystem includes RFID base stations and backend servers set up at drone take-off and landing points and customs inspection routes. RFID base stations are typically UHF devices, possessing long-range, multi-tag group reading capabilities. Drones do not need to land or stop when approaching take-off and landing points or routes. The ground readers in the RFID base stations deployed at the site can automatically read the electronic tags of drones flying through their identification area from a distance (e.g., 15-20 meters), thereby quickly completing identity authentication, flight recording, and regulatory inspection, greatly improving the efficiency of cross-border transportation.

[0038] Therefore, this system proposes a cloud-based collaborative remote inspection method, employing a "ground-air-cloud" collaborative approach. Ground equipment is only responsible for collecting the UAV's identity ID; complex cargo information matching and authorization checks are completed in the cloud. This method enables non-contact, non-stop, and remote inspection of high-speed moving targets, representing a significant innovation in the field of low-altitude cross-border logistics.

[0039] In one embodiment, such as Figure 2 As shown, a method for identifying cargo transported by drones is provided, which is implemented through a label anti-counterfeiting authentication system, including the following steps:

[0040] Step 202: Trigger the in-cabin reader to obtain the initial tag information of the loaded cargo.

[0041] All cargo inside the cabin is affixed with RFID electronic tags; the initial tag information in the RFID electronic tags includes password area data, which is data read from the User area of ​​the electronic tag.

[0042] Specifically, such as Figure 3 As shown, Figure 3 This is a schematic diagram illustrating the principle of a drone cargo transportation identification system. After initial loading is completed and the drone's cargo door is closed, the drone's onboard reader is activated and reads the initial tag information attached to all cargo within the cargo compartment at once. The initial tag information typically contains multiple data areas, such as... Figure 4 The data shown includes TID area data, EPC area data, etc. Figure 4 This is a schematic diagram of the data area of ​​an electronic tag for goods in one embodiment.

[0043] In one embodiment, such as Figure 4 The cargo electronic tags shown, such as the C899 electronic tag, not only have all the functions of ordinary electronic tags, but also have a built-in unique key "fingerprint". Through hardware encryption technology, it prevents tag forgery and data tampering, and provides four lines of defense (TID identifier + random number + ciphertext + special instructions) to ensure data authenticity, fundamentally eliminating the possibility of chip forgery and tampering.

[0044] Step 204: Tag authentication is performed on the data in the password area, and the cargo status is monitored during the transport by the drone.

[0045] Specifically, after reading the initial tag information, it is uploaded to the anti-counterfeiting verification platform via the wireless communication module. The anti-counterfeiting verification platform performs tag authentication on the data in the password area to verify the authenticity and validity of the tag. When the tag authentication is successful, the actual loaded cargo list is obtained. Finally, the drone is triggered to carry out in-transit transportation based on the actual loaded cargo list. During the drone's flight, the in-cabin reader is triggered again to read the candidate tag information of the cargo during in-transit transportation. Then, based on the candidate tag information and the actual loaded cargo list, the cargo information and cargo status during real-time transportation by the drone are monitored to determine whether the cargo is lost, whether the cargo's "attitude" has shifted, or whether it has tipped over.

[0046] In one embodiment, the anti-counterfeiting verification system software, database, and server with independently deployed HSM cryptographic machine devices in the anti-counterfeiting verification platform can be used to implement anti-counterfeiting verification services. The HSM cryptographic machine, a host security module based on modern cryptographic technology, is a hardware device with physical security protection measures. It has an autonomous key management mechanism, encapsulating the cryptographic operation process internally to provide secure application-layer cryptographic services for business systems, including key management, message verification, data encryption, signature generation and verification, etc., ensuring the security, validity, integrity, and non-repudiation of the entire process of business data generation, transmission, reception, and processing.

[0047] Step 206: Trigger the ground reader to obtain the drone tag information and perform anti-counterfeiting authentication on the drone tag information.

[0048] Specifically, when a drone flies over a ground-based RFID checkpoint, it triggers a ground reader to remotely read the drone's electronic tag and upload the tag information to an anti-counterfeiting verification platform. The platform then performs anti-counterfeiting authentication on the data area of ​​the drone's tag. Once authentication is successful, rapid inspection and release can be completed without intercepting the drone. In simple terms, the anti-counterfeiting verification platform can be deployed in, but is not limited to, a checkpoint management system, a backend server, or other cloud platforms.

[0049] Step 208: Trigger the in-cabin reader to retrieve the target tag information of the cargo again to determine the cargo delivery status.

[0050] Specifically, when the drone arrives at its destination and the cargo door opens, the in-cabin reader is triggered to scan the target tag information of the cargo again. If the scanned target tag information indicates "empty cargo", the cargo "delivery successful" signal is generated by combining the relevant information of the destination and uploaded to the cloud platform, thus closing the loop of this waybill process.

[0051] In the aforementioned drone cargo transportation identification method, the initial tag information of the cargo is obtained by first triggering the in-cabin reader, laying the foundation for subsequent authentication and monitoring; then, the data in the tag password area is authenticated and the status of the cargo in transit is monitored to ensure the safety of the cargo during transportation; next, the anti-counterfeiting of the drone tag is authenticated by the ground reader to ensure the reliability of the transport entity; finally, the target tag information is obtained to determine the delivery status, forming a perfect closed loop of initial loading - in-transit monitoring - remote verification - delivery confirmation, which improves the safety and efficiency of low-altitude logistics.

[0052] In one embodiment, tag authentication of the password area data includes: decrypting the anti-counterfeiting ciphertext to obtain plaintext including a second random number; and performing tag authentication based on the first random number and the second random number.

[0053] The initial tag information also includes key storage area data, see reference. Figure 4 As shown; the password area data includes anti-counterfeiting ciphertext and a first random number; the anti-counterfeiting ciphertext is determined based on the key storage area data and the first random number.

[0054] Specifically, when reading electronic tags on loaded goods, the in-cabin reader generates a first random number before each reading operation. This first random number is sent as a parameter to the electronic tag within the radio frequency range via an RF signal. The electronic tag on the loaded goods receives the RF signal and, upon receiving the first random number from the reader, encrypts it using a built-in key in its key storage area to obtain anti-counterfeiting ciphertext. The electronic tag stores the first random number and the generated anti-counterfeiting ciphertext in its password area, and combines this with data from other areas to send the initial tag information back to the reader. The in-cabin reader then reports this initial tag information to the anti-counterfeiting verification platform. The anti-counterfeiting verification platform parses the tag information from the in-cabin reader. The verification logic involves decrypting the anti-counterfeiting ciphertext to obtain plaintext including a second random number, and verifying whether the first random number matches the decrypted second random number. If they match, the tag authentication is successful.

[0055] In this embodiment, the anti-counterfeiting ciphertext is first obtained by encrypting the data using a first random number, and then the plaintext containing a second random number is decrypted. This achieves tag authentication using two random numbers, determining whether the drone should take off. Therefore, dual random number verification strengthens tag authenticity verification, and combined with key protection, enhances anti-counterfeiting security and ensures reliable information retrieval.

[0056] In one embodiment, monitoring the cargo status of a drone during transit includes: obtaining a list of actually loaded cargo when tag authentication is successful, and triggering the drone to perform transit when the list of actually loaded cargo matches a preset task list; triggering the in-cabin reader to obtain candidate tag information of the cargo during transit according to a preset cycle; and determining the cargo status based on the candidate tag information under different cycles.

[0057] Specifically, when tag authentication is successful, a list of actual loaded goods is obtained. This list is then compared with a pre-set task list. If they match, a verification success command is generated, authorizing the drone to proceed with in-transit transportation. If they do not match, a verification failure alarm is generated, prompting staff to open the cabin for a second check. During the drone's flight, the in-cabin reader is triggered again at preset intervals to read candidate tag information for the goods in transit. Then, based on the candidate tag information and the actual loaded goods list at different intervals, the drone dynamically monitors the cargo status during transit to determine its condition.

[0058] In this embodiment, the actual list of loaded goods is first obtained through tag authentication. Transportation is triggered once it matches the preset task list to ensure order matching. Then, candidate tag information of goods in transit is obtained according to a preset cycle. The status of goods is determined based on different cycle information, forming a link of order verification - triggering transportation - cycle monitoring to ensure transportation accuracy and cargo safety.

[0059] In one embodiment, determining the cargo status based on candidate tag information under different periods includes: comparing the actual loaded cargo list with the candidate tag information under different periods to determine the loss of cargo in transit; determining the signal strength changes of candidate tag information under different periods, and determining the attitude of cargo in transit based on the signal strength changes.

[0060] The cargo status includes whether it is lost or in its current position.

[0061] Specifically, during the drone's flight, the in-cabin reader periodically transmits radio frequency signals and scans the cargo tags within the cabin at preset time intervals. Each scan result is compared with the actual loaded cargo list. If any cargo electronic tag is found to be missing, confirming a loss of cargo en route, an abnormal cargo status alarm is immediately generated. The alarm information, the lost tag ID, and the current location information are uploaded to the backend server via a wireless communication module. Furthermore, the system determines the signal strength changes of candidate tag information at different intervals and uses the trend of these signal strength changes to determine the attitude of the cargo en route. For example, a weakening signal strength indicates that the cargo has shifted away from the in-cabin reader.

[0062] In this embodiment, by periodically scanning during flight and comparing with a baseline list of actual loaded cargo, it is possible not only to detect whether cargo has fallen off, but also to provide a data basis for future judgment of cargo attitude by analyzing data such as changes in signal strength, thus realizing dynamic periodic monitoring and intelligent judgment of UAV transportation in transit.

[0063] In one embodiment, the drone tag information includes identification area data; anti-counterfeiting authentication of the drone tag information includes: generating a query request and obtaining drone waybill information; identifying the encrypted identifier in the identification area data through a preset encoding rule; and performing anti-counterfeiting authentication on the password area data based on the drone waybill information and the encrypted identifier.

[0064] Among them, the identification area data is as follows Figure 4 The TID area data shown; the preset encoding rules include the TID area encoding rules including tag type, manufacturer code, chip model and unique identification code, which can ensure global uniqueness.

[0065] Specifically, during remote inspection, anti-counterfeiting authentication of the drone tag information is required. The anti-counterfeiting verification platform generates and sends query requests to the backend server and other cloud platforms to obtain the drone waybill information, cargo list, and real-time status corresponding to the drone. After confirming that the drone waybill information is correct, the anti-counterfeiting verification platform also identifies the encrypted identifier in the tag area data through preset encoding rules. Once the encrypted identifier is read and the tag is confirmed to be encrypted, an access password is required. That is, only authorized devices can access the password area data in the drone tag information. After confirming that access rights to the drone are granted, inspection point personnel can complete rapid inspection and release without intercepting the drone.

[0066] In this embodiment, a query request is first generated to obtain the drone waybill information. Then, the encrypted identifier in the identifier area data is identified according to a preset coding rule. Finally, the waybill information and the encrypted identifier are combined to perform anti-counterfeiting authentication on the password area data. This process forms a multi-layered verification mechanism, effectively preventing label forgery and ensuring the authenticity of waybill and cargo information.

[0067] In one embodiment, both the initial label information and the target label information include coded area data; the method further includes: determining the target coding rule corresponding to the coded area data, and verifying the coded area data through the target coding rule; when the verification is successful, changing the shipping information in the database according to the preset task list; and verifying the status of the goods data in the coded area data through the shipping information.

[0068] The encoded area data is read from the EPC area of ​​the electronic tag, for reference. Figure 4 As shown, the target coding rule is the EPC coding rule for the coding area. Before using electronic tags to manage items, the items need to be labeled. After labeling, the coding area data information of the tag is entered into the database. The coding area serves as a unique identifier and is associated with the basic information of the item, forming a one-item-one-code binding relationship.

[0069] Specifically, throughout the loading, transportation, and final delivery processes, remote status verification of goods can be performed based on the tag information read from the electronic tags. When loading begins, the coded data in the electronic tag is scanned to verify if it conforms to the corresponding target coding rules. If verification is successful, the shipping information in the database is updated according to a pre-set task list. Then, during transportation or final delivery, the coded data in the electronic tag is read again. After verifying that the coded data conforms to the corresponding target coding rules, the shipping information for the current goods is compared to whether it is in a "outbound" status. If not, it is identified as goods not permitted to be released, or goods omitted from the loading statistics, etc.; otherwise, it is allowed to proceed without intercepting the drone or can be delivered directly.

[0070] In this embodiment, by verifying the data in the coding area multiple times during transportation, and then changing the shipping information according to the order, the status of the cargo data can be verified. This enables the linkage verification of data, orders, and shipping status, ensuring information consistency and improving the accuracy and standardization of cargo management.

[0071] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise expressly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders.

[0072] Based on the same inventive concept, this application also provides a drone cargo transportation identification device for implementing the drone cargo transportation identification method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more drone cargo transportation identification device embodiments provided below can be found in the limitations of the drone cargo transportation identification method described above, and will not be repeated here.

[0073] In one embodiment, a drone cargo transportation identification device is provided, comprising: a loading verification module, an in-transit monitoring module, a remote inspection module, and a delivery confirmation module, wherein:

[0074] The loading verification module is used to trigger the in-cabin reader to obtain the initial tag information of the loaded cargo; the initial tag information includes password area data; and the password area data is used for tag authentication.

[0075] The on-the-go monitoring module is used to monitor the status of cargo transported by drones.

[0076] The remote verification module is used to trigger the ground reader to obtain the drone tag information and perform anti-counterfeiting authentication on the drone tag information.

[0077] The delivery confirmation module is used to trigger the in-cabin reader to retrieve the target tag information of the cargo again and determine the delivery status of the cargo.

[0078] The various modules in the aforementioned drone cargo transportation identification 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 a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0079] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational 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 a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores tag information. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for identifying cargo transport using a drone.

[0080] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0081] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0082] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0083] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0084] 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, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0085] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for identifying cargo transported by unmanned aerial vehicles (UAVs), characterized in that, The method comprises: triggering the in-cabin reader to obtain initial tag information of the loaded goods; the initial tag information comprises password area data; performing tag authentication on the password area data and monitoring the goods state during the in-transit transportation of the UAV; triggering the ground reader to obtain UAV tag information and performing anti-fake authentication on the UAV tag information; triggering the in-cabin reader to obtain target tag information of the goods again to determine the goods delivery situation; the monitoring of the goods state during the in-transit transportation of the UAV comprises: obtaining an actual loaded goods list when the tag authentication is passed, and triggering the UAV to perform in-transit transportation when the actual loaded goods list is the same as a preset task list; triggering the in-cabin reader to obtain candidate tag information of the goods during the in-transit transportation according to a preset period; and determining the goods state according to the candidate tag information under different periods; the goods state comprises a loss situation and a posture situation; the determination of the goods state according to the candidate tag information under different periods comprises: comparing the actual loaded goods list with the candidate tag information under different periods to determine the loss situation of the in-transit goods; determining the signal strength change of the candidate tag information under different periods, and determining the posture situation of the in-transit goods according to the signal strength change.

2. The method of claim 1, wherein, the initial tag information further comprises secret key storage area data; and the password area data comprises anti-fake ciphertext and a first random number; the anti-fake ciphertext is determined according to the secret key storage area data and the first random number; the tag authentication on the password area data comprises: decrypting the anti-fake ciphertext to obtain plaintext comprising a second random number; performing tag authentication according to the first random number and the second random number.

3. The method of claim 1, wherein, the UAV tag information comprises identification area data; the anti-fake authentication on the UAV tag information comprises: generating a query request and obtaining UAV waybill information; identifying encrypted identification in the identification area data through a preset encoding rule; performing anti-fake authentication on the password area data in the UAV tag information based on the UAV waybill information and the encrypted identification.

4. The method according to any one of claims 1 to 3, characterized in that, the initial tag information and the target tag information both comprise encoding area data; the method further comprises: determining a target encoding rule corresponding to the encoding area data, and verifying the encoding area data through the target encoding rule; when the verification is passed, changing the outbound information in the database according to a preset task list; verifying the state of the goods data in the encoding area data through the outbound information.

5. A drone cargo transport identification system, comprising: The system for implementing the method in any one of claims 1 to 4 comprises a goods subsystem, a UAV subsystem, a ground base station subsystem and an anti-fake verification platform, wherein: the goods subsystem is configured to trigger the in-cabin reader to obtain initial tag information of the loaded goods; the initial tag information comprises password area data; the UAV subsystem is configured to monitor the goods state during the in-transit transportation of the UAV; the ground base station subsystem is configured to trigger the ground reader to obtain UAV tag information; the anti-fake verification platform is configured to perform tag authentication on the password area data and perform anti-fake authentication on the UAV tag information; The cargo subsystem is used to trigger the cabin reader / writer to acquire the target label information of the cargo again, and determine the delivery status of the cargo.

6. The system of claim 5, wherein, The cargo subsystem comprises a cargo electronic label and a wireless communication module; the UAV subsystem comprises a UAV electronic label, a label reader / writer carried on the UAV, and an airborne control unit, the label reader / writer is used to collect information of the cargo electronic label and control the airborne control unit; the ground base station subsystem comprises a ground reader / writer and a background server. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the method in any one of claims 1 to 4.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 4.

Images