Broken luggage processing method and device and electronic equipment

Abstract

The invention discloses a damaged luggage processing method and device and electronic equipment. The method comprises the steps that luggage loss assessment information, sent by a target user through a user side, of target luggage is received, and luggage retention information of the target user is acquired; verifying the luggage loss assessment information according to the luggage retention information to obtain a verification result; under the condition that the verification result represents that the luggage damage assessment information is not abnormal, luggage damage information of the target luggage is acquired, and a luggage damage assessment result is determined according to the luggage damage assessment information and the luggage damage information; and inputting the luggage loss assessment result into the target reasoning model to obtain processing scheme information, and sending the processing scheme information to the user side. According to the method and the device, the problem of relatively low efficiency of manually detecting and processing the damaged luggage in related technologies is solved.

Description

Technical Field

[0001] This application relates to the field of airport baggage handling, and more specifically, to a method, apparatus, and electronic device for handling damaged baggage. Background Technology

[0002] When target users travel by plane, there may be situations where checked baggage is damaged during transportation. In the event of baggage damage or breakage, it is necessary to inspect the baggage and determine the compensation plan based on the inspection results.

[0003] Currently, the main method used for baggage inspection and compensation determination is still manual processing. This approach is not only time-consuming and error-prone, but also fails to meet the expectations of modern users for rapid response and transparent service. Especially in the baggage damage assessment and compensation process, the lack of objective standards and automated tools can lead to longer processing times, decreased user satisfaction, and unclear attribution of responsibility for baggage.

[0004] There is currently no effective solution to the problem of low efficiency in manually inspecting and processing damaged luggage in related technologies. Summary of the Invention

[0005] The main objective of this application is to provide a method, apparatus, and electronic device for handling damaged baggage, in order to solve the problem of low efficiency in the related art of manually inspecting and handling damaged baggage.

[0006] To achieve the above objectives, according to one aspect of this application, a method for handling damaged baggage is provided. The method includes: receiving baggage damage assessment information of a target baggage sent by a target user through a user terminal, and obtaining baggage retention information of the target user; verifying the baggage damage assessment information based on the baggage retention information to obtain a verification result; if the verification result indicates that the baggage damage assessment information is normal, obtaining baggage damage information of the target baggage, and determining a baggage damage assessment result based on the baggage damage assessment information and the baggage damage information; inputting the baggage damage assessment result into a target inference model to obtain processing plan information, and sending the processing plan information to the user terminal.

[0007] Optionally, baggage retention information is generated as follows: multiple preset baggage collection nodes are obtained, and baggage storage information under each baggage collection node is collected to obtain multiple baggage storage information, wherein each baggage storage information is used to indicate the storage address of the baggage information collected by the target baggage under a baggage collection node; the multiple baggage storage information and the identification information of the target baggage are associated and stored in the blockchain to obtain baggage retention information.

[0008] Optionally, the baggage retention information includes multiple baggage storage information, which is generated as follows: For any baggage collection node, the initial image information and identification information of the target baggage are collected; the hash value of the initial image information is calculated, and the hash value and the initial image information are used to determine the initial baggage information; the initial baggage information is signed using the private key associated with the baggage collection node to obtain candidate baggage information, and the candidate baggage information and identification information are associated and stored in the target database; the storage address of the candidate baggage information in the target database is obtained, and the storage address is determined as the baggage storage information.

[0009] Optionally, the baggage damage assessment information is verified based on the baggage retention information, and the verification results include: comparing the initial image information under each baggage collection node with the target image information carried in the baggage damage assessment information in turn to obtain multiple comparison results; if there is no comparison result with consistent image information among the multiple comparison results, the verification result is determined to be abnormal; if there is a comparison result with consistent image information among the multiple comparison results, the verification result is determined to be without abnormality.

[0010] Optionally, obtaining the damage information of the target baggage includes: obtaining abnormal comparison results that are consistent with the comparison results, and sequentially determining the timestamp of the baggage collection node to which each abnormal comparison result belongs, thus obtaining multiple timestamps; determining the baggage collection node with the earliest timestamp as the abnormal node, and obtaining the initial image information under the abnormal node; inputting the initial image information and the target image information into a multimodal model to obtain the baggage damage information, wherein the multimodal model is used to identify the distinguishing features between the initial image information and the target image information, and to determine the damage information based on the distinguishing features.

[0011] Optionally, determining the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information includes: obtaining the target text information carried in the baggage damage assessment information and determining whether the content of the target text information is the same as that of the baggage damage information; if the content of the target text information is the same as that of the baggage damage information, determining the baggage damage assessment information as the baggage damage assessment result; if the content of the target text information is less than that of the baggage damage information, determining the baggage damage information as the baggage damage assessment result; if the content of the target text information is more than that of the baggage damage information, obtaining the additional content in the target text information and sending the additional content to the verification device; and upon receiving feedback information from the verification device, correcting the additional content in the baggage damage assessment information according to the feedback information to obtain the corrected baggage damage assessment information, and determining the corrected baggage damage assessment information as the baggage damage assessment result.

[0012] Optionally, the target inference model is obtained by: acquiring multiple historical baggage damage assessment results, as well as the damage assessment rules and handling schemes for each historical baggage damage assessment result; determining each historical baggage damage assessment result, damage assessment rules, and handling scheme as a set of sample data to obtain multiple sets of sample data; and using the multiple sets of sample data to train the large inference model to obtain the target inference model.

[0013] To achieve the above objectives, according to another aspect of this application, a damaged baggage processing device is provided. The device includes: a first acquisition unit, configured to receive baggage damage assessment information of a target baggage sent by a target user through a user terminal, and acquire baggage retention information of the target user; a verification unit, configured to verify the baggage damage assessment information based on the baggage retention information, and obtain a verification result; a second acquisition unit, configured to acquire baggage damage information of the target baggage when the verification result indicates that the baggage damage assessment information is normal, and determine the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information; and a third acquisition unit, configured to input the baggage damage assessment result into a target inference model to obtain processing scheme information, and send the processing scheme information to the user terminal.

[0014] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described method for handling damaged luggage when it runs.

[0015] To achieve the above objectives, according to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the above-described method for handling damaged luggage.

[0016] In this embodiment, the method involves receiving luggage damage assessment information from a target user via a user terminal and obtaining luggage retention information from the target user; verifying the luggage damage assessment information based on the luggage retention information to obtain a verification result; if the verification result indicates that the luggage damage assessment information is normal, obtaining luggage damage information from the target luggage and determining the luggage damage assessment result based on the luggage damage assessment information and the luggage damage information; inputting the luggage damage assessment result into a target inference model to obtain processing plan information, and sending the processing plan information to the user terminal. By storing luggage retention information and comparing it with the luggage damage assessment information fed back by the user, it is possible to determine whether the target luggage is damaged and the extent of the damage. The target inference model is then used to generate processing plan information based on the damage situation. This approach not only accurately generates a disposal plan for damaged luggage but also improves the detection and processing efficiency of damaged luggage, thereby solving the technical problem of low efficiency in manually detecting and processing damaged luggage in related technologies. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 A hardware block diagram of a computer terminal for implementing a method for handling damaged luggage is shown.

[0019] Figure 2 This is a flowchart of a method for handling damaged luggage according to Embodiment 1 of this application;

[0020] Figure 3 This is a schematic diagram of a damaged luggage processing device provided according to Embodiment 2 of this application;

[0021] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] It should be noted that the methods, devices, and electronic equipment for handling damaged baggage as defined in this disclosure can be used in the field of airport baggage handling, or in any field other than airport baggage handling. The application fields of the methods, devices, and electronic equipment for handling damaged baggage as defined in this disclosure are not limited.

[0026] It should be noted that all information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) used in this application are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with the relevant laws, regulations, and standards of the relevant regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse use. If the user chooses to refuse, the process will proceed to the expert decision-making process. For example, this system has an interface with relevant users or organizations. Before obtaining relevant information, a request to obtain the information needs to be sent to the aforementioned user or organization through the interface. After receiving consent from the aforementioned user or organization, the relevant information is obtained. Users can view the purpose of data use in real time through the authorization interface and have the right to withdraw authorization or delete data at any time. After authorization is withdrawn, the system will terminate the relevant data processing within 24 hours.

[0027] The embodiments or examples disclosed herein are not exhaustive, but merely illustrative of some embodiments or examples, and are not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment or example can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment or example can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment or example can be arbitrarily interchanged. Furthermore, optional methods or examples in a particular embodiment or example can be arbitrarily combined; moreover, embodiments or examples can be arbitrarily combined. For example, some or all steps of different embodiments or examples can be arbitrarily combined, and a particular embodiment or example can be arbitrarily combined with optional methods or examples of other embodiments or examples.

[0028] For ease of description, the following explains some of the nouns or terms used in the embodiments of this application:

[0029] MLLM (Multi-Modal Large Language Model): MLLM is a deep learning model that can process and understand multiple types of input (including but not limited to text, images, audio, and video).

[0030] RLLM (Reasoning Large Language Model): RLLM is a language model with advanced reasoning and decision-making capabilities. It can perform logical reasoning based on complex contexts and rules.

[0031] OSS (Object Storage System): OSS is a cloud storage service used to store unstructured data (such as images, videos, and other files).

[0032] Example 1

[0033] According to an embodiment of this application, an embodiment of a method for handling damaged luggage is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a method for handling damaged luggage is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, processing devices such as microprocessors or programmable logic devices), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface, a universal serial bus port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0035] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0036] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the damaged luggage handling method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned damaged luggage handling method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0037] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0038] The display may be, for example, a touchscreen LCD display that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0039] Under the aforementioned operating environment, this application provides the following: Figure 2 The method for handling damaged luggage is shown. Figure 2 This is a flowchart of a method for handling damaged luggage according to Embodiment 1 of this application, as follows: Figure 2 As shown, the method includes:

[0040] Step S201: Receive the baggage damage assessment information of the target baggage sent by the target user through the user terminal, and obtain the baggage retention information of the target user.

[0041] It should be noted that the executing entity in this embodiment can be a baggage damage handling system. After receiving baggage damage assessment information sent by the user, the system can determine the disposal plan for the target baggage based on the baggage damage assessment information. The baggage damage assessment information refers to the detailed information reported by the target user through a mobile application or other user terminal regarding any physical damage that the baggage may suffer after transportation, including but not limited to damage photos, videos, text descriptions, etc. The baggage retention information refers to the original state data of the baggage recorded by the system before the baggage is transported, in order to ensure the traceability of changes in the baggage status, including baggage size, weight, and images of six views.

[0042] Specifically, when the system receives a damage assessment request sent by the target user through the user terminal, it first obtains the baggage damage assessment information from the request and retrieves the baggage retention information of the target baggage from the database or blockchain. The baggage damage assessment information may include pictures taken by the user of the damaged location of the suitcase, as well as information on other damaged items in the suitcase. For example, the baggage damage assessment information may include pictures showing a hole in the side of the suitcase, and may also include text descriptions, such as a damaged shirt among the internal items, along with a picture of the shirt. The baggage retention information may include relevant records of the target baggage when it was checked in, such as six-view images, baggage dimensions, weight, and other data, providing the original comparison basis for subsequent intelligent damage assessment.

[0043] Step S202: Verify the baggage damage assessment information based on the baggage retention information to obtain the verification result.

[0044] It should be noted that the verification results can be the conclusions drawn from comparing and analyzing the baggage damage assessment information and baggage retention information submitted by the target user using MLLM (Multimodal Large Model). This can be used to confirm whether the damage to the baggage actually occurred during transportation, rather than being caused by the user or being inherent damage to the baggage.

[0045] Specifically, the system compares photos of baggage damage reported by the target user with images of the baggage that have been stored online. By utilizing the image semantic recognition capabilities of the MLLM model, it not only verifies whether the baggage is indeed damaged but also accurately identifies the specific location, type, and extent of the damage, ensuring the accuracy of intelligent damage assessment. Simultaneously, the system checks all documented information about the baggage during transportation, including photographic records of each stage, to determine the exact point at which the damage occurred, such as at a specific transit airport. Based on this information, a verification result is generated.

[0046] Step S203: If the verification result indicates that there are no abnormalities in the baggage damage assessment information, obtain the baggage damage information of the target baggage, and determine the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information.

[0047] Specifically, after confirming that the baggage damage information is correct, the system will call the MLLM model to further analyze and describe the specific damage to the baggage, such as whether the items are damaged, the degree of damage, and whether they affect use, thereby automatically identifying the damage information and determining the baggage damage assessment result for the target baggage.

[0048] For example, the system uses MLLM to identify a hole in the side of the target suitcase and a tear in the shirt inside. Then, the system integrates the luggage damage assessment information with detailed damage details to determine the damage assessment result. For instance, it clearly indicates the type and size of the damage to the suitcase, as well as the extent and location of the tear in the shirt, ultimately arriving at the specific damage assessment conclusion: "The suitcase has penetrating damage on the side, and the shirt is torn."

[0049] Step S204: Input the baggage damage assessment results into the target inference model to obtain the processing plan information, and send the processing plan information to the user terminal.

[0050] It should be noted that the target inference model can be an RLLM (Large Inference Model), which can generate a compensation plan based on baggage damage assessment results, basic baggage information, and airline compensation terms. The processing plan information is a compensation plan provided by the system to the target user based on the above analysis, which may include, but is not limited to, specific information such as compensation amount, compensation method, and execution process.

[0051] Specifically, after obtaining the baggage damage assessment results, basic baggage information, such as dimensions, weight, and applicable regulations, can be submitted as input data to the RLLM model. The RLLM model can then deduce the most suitable baggage handling plan based on the specific content of the regulations, combined with the degree and type of damage. This generated plan is then sent to the user, allowing them to select the most suitable solution from multiple options, thus completing the automated generation process for damaged baggage handling plans.

[0052] For example, RLLM can generate the following processing solution information: "Compensation of 300 yuan in cash for the suitcase, 400 yuan in cash for the shirt, totaling 700 yuan. The target user needs to provide the original purchase receipt within 7 days to confirm the compensation amount." The above processing solution information is then sent to the user's terminal in electronic form for them to view and confirm, thus completing the automatic generation process of the damaged luggage processing solution.

[0053] The damaged baggage handling method provided in this application embodiment receives baggage damage assessment information sent by a target user through a user terminal and obtains the target user's baggage retention information; verifies the baggage damage assessment information based on the baggage retention information to obtain a verification result; if the verification result indicates that the baggage damage assessment information is normal, obtains the baggage damage information of the target baggage and determines the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information; inputs the baggage damage assessment result into a target inference model to obtain handling plan information, and sends the handling plan information to the user terminal. By storing the baggage retention information and comparing it with the baggage damage assessment information fed back by the user, it is determined whether the target baggage is damaged and the extent of the damage. The target inference model is used to generate handling plan information based on the damage situation. This method achieves the technical effect of improving the detection and handling efficiency of damaged baggage while accurately generating a handling plan for damaged baggage, thereby solving the technical problem of low efficiency in the manual detection and handling of damaged baggage in related technologies.

[0054] To ensure the accuracy and completeness of baggage retention information, optionally, in the damaged baggage handling method provided in this application embodiment, the baggage retention information is generated in the following manner: multiple preset baggage collection nodes are obtained, and baggage storage information under each baggage collection node is collected to obtain multiple baggage storage information, wherein each baggage storage information is used to indicate the storage address of the baggage information collected under a baggage collection node for the target baggage; the multiple baggage storage information and the identification information of the target baggage are associated and stored in the blockchain to obtain baggage retention information.

[0055] It's important to note that baggage collection nodes are pre-defined key locations in the airport baggage handling process, such as baggage check-in counters, security checkpoints, boarding gates, transfer stations, and baggage claim areas, used to collect information about the status of target baggage. Baggage storage information, generated by each baggage collection node, includes the status of a specific piece of baggage recorded at that node, including but not limited to six-view images of the baggage, dimensions, weight, and the storage address of this information on OSS (Object Storage System). Identification information is a unique identifier assigned to each piece of baggage in the system, such as a suitcase ID, facilitating subsequent tracing and management of baggage records on the blockchain. Linking storage to the blockchain represents storing baggage storage information and identification information together on the chain, establishing a timeline link between baggage information and the baggage throughout the entire processing flow, ensuring the integrity and immutability of baggage information.

[0056] Specifically, at the beginning of the baggage handling process, the system first identifies pre-set baggage collection nodes and acquires basic and image information of the baggage at each node, such as six-view images, dimensions, and weight. This data is then stored as baggage storage information. Subsequently, as the baggage enters the transportation chain, the system automatically triggers the collection mechanism at each key node, such as the security checkpoint, boarding gate, transfer station, and baggage claim area, ensuring that the baggage's storage information is comprehensively recorded at different stages.

[0057] Furthermore, the system links the baggage storage information collected at each baggage collection node with the target baggage's identification information, forming a complete record of the baggage at different stages. After each data collection is completed, the system generates corresponding storage information and endorses it with a digital identity to prove the authenticity and completeness of the information. Then, this endorsed baggage storage information, along with the identification information, is encrypted and stored on the blockchain, thereby recording the complete baggage retention information of the target baggage in the blockchain, ensuring the secure storage of baggage information and future traceability.

[0058] This embodiment comprehensively and promptly records the information of the target baggage at each baggage collection node, providing an objective and authentic source of original data for subsequent intelligent damage assessment and compensation. Furthermore, by storing the acquired information on the blockchain, the credibility and security of the baggage information are ensured by leveraging the decentralized and tamper-proof characteristics of the blockchain.

[0059] To ensure the accuracy of baggage storage information, optionally, in the damaged baggage handling method provided in this application embodiment, the baggage retention information includes multiple baggage storage information, which is generated in the following manner: for any baggage collection node, initial image information and identification information of the target baggage are collected; the hash value of the initial image information is calculated, and the hash value and the initial image information are used to determine the initial baggage information; the initial baggage information is signed using the private key associated with the baggage collection node to obtain candidate baggage information, and the candidate baggage information and identification information are associated and stored in the target database; the storage address of the candidate baggage information in the target database is obtained, and the storage address is determined as the baggage storage information.

[0060] It should be noted that baggage storage information refers to the target baggage status information collected at each baggage collection node, including but not limited to six-view photos of the baggage, as well as attributes such as size and weight, used to store the original status record of the baggage at that node on the blockchain. Initial image information refers to the images of the target baggage collected at each baggage collection node, including images from six different perspectives, used for subsequent intelligent damage assessment analysis. Identification information is information used to uniquely identify a piece of baggage, such as a luggage ID (Identification), ensuring the tracking and management of baggage in the system. The hash value can be a fixed-length numeric string calculated from the initial image information, used for quickly comparing and verifying the integrity of baggage images, preventing tampering during transmission or storage. Candidate baggage information includes the hash value of the initial image information, the initial image information itself, and integrated data of the baggage identification information, which, after digital signing, serves as preparation information for on-chain evidence storage. The target database can be a block in the blockchain network or external storage connected to the blockchain, used to store candidate baggage information and identification information, providing a basis for subsequent intelligent damage assessment and compensation determination. The storage address is the specific location of the candidate baggage information stored in the target database, used for quick location and retrieval.

[0061] Specifically, for any baggage collection node, when the target baggage arrives at that node, an automatic scanning device captures images of the baggage from six different angles and records the baggage ID (identification information). Subsequently, the system calculates the hash value of the target baggage image using a pre-set encryption algorithm to ensure the integrity and tamper-proof nature of the image data. The hash value and the image itself together constitute the initial baggage information. This step ensures a comprehensive record of the baggage at the initial check-in point, providing raw data for subsequent intelligent damage assessment.

[0062] Furthermore, after obtaining the image information and hash value, the system uses the node's private key to digitally sign the initial baggage information, generating candidate baggage information. The digital signing process not only confirms the source of the information but also further ensures the non-repudiation of the information and the consistency of the data. Then, the system stores this digitally signed candidate baggage information along with the baggage ID in the target database. In this embodiment, the target database can be an external OSS (Object Storage System). This way, even if the baggage passes through multiple transit stations during transportation, the information collected at each station can be accurately recorded and correlated, facilitating subsequent intelligent analysis.

[0063] Furthermore, once the candidate baggage information is successfully stored in the target database, since different nodes correspond to different target databases, it is necessary to uniformly store the storage addresses of the candidate baggage information in the blockchain. This allows the blockchain to be used to directly retrieve the information storage addresses of all nodes when querying candidate baggage information, and then retrieve the candidate baggage information from the storage addresses. Therefore, the storage addresses can be stored in the blockchain as baggage storage information, thus completing the baggage storage information generation process.

[0064] This embodiment utilizes digital signatures, blockchain, and OSS storage technologies to obtain comprehensive, secure, and reliable baggage storage information. For each piece of baggage, the system can accurately and completely record its storage information at each key stage of its transportation journey, ensuring the immutability and traceability of this information, guaranteeing the originality and integrity of the data, and laying the information foundation for subsequent damage handling procedures.

[0065] To ensure the accuracy of baggage damage assessment information, optionally, in the damaged baggage processing method provided in this application embodiment, the baggage damage assessment information is verified based on the baggage retention information, and the verification results are obtained by: sequentially comparing the initial image information under each baggage collection node with the target image information carried in the baggage damage assessment information to obtain multiple comparison results; if there is no comparison result with consistent image information among the multiple comparison results, the verification result is determined to be abnormal; if there is a comparison result with consistent image information among the multiple comparison results, the verification result is determined to be without abnormality.

[0066] Specifically, after receiving the baggage damage assessment information sent by the user, it is necessary to first verify the authenticity and accuracy of the information, and then determine whether the baggage damage assessment information is accurate based on the verification results. When verifying the baggage damage assessment information, it is first necessary to obtain the baggage storage information under each baggage collection node based on the target baggage's identification information, and then obtain the initial image information under each baggage collection node. The images in the initial image information are then compared sequentially with the images provided by the user in the baggage damage assessment information to obtain the comparison results for each node.

[0067] Furthermore, after obtaining multiple comparison results, it is possible to sequentially identify whether each comparison result is consistent with the image information. If there is no comparison result with consistent image information, it indicates that the image in the baggage damage assessment information provided by the user is inaccurate, or that the baggage damage shown in the baggage damage assessment information did not occur during baggage transportation, but may be caused by the user himself. At this time, the verification result is determined to be abnormal, and the abnormal result can be fed back to the user.

[0068] If one or more verification results indicate that the image information is consistent, it means that the baggage damage assessment information provided by the user is accurate, and the damage occurred during the transportation process and was collected by the baggage collection node. In this case, it can be determined that there is no abnormality in the verification results, and the subsequent process of determining the damage information and the compensation plan can be executed.

[0069] This embodiment ensures the accuracy of the baggage damage assessment information provided by the user by comparing the baggage retention information with the baggage damage assessment information at each node, thereby ensuring the accuracy and effectiveness of the subsequent process of determining damage information and compensation plan.

[0070] To accurately identify the location and state of damage to the target baggage, optionally, in the baggage processing method provided in this application embodiment, obtaining the baggage damage information of the target baggage includes: obtaining abnormal comparison results that are consistent with the comparison results, and sequentially determining the timestamp of the baggage collection node to which each abnormal comparison result belongs, thereby obtaining multiple timestamps; determining the baggage collection node with the earliest timestamp as the abnormal node, and obtaining the initial image information under the abnormal node; inputting the initial image information and the target image information into a multimodal model to obtain baggage damage information, wherein the multimodal model is used to identify the distinguishing features between the initial image information and the target image information, and to determine the damage information based on the distinguishing features.

[0071] It should be noted that the timestamp is a time label for the image information recorded under each baggage collection node, used to accurately identify the collection time of each image, thereby determining the time when the damage occurred.

[0072] Specifically, if the verification result is no abnormality, an abnormal comparison result with consistent comparison results can be obtained. This abnormal comparison result indicates that the image information in the user's baggage damage assessment information is consistent with the image information in the baggage retention information corresponding to the comparison result. At this time, it is necessary to obtain at least one abnormal comparison result and obtain the baggage collection node with the earliest timestamp among the baggage collection nodes corresponding to at least one abnormal comparison result, so as to complete the determination of the abnormal node. That is, the baggage in the image information recorded by the node before the abnormal node is not damaged, while the baggage in the image information recorded under the abnormal node is damaged, indicating that the damage occurred in the transportation process corresponding to the abnormal node.

[0073] It should be noted that each baggage collection node is set after each segment of the transportation process or each transportation operation, and is used to record the status image of the baggage after the completion of the transportation operation or the completion of the transportation segment.

[0074] Furthermore, after identifying the anomalous node, initial image information of that node can be obtained. This initial image information, along with the target image information (i.e., the image information contained in the baggage damage assessment information), is then input into a multimodal model (MLLM model). The MLLM model then performs in-depth analysis on the two sets of images to identify specific damage characteristics, such as the location, shape, and size of the damage, and determines the damage information of the baggage based on these characteristics. For example, the model might identify a penetrating damage with an aspect ratio of 1:1 on the side of the target suitcase, and tear marks on the internal clothing, thus obtaining the basis information for subsequent damage assessment procedures.

[0075] This embodiment identifies the damage occurrence node by determining abnormal information, and compares the image at that node with the image sent by the user to determine the abnormal occurrence node and damage information, thereby laying the information foundation for subsequent damage assessment.

[0076] Optionally, in the damaged baggage handling method provided in this application embodiment, determining the baggage damage assessment result based on baggage damage assessment information and baggage damage information includes: obtaining target text information carried in the baggage damage assessment information and determining whether the content of the target text information is the same as that of the baggage damage information; if the content of the target text information is the same as that of the baggage damage information, determining the baggage damage assessment information as the baggage damage assessment result; if the content of the target text information is less than that of the baggage damage information, determining the baggage damage information as the baggage damage assessment result; if the content of the target text information is more than that of the baggage damage information, obtaining additional content in the target text information and sending the additional content to the verification device; and upon receiving feedback information from the verification device, correcting the additional content in the baggage damage assessment information according to the feedback information to obtain corrected baggage damage assessment information, and determining the corrected baggage damage assessment information as the baggage damage assessment result.

[0077] It should be noted that the target text information refers to the textual description information provided by the target user when generating baggage damage assessment information, which may include the damage to the baggage, such as describing the damaged parts, damage type and damage extent.

[0078] Specifically, when the system receives baggage damage assessment information, it first parses the target text information, which is usually filled in by the target user when reporting the damage, describing the condition of the suitcase. The system then compares the target text information with the baggage damage information to check whether the damage described in the two are completely consistent. For example, if the target text information describes "a hole in the side of the suitcase and a torn shirt inside," and the baggage damage information also confirms this, the system will determine that the two contents match.

[0079] If the target text information and the baggage damage information are exactly the same, the system can directly adopt the target text information in the baggage damage assessment information as the final damage assessment result without additional verification or correction process.

[0080] If the damage description in the target text is relatively brief and insufficient to cover all the damage details detected in the luggage damage information, the system will use the luggage damage information as the final damage assessment result. For example, if the target user only describes "a hole in the side of the suitcase," but the MLLM model also detects that the luggage wheel has fallen off, the system will consider the more comprehensive luggage damage information as the final damage assessment result.

[0081] If the target text information contains content beyond the description of luggage damage, the system needs to separate this additional content and send it to the verification device for further verification. For example, if the target user describes "a hole in the side of the suitcase, a torn inner shirt, and a wheel that has fallen off," but the luggage damage information only confirms the first two damages, the system will pass the description of the fallen wheel as additional content to the verification device.

[0082] Furthermore, after receiving the additional information, the verification device needs to determine its reasonableness. Assuming the verification device confirms that a wheel has fallen off, the additional information is deemed correct and no modification is needed; the baggage damage assessment information can be directly confirmed as the baggage damage assessment result.

[0083] In cases where there are anomalies in the additional information, such as additional information indicating that the wheel has fallen off or the computer is lost, but after verification it is determined that only the wheel has fallen off, the additional information in the baggage damage assessment information can be modified to indicate that the wheel has fallen off. This will result in updated baggage damage assessment information, which will then be used as the baggage damage assessment result. This ensures the accuracy of the baggage damage assessment result, allowing subsequent models to determine the disposal plan based on the baggage damage assessment result.

[0084] This embodiment ensures the accuracy of the subsequent handling plan by accurately determining the baggage damage assessment results.

[0085] Optionally, in the method for handling damaged baggage provided in this application embodiment, the target inference model is obtained in the following manner: acquiring multiple historical baggage damage assessment results, as well as the damage assessment rules and handling schemes for each historical baggage damage assessment result; determining each historical baggage damage assessment result, damage assessment rules, and handling scheme as a set of sample data to obtain multiple sets of sample data; using multiple sets of sample data to train the large inference model to obtain the target inference model.

[0086] It should be noted that historical baggage damage assessment results refer to damage assessment information recorded by the system or manually in past baggage damage cases, including descriptions of the damage condition, type of damage, and extent of damage. Damage assessment rules can be a set of rules used to determine whether baggage damage meets the compensation standards, covering compensation thresholds for various types of damage, and the logic for determining liability.

[0087] Specifically, when training the target inference model, the system first extracts multiple historical baggage damage assessment cases from the database, covering various types and degrees of baggage damage. Simultaneously, the system also obtains the damage assessment rules and handling plans related to each case. The damage assessment rules detail the conditions and standards for compensation, while the handling plans record the specific compensation or repair measures.

[0088] For each historical case, the system combines the damage assessment results, damage assessment rules, and handling solutions into a set of structured sample data. This sample data contains the complete logical chain of intelligent damage assessment and compensation determination, as well as the final compensation decision. In this way, the system compiles a training set containing multiple sets of sample data for subsequent training of the target inference model.

[0089] Finally, the system uses the compiled sample data as input to train the large-scale reasoning model. During training, the model learns how to deduce appropriate handling solutions from baggage damage descriptions and damage assessment rules. The RLLM model, through deep learning algorithms, understands the details of each damage case, identifies applicable rules, and imitates historical handling solutions, gradually improving the accuracy of its reasoning. Ultimately, the trained large-scale reasoning model will be transformed into a target reasoning model, focusing on the intelligent claims assessment reasoning task for damaged baggage.

[0090] This embodiment uses historical loss assessment results and processing schemes to train the model, ensuring the accuracy of the model's generated results.

[0091] The following is an optional embodiment of a method for handling damaged baggage according to Embodiment 1 of this application. Assume that passenger A flies from airport M to airport N. He checks in his baggage at airport M. His suitcase is 30×40×60cm in size and weighs 15kg. When he arrives at airport N and collects his baggage, he finds that there is a crack in the suitcase and the contents are exposed. There is no damage or loss of the contents. He then initiates a claim for damage through the baggage system.

[0092] Step 1: Pre-shipment documentation:

[0093] Passenger A checks in their baggage at Airport M. Airport M measures and photographs the baggage's dimensions, weight, and six-view drawings, and enters this information into the baggage system, which then stores the information on the blockchain. At each transfer stage at Airport M, the six-view drawings of the baggage are measured and photographed, and the relevant information is entered into the baggage system, which also stores the information on the blockchain.

[0094] Step 2: Evidence Storage During Transit:

[0095] When the baggage arrives at Airport N, each transfer link at Airport N takes photos of the baggage from six different views and enters the relevant information into the baggage system. The system then stores the relevant information on the blockchain for verification.

[0096] Step 3: Post-transport loss reporting:

[0097] Passenger A arrives at Airport N and goes to collect their checked baggage. They discover a hole in the side of their suitcase and a torn shirt inside. Passenger A takes a photo of the damage and enters the image and description (hole in the suitcase, torn shirt) into the baggage reporting system. The system stores the damaged image on the OSS storage device and uploads the OSS receipt, image hash value, and image description to the blockchain for evidence storage.

[0098] Step 4: Intelligent Damage Assessment

[0099] The blockchain system's monitoring function automatically triggers intelligent damage assessment upon detecting a post-transport damage report. The system traces back the case information on the chain, extracting evidence images from each stage of the damage report, including pre-transport, during-transport, and post-transport stages. These images are then sent to the MLLM (Multi-Level Model) for baggage damage identification. The MLLM model's identification results for the post-transport images are: baggage damaged, with a hole in the side of the suitcase, and the contents exposed. The MLLM model's identification results for the pre-transport images are: baggage intact. The MLLM model's identification results for the during-transport images at airport M are: baggage intact. The MLLM model's identification results for the during-transport images at airport N are: baggage damaged, with a hole in the side of the suitcase. The results of these three steps are endorsed using the MLLM digital identity and stored on the blockchain as evidence.

[0100] Step 5: Intelligent Claims Settlement

[0101] The blockchain system's monitoring function automatically triggers the intelligent claims settlement function upon detecting information in the intelligent damage assessment process. It backtracks on-chain case information, extracting baggage size information, baggage weight, passenger damage report description, and intelligent damage assessment information, adding these to a text file T. The system also extracts the airport's "Baggage Compensation Terms" and adds them to T. Using a large RLLM model, it integrates basic baggage information, baggage damage assessment information, and the context of the compensation terms to intelligently infer a baggage compensation plan, including liability determination information. This compensation plan is then stored on the blockchain as evidence, thus completing the damaged baggage handling process.

[0102] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0103] Example 2

[0104] This application also provides a damaged baggage processing device. It should be noted that the damaged baggage processing device of this application can be used to execute the damaged baggage processing method provided in the above embodiments. The damaged baggage processing device provided in this application will be described below.

[0105] According to an embodiment of this application, an apparatus for implementing the above-described method for handling damaged luggage is also provided. Figure 3 This is a schematic diagram of a damaged luggage processing device according to Embodiment 2 of this application, as shown below. Figure 3 As shown, the device includes:

[0106] The first acquisition unit 31 is used to receive the luggage damage assessment information of the target luggage sent by the target user through the user terminal, and to acquire the luggage retention information of the target user.

[0107] The verification unit 32 is used to verify the baggage damage assessment information based on the baggage retention information and obtain the verification result.

[0108] The second acquisition unit 33 is used to acquire the baggage damage information of the target baggage when the verification result indicates that there is no abnormality in the baggage damage assessment information, and to determine the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information.

[0109] The third acquisition unit 34 is used to input the baggage damage assessment results into the target reasoning model, obtain the processing plan information, and send the processing plan information to the user terminal.

[0110] The damaged baggage handling device provided in this application embodiment receives baggage damage assessment information sent by a target user through a user terminal by a first acquisition unit 31, and acquires baggage retention information of the target user; a verification unit 32 verifies the baggage damage assessment information based on the baggage retention information to obtain a verification result; a second acquisition unit 33, if the verification result indicates that the baggage damage assessment information is normal, acquires the baggage damage information of the target baggage, and determines the baggage damage assessment result based on the baggage damage assessment information and the baggage damage information; a third acquisition unit 34 inputs the baggage damage assessment result into a target inference model to obtain handling plan information, and sends the handling plan information to the user terminal. By storing baggage retention information and comparing it with the baggage damage assessment information fed back by the user, it determines whether the target baggage is damaged and the extent of the damage. The target inference model then generates handling plan information based on the damage situation. This achieves the technical effect of improving the detection and handling efficiency of damaged baggage while accurately generating a handling plan for damaged baggage, thereby solving the technical problem of low efficiency in manually detecting and handling damaged baggage in related technologies.

[0111] Optionally, in the damaged luggage processing device provided in this application embodiment, the luggage retention information is generated by the following device: a fourth acquisition unit, used to acquire multiple preset luggage collection nodes and collect luggage storage information under each luggage collection node to obtain multiple luggage storage information, wherein each luggage storage information is used to indicate the storage address of luggage information collected under a luggage collection node for the target luggage; and a storage unit, used to associate and store the multiple luggage storage information and the identification information of the target luggage to the blockchain to obtain luggage retention information.

[0112] Optionally, in the damaged baggage processing device provided in this application embodiment, the baggage retention information includes multiple baggage storage information, which is generated by the following devices: a collection unit, used to collect initial image information and identification information of the target baggage for any baggage collection node; a calculation unit, used to calculate the hash value of the initial image information and determine the hash value and the initial image information as the initial baggage information; a signature unit, used to sign the initial baggage information using the private key associated with the baggage collection node to obtain candidate baggage information, and associate and store the candidate baggage information and identification information in the target database; and a first determination unit, used to obtain the storage address of the candidate baggage information in the target database and determine the storage address as the baggage storage information.

[0113] Optionally, in the damaged baggage processing device provided in this application embodiment, the verification unit 32 includes: a comparison module, used to sequentially compare the initial image information under each baggage collection node with the target image information carried in the baggage damage assessment information to obtain multiple comparison results; a first determination module, used to determine that the verification result is abnormal when there is no comparison result representing consistent image information among the multiple comparison results; and a second determination module, used to determine that the verification result is not abnormal when there is a comparison result representing consistent image information among the multiple comparison results.

[0114] Optionally, in the damaged baggage processing device provided in this application embodiment, the second acquisition unit 33 includes: a first acquisition module, used to acquire abnormal comparison results that are consistent with the comparison results, and sequentially determine the timestamp of the baggage collection node to which each abnormal comparison result belongs, to obtain multiple timestamps; a third determination module, used to determine the baggage collection node with the earliest timestamp as an abnormal node, and acquire the initial image information under the abnormal node; and an input module, used to input the initial image information and the target image information into a multimodal model to obtain baggage damage information, wherein the multimodal model is used to identify the distinguishing features between the initial image information and the target image information, and to determine the damage information based on the distinguishing features.

[0115] Optionally, in the damaged baggage processing device provided in this application embodiment, the second acquisition unit 33 includes: a second acquisition module, used to acquire target text information carried in the baggage damage assessment information and determine whether the target text information is the same as the content of the baggage damage information; a fourth determination module, used to determine the baggage damage assessment information as the baggage damage assessment result when the content of the target text information is the same as the content of the baggage damage information; a fifth determination module, used to determine the baggage damage information as the baggage damage assessment result when the content of the target text information is less than the content of the baggage damage information; a sending module, used to acquire additional content in the target text information and send the additional content to the verification device when the content of the target text information is more than the content of the baggage damage information; and a correction module, used to correct the additional content in the baggage damage assessment information according to the feedback information received from the verification device, to obtain the corrected baggage damage assessment information, and to determine the corrected baggage damage assessment information as the baggage damage assessment result.

[0116] Optionally, in the damaged baggage processing apparatus provided in this application embodiment, the target inference model is obtained through the following devices: a fifth acquisition unit, used to acquire multiple historical baggage damage assessment results, as well as the damage assessment rules and processing schemes for each historical baggage damage assessment result; a second determination unit, used to determine each historical baggage damage assessment result, damage assessment rules, and processing scheme as a set of sample data, thereby obtaining multiple sets of sample data; and a training unit, used to train the inference big model using multiple sets of sample data, thereby obtaining the target inference model.

[0117] It should be noted that the first acquisition unit 31, verification unit 32, second acquisition unit 33, and third acquisition unit 34 mentioned above correspond to steps S201 to S204 in Embodiment 1. The instances and application scenarios implemented by each of the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0118] Example 3

[0119] Embodiments of this application may provide an electronic device. Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (Only one is shown) processor 1002, memory 1004, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0120] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0121] Those skilled in the art will understand that Figure 4 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 4 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 4 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 4 The different configurations shown.

[0122] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0123] Example 4

[0124] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the damaged luggage handling method provided in Embodiment 1.

[0125] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0126] Embodiments of this application also provide a computer program product, which, when executed on a data processing device, is a program adapted to perform the steps of a method for handling damaged baggage.

[0127] Embodiments of this application also provide a computer-readable storage medium, which includes a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described method for handling damaged luggage.

[0128] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0129] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0131] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0133] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0134] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for handling damaged luggage, characterized in that, include: Receive luggage damage assessment information of the target luggage sent by the target user through the user terminal, and obtain the luggage retention information of the target user; The baggage damage assessment information is verified based on the baggage retention information to obtain the verification result; If the verification result indicates that the baggage damage assessment information is normal, the baggage damage information of the target baggage is obtained, and the baggage damage assessment result is determined based on the baggage damage assessment information and the baggage damage information. The baggage damage assessment results are input into the target inference model to obtain processing plan information, and the processing plan information is sent to the user terminal.

2. The method according to claim 1, characterized in that, The baggage retention information is generated in the following way: Multiple preset baggage collection nodes are obtained, and baggage storage information under each baggage collection node is collected to obtain multiple baggage storage information. Each baggage storage information is used to indicate the storage address of the baggage information collected under a baggage collection node for the target baggage. Multiple baggage storage information and the identification information of the target baggage are associated and stored in the blockchain to obtain the baggage retention information.

3. The method according to claim 1, characterized in that, The baggage retention information includes multiple baggage storage information entries, which are generated in the following manner: For any baggage collection node, the initial image information and identification information of the target baggage are collected; Calculate the hash value of the initial image information, and use the hash value and the initial image information to determine the initial baggage information; The initial baggage information is signed using the private key associated with the baggage collection node to obtain candidate baggage information, and the candidate baggage information and the identification information are associated and stored in the target database. Obtain the storage address of the candidate baggage information in the target database, and determine the storage address as the baggage storage information.

4. The method according to claim 3, characterized in that, The baggage damage assessment information is verified based on the baggage retention information, and the verification results include: The initial image information of each baggage collection node is compared with the target image information carried in the baggage damage assessment information in turn to obtain multiple comparison results; If no consistent image information is found among the multiple comparison results, the verification result is determined to be abnormal. If among the multiple comparison results there are comparison results that represent consistent image information, the verification result is determined to be without anomalies.

5. The method according to claim 4, characterized in that, Obtaining the damage information of the target luggage includes: The comparison results are obtained as consistent abnormal comparison results, and the timestamps of the baggage collection nodes to which each abnormal comparison result belongs are determined in sequence to obtain multiple timestamps; The earliest baggage collection node with the timestamp is identified as an abnormal node, and the initial image information under the abnormal node is obtained. The initial image information and the target image information are input into a multimodal model to obtain the luggage damage information. The multimodal model is used to identify the distinguishing features between the initial image information and the target image information, and to determine the damage information based on the distinguishing features.

6. The method according to any one of claims 1 to 5, characterized in that, The baggage damage assessment result is determined based on the baggage damage information and the baggage damage information, including: Obtain the target text information carried in the baggage damage assessment information, and determine whether the target text information is the same as the content of the baggage damage information; If the target text information is identical to the baggage damage information, the baggage damage assessment information will be determined as the baggage damage assessment result. If the content of the target text information is less than the baggage damage information, the baggage damage information is determined as the baggage damage assessment result; If the content of the target text information is greater than the luggage damage information, additional content in the target text information is obtained and sent to the verification device. Upon receiving feedback information from the verification device, the additional content in the baggage damage assessment information is corrected based on the feedback information to obtain the corrected baggage damage assessment information, and the corrected baggage damage assessment information is determined as the baggage damage assessment result.

7. The method according to any one of claims 1 to 5, characterized in that, The target reasoning model is obtained in the following way: Obtain multiple historical baggage damage assessment results, as well as the assessment rules and handling solutions for each historical baggage damage assessment result; Each historical baggage damage assessment result, assessment rule, and handling plan is identified as a set of sample data, resulting in multiple sets of sample data. The target inference model is obtained by training the large inference model using the multiple sets of sample data.

8. A device for handling damaged luggage, characterized in that, include: The first acquisition unit is used to receive luggage damage assessment information of target luggage sent by the target user through the user terminal, and to acquire luggage retention information of the target user; The verification unit is used to verify the baggage damage assessment information based on the baggage retention information and obtain the verification result; The second acquisition unit is used to acquire the baggage damage information of the target baggage when the verification result indicates that the baggage damage information is normal, and to determine the baggage damage assessment result based on the baggage damage information and the baggage damage information. The third acquisition unit is used to input the baggage damage assessment result into the target inference model to obtain processing plan information, and send the processing plan information to the user terminal.

9. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method for handling damaged luggage as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method for handling damaged luggage as described in any one of claims 1 to 7.

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