Cloud computing and timestamp-based travel data management method and system and computing device

Abstract

This invention provides a travel data management method, system, and computing device based on cloud computing and timestamps. The method includes: acquiring at least one geographic image uploaded by a user during the execution of a travel plan; generating a time-associated compliant geographic area based on the travel plan; matching the geographic coordinates with the compliant geographic area to obtain a first matching result; comparing the captured timestamp metadata with the corresponding travel plan time in the travel plan to obtain a time comparison result; generating a travel behavior authenticity verification result based on the first matching result and the time comparison result; and automatically generating an electronic audit voucher containing a timestamp, spatial trajectory chain, and geographic image when the authenticity verification result is successful. According to the technical solution of this invention, the accuracy of travel behavior authenticity verification can be improved, highly reliable electronic audit vouchers can be automatically generated, and a data closed loop can be provided for intelligent travel management.

Description

Technical Field

[0001] This invention relates to the field of cloud computing technology, specifically to a travel data management method, system, and computing device based on cloud computing and timestamps. Background Technology

[0002] Travel expenses refer to the intercity transportation, meal, accommodation, and local transportation costs incurred by employees of an organization when temporarily traveling to areas outside their permanent residence for official business. Several problems exist regarding the reimbursement of travel expenses. First, some organizations reimburse expenses exceeding standards or scope. For example, some employees use transportation exceeding their class of service and stay in accommodations exceeding standards, with the excess still being reimbursed by the organization. Some also reimburse meal allowances while simultaneously reimbursing meal expenses incurred during the business trip. Second, some organizations fraudulently obtain travel expenses. For example, some organizations reimburse local transportation allowances even when the organization provides a vehicle, or falsely report the number of business trip days to obtain additional travel expenses. Third, some organizations fail to follow proper travel approval procedures. For example, travel approval forms may be delayed until after the trip, or they may be submitted retroactively when submitting expense reports upon return.

[0003] Traditional travel expense reimbursement and auditing rely on manual documentation. Companies have long depended on paper or electronic receipts such as invoices, itineraries, and hotel bills for travel expense reimbursement, which carries risks such as forgery, duplicate reimbursements, and falsified itineraries. Furthermore, manual review is inefficient and costly. Existing methods typically define static geographical areas based on preset rules for attendance or sign-in, but they lack adaptability to dynamic changes in the time dimension (such as travel time and meeting arrangements) and fail to accurately reflect compliance boundaries.

[0004] Therefore, a technical solution is needed to improve the accuracy of travel document authenticity verification, automatically generate highly credible electronic audit vouchers, and provide a data closed loop for intelligent travel management. Summary of the Invention

[0005] This invention aims to provide a travel data management method, system, and computing device based on cloud computing and timestamps, which can improve the accuracy of travel behavior authenticity verification, automatically generate highly credible electronic audit vouchers, and provide a data closed loop for intelligent travel management.

[0006] According to one aspect of the present invention, a travel data management method based on cloud computing and timestamps is provided, the method comprising: Obtain at least one geographic image uploaded by the user during the execution of a travel plan, the geographic image containing geographic coordinates and shooting timestamp metadata; Based on the travel plan, generate compliant geographic regions that are time-related; The geographic coordinates are matched with the compliant geographic areas to obtain a first matching result; The shooting timestamp metadata is compared with the corresponding travel plan time in the travel plan to obtain the time comparison result; Based on the first matching result and the time comparison result, a authenticity verification result of the difference travel behavior is generated; When the authenticity verification result is successful, an electronic audit certificate containing a timestamp, spatial trajectory chain, and geographic image is automatically generated.

[0007] According to some embodiments, the method further includes: Visual scene features in the geographic image are identified and extracted. The visual scene features are then cross-validated against the geographic scene expected based on the geographic coordinates to obtain the visual comparison results.

[0008] According to some embodiments, the shooting time inferred through image lighting analysis is consistent with the shooting timestamp.

[0009] According to some embodiments, visual scene features in the geographic image are identified and extracted, and the visual scene features are compared with the expected geographic scene based on the geographic coordinates through consistency cross-validation to obtain the visual comparison result, including: The standard landmark information of the geographic coordinates is obtained by querying the electronic map database using the geographic coordinates. Calculate the semantic similarity between the visual scene features and the standard landmark information; If the semantic similarity is greater than and / or equal to a preset threshold, it is determined to be consistent; if the semantic similarity is lower than the preset threshold, it is determined to be inconsistent. The consistency cross-validation comparison includes calculating the similarity score between the visual scene features and the expected geographical scene, and setting a threshold to determine whether they are consistent.

[0010] According to some embodiments, based on the first matching result and the time comparison result, a authenticity verification result of the travel behavior is generated, including: The similarity score is quantified using one or more combinations of cosine similarity and / or Euclidean distance and / or structural similarity index.

[0011] According to some embodiments, the compliant geographic area is represented in the form of polygons and / or circular geofences, and path accessibility constraints are corrected in conjunction with the transportation network topology.

[0012] According to some embodiments, the method further includes: Acquire and analyze multiple actual spatial trajectories and multiple anomaly verification results generated during multiple travel trips; Based on clustering algorithms, frequently visited geographical areas are identified from multiple actual spatial trajectories. Based on the anomaly verification results, recurring abnormal behavior patterns are identified.

[0013] According to another aspect of the present invention, a travel data management system based on cloud computing and timestamps is provided, the system comprising: The data acquisition module is used to acquire at least one geographic image uploaded by the user during the execution of the travel plan. The geographic image contains geographic coordinates and shooting timestamp metadata. The compliance geographic area generation module is used to generate time-related compliance geographic areas based on the travel plan. The compliant geographic area matching module is used to match the geographic coordinates with the compliant geographic area to obtain a first matching result; The travel time comparison module is used to compare the shooting timestamp metadata with the corresponding travel plan time in the travel plan and obtain the time comparison result; The travel behavior verification module is used to generate a travel behavior authenticity verification result based on the first matching result and the time comparison result; The intelligent audit module is used to automatically generate an electronic audit certificate containing a timestamp, spatial trajectory chain, and geographic image when the authenticity verification result is passed.

[0014] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method as described in any of the preceding claims.

[0015] According to another aspect of the present invention, a computing device is provided, comprising: a processor; and

[0016] A memory storing a computer program that, when executed by the processor, causes the processor to perform the method described in any of the preceding methods.

[0017] According to embodiments of the present invention, a travel data management method based on cloud computing and timestamps is provided. The method generates a time-associated compliant geographical area based on the travel plan, acquires geographical images uploaded by users, identifies and extracts visual scene features from the geographical images, and matches geographical coordinates with the compliant geographical area. A consistency cross-validation comparison is performed between the visual scene features and the expected geographical scene based on the geographical coordinates. Based on the matching result and the consistency cross-validation comparison result, a verification result of the travel behavior is generated. When the verification result is successful, an electronic audit certificate containing a timestamp, spatial trajectory chain, and the geographical image is automatically generated. In summary, the present invention can improve the accuracy of travel behavior authenticity verification, automatically generate highly reliable electronic audit certificates, and provide a data closed loop for intelligent travel management.

[0018] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0020] Figure 1 A flowchart illustrating a cloud-based and timestamped travel data management method according to an example embodiment is shown.

[0021] Figure 2 A schematic diagram illustrating the authenticity verification process for travel behavior according to an example embodiment.

[0022] Figure 3 This diagram illustrates a system schematic for cloud-based and timestamped travel data management according to an example embodiment.

[0023] Figure 4 A block diagram of a computing device according to an exemplary embodiment is shown. Detailed Implementation

[0024] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0025] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a full understanding of embodiments of the invention. However, those skilled in the art will recognize that the technical solutions of the invention can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of the invention.

[0026] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0028] It should be understood that although the terms first, second, third, etc., may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Therefore, the first component discussed below may be referred to as the second component without departing from the teachings of the present invention. As used herein, the term "and / or" includes all combinations of any one and more of the associated listed items.

[0029] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily essential for implementing the present invention, and therefore cannot be used to limit the scope of protection of the present invention.

[0030] With the acceleration of globalization, business trips by employees are increasing, making the effective management and verification of these travel activities a crucial aspect of corporate management. Traditional methods rely primarily on manual review of paper or electronic documents such as invoices and itineraries, which is not only inefficient but also prone to issues like forgery and duplicate reimbursements. In recent years, while some location-based services (LBS) technologies have been applied to travel management, they often only provide basic location information and struggle to fully verify the consistency between the user's actual location and the booked itinerary.

[0031] Travel expenses refer to the intercity transportation, meal, accommodation, and local transportation costs incurred by employees of an organization when temporarily traveling to areas outside their permanent residence for official business. Several problems exist regarding the reimbursement of travel expenses. First, some organizations reimburse expenses exceeding standards or scope. For example, some employees use transportation exceeding their class of service and stay in accommodations exceeding standards, with the excess still being reimbursed by the organization. Some also reimburse meal allowances while simultaneously reimbursing meal expenses incurred during the business trip. Second, some organizations fraudulently obtain travel expenses. For example, some organizations reimburse local transportation allowances even when the organization provides a vehicle, or falsely report the number of business trip days to obtain additional travel expenses. Third, some organizations fail to follow proper travel approval procedures. For example, travel approval forms may be delayed until after the trip, or they may be submitted retroactively when submitting expense reports upon return.

[0032] Traditional travel expense reimbursement and auditing rely on manual documentation. Companies have long depended on paper or electronic receipts such as invoices, itineraries, and hotel bills for travel expense reimbursement, which carries risks such as forgery, duplicate reimbursements, and falsified itineraries. Furthermore, manual review is inefficient and costly. Existing methods typically define static geographical areas based on preset rules for attendance or sign-in, but they lack adaptability to dynamic changes in the time dimension (such as travel time and meeting arrangements) and fail to accurately reflect compliance boundaries.

[0033] To this end, this invention proposes a travel data management method, system, and computing device based on cloud computing and timestamps, which can improve the accuracy of verifying the authenticity of travel activities, automatically generate highly credible electronic audit vouchers, and provide a data closed loop for intelligent travel management.

[0034] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention.

[0035] Figure 1 A flowchart illustrating a cloud-based and timestamped travel data management method according to an example embodiment is shown.

[0036] See Figure 1 This invention provides a travel data management method utilizing cloud computing technology. The travel management method, built on a cloud platform, migrates traditional offline or locally deployed reimbursement processes to a cloud-based intelligent management solution. It integrates functions such as expense application, itinerary booking, invoice uploading, approval workflow management, image data analysis, and user data analysis. Through the internet, it enables cross-regional, multi-terminal collaborative work, reducing enterprise costs, providing automated management capabilities, and enhancing management efficiency.

[0037] In S101, at least one geographic image uploaded by the user during the execution of the travel plan is obtained, the geographic image containing geographic coordinates and shooting timestamp metadata.

[0038] According to some embodiments, the geographic imagery can be acquired autonomously by the user through the camera of a mobile device.

[0039] In S103, a time-related compliant geographic area is generated based on the travel plan.

[0040] According to some implementations, before generating compliant geographic regions, the travel plan is semantically parsed to identify key location entities such as meeting venues, hotels, and transportation hubs.

[0041] According to some embodiments, the travel time is calculated based on the transportation ticket information in the travel plan, and the compliant geographical area of ​​the travel time is defined as a reasonable area on the transportation route. A tolerance (e.g., ±15 minutes) can be added to the calculation of the travel time to handle delays or early arrivals. If there are transfers, each segment of the journey needs to be processed separately.

[0042] According to some embodiments, the compliant geographic area is represented in the form of polygons and / or circular geofences, and path accessibility constraints are corrected in conjunction with the transportation network topology.

[0043] According to some implementations, the overall process for generating compliant geographic regions is as follows: parsing transportation ticket information to extract the trip's origin and destination points, time, and mode of transportation; calculating the travel time and determining the time window based on departure and arrival times; generating an initial compliant geographic region (rough fence) and constructing polygonal or circular regions based on routes or buffer zones; integrating the transportation network topology and using road network / rail / route data to correct the region's accessibility; and outputting the final compliant geographic fence and attribute metadata (time window, mode of transportation, etc.).

[0044] According to some implementation examples, transportation ticket information, such as electronic tickets for air tickets, train tickets, bus tickets, and taxi orders, is parsed to extract fields such as departure point, destination, departure time, arrival time, mode of transportation, and flight / train number.

[0045] According to some embodiments, an initial compliant geographic area, i.e., a coarse fence, is generated, which can be based on a route buffer. The actual driving and running paths are obtained using map services, buffer analysis is performed on the paths, and the initial compliant geographic area is output.

[0046] According to some embodiments, generating an initial compliant geographic area can also be based on a start-end point to output a circular fence. Circles of radius R are drawn with the start and end points as centers (R depends on vehicle speed and time error). Alternatively, an ellipse can be used, with the major axis being the line connecting the start and end points and the minor axis reflecting lateral offset tolerance, ultimately outputting an initial compliant geographic area approximating a circle or polygon.

[0047] According to some implementations, accessibility constraints are corrected by combining the traffic network topology to exclude inaccessible areas (such as rivers, restricted areas, and roadless areas), ensuring that all points within the fence can be reached within time by legal transportation methods. Accessibility constraint correction includes: loading traffic network data, performing accessibility modeling, and calculating all nodes reachable within the travel time period, starting from the origin.

[0048] According to some implementations, the fence is finally trimmed, and the initial compliant geographic area is spatially intersected with the accessible area to exclude inaccessible islands, military zones, water areas, etc. (land use / administrative division layers can be superimposed for filtering) to obtain a compliant geographic fence that conforms to actual traffic capacity.

[0049] In S105, visual scene features in the geographic image are identified and extracted, and the geographic coordinates are matched with the compliant geographic area to obtain a first matching result.

[0050] According to some embodiments, it is determined whether the visual scene features match the type and location of the event in the travel plan, and whether the shooting time inferred through image light and shadow analysis matches the planned time of the event.

[0051] According to some embodiments, a geographic image and its geographic coordinates in the image metadata are obtained, and combined with a predefined compliant geographic area, a match is made to determine whether the image was actually taken within the compliant geographic area.

[0052] According to some embodiments, the present invention incorporates tolerance processing. If there is an error in the geographic coordinate matching, the compliant area can be expanded by a buffer zone (e.g., +50 meters), or the minimum distance from the point to the polygon boundary can be calculated and a threshold can be set (e.g., ≤30 meters is considered compliant). If there are multiple visual matching candidate points, compliance can be determined as long as one of them is within the compliant area and has a high confidence level.

[0053] According to some embodiments, the visual scene features are cross-validated and compared with the expected geographical scene based on the geographical coordinates to obtain the visual comparison results. The extracted explicit geographical coordinates, shooting timestamps, and implicit scene information are automatically matched and spatially logically consistent with the travel plan. The spatial logical consistency verification includes trajectory rationality analysis based on the geographical coordinates and timestamps of two consecutive images.

[0054] According to some embodiments, the consistency cross-validation comparison includes calculating a similarity score between the visual scene features and the expected geographical scene, and setting a threshold to determine whether they are consistent. The similarity score is quantified using one or more combinations of cosine similarity and / or Euclidean distance or structural similarity index.

[0055] According to some embodiments, the standard landmark information of the geographic coordinates is obtained by querying an electronic map database, and the semantic similarity between the visual scene features and the standard landmark information is calculated. If the semantic similarity is greater than or equal to a preset threshold, it is determined to be consistent; if the semantic similarity is lower than the preset threshold, it is determined to be inconsistent.

[0056] In S107, the shooting timestamp metadata is compared with the corresponding travel plan time in the travel plan to obtain the time comparison result.

[0057] According to some embodiments, the shooting timestamp and the travel plan time are synchronized in the same time zone.

[0058] According to some implementations, the image capture timestamp is extracted, and the corresponding travel plan time window is obtained. The two are then compared logically, meaning the capture timestamp time falls within the travel plan time window. Considering common business practices, a certain degree of deviation (such as traffic delays or clock-in delays) can be allowed, and a time tolerance can be introduced to improve the flexibility and accuracy of the comparison.

[0059] In S109, based on the first matching result and the time comparison result, a verification result of the authenticity of the difference travel behavior is generated.

[0060] According to some embodiments, see Figure 2 Combining the first matching result obtained in S105, the visual comparison result, and the time comparison result obtained in S107, the formality verification result is obtained. If the matching result between the geographic coordinates and the compliant geographic area is successful, the consistency cross-validation comparison result is consistent, and the time comparison is consistent, then the authenticity verification result of the travel behavior is determined.

[0061] According to some embodiments, the first matching result and the visual comparison result are used to determine whether the geographic coordinates are within a compliant geographic area, i.e., spatial compliance, and the temporal comparison result is used to determine whether the shooting time is within a compliant time window, i.e., temporal compliance. Only when both spatial and temporal compliance are met is the captured image considered a valid travel voucher.

[0062] For example, if the expense item is "customer dinner" but the image is analyzed by light and shadow and shows lunchtime, or if the restaurant is identified as a "fast food restaurant" which does not match the high expense amount, then it will be automatically marked as "the reason and scenario do not match".

[0063] In S111, when the authenticity verification result is successful, an electronic audit certificate containing a timestamp, spatial trajectory chain, and geographic image is automatically generated.

[0064] According to some embodiments, the electronic audit credentials are stored using blockchain technology via hashing to ensure the immutability of timestamps, spatial trajectory chains, and geographic images.

[0065] According to some embodiments, the method of the present invention further includes: acquiring and analyzing multiple actual spatial trajectories and multiple anomaly verification results generated during multiple business trips; identifying frequently visited geographical areas from the multiple actual spatial trajectories based on a clustering algorithm; and mining recurring abnormal behavior patterns based on the anomaly verification results, and generating optimization suggestions for business trip policies.

[0066] This invention establishes an adaptive boundary adjustment mechanism by combining time comparison with scene recognition and geographic coordinate matching, effectively and automatically determining the authenticity of business trips. This invention improves the accuracy of business trip authenticity verification, automatically generates highly reliable electronic audit vouchers, and provides a data closed loop for intelligent business trip management.

[0067] This invention relies solely on geotagged photos taken by users' mobile phones, without needing to connect to third-party systems. By applying a dynamic tolerance mechanism, it avoids misjudgments due to reasonable deviations such as traffic delays, and automatically generates auditable electronic vouchers, realizing "image as evidence".

[0068] This invention provides an enterprise-level online retail service solution. With the digital capabilities of cloud platform intelligent selection, it meets the personalized, customized and differentiated consumer product demands of enterprise and institutional clients in terms of employee consumption, benefits and operational procurement. It helps enterprises build and integrate consumer product supply chains, provides ideas for the financial informatization construction of enterprises and institutions, and helps digital transformation and high-quality development.

[0069] Figure 3 This diagram illustrates a system schematic for cloud-based and timestamped travel data management according to an example embodiment.

[0070] See Figure 3 , Figure 3 A system for optimizing travel plans is shown, comprising: a data acquisition module 01, a compliant geographic area generation module 02, a compliant geographic area matching module 03, a travel time comparison module 04, a travel behavior verification module 05, and an intelligent audit module 06.

[0071] The data acquisition module 01 is used to acquire at least one geographic image uploaded by the user during the execution of a business trip plan. The geographic image includes geographic coordinates and shooting timestamp metadata. The compliant geographic area generation module 02 is used to generate a compliant geographic area associated with time based on the business trip plan. The compliant geographic area matching module 03 is used to identify and extract visual scene features in the geographic image, match the geographic coordinates with the compliant geographic area, and obtain a first matching result. The business trip time comparison module 04 is used to compare the shooting timestamp metadata with the corresponding business trip plan time in the business trip plan and obtain a time comparison result. The business trip behavior verification module 05 is used to generate a business trip behavior authenticity verification result based on the first matching result, the visual comparison result, and the time comparison result. The intelligent audit module 06 is used to automatically generate an electronic audit voucher containing a timestamp, a spatial trajectory chain, and the geographic image when the authenticity verification result is verified as passed. The system of the present invention also includes a consistency cross-validation module, which is used to perform consistency cross-validation comparison between the visual scene features and the expected geographic scene based on the geographic coordinates to obtain a visual comparison result. Figure 3 The system shown is Figure 1 The methods shown correspond to each other, and the same content will not be repeated.

[0072] According to some embodiments, the system of the present invention performs time and space consistency verification between captured images and preset travel plans, completes automatic intelligent matching and comparison, and generates complete electronic vouchers with timestamps, spatial trajectories and behavioral evidence, which significantly improves the intelligence level and audit efficiency of travel management.

[0073] According to some embodiments, the system of the present invention is adapted to different operating system platforms (iOS, Android, HarmonyOS), embedded in mobile devices, and realizes convenient and fast function calls and data interaction through a unified API interface.

[0074] According to some embodiments, the present invention is not only applicable to the travel management system of large enterprises, but can also be widely applied to organizations that require strict travel control, such as government agencies, scientific research institutions, and educational systems, and has important practical significance and broad application prospects.

[0075] This invention provides an enterprise-level online retail service solution. With the digital capabilities of intelligent selection, it meets the personalized, customized, and differentiated consumer product demands of enterprise and institutional clients in areas such as employee consumption, benefits, and operational procurement. It helps enterprises build and integrate consumer product supply chains, provides ideas for the financial informatization construction of enterprises and institutions, and helps digital transformation and high-quality development.

[0076] This invention achieves high-precision and robust image recognition of travel destinations, overcoming interference from changes in lighting, weather, and viewing angle; it supports rapid feature retrieval and matching, ensuring real-time performance while improving recognition accuracy; it automatically matches and verifies the consistency of image recognition results with preset travel plans, ensuring the authenticity of travel activities, reducing manual intervention, and improving approval efficiency; it generates complete electronic vouchers containing timestamps, spatial trajectories, and image evidence, enhancing audit traceability; and it supports automatic archiving and analysis of anomaly identification records, helping companies continuously optimize their travel policies.

[0077] Figure 4 A block diagram of a computing device according to an exemplary embodiment of the present invention is shown.

[0078] like Figure 4 As shown, the computing device 30 includes a processor 12 and a memory 14. The computing device 30 may also include a bus 22, a network interface card 16, and an I / O interface 18. The processor 12, memory 14, network interface card 16, and I / O interface 18 can communicate with each other via the bus 22.

[0079] Processor 12 may include one or more general-purpose CPUs (Central Processing Units), microprocessors, or application-specific integrated circuits, for executing relevant program instructions. According to some embodiments, computing device 30 may also include a high-performance display adapter (GPU) 20 for accelerating processor 12.

[0080] Memory 14 may include a machine system readable medium in the form of volatile memory, such as random access memory (RAM), read-only memory (ROM), and / or cache memory. Memory 14 is used to store one or more programs containing instructions, as well as data. Processor 12 may read the instructions stored in memory 14 to perform the methods described above according to embodiments of the present invention.

[0081] The computing device 30 can also communicate with one or more networks via the network interface card 16. The network interface card 16 can be a DPU smart network card.

[0082] Bus 22 can include address bus, data bus, control bus, etc. Bus 22 provides a path for exchanging information between components.

[0083] It should be noted that, in specific implementations, the computing device 30 may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the device described above may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0084] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), network storage devices, cloud storage devices, or any type of medium or device suitable for storing instructions and / or data.

[0085] This invention also provides a computer program product comprising a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0086] Those skilled in the art will clearly understand that the technical solutions of the present invention can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware capable of independently performing or cooperating with other components to perform a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit, etc.

[0087] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0088] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0089] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0090] 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.

[0091] Furthermore, the functional units in the various embodiments of the present invention 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.

[0092] 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 device. Based on this understanding, the technical solution of the present invention, 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 memory 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 of the various embodiments of the present invention.

[0093] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0094] Exemplary embodiments of the present invention have been specifically shown and described above. It should be understood that the present invention is not limited to the detailed structures, arrangements, or implementations described herein; rather, the present invention is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended provisions.

Claims

1. A cloud computing-based travel data management method, characterized by, The method includes: Obtain at least one geographic image uploaded by the user during the execution of a travel plan, the geographic image containing geographic coordinates and shooting timestamp metadata; Based on the travel plan, generate compliant geographic regions that are time-related; The geographic coordinates are matched with the compliant geographic areas to obtain a first matching result; The shooting timestamp metadata is compared with the corresponding travel plan time in the travel plan to obtain the time comparison result; Visual scene features in the geographic image are identified and extracted. These visual scene features are then cross-validated against a predicted geographic scene based on the geographic coordinates to obtain a visual comparison result. The process involves querying an electronic map database using the geographic coordinates to obtain standard landmark information for those coordinates; calculating the semantic similarity between the visual scene features and the standard landmark information; determining consistency if the semantic similarity is greater than and / or equal to a preset threshold, and determining inconsistency if the semantic similarity is lower than the preset threshold. The consistency cross-validation includes calculating a similarity score between the visual scene features and the predicted geographic scene, and setting a threshold to determine consistency. Based on the first matching result, the time comparison result, and the visual comparison result, a authenticity verification result of the difference travel behavior is generated; When the authenticity verification result is successful, an electronic audit certificate containing a timestamp, spatial trajectory chain, and geographic image is automatically generated.

2. The method of claim 1, wherein, Also includes: Whether the shooting time inferred by image light and shadow analysis matches the shooting timestamp.

3. The method of claim 1, wherein, Based on the first matching result and the time comparison result, a authenticity verification result for the difference travel behavior is generated, including: The similarity score is quantified using one or more combinations of cosine similarity and / or Euclidean distance and / or structural similarity index.

4. The method of claim 1, wherein, The compliant geographic areas are represented in the form of polygonal and / or circular geofences, and path accessibility constraints are corrected in conjunction with the transportation network topology.

5. The method of claim 1, wherein, The method further includes: Acquire and analyze multiple actual spatial trajectories and multiple anomaly verification results generated during multiple travel trips; Based on clustering algorithms, frequently visited geographical areas are identified from multiple actual spatial trajectories. Based on the anomaly verification results, recurring abnormal behavior patterns are identified.

6. A computer program product, characterised in that, Includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-5.

7. A computing device, comprising: include: processor; as well as A memory storing a computer program that, when executed by the processor, causes the processor to perform the method as described in any one of claims 1-5.

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