Vehicle Certificate of Title Processing Method, Device, Equipment and Medium Based on RPA and AI

Abstract

The present application provides a method, apparatus, device and medium for processing vehicle ownership certificates based on RPA and AI. Among them, the method includes: S1. Identify the content of each picture corresponding to the same vehicle ownership certificate to obtain an identification result containing multiple key information, and the key information includes vehicle registration number information, vehicle model information, engine model information and registration date information; S2. Determine whether each item of key information meets the corresponding coding requirements, and the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format; S3. Determine the storage address of the identification result according to the judgment result, and store the identification result according to the storage address. By adopting the above technical solution, the problems of low efficiency and accuracy in manually processing the content of vehicle ownership certificates are solved.

Description

Technical Field

[0001] The present application relates to the field of process automation technology, and in particular to a vehicle title certificate processing method, device, equipment and medium based on RPA and AI. Background Art

[0002] Robotic Process Automation (RPA) uses specific "robot software" to simulate human operations on computers and automatically execute process tasks according to rules.

[0003] Artificial Intelligence (AI) is a technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

[0004] RPA offers unique advantages: low-code and non-invasive. Low-code means RPA doesn't require advanced IT expertise to operate, allowing business personnel without programming skills to develop processes. Non-invasive means RPA can simulate human operations without requiring open interfaces in software systems. However, traditional RPA has limitations: it relies solely on fixed rules and has limited application scenarios. With the continuous development of AI technology, the deep integration of RPA and AI has overcome these limitations. RPA + AI = Handwork + Headwork, significantly changing the value of the workforce.

[0005] In the prior art, vehicle title certificates are processed manually. This process involves scanning the certificate with a desktop scanner and manually entering information from the certificate, such as name, ID card, vehicle registration number, vehicle model, engine number, serial number, and registration date, into the system. Since the Archives Administration processes thousands, or even tens of thousands, of vehicle title certificates daily, manually entering them into its internal digital system can lead to low efficiency and accuracy. Summary of the Invention

[0006] The present application provides a method, apparatus, device, and medium for processing vehicle title certificates based on RPA and AI to address the low efficiency and accuracy of manual processing of vehicle title certificates. The technical solution is as follows:

[0007] In a first aspect, an embodiment of the present application provides a method for processing vehicle title certificates based on RPA and AI, including:

[0008] S1. Identify the content of each picture corresponding to the same vehicle property certificate to obtain an identification result containing multiple key information, where the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information;

[0009] S2. Determine whether each key information meets the corresponding coding requirements, where the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format;

[0010] S3. Determine the storage address of the identification result according to the judgment result, and store the identification result according to the storage address.

[0011] Optionally, step S1 specifically includes:

[0012] Call the optical character recognition OCR component to identify the content of each picture corresponding to the same vehicle property certificate to obtain an identification result containing multiple key information.

[0013] Optionally, before identifying the content of each picture corresponding to the same vehicle property certificate, the method provided by the embodiment of the present application further includes:

[0014] Determine the vehicle registration number information in each picture, and determine each picture belonging to the same vehicle property certificate according to the vehicle registration number information;

[0015] Among them, the vehicle registration number information in different page pictures belonging to the same vehicle property certificate is the same.

[0016] Optionally, step S2 specifically includes:

[0017] S21. Store each key information into a table according to the corresponding preset field;

[0018] S22. For each key information that has been stored, judge whether each key information meets the corresponding coding requirements based on the natural language processing NLP service;

[0019] Correspondingly, step S3 specifically includes:

[0020] S31. If each key information meets the corresponding coding requirements, store the table into the first folder corresponding to the first storage address;

[0021] S32. If there is at least one key information that does not meet the corresponding coding requirements, store the table and the corresponding vehicle property certificate picture into the second folder corresponding to the second storage address, where the first storage address and the second storage address are different.

[0022] Optionally, the method provided by the embodiment of the present application further includes:

[0023] S23. Mark the key information in the table that does not meet the corresponding coding requirements.

[0024] Optionally, the method provided in the embodiments of the present application further includes:

[0025] Initiate a manual review request, which is used to instruct the user to correct the key information that does not meet the corresponding coding requirements.

[0026] Optionally, the method provided in the embodiments of the present application further includes:

[0027] Enter the recognition results in the first folder into the business operation system, and

[0028] Enter the recognition results with the corrected key information into the business operation system.

[0029] In a second aspect, the embodiments of the present application provide a vehicle property certificate processing device based on RPA and AI, including:

[0030] An identification module, configured to identify the content of each picture corresponding to the same vehicle property certificate, and obtain an identification result including a plurality of key information, where the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information;

[0031] A matching module, configured to determine whether each item of key information meets the corresponding coding requirements, where the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to a preset date format;

[0032] A storage module, configured to determine the storage address of the recognition result according to the judgment result, and store the recognition result according to the storage address.

[0033] Optionally, the identification module is specifically configured to:

[0034] Call the optical character recognition (OCR) component to identify the content of each picture corresponding to the same vehicle property certificate, and obtain an identification result including a plurality of key information.

[0035] Optionally, the device provided in the embodiments of the present application further includes:

[0036] A registration number information determination module, configured to determine the vehicle registration number information in each picture, and determine each picture belonging to the same vehicle property certificate according to the vehicle registration number information;

[0037] Among them, the vehicle registration number information in different page pictures belonging to the same vehicle property certificate is the same.

[0038] Optionally, the matching module is specifically configured to:

[0039] Store each key information into a table according to the corresponding preset fields;

[0040] For each stored key information, based on the natural language processing NLP service, determine whether each key information meets the corresponding coding requirements;

[0041] Correspondingly, the storage module is specifically configured to:

[0042] If each key information meets the corresponding coding requirements, store the table into the first folder corresponding to the first storage address;

[0043] If there is at least one key information that does not meet the corresponding coding requirements, store the table and the corresponding vehicle property certificate picture into the second folder corresponding to the second storage address, where the first storage address and the second storage address are different.

[0044] Optionally, the device provided by the embodiment of the present application further includes:

[0045] The marking module is configured to mark the key information in the table that does not meet the corresponding coding requirements.

[0046] Optionally, the device provided by the embodiment of the present application further includes:

[0047] The request sending module is configured to initiate an artificial review request, and the artificial review request is used to instruct the user to correct the key information that does not meet the corresponding coding requirements.

[0048] Optionally, the device provided by the embodiment of the present application further includes:

[0049] The information entry module is configured to enter the recognition result in the first folder into the business operation system, and enter the recognition result after correcting the key information into the business operation system.

[0050] In a third aspect, an embodiment of the present application provides a device for processing vehicle property certificates. The device includes: a memory and a processor. Among them, the memory and the processor communicate with each other through an internal connection path. The memory is used to store instructions, and the processor is used to execute the instructions stored in the memory. When the processor executes the instructions stored in the memory, the processor executes the method in any one of the above aspects.

[0051] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on a computer, the method in any one of the above aspects is executed.

[0052] In the technical solution provided by the embodiment of the present application, the RPA robot identifies the content of each picture corresponding to the same vehicle property certificate, solving the problem of being time-consuming and laborious when manually processing a large number of vehicle property certificate pictures. Moreover, the RPA robot saves the time for manually judging key information by replacing manual judgment on whether each key information meets the corresponding coding requirements, improving the processing efficiency and accuracy of key information. In addition, the RPA robot determines the storage address of the recognition result according to the judgment result and stores the recognition result according to the storage address, further saving the time for manually processing the recognition result and improving the processing efficiency of the vehicle property certificate recognition result.

[0053] The advantages or beneficial effects in the above technical solution at least include:

[0054] 1. The RPA robot identifies the content of each picture corresponding to the same vehicle property certificate, solving the problem of being time-consuming and laborious when manually processing a large number of vehicle property certificate pictures. Moreover, the RPA robot saves the time for manually judging key information by replacing manual judgment on whether each key information meets the corresponding coding requirements, improving the processing efficiency and accuracy of key information.

[0055] 2. By adopting the method of combining RPA and AI to identify the picture content of the vehicle property certificate, the time for manually scanning pictures is saved, and the recognition efficiency and accuracy of the pictures are improved.

[0056] 3. By storing the recognition results corresponding to each key information that meets the corresponding coding requirements and the recognition results corresponding to the key information that does not meet the corresponding coding requirements at different storage addresses, it helps to manage different recognition results and is also convenient for subsequent staff to uniformly correct the key information that does not meet the corresponding coding requirements.

[0057] The above summary is only for the purpose of the specification and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present application will be readily apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In the drawings, unless otherwise specified, the same reference numerals throughout the several views denote the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0059] Figure 1 is a flowchart of a method for processing vehicle property certificates based on RPA and AI provided by Embodiment 1 of the present application;

[0060] Figure 2a This is a flowchart of a method for processing vehicle ownership certificates based on RPA and AI provided in the second embodiment of this application;

[0061] Figure 2b This is a screenshot of the effect of the first page picture of a vehicle ownership certificate provided in the second embodiment of this application;

[0062] Figure 2c This is a screenshot of the effect of the third page picture of a vehicle ownership certificate provided in the second embodiment of this application;

[0063] Figure 3 This is a structural block diagram of a device for processing vehicle ownership certificates based on RPA and AI provided in the third embodiment of this application;

[0064] Figure 4 This is a structural block diagram of a device for processing vehicle ownership certificates provided in the fourth embodiment of this application. Detailed implementation manners

[0065] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions from beginning to end. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present application and should not be construed as a limitation to the present application.

[0066] In the description of the present application, the term "vehicle ownership certificate" refers to an important certificate for proving the ownership of a motor vehicle and recording other conditions. Among them, there is a unique corresponding identifier for the vehicle ownership certificate, that is, the vehicle registration number information.

[0067] In the description of the present application, the term "coding requirement" refers to the standards corresponding to different key information. For example, there is a fixed digit requirement for the ID number, and there is also a corresponding digit requirement for the vehicle registration number.

[0068] In the description of the present application, the term "NLP" refers to Natural Language Processing, which is a discipline that specifically studies the language problems of the interaction between humans and computers. In the embodiments of the present application, the NLP service is used to judge whether the key information meets the corresponding coding requirements. For example, it is judged whether the number of digits of the ID number is the first set number of digits, and whether the number of digits of the vehicle registration number is the second set number of digits.

[0069] In the description of the present application, the term "OCR" refers to Optical Character Recognition, specifically a process in which an electronic device examines the characters printed on paper, determines their shapes by detecting dark and bright patterns, and then translates the shapes into computer text using character recognition methods; that is, for printed characters, it adopts an optical method to convert the text in a paper document into an image file of black and white dot matrices, and converts the text in the image into a text format through recognition software for further editing and processing by word processing software.

[0070] In the description of the present application, the term "preset field" refers to the key information in the vehicle ownership certificate. For example, name, ID card, vehicle registration number, vehicle model, registration date, etc. The "attribute value" corresponding to the "preset field" refers to the specific content of the key information. For example, the attribute value corresponding to "name" is "Zhang San", and the attribute value corresponding to "registration date" is December 30, 2021.

[0071] In the description of the present application, the term "manual review request" refers to Robotic Process Automation (RPA). When the robot determines that the key information does not meet the corresponding coding requirements, it sends a manual review request to the staff to request the staff to correct the key information that does not meet the coding requirements.

[0072] In the description of the present application, the term "business operation system" is a business operation system used within an enterprise for managing vehicle ownership certificate information, in which the key information in the vehicle ownership certificate is recorded.

[0073] With reference to the following description and drawings, these and other aspects of the embodiments of the present application will become clear. In these descriptions and drawings, some specific implementation manners in the embodiments of the present application are specifically disclosed to represent some ways of implementing the principles of the embodiments of the present application, but it should be understood that the scope of the embodiments of the present application is not limited thereto. On the contrary, the embodiments of the present application include all variations, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0074] The following describes in detail the vehicle ownership certificate processing method, device, equipment, and medium provided by the embodiments of the present application based on RPA and AI with reference to the drawings.

[0075] Embodiment 1

[0076] Figure 1FIG. 0 is a flowchart of a method for processing vehicle property certificates provided in the first embodiment of the present application. This method can be applied to the management process of vehicle property certificate information. The technical solution of this embodiment is executed by an RPA robot, which can be carried on the UiBot Creator platform. The UiBot Creator platform is a professional and powerful robot production tool that provides a good carrier for the robot. In this embodiment, the RPA robot can be set to start regularly every day, and check whether there is vehicle property certificate information that needs to be identified and entered in the set folder, so as to avoid the backlog of vehicle property certificate information to be processed, and achieve the effect of improving the processing efficiency of vehicle property certificate information. As Figure 1 shown, the method provided in this embodiment includes:

[0077] S110. Identify the content of each picture corresponding to the same vehicle property certificate to obtain an identification result containing multiple key information.

[0078] Among them, the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information.

[0079] In this embodiment, for the vehicle property certificates submitted by employees to the financial system, the vehicle property certificates usually exist in the form of pictures or photocopies. When the RPA robot identifies the content of the vehicle property certificate, it can combine the OCR ability in the Artificial Intelligence (AI) technology to identify the picture of the vehicle property certificate to obtain the identification result of the vehicle property certificate content.

[0080] In this embodiment, the AI platform with picture and table recognition functions is the UiBot Mage platform. The UiBot Mage platform is a tool-type product that mainly provides AI capability support for RPA robot developers. Both the platform and the UiBot Creator platform carried by the RPA robot rely on the UiBot platform. The UiBot platform is a process automation expert and is a platform that provides intelligent robot services for the entire business process for various types of requirements.

[0081] Optionally, a target account that logs in to both the RPA platform and the AI platform, that is, the UiBot account, can be used to combine the platform carried by the RPA robot with the AI platform. After using the target account to log in to both the platform carried by the RPA robot and the AI platform, the platform carried by the RPA robot establishes a communication connection with the AI platform, that is, the RPA robot can directly call the OCR recognition function published by the AI platform to recognize the content of the vehicle ownership certificate. With this setting, compared with the related technology where the OCR function is first used in the AI platform to recognize each picture of the vehicle ownership certificate, and then the recognized data is exported manually and then imported into the RPA platform manually, this embodiment combines the RPA platform with the AI platform, solving the problem of time-consuming and laborious in the process of recognizing vehicle ownership certificate pictures in the related technology and improving the recognition efficiency of vehicle ownership certificate pictures. In addition, in the case of a large number of vehicle ownership certificate pictures, compared with the related technology where pictures are scanned manually in sequence, this embodiment effectively saves the time of staff and reduces the labor cost.

[0082] S120. Determine whether each key piece of information meets the corresponding coding requirements.

[0083] Among them, the coding requirements for different key pieces of information are different. For example, the coding requirements may include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format. For example, the slash " / " is used as the separator between the year, month, and day, etc.

[0084] Specifically, for the key piece of information of the ID card number, the RPA robot can determine whether the number of digits of the ID card number is the first set number of digits. If the number of digits of the ID card number is the first set number of digits, it is determined that the key piece of information of the ID card number meets the corresponding coding requirements; if the number of digits of the ID card number is not the first set number of digits, it is determined that the key piece of information of the ID card number does not meet the corresponding coding requirements.

[0085] For the key piece of information of the vehicle registration number, the RPA robot can determine whether the number of digits of the vehicle registration number is the second set number of digits. If the number of digits of the vehicle registration number is the second set number of digits, it is determined that the key piece of information of the vehicle registration number meets the corresponding coding requirements; if the number of digits of the vehicle registration number is not the second set number of digits, it is determined that the key piece of information of the vehicle registration number does not meet the corresponding coding requirements.

[0086] For the key piece of information of the registration date, the RPA robot can determine whether the registration date conforms to the preset format. If the format of the registration date is the preset format, it is determined that the key piece of information of the registration date meets the corresponding coding requirements; if the format of the registration date is the preset format, it is determined that the key piece of information of the registration date does not meet the corresponding coding requirements.

[0087] S130. Determine the storage address of the recognition result according to the judgment result, and store the recognition result according to the storage address.

[0088] In this embodiment, the judgment result includes the situation where each key information meets the corresponding coding requirements, that is, the matching is successful, and the situation where at least one key information does not meet the corresponding coding requirements, that is, the matching fails. For different matching situations, the storage address of the recognition result of the vehicle property certificate content in this embodiment is different. Such a setting is to facilitate the unified processing of different judgment results by the RPA robot. For example, in the case of successful matching, the RPA robot can store the recognition result in a specified folder, and can name the folder "processing successful", and then can enter each key information into the business operation system. In the case of failed matching, the RPA robot can store the recognition result in another specified folder, and can name the folder "processing failed". For the folder of processing failed, the RPA robot can initiate a manual review request to indicate that the human operator corrects the key information that does not meet the corresponding coding requirements in this folder.

[0089] Further, after the RPA robot stores the recognition result of the vehicle property certificate, it can delete the vehicle property certificate information corresponding to the recognition result stored in the original set folder, so that the set folder stores only the vehicle property certificate information to be processed.

[0090] In this embodiment, the RPA robot solves the problem of time-consuming and laborious manual processing of a large number of vehicle property certificate pictures by recognizing the content of each picture corresponding to the same vehicle property certificate. The RPA robot saves the time for manual judgment of key information by replacing manual judgment of whether each key information meets the corresponding coding requirements, and improves the processing efficiency and accuracy of key information. In addition, the RPA robot further saves the time for manual processing of the recognition result by determining the storage address of the recognition result according to the judgment result and storing the recognition result according to the storage address, and improves the processing efficiency of the vehicle property certificate recognition result.

[0091] Embodiment 2

[0092] Figure 2a The figure is a flowchart of a method for processing vehicle property certificates based on RPA and AI provided in Embodiment 2 of this application. On the basis of the above embodiment, the operation process before recognizing the content of each picture corresponding to the vehicle property certificate, the operation process of determining the storage address of the recognition result according to the judgment result, and the subsequent correction process of the key information that does not meet the corresponding coding requirements are refined. As Figure 2a shown, the method provided in this embodiment includes:

[0093] S210. Determine the vehicle registration number information in each picture, and determine the pictures belonging to the same vehicle property certificate according to the vehicle registration number information.

[0094] Among them, the vehicle registration number information is the unique identifier of the vehicle property certificate. There are multiple pages for the same vehicle property certificate, and each page has identification information corresponding to the vehicle property certificate, that is, the vehicle registration number information.

[0095] In this embodiment, before the RPA robot recognizes the content of each page picture of the vehicle property certificate, it can first determine the vehicle registration number information in each picture, and determine the pictures belonging to the same vehicle property certificate according to the vehicle registration number information. The advantage of this setting is that when the number of pictures of the vehicle property certificate processed by the RPA robot is large, it can effectively classify each picture according to its belonging vehicle registration number information, so as to facilitate the subsequent recognition of the content of each picture belonging to the same vehicle property certificate.

[0096] Specifically, Figure 2b It is a screenshot of the effect of the first page picture of the vehicle property certificate. For the first page picture of the vehicle property certificate, its vehicle registration number information is located below the barcode in the upper right corner. Figure 2c It is a screenshot of the effect of the third page picture of a vehicle property certificate provided in the second embodiment of the present application. Its vehicle registration number information is also located in the upper right corner of the picture. The RPA robot can first recognize the layout information of the picture to obtain the region of interest (ROI), that is, the region where the vehicle registration number information is located, and then extract the vehicle registration number information from this region of interest. Among them, for the first page picture of the vehicle property certificate, the RPA robot can also call the OCR component to recognize the barcode on the first page to obtain the vehicle registration number information.

[0097] In this embodiment, after the RPA robot obtains the vehicle registration number information corresponding to each picture, it can establish an association relationship between the pictures according to the vehicle registration number information, that is, determine the pictures belonging to the same vehicle property certificate, so as to uniformly process the pictures belonging to the same vehicle property certificate.

[0098] S220. Call the optical character recognition OCR component to recognize the content of each picture corresponding to the same vehicle property certificate.

[0099] S230. Store each key information into a table according to the corresponding preset fields.

[0100] Specifically, Table 1 below is the motor vehicle property right registration form. As shown in Table 1, it contains preset fields, namely the table headers, such as name, ID card, vehicle registration number, vehicle model, engine number, number, registration date, file name, and input status, etc. The RPA robot can fill in the corresponding table headers with each key information. Such a setting is to uniformly process the recognition results of the same vehicle property right certificate and is also convenient for subsequent entry of each key information in the same vehicle property right certificate into the business processing system.

[0101] Table 1 Motor Vehicle Property Right Registration Certificate

[0102] Name ID Card Vehicle Registration Number Vehicle Model Engine Number Number Registration Date File Name Input Status

[0103] S240. For each key information that has been stored, based on the NLP service, determine whether each key information meets the corresponding coding requirements. If so, execute step S250; otherwise, execute step S260.

[0104] S250. Save the form into the first folder corresponding to the first storage address and continue to execute step S280.

[0105] S260. Save the form and the corresponding vehicle property right certificate picture into the second folder corresponding to the second storage address, and mark the key information in the form that does not meet the corresponding coding requirements, and continue to execute step S270.

[0106] Among them, the storage addresses of the second folder and the first folder are different. In this embodiment, the recognition results corresponding to the key information that meets the corresponding coding requirements and the recognition results corresponding to the key information that does not meet the corresponding coding requirements are stored using different storage addresses. Such a setting is to facilitate the management of different recognition results and is also convenient for subsequent staff to uniformly correct the key information that does not meet the corresponding coding requirements.

[0107] In this embodiment, to mark the key information in the form that does not meet the corresponding coding requirements, the background corresponding to the key information that does not meet the corresponding coding requirements can be highlighted, or the key information that does not meet the corresponding coding requirements and other key information that meets the corresponding coding requirements can be distinguished and displayed in different colors. Such a setting is convenient for subsequent manual correction of the key information that does not meet the corresponding coding requirements, enabling a direct and clear understanding of which key information needs to be corrected and which does not.

[0108] S270. Initiate a manual review request and continue to execute step S280.

[0109] For example, the RPA robot sends an email or SMS notification to the relevant staff member requesting manual review. Upon receiving the manual review request, the staff member can modify the form stored in the second folder. Specifically, if the staff member does not modify key information to meet the corresponding coding requirements, they can modify it based on the original images corresponding to the vehicle title certificate. After the modification is completed, a correction mark can be added to the key information. For example, the original mark can be deleted to indicate that the key information now meets the corresponding coding requirements.

[0110] For example, an RPA robot can send a manual review request to a human-machine collaboration server via an RPA robot server. This manual review request includes the recognition results for key information that does not meet the corresponding coding requirements, as well as an original image of the vehicle title certificate. The human-machine collaboration server is a platform that manages the collaborative work between humans and robots, supporting the assignment of tasks requiring human judgment and decision-making to human personnel. Upon receiving the manual review request from the RPA robot server, the human-machine collaboration server displays the recognition results and the original image of the vehicle title certificate to the user through the client's display interface. The user can modify the key information on this interface and, after completing the modification, trigger a submit command to upload the modified recognition results to the human-machine collaboration server. The human-machine collaboration server then sends the modified results to the RPA robot server, which in turn controls the RPA robot to upload the modified results to the enterprise's internal business operating system.

[0111] S280: Enter the recognition result in the first folder into the business operating system, and enter the recognition result after the key information is corrected into the business operating system.

[0112] In this embodiment, after the RPA robot enters the key information into the business operating system, it can modify the entry status in Table 1 above to "entered".

[0113] The technical solution provided in this embodiment determines the vehicle registration number information in each image before identifying the content of each image corresponding to the same vehicle title certificate. This allows the images belonging to the same vehicle title certificate to be identified based on the vehicle registration number information. This allows the RPA robot to effectively classify each image according to its vehicle registration number information, even when processing a large number of vehicle title certificate images, facilitating subsequent content identification of images belonging to the same vehicle title certificate. Furthermore, by storing the recognition results corresponding to key information that meets the corresponding coding requirements in different storage addresses than the recognition results corresponding to key information that does not meet the corresponding coding requirements, it facilitates the management of different recognition results and facilitates subsequent staff to uniformly correct key information that does not meet the corresponding coding requirements.

[0114] Embodiment III

[0115] Figure 3 As shown in the structural block diagram of a vehicle property certificate processing device based on RPA and AI provided in Embodiment III of this application, the device can be implemented in software and / or hardware. As Figure 3 shown, the device includes: an identification module 310, a matching module 320, and a storage module 330, where

[0116] The identification module 310 is configured to identify the content of each picture corresponding to the same vehicle property certificate, and obtain an identification result including multiple key information, where the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information;

[0117] The matching module 320 is configured to determine whether each key information meets the corresponding coding requirements, where the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format;

[0118] The storage module 330 is configured to determine the storage address of the identification result according to the judgment result, and store the identification result according to the storage address.

[0119] Optionally, the identification module 310 is specifically configured to:

[0120] Call the optical character recognition OCR component to identify the content of each picture corresponding to the same vehicle property certificate, and obtain an identification result including multiple key information.

[0121] Optionally, the device provided in the embodiment of this application further includes:

[0122] The registration number information determination module is configured to determine the vehicle registration number information in each picture, and determine each picture belonging to the same vehicle property certificate according to the vehicle registration number information;

[0123] Among them, the vehicle registration number information in different page pictures belonging to the same vehicle property certificate is the same.

[0124] Optionally, the matching module 320 is specifically configured to:

[0125] Store each key information into a table according to the corresponding preset fields;;

[0126] For each key information that has been stored, based on the natural language processing NLP service, determine whether each key information meets the corresponding coding requirements;

[0127] Correspondingly, the storage module 330 is specifically configured to:

[0128] If all key information meets the corresponding coding requirements, the form is stored in the first folder corresponding to the first storage address;

[0129] If there is at least one piece of key information that does not meet the corresponding coding requirements, the form and the picture of the vehicle ownership certificate corresponding thereto are stored in the second folder corresponding to the second storage address, where the first storage address and the second storage address are different.

[0130] Optionally, the device provided by the embodiment of the present application further includes:

[0131] A marking module, configured to mark the key information in the form that does not meet the corresponding coding requirements.

[0132] Optionally, the device provided by the embodiment of the present application further includes:

[0133] A request sending module, configured to initiate a manual review request, and the manual review request is used to instruct the user to correct the key information that does not meet the corresponding coding requirements.

[0134] Optionally, the device provided by the embodiment of the present application further includes:

[0135] An information entry module, configured to enter the recognition result in the first folder into the business operation system, and enter the recognition result after correcting the key information into the business operation system.

[0136] For the functions of the modules in each device of the embodiment of the present application, reference may be made to the corresponding descriptions in the above method, which will not be elaborated herein.

[0137] Embodiment 4

[0138] Figure 4 It is a structural block diagram of a device for processing vehicle ownership certificates provided by Embodiment 4 of the present application. As Figure 4 shown, the device includes: a memory 910 and a processor 920, and a computer program that can run on the processor 920 is stored in the memory 910. When the processor 920 executes the computer program, the method in the above embodiment is implemented. The number of the memory 910 and the processor 920 can be one or more.

[0139] The device further includes:

[0140] A communication interface 930, used for communicating with external devices and performing data interaction and transmission.

[0141] If the memory 910, the processor 920, and the communication interface 930 are implemented independently, the memory 910, the processor 920, and the communication interface 930 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 only a thick line is used to represent it in Figure 4 , but it does not mean that there is only one bus or one type of bus.

[0142] Optionally, in a specific implementation, if the memory 910, the processor 920, and the communication interface 930 are integrated on a single chip, the memory 910, the processor 920, and the communication interface 930 can communicate with each other through an internal interface.

[0143] The embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, the method provided in the embodiment of the present application is implemented.

[0144] The embodiment of the present application also provides a chip, which includes a processor for calling and running an instruction stored in a memory, so that a communication device installed with the chip executes the method provided in the embodiment of the present application.

[0145] The embodiment of the present application also provides a chip, including: an input interface, an output interface, a processor, and a memory. The input interface, the output interface, the processor, and the memory are connected through an internal connection path. The processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided in the embodiment of the application.

[0146] It should be understood that the above-mentioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. It is worth noting that the processor can be a processor that supports the advanced RISC machines (ARM) architecture.

[0147] Further, optionally, the above-mentioned memory can include a read-only memory and a random access memory, and can also include a non-volatile random access memory. The memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0148] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0149] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0150] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" can explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality" means two or more unless otherwise specifically defined.

[0151] Any process or method description represented in the flowchart or described in other ways herein can be understood to represent a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. And the scope of the preferred embodiments of the present application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed.

[0152] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatuses, or devices.

[0153] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the method in the above embodiments can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0154] In addition, each functional unit in various embodiments of the present application can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a magnetic disk, an optical disk, etc.

[0155] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various changes or substitutions, and these should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A vehicle property certificate processing method based on robotic process automation (RPA) and artificial intelligence (AI), which is applied to an RPA robot, characterized in that Including: S1. Identify the content of each picture corresponding to the same vehicle ownership certificate to obtain an identification result containing multiple key information, where the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information; S2. Determine whether each key information meets the corresponding coding requirements, where the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format; S3. Determine the storage address of the identification result according to the judgment result, and store the identification result according to the storage address; S4. The RPA robot sends an artificial review request to the human-machine collaboration server through the RPA robot server. The artificial review request includes the identification result to which the key information that does not meet the corresponding coding requirements belongs, and the original picture of the vehicle ownership certificate. Among them, the human-machine collaboration server is a platform for managing the collaborative work of humans and robots. When the human-machine collaboration server receives the artificial review request sent by the RPA robot server, it displays the identification result and the original picture of the vehicle ownership certificate to the user through the display interface of the client. The user corrects the key information on this interface, and after the correction is completed, by triggering the submission instruction, uploads the corrected identification result to the human-machine collaboration server again. The human-machine collaboration server sends the correction result to the RPA robot server, and the RPA robot server controls the RPA robot to upload the correction result to the business operation system within the enterprise; Among them, the step S1 specifically includes: Establish a communication connection between the platform carried by the RPA robot and the AI platform through a target account that simultaneously logs in to the RPA platform and the AI platform. Among them, both the AI platform and the platform carried by the RPA robot rely on the UiBot platform; The RPA robot calls the optical character recognition OCR component of the AI platform to identify the content of each picture corresponding to the same vehicle ownership certificate to obtain an identification result containing multiple key information.

2. The method according to claim 1, characterized in that Before identifying the content of each picture corresponding to the same vehicle ownership certificate, the method further includes: Determine the vehicle registration number information in each picture, and determine each picture belonging to the same vehicle ownership certificate according to the vehicle registration number information; Among them, the vehicle registration number information in different page pictures belonging to the same vehicle ownership certificate is the same.

3. The method according to claim 1, characterized in that, The step S2 specifically includes: S21. Store each key information into a table according to the corresponding preset field; S22. For each key information that has been stored, judge whether each key information meets the corresponding coding requirements based on the natural language processing NLP service; Correspondingly, the step S3 specifically includes: S31. If each key information meets the corresponding coding requirements, store the table into the first folder corresponding to the first storage address; S32. If there is at least one piece of key information that does not meet the corresponding coding requirements, store the said form and the corresponding vehicle ownership certificate picture in the second folder corresponding to the second storage address, where the first storage address and the second storage address are different.

4. The method according to claim 3, wherein The method further includes: S23. Mark the key information in the said form that does not meet the corresponding coding requirements.

5. The method according to claim 4, wherein The method further includes: Enter the recognition result in the first folder into the business operation system.

6. A vehicle property certificate processing device based on RPA and AI, characterized in that, It includes: A recognition module, configured to recognize the content of each picture corresponding to the same vehicle ownership certificate, and obtain a recognition result containing multiple pieces of key information, where the key information includes vehicle registration number information, vehicle model information, engine model information, and registration date information; A matching module, configured to determine whether each piece of key information meets the corresponding coding requirements, where the coding requirements include that the number of digits of the ID card number is the first set number of digits, the number of digits of the vehicle registration number is the second set number of digits, and the registration date conforms to the preset date format; A storage module, configured to determine the storage address of the recognition result according to the judgment result, and store the recognition result according to the storage address; A request sending module, configured to send an artificial review request to the human-machine collaboration server through the RPA robot server by the RPA robot. The artificial review request includes the recognition result to which the key information that does not meet the corresponding coding requirements belongs, and the original picture of the vehicle ownership certificate. Among them, the human-machine collaboration server is a platform for managing the collaborative work of humans and robots. When the human-machine collaboration server receives the artificial review request sent by the RPA robot server, it displays the recognition result and the original picture of the vehicle ownership certificate to the user through the display interface of the client. The user corrects the key information on this interface, and after the correction is completed, by triggering a submission instruction, upload the corrected recognition result to the human-machine collaboration server again. The human-machine collaboration server sends the correction result to the RPA robot server, and the RPA robot server controls the RPA robot to upload the correction result to the business operation system within the enterprise; Among them, the recognition module is specifically configured to: Establish a communication connection between the platform carried by the RPA robot and the AI platform through a target account that logs in to both the RPA platform and the AI platform at the same time. Among them, both the AI platform and the platform carried by the RPA robot rely on the UiBot platform; The RPA robot calls the optical character recognition OCR component of the AI platform to recognize the content of each picture corresponding to the same vehicle ownership certificate, and obtain a recognition result containing multiple pieces of key information.

7. The device according to claim 6, characterized in that, The device further includes: A registration number information determination module, configured to determine the vehicle registration number information in each picture, and determine each picture belonging to the same vehicle ownership certificate according to the vehicle registration number information; Among them, the vehicle registration number information in different page pictures belonging to the same vehicle ownership certificate is the same.

8. The device according to claim 6, characterized in that, The matching module is specifically configured to: Store each piece of key information in a form according to the corresponding preset fields; For each stored key information, based on the natural language processing NLP service, determine whether each key information meets the corresponding coding requirements; Correspondingly, the storage module is specifically configured to: If each key information meets the corresponding coding requirements, store the form in the first folder corresponding to the first storage address; If there is at least one key information that does not meet the corresponding coding requirements, store the form and the corresponding vehicle ownership certificate picture in the second folder corresponding to the second storage address, where the first storage address and the second storage address are different.

9. The device according to claim 8, characterized in that, The device further includes: A marking module, configured to mark the key information in the form that does not meet the corresponding coding requirements.

10. An apparatus for processing vehicle property certificates, characterized in that, Including: A processor and a memory, wherein instructions are stored in the memory, and the instructions are loaded and executed by the processor to implement the method according to any one of claims 1 to 5.

11. A computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the method according to any one of claims 1-5 is implemented.

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