Meter reading agent, meter reading method, storage medium and electronic equipment

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a meter reading agent, a meter reading method, a storage medium and electronic equipment, and the meter reading agent comprises a data acquisition module which is used for acquiring to-be-read meter data; the OCR identification module is used for identifying the data to be subjected to meter reading to obtain identification data; the data verification module is used for verifying the identification data and judging whether the identification data accord with a preset verification rule or not; the auditing module is used for auditing the identification data when the identification data does not conform to the preset verification rule to obtain data confirmed after auditing; and the data storage module is used for storing the identification data conforming to the preset verification rule and the data confirmed after auditing. Therefore, the high efficiency of the OCR technology and the accuracy of manual auditing are combined, the accuracy and efficiency of meter reading can be effectively improved, and the workload and the error rate of manual meter reading are reduced.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to a meter reading agent, meter reading method, storage medium, and electronic device. Background Technology

[0002] Traditional meter reading methods mainly rely on manual reading, which suffers from problems such as high workload, low efficiency, and high error rate. With the development of technology, OCR (Optical Character Recognition) technology has been applied to the field of meter reading. However, existing meter reading systems based on OCR technology often lack effective data verification and manual review mechanisms, resulting in insufficient accuracy of meter reading results. Summary of the Invention

[0003] This application provides a meter reading agent, meter reading method, storage medium, and electronic device to solve the above-mentioned problems in the prior art and improve the accuracy and efficiency of meter reading.

[0004] To achieve the above objectives, this application adopts the following technical solution: Firstly, a meter reading intelligent agent is provided, including: The data acquisition module is used to acquire the meter reading data. The OCR recognition module is used to recognize the meter reading data to obtain the recognition data; The data verification module is used to verify the identification data and determine whether it conforms to the preset verification rules. The review module is used to review the identification data when the identification data does not conform to the preset verification rules, and obtain the data confirmed after review. The data storage module is used to store the identification data that conforms to the preset verification rules and the data confirmed after review. Secondly, a meter reading method is provided, including: S1: Obtain the meter reading data through the data acquisition module; S2: The meter reading data is identified by the OCR recognition module to obtain the identified data; S3: The identification data is verified by the data verification module to determine whether it conforms to the preset verification rules; S4: If the identification data conforms to the preset verification rules, then the identification data is stored through the data storage module; S5: If the identification data does not conform to the preset verification rules, the identification data is reviewed by the review module and the data confirmed after review is stored by the data storage module. Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the meter reading method as described in any one of the first aspects above.

[0005] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the meter reading method as described in any one of the first aspects above.

[0006] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the meter reading method described in any one of the first aspects.

[0007] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0008] In this embodiment, the meter reading agent includes a data acquisition module for acquiring meter reading data, an OCR recognition module for recognizing the meter reading data to obtain recognized data, a data verification module for verifying the recognized data and determining whether it conforms to preset verification rules, an auditing module for auditing the recognized data when it does not conform to the preset verification rules to obtain audited and confirmed data, and a data storage module for storing the recognized data that conforms to the preset verification rules and the audited and confirmed data. Therefore, by combining the efficiency of OCR technology with the accuracy of manual auditing, the accuracy and efficiency of meter reading can be effectively improved, while reducing the workload and error rate of manual meter reading.

[0009] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0010] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a schematic diagram of the structure of a meter reading intelligent agent provided in an embodiment of this application; Figure 2 This is a flowchart of a meter reading method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0011] The embodiments of the technical solutions of this application will now be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of this application, and are therefore merely examples and should not be used to limit the scope of protection of this application. When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but can be changed as will become apparent upon understanding this disclosure, except for operations that must be performed in a specific order. Furthermore, for clarity and conciseness, descriptions of features known in the art may be omitted.

[0012] The embodiments described in the following examples of this disclosure are not representative of all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0013] See Figure 1 This is a schematic diagram of the structure of the meter reading intelligent agent provided in the first embodiment of this application.

[0014] like Figure 1 As shown, the meter reading intelligent agent 100 may include: Data acquisition module 11 is used to acquire the meter reading data; The OCR recognition module 12 is used to recognize the meter reading data and obtain the recognition data. Data verification module 13 is used to verify the identified data and determine whether it conforms to preset verification rules; The review module 14 is used to review the identified data when it does not conform to the preset verification rules, and obtain the data confirmed after review. The data storage module 15 is used to store identification data that conforms to preset verification rules and data confirmed after review.

[0015] Data acquisition module 11 It should be noted that the data acquisition module is used to acquire the meter reading data. The data acquisition module 11 may include an image acquisition unit, which is used to acquire image information containing the meter reading data. For example, in an electricity meter reading scenario, the image acquisition unit can be a camera, installed in a suitable location to capture images of the electricity meter, acquiring images containing the meter reading data awaiting reading.

[0016] The OCR recognition module 12 can be used to recognize the meter reading data and obtain the recognized data.

[0017] The OCR recognition module 12 may include an image preprocessing unit and a character recognition unit.

[0018] The image preprocessing unit is used to preprocess the acquired image information. The image preprocessing unit includes at least one of the following: an image enhancement subunit, an image binarization subunit, and an image denoising subunit.

[0019] The image enhancement subunit is used to enhance the contrast or brightness of an image. For example, when the captured image has low contrast due to insufficient light, the image enhancement subunit can improve the contrast of the image by adjusting the pixel values, making the characters in the image clearer and more legible.

[0020] The image binarization subunit is used to convert an image into a black-and-white binary image. By setting an appropriate threshold, the pixels in the image are divided into black and white categories, removing redundant information and highlighting character features to facilitate subsequent character recognition.

[0021] The image denoising subunit is used to remove noise from an image. During image acquisition, various types of noise may interfere with the image, such as electronic noise and sensor noise. The image denoising subunit can use filtering algorithms and other methods to remove this noise and improve image quality.

[0022] The character recognition unit is used to recognize characters in the preprocessed image information to obtain recognized data. The character recognition unit can employ existing OCR recognition algorithms, such as neural network-based OCR algorithms, to accurately recognize characters in the image.

[0023] The data verification module is used to verify the identified data and determine whether it conforms to the preset verification rules.

[0024] The preset verification rules include at least one of the following: data format verification rules, data range verification rules, and data logic verification rules.

[0025] Data format validation rules are used to verify whether the number of digits or the position of the decimal point in the identified data meets the requirements. For example, in the reading of an electricity meter, the reading is required to be a 5-digit integer with a maximum of 2 decimal places. Data format validation rules can verify the number of digits and the position of the decimal point in the identified data to ensure the correctness of the data format.

[0026] Data range verification rules are used to verify whether the identified data is within a preset reasonable value range. For example, for the residential electricity consumption of a certain area, a reasonable electricity consumption range is preset based on historical data and actual electricity consumption. The data range verification rules can determine whether the identified data is within this range. If it exceeds the range, the data is considered to be potentially erroneous.

[0027] Data logic verification rules are used to verify whether the logical relationships between data are reasonable. For example, in electricity meter reading, the electricity consumption at different times should meet certain logical relationships, such as the peak electricity consumption plus the off-peak electricity consumption should equal the total electricity consumption. Data logic verification rules can verify these logical relationships.

[0028] The review module is used to review the identified data when it does not meet the preset verification rules, and obtain the data after review and confirmation.

[0029] Optionally, the audit module includes an audit prompt unit and an audit record unit.

[0030] The review prompt unit is used to notify reviewers to review identification data that does not conform to preset verification rules through interface prompts or sound prompts. For example, when the data verification module finds that the identification data does not conform to the verification rules, the review prompt unit can pop up a prompt box on the system's operation interface, displaying the data information that needs to be reviewed, or remind the reviewer through sound prompts.

[0031] The audit record unit is used to record audit process information and result data. It can record the auditor's operating steps, audit time, audit comments, and finally confirmed data, facilitating subsequent retrieval and traceability.

[0032] The data storage module stores identification data that conforms to preset verification rules, as well as data confirmed after review. The data storage module can be in the form of a database to store accurate data long-term for subsequent data analysis and use.

[0033] Optionally, the data acquisition module includes an image acquisition unit, which is used to acquire image information containing the meter reading data. Optionally, the OCR recognition module includes an image preprocessing unit and a character recognition unit; The image preprocessing unit is used to preprocess the acquired image information; The character recognition unit is used to perform character recognition on the preprocessed image information to obtain recognition data. Optionally, the image preprocessing unit includes at least one of an image enhancement subunit, an image binarization subunit, and an image denoising subunit; The image enhancement subunit is used to enhance the contrast or brightness of an image; The image binarization subunit is used to convert an image into a black-and-white binary image; The image denoising subunit is used to remove noise from an image. Optionally, the preset verification rules include at least one of the following: data format verification rules, data range verification rules, and data logic verification rules; Data format validation rules are used to verify whether the number of digits or the position of the decimal point in the data meets the requirements. Data range verification rules are used to verify whether the identified data is within a preset reasonable value range; Data logic verification rules are used to verify whether the logical relationships between data are reasonable. Optionally, the review module includes a review prompt unit and a review record unit; The audit prompt unit is used to notify auditors to audit identification data that does not conform to the preset verification rules through interface prompts or sound prompts; The audit record unit is used to record audit process information and result data. It should be noted that the subject executing the meter reading method in this embodiment can be a meter reading intelligent agent, and this application embodiment does not limit this.

[0034] In this embodiment, the meter reading agent includes a data acquisition module for acquiring meter reading data, an OCR recognition module for recognizing the meter reading data to obtain recognized data, a data verification module for verifying the recognized data and determining whether it conforms to preset verification rules, an auditing module for auditing the recognized data when it does not conform to the preset verification rules to obtain audited and confirmed data, and a data storage module for storing the recognized data that conforms to the preset verification rules and the audited and confirmed data. Therefore, by combining the efficiency of OCR technology with the accuracy of manual auditing, the accuracy and efficiency of meter reading can be effectively improved, while reducing the workload and error rate of manual meter reading.

[0035] See Figure 2 This is a flowchart illustrating the meter reading method provided in an embodiment of this application. Figure 2 As shown, the meter reading method may include the following steps: S1: Obtain the meter reading data through the data acquisition module; S2: The meter reading data is identified by the OCR recognition module to obtain the identified data; S3: The identification data is verified by the data verification module to determine whether it conforms to the preset verification rules; S4: If the identification data conforms to the preset verification rules, then the identification data is stored through the data storage module; S5: If the identification data does not conform to the preset verification rules, the identification data is reviewed by the review module and the data confirmed after review is stored by the data storage module.

[0036] Optionally, the meter reading data is image information containing the meter reading data acquired by the image acquisition unit. It should be noted that the specific implementation of the above method can refer to the above proportions, and will not be elaborated upon here.

[0037] In this embodiment, the meter reading data is first acquired, then recognized by an OCR module to obtain the recognized data. A data verification module then verifies the recognized data to determine if it conforms to preset verification rules. An auditing module then audits the recognized data if it does not conform to the preset verification rules, obtaining the audited and confirmed data. Finally, a data storage module stores the recognized data conforming to the preset verification rules and the audited and confirmed data. Therefore, by combining the efficiency of OCR technology with the accuracy of manual auditing, the accuracy and efficiency of meter reading can be effectively improved, while reducing the workload and error rate of manual meter reading.

[0038] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0039] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 3 As shown, the electronic device 5 of this embodiment includes: at least one processor 50 ( Figure 3 (Only one is shown in the image) a processor, a memory 51, and a computer program 52 stored in the memory 51 and executable on the at least one processor 50, wherein the processor 50 executes the computer program 52 to implement the steps in any of the above embodiments of the product model intelligent matching method based on serial number.

[0040] The electronic device may be a desktop computer, laptop, handheld computer, or cloud server, etc. This electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 3 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0041] The processor 50 may be a central processing unit (CPU), or it may be 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. A general-purpose processor may be a microprocessor or any conventional processor.

[0042] In some embodiments, the memory 51 may be an internal storage unit of the electronic device 5, such as a hard disk or memory of the electronic device 5. In other embodiments, the memory 51 may be an external storage device of the electronic device 5, such as a plug-in hard disk, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard equipped on the electronic device 5. Furthermore, the memory 51 may include both internal and external storage units of the electronic device 5. The memory 51 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0043] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps in the above-described method embodiments.

[0044] This application provides a computer program product that, when run on an electronic device, enables the electronic device to implement the steps described in the various method embodiments above.

[0045] If the integrated unit is implemented as a software functional unit and used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a device / electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0046] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0047] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0048] In the embodiments provided in this application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0049] 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.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0051] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0052] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0053] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0054] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0055] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0056] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0057] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A meter reading intelligent agent, characterized in that, include: The data acquisition module is used to acquire the meter reading data. The OCR recognition module is used to recognize the meter reading data to obtain the recognition data; The data verification module is used to verify the identification data and determine whether it conforms to the preset verification rules. The review module is used to review the identification data when the identification data does not conform to the preset verification rules, and obtain the data confirmed after review. The data storage module is used to store the identification data that conforms to the preset verification rules and the data confirmed after review.

2. The meter reading intelligent agent according to claim 1, characterized in that, The data acquisition module includes an image acquisition unit, which is used to acquire image information containing the meter reading data.

3. The meter reading intelligent agent according to claim 2, characterized in that, The OCR recognition module includes an image preprocessing unit and a character recognition unit; The image preprocessing unit is used to preprocess the acquired image information; The character recognition unit is used to perform character recognition on the preprocessed image information to obtain the recognition data.

4. The meter reading intelligent agent according to claim 3, characterized in that, The image preprocessing unit includes at least one of an image enhancement subunit, an image binarization subunit, and an image denoising subunit; The image enhancement subunit is used to enhance the contrast or brightness of the image; The image binarization subunit is used to convert the image into a black-and-white binary image; The image denoising subunit is used to remove noise from the image.

5. The meter reading intelligent agent according to claim 1, characterized in that, The preset verification rules include at least one of data format verification rules, data range verification rules, and data logic verification rules; The data format verification rules are used to verify whether the number of digits or the position of the decimal point in the identified data meets the requirements. The data range verification rule is used to verify whether the identified data is within a preset reasonable value range; The data logic verification rules are used to verify whether the logical relationship between the identified data is reasonable.

6. The meter reading intelligent agent according to claim 1, characterized in that, The audit module includes an audit prompt unit and an audit record unit; The audit prompt unit is used to notify the auditors to audit the identification data that does not conform to the preset verification rules through interface prompts or sound prompts. The audit record unit is used to record audit process information and result data.

7. A meter reading method, characterized in that, The method applied to the meter reading intelligent agent as described in any one of claims 1-6 includes the following steps: S1: Obtain the meter reading data through the data acquisition module; S2: The meter reading data is identified by the OCR recognition module to obtain the identified data; S3: The identification data is verified by the data verification module to determine whether it conforms to the preset verification rules; S4: If the identification data conforms to the preset verification rules, then the identification data is stored through the data storage module; S5: If the identification data does not conform to the preset verification rules, the identification data is reviewed by the review module and the data confirmed after review is stored by the data storage module.

8. The meter reading method according to claim 7, characterized in that, The meter reading data is image information containing the meter reading data acquired by the image acquisition unit.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the meter reading method as described in any one of claims 7-8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the meter reading method as described in any one of claims 7-8.

Images