Water meter reading data management system

Abstract

The present invention relates to a water meter reading data management system, comprising a model analysis device, a visual meter reading device, a multi-level optimization device, a parameter extraction device, etc. The water meter reading data management system of the present invention is intelligent in design and widely used.

Description

Technical Field

[0001] The present invention relates to the field of water meters, and more particularly to a water meter reading data management system. Background Art

[0002] In general, although the basic functions of grey water meters and tap water meters are the same, they may differ in design, material, accuracy, installation location and reading method to adapt to the special properties of grey water and the specific needs of the system. The water charges for grey water and tap water may be different, depending on the local water supply policy and the cost of grey water. The supply of tap water involves costs such as collection, treatment, transportation and disinfection, while the treatment cost of grey water may be lower than that of tap water. In areas with tight water resources, the government may grant preferential policies for the use of grey water to promote the rational use of water resources. In addition, the purposes of use of tap water and grey water are different, and the water charges may be different depending on the use.

[0003] Generally, the water meter is installed in a relatively concealed and well-encapsulated space, and no one will check whether the water meter has any faults for a long time or even several years. During normal operation, the meter reading data will show a regular and reasonable state, but if the meter reading data is abnormal, it may reflect that there is a problem with the equipment. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides a water meter reading data management system, which performs each training action on the extreme learning machine neural network to complete the analysis of the extreme learning machine neural network to the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter of the set reclaimed water meter, thereby providing a targeted intelligent detection model for the intelligent detection of surface rupture of the set reclaimed water meter, and then performs a bird's-eye view action on the surface of the set reclaimed water meter to obtain and output a corresponding field bird's-eye view image, and performs grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field bird's-eye view image in sequence, To obtain and output the corresponding multi-level optimized image, thereby improving the picture quality of the on-site image and providing more reliable basic data for subsequent intelligent detection. Finally, based on the depth of field values ​​corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimized image, the vertical coordinate values ​​corresponding to each edge pixel point, the horizontal coordinate values ​​corresponding to each edge pixel point and the set relevant parameters of the grey water meter, the intelligent detection of whether there is a surface body crack on the surface of the grey water meter is performed, thereby completing the intelligent detection of surface cracks of the grey water meter based on targeted screening of multiple visual information and setting relevant parameters of the grey water meter.

[0005] According to the present invention, a water meter reading data management system is provided, the system comprising: A model parsing device, used for parsing an extreme learning machine neural network into an intelligent detection model, wherein parsing the extreme learning machine neural network into the intelligent detection model comprises: performing each training action on the extreme learning machine neural network to complete the parsing of the extreme learning machine neural network into the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter of the reclaimed water meter; The visual meter reading device is arranged just above the surface of the set recycled water meter and is used to perform a bird's-eye view action on the surface of the set recycled water meter to obtain and output a corresponding on-site bird's-eye view image; A multi-level optimization device, connected to the visual meter reading device and comprising a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, for successively performing grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output a corresponding multi-level optimized image; A parameter extraction device is used to output the water pipe diameter, working pressure, ambient temperature, ambient atmospheric pressure and ambient air humidity of the reclaimed water meter as various relevant parameters for setting the reclaimed water meter; A rupture detection device is connected to the model analysis device, the parameter extraction device and the multi-level optimization device respectively, and is used to detect whether there is a body rupture on the surface of the set grey water meter based on the respective depth of field values ​​corresponding to the respective edge pixels of the imaging area of ​​the water meter surface in the multi-level optimization image, the respective vertical coordinate values ​​corresponding to the respective edge pixels, the respective horizontal coordinate values ​​corresponding to the respective edge pixels, and the set parameters of the grey water meter by using an intelligent detection model; Wherein, the intelligent detection model is used to intelligently detect whether there is a body rupture on the surface of the set grey water meter based on each depth of field value corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimization image, each vertical coordinate value corresponding to each edge pixel point, each horizontal coordinate value corresponding to each edge pixel point, and various relevant parameters of the set grey water meter. The intelligent detection model includes: the intelligent detection model outputs a body rupture mark indicating whether there is a body rupture on the surface of the set grey water meter; Among them, the intelligent detection model is used to detect whether there is a body rupture on the surface of the water meter based on the depth of field values ​​corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimized image, the vertical coordinate values ​​corresponding to each edge pixel point, the horizontal coordinate values ​​corresponding to each edge pixel point, and various relevant parameters of the set grey water meter. The setting of the grey water meter also includes: identifying the water meter surface imaging area in the multi-level optimized image based on the surface color imaging characteristics of the grey water meter.

[0006] Therefore, the present invention has at least the following three beneficial technical effects: Technical effect A: Each training action is performed on the extreme learning machine neural network to complete the analysis of the extreme learning machine neural network to the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter of the set grey water meter, thereby providing a targeted intelligent detection model for the intelligent detection of surface rupture of the set grey water meter; Technical effect B: A bird's-eye view action is performed on the surface of a set reclaimed water meter to obtain and output a corresponding on-site bird's-eye view image, and grayscale transformation enhancement processing, frequency domain enhancement processing, and artifact elimination processing are successively performed on the received on-site bird's-eye view image to obtain and output a corresponding multi-level optimized image, thereby improving the picture quality of the on-site image and providing more reliable basic data for subsequent intelligent detection; Technical effect C: Based on the depth of field values ​​corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimized image, the vertical coordinate values ​​corresponding to each edge pixel point, the horizontal coordinate values ​​corresponding to each edge pixel point and the relevant parameters of the set grey water meter, it is intelligently detected whether there is a body rupture on the surface of the set grey water meter, wherein the intelligent detection model outputs a body rupture mark indicating whether there is a body rupture on the surface of the set grey water meter, and the relevant parameters of the set grey water meter are the water pipe diameter, working pressure, temperature of the environment, atmospheric pressure of the environment and air humidity of the environment, thereby completing the intelligent detection of surface rupture of the set grey water meter based on multiple visual information screened in a targeted manner and the relevant parameters of the set grey water meter.

[0007] The water meter reading data management system of the present invention is intelligently designed and widely used. Since it can use the visual meter reading data of the visual meter reading device of the reclaimed water meter, an intelligent detection model is used to perform intelligent detection on the surface cracks of the set reclaimed water meter, thereby providing a meter body crack detection solution using existing hardware resources for the reclaimed water meter in a relatively concealed and relatively complete package space. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Those skilled in the art may better understand the numerous advantages of the present invention by referring to the accompanying drawings, in which:

[0009] Figure 1 It is a schematic diagram of the internal structure of a water meter reading data management system according to the first embodiment of the present invention.

[0010] Figure 2 It is a schematic diagram of the internal structure of a water meter reading data management system according to the second embodiment of the present invention.

[0011] Figure 3It is a schematic diagram of the internal structure of a water meter reading data management system according to the third embodiment of the present invention. DETAILED DESCRIPTION

[0012] At present, when a problem occurs with the equipment, for example, no personnel will observe whether there is any crack on the surface of the grey water meter. How to use existing mechanisms, such as using the existing remote meter reading mechanism to use an electronic observation mode to observe whether there is any crack on the surface of the grey water meter is one of the technical problems that need to be solved at present.

[0013] The implementation scheme of the water meter reading data management system of the present invention will be described in detail below with reference to the accompanying drawings.

[0014] Figure 1 1 is a schematic diagram of the internal structure of a water meter reading data management system according to a first embodiment of the present invention, the system comprising: A model parsing device, used for parsing an extreme learning machine neural network into an intelligent detection model, wherein parsing the extreme learning machine neural network into the intelligent detection model comprises: performing each training action on the extreme learning machine neural network to complete the parsing of the extreme learning machine neural network into the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter of the reclaimed water meter; For example, a model parsing device is used to parse an extreme learning machine neural network into an intelligent detection model, wherein parsing the extreme learning machine neural network into the intelligent detection model includes: performing each training action on the extreme learning machine neural network to complete the parsing of the extreme learning machine neural network into the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively associated with the water pipe diameter set for the reclaimed water meter, including: using a numerical conversion formula to represent the numerical conversion relationship of the number of training actions performed on the extreme learning machine neural network and the water pipe diameter set for the reclaimed water meter; The visual meter reading device is arranged just above the surface of the set recycled water meter and is used to perform a bird's-eye view action on the surface of the set recycled water meter to obtain and output a corresponding on-site bird's-eye view image; A multi-level optimization device, connected to the visual meter reading device and comprising a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, for successively performing grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output a corresponding multi-level optimized image; A parameter extraction device is used to output the water pipe diameter, working pressure, ambient temperature, ambient atmospheric pressure and ambient air humidity of the reclaimed water meter as various relevant parameters for setting the reclaimed water meter; A rupture detection device is connected to the model analysis device, the parameter extraction device and the multi-level optimization device respectively, and is used to detect whether there is a body rupture on the surface of the set grey water meter based on the respective depth of field values ​​corresponding to the respective edge pixels of the imaging area of ​​the water meter surface in the multi-level optimization image, the respective vertical coordinate values ​​corresponding to the respective edge pixels, the respective horizontal coordinate values ​​corresponding to the respective edge pixels, and the set parameters of the grey water meter by using an intelligent detection model; Wherein, the intelligent detection model is used to intelligently detect whether there is a body rupture on the surface of the set grey water meter based on each depth of field value corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimization image, each vertical coordinate value corresponding to each edge pixel point, each horizontal coordinate value corresponding to each edge pixel point, and various relevant parameters of the set grey water meter. The intelligent detection model includes: the intelligent detection model outputs a body rupture mark indicating whether there is a body rupture on the surface of the set grey water meter; Wherein, the intelligent detection model is used to detect whether there is a body rupture on the surface of the water meter based on the respective depth of field values ​​corresponding to the respective edge pixels in the imaging area of ​​the water meter surface in the multi-level optimized image, the respective vertical coordinate values ​​corresponding to the respective edge pixels, the respective horizontal coordinate values ​​corresponding to the respective edge pixels, and the various relevant parameters of the set reclaimed water meter. The setting of whether there is a body rupture on the surface of the reclaimed water meter also includes: identifying the water meter surface imaging area in the multi-level optimized image based on the surface color imaging characteristics of the reclaimed water meter; Wherein, the multi-level optimization device is connected to the visual meter reading device and includes a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, and is used to successively perform grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output the corresponding multi-level optimization image, including: the front-end optimization unit, the mid-end optimization unit and the terminal optimization unit are connected in sequence; And wherein, the multi-level optimization device is connected to the visual meter reading device and includes a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, which is used to successively perform grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output the corresponding multi-level optimized image. It also includes: the front-end optimization unit, the mid-end optimization unit and the terminal optimization unit are respectively used to perform grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received image signal.

[0015] Figure 2 It is a schematic diagram of the internal structure of a water meter reading data management system according to the second embodiment of the present invention.

[0016] and Figure 1 different, Figure 2The water meter reading data management system in the system can also include the following components: An information extraction component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively; The information extraction component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device, and includes: the information extraction component is used to respectively realize the on-site measurement of the current power of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device.

[0017] Figure 3 It is a schematic diagram of the internal structure of a water meter reading data management system according to the third embodiment of the present invention.

[0018] and Figure 1 different, Figure 3 The water meter reading data management system in the system can also include the following components: An on-site measurement component is disposed near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device; Among them, the on-site measurement component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device, including: the on-site measurement component is used to respectively realize the on-site measurement of the current heat of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device.

[0019] Next, the specific structure of the water meter reading data management system of the present invention will be further described.

[0020] In a water meter reading data management system according to any embodiment of the present invention: Using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device to obtain output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device respectively; Among them, using the MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing histogram equalization on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively; Among them, using the MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing logarithmic image enhancement on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively; Among them, using the MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing exponential image enhancement on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively; And wherein, using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing image enhancement processing based on high contrast retention on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

[0021] In addition, in the water meter reading data management system, each training action is performed on the extreme learning machine neural network to complete the analysis of the extreme learning machine neural network to the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter set for the grey water meter, including: using an information mapping formula to represent the information mapping relationship between the number of training actions performed on the extreme learning machine neural network and the water pipe diameter set for the grey water meter.

[0022] While there has been described what are considered to be preferred embodiments of the present invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such embodiments that fall within the true scope of the invention.

Claims

1. A water meter reading data management system, characterized in that: The system comprises: A model parsing device, used for parsing an extreme learning machine neural network into an intelligent detection model, wherein parsing the extreme learning machine neural network into the intelligent detection model comprises: performing each training action on the extreme learning machine neural network to complete the parsing of the extreme learning machine neural network into the intelligent detection model, and the number of training actions performed on the extreme learning machine neural network is positively correlated with the water pipe diameter of the reclaimed water meter; The visual meter reading device is arranged just above the surface of the set recycled water meter and is used to perform a bird's-eye view action on the surface of the set recycled water meter to obtain and output a corresponding on-site bird's-eye view image; A multi-level optimization device, connected to the visual meter reading device and comprising a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, for successively performing grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output a corresponding multi-level optimized image; A parameter extraction device is used to output the water pipe diameter, working pressure, ambient temperature, ambient atmospheric pressure and ambient air humidity of the reclaimed water meter as various relevant parameters for setting the reclaimed water meter; A rupture detection device is connected to the model analysis device, the parameter extraction device and the multi-level optimization device respectively, and is used to detect whether there is a body rupture on the surface of the set grey water meter based on the respective depth of field values ​​corresponding to the respective edge pixels of the imaging area of ​​the water meter surface in the multi-level optimization image, the respective vertical coordinate values ​​corresponding to the respective edge pixels, the respective horizontal coordinate values ​​corresponding to the respective edge pixels, and the set parameters of the grey water meter by using an intelligent detection model; Wherein, the intelligent detection model is used to intelligently detect whether there is a body rupture on the surface of the set grey water meter based on each depth of field value corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimization image, each vertical coordinate value corresponding to each edge pixel point, each horizontal coordinate value corresponding to each edge pixel point, and various relevant parameters of the set grey water meter. The intelligent detection model includes: the intelligent detection model outputs a body rupture mark indicating whether there is a body rupture on the surface of the set grey water meter; Among them, the intelligent detection model is used to detect whether there is a body rupture on the surface of the water meter based on the depth of field values ​​corresponding to each edge pixel point in the imaging area of ​​the water meter surface in the multi-level optimized image, the vertical coordinate values ​​corresponding to each edge pixel point, the horizontal coordinate values ​​corresponding to each edge pixel point, and various relevant parameters of the set grey water meter. The setting of the grey water meter also includes: identifying the water meter surface imaging area in the multi-level optimized image based on the surface color imaging characteristics of the grey water meter.

2. The water meter reading data management system according to claim 1, characterized in that: A multi-level optimization device, connected to the visual meter reading device and comprising a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, for successively performing grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output a corresponding multi-level optimization image, comprising: the front-end optimization unit, the mid-end optimization unit and the terminal optimization unit are sequentially connected; Among them, the multi-level optimization device is connected to the visual meter reading device and includes a front-end optimization unit, a mid-end optimization unit and a terminal optimization unit, which is used to successively perform grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received field overhead image to obtain and output the corresponding multi-level optimized image. It also includes: the front-end optimization unit, the mid-end optimization unit and the terminal optimization unit are respectively used to perform grayscale transformation enhancement processing, frequency domain enhancement processing and artifact elimination processing on the received image signal.

3. The water meter reading data management system according to claim 2, characterized in that: The system further comprises: An information extraction component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively; The information extraction component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device, and includes: the information extraction component is used to respectively realize the on-site measurement of the current power of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device.

4. The water meter reading data management system according to claim 2, characterized in that: The system further comprises: An on-site measurement component is disposed near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit, and the visual meter reading device; Among them, the on-site measurement component is arranged near the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device and is respectively connected to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device, including: the on-site measurement component is used to respectively realize the on-site measurement of the current heat of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device.

5. The water meter reading data management system according to any one of claims 2 to 4, characterized in that: An MSP430 single-chip microcomputer is used to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

6. The water meter reading data management system according to claim 5, characterized in that: The method of using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively comprises: performing histogram equalization on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

7. The water meter reading data management system according to claim 5, characterized in that: Using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing logarithmic image enhancement on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

8. The water meter reading data management system according to claim 5, characterized in that: Using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively includes: performing exponential image enhancement on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

9. The water meter reading data management system according to claim 5, characterized in that: The method of using an MSP430 single-chip microcomputer to perform image data processing on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively comprises: performing image enhancement processing based on high contrast retention on the output data of the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device to obtain the output processing data corresponding to the front-end optimization unit, the mid-end optimization unit, the terminal optimization unit and the visual meter reading device respectively.

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