Water level monitoring method and monitoring system

Abstract

The application provides a water gauge water level monitoring method and monitoring system, and relates to the technical field of water level monitoring. Through the combination of macro water level information of the water gauge and micro water level information of the monitoring array, accurate monitoring of the water level is realized. The image is pre-processed to weaken the influence of weather on the collected image and improve the recognition accuracy; when the water gauge recognition is affected by the environment and the accuracy is reduced, the multi-point and real-time relative water level data provided by the monitoring array can be effectively supplemented and corrected. Especially when the water level changes sharply, the system can identify and start a more detailed monitoring process in time, and use the distributed data of the monitoring array to capture the details of the water surface fluctuation, so as to calculate a more accurate average water level. This multi-source information fusion and dynamic response mechanism effectively overcomes the limitations of single water gauge image recognition in harsh environments, and significantly improves the accuracy and reliability of water level monitoring.

Description

Technical Field

[0001] This invention relates to the field of water level monitoring technology, and more specifically, to a water level monitoring method and system. Background Technology

[0002] Intelligent image-based water level recognition technology is unaffected by external factors or water quality, enabling intelligent identification and analysis of water levels in rivers, lakes, and reservoirs, thus increasing the diversity of hydrological monitoring methods. Water level monitoring is particularly important during periods of high tide or flooding.

[0003] Deep learning-based water level gauge image recognition involves capturing images of water level gauges using a camera, segmenting and cropping the captured images to obtain identifiable regions, and finally identifying the water level in the cropped regions. However, because the water level gauge and the camera are in an open environment, the image acquisition process is affected and limited by environmental factors such as weather and water level fluctuations in adverse conditions, directly impacting the recognition results and requiring improvement in accuracy. Summary of the Invention

[0004] The problem that this invention aims to solve is that existing water level monitoring methods are affected by environmental factors in image acquisition, and the accuracy of the recognition results needs to be improved.

[0005] To address the above problems, in a first aspect, the present invention provides a method for monitoring water levels using a water gauge, comprising: The system acquires a panoramic view of the water level gauge and the monitoring array, as well as a top view of the monitoring array. The monitoring array is deployed near the water level gauge and consists of multiple monitoring units connected to each other. These units are fixed around the water level gauge and within the acquisition range of the panoramic view. Each monitoring unit is numbered systematically and includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. Preprocess the panoramic and top-down views; Identify water level readings from water gauges in multiple pre-processed panoramic images; If the change in water level scale exceeds a preset threshold within a preset time, identify the real-time color and brightness of the indicator lights on each monitoring unit in the top view; Based on real-time color and real-time brightness, analyze the relative water level value monitored by each monitoring unit; Compare the relative water level values ​​of all monitoring units, and determine the maximum and minimum values ​​in each row and column of the monitoring array and their corresponding monitoring unit numbers; Based on the maximum and minimum values, and the monitoring unit numbers corresponding to the maximum and minimum values, the relative average water level is obtained through analysis. Based on the location markers of the water gauge and monitoring unit in the panoramic image, determine the absolute height corresponding to the location markers; The absolute water level value is obtained based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

[0006] Secondly, the present invention also provides a water level monitoring system, comprising: A monitoring array is deployed near the water level gauge. The monitoring array consists of multiple monitoring units connected to each other, fixed around the water level gauge and within the panoramic image acquisition range. Each monitoring unit is regularly numbered and includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. The image acquisition module is used to acquire panoramic views of the water gauge and the monitoring array, as well as top views of the monitoring array. The monitoring array includes multiple monitoring units, each of which is regularly numbered. Each monitoring unit includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. The image preprocessing module is used to preprocess panoramic and top-down views; The image recognition module is used to identify the water level scales measured by water gauges in multiple pre-processed panoramic images; The joint identification module is used to identify the real-time color and real-time brightness of the indicator lights on each monitoring unit in the top view if the change in the water level scale exceeds a preset threshold within a preset time. The relative water level analysis module is used to analyze the relative water level value monitored by each monitoring unit based on real-time color and real-time brightness; it is also used to compare the relative water level values ​​of all monitoring units, and in the monitoring array, to determine the maximum and minimum values ​​in each row and column and their corresponding monitoring unit numbers; it is also used to analyze and obtain the average relative water level based on the maximum and minimum values ​​and the monitoring unit numbers corresponding to the maximum and minimum values ​​respectively. The image recognition module is also used to determine the absolute height corresponding to the position marker based on the position markers of the water gauge and the monitoring unit in the panoramic image; The absolute water level analysis module is used to obtain the absolute water level value based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

[0007] Thirdly, the present invention also provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is used to implement the above-described water level monitoring method when executing the computer program.

[0008] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described water level monitoring method.

[0009] This invention provides a method and system for monitoring water levels using a water gauge. Compared with existing technologies, it has the following advantages: By combining macroscopic water level information from water gauges with microscopic water level information from monitoring arrays, precise water level monitoring is achieved. Image preprocessing reduces the impact of weather on the acquired images, improving recognition accuracy. When water gauge recognition is affected by environmental factors (such as water surface fluctuations) leading to decreased accuracy, the multi-point, real-time relative water level data provided by the monitoring array can effectively supplement and correct for this. Especially when water level changes drastically, the system can promptly identify and initiate a more refined monitoring process, utilizing the distributed data from the monitoring array to capture details of water surface fluctuations, thereby calculating a more accurate average water level. This multi-source information fusion and dynamic response mechanism effectively overcomes the limitations of single water gauge image recognition in harsh environments, significantly improving the accuracy and reliability of water level monitoring. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a schematic diagram of the deployment of a monitoring array provided in an embodiment of the present invention; Figure 2 This is a schematic diagram showing the height correspondence between a monitoring array and a water gauge, provided as an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of a monitoring unit provided in an embodiment of the present invention; Figure 4 A schematic flowchart of a water level monitoring method provided in an embodiment of the present invention; Figure 5 This is a schematic diagram comparing the original image and the image after dehazing, provided in an embodiment of the present invention. Figure 6 This is a schematic diagram comparing the image before and after grayscale processing provided in an embodiment of the present invention. Figure 7 This is a schematic diagram of an image after binarization, provided in an embodiment of the present invention. Figure 8 This is a schematic diagram of a water level monitoring system provided in an embodiment of the present invention.

[0012] Explanation of reference numerals in the attached figures: 1. Transparent cover; 2. Indicator lights; 3. Base plate; 4. Floating frame; 5. Side holes; 6. Bottom holes; 7. Support column; 8. Floating element; 9. Collar; 10. Ball bearing; 11. Resistance plate; 12. Insulating tape; 13. Conductive sheet; 14. Position marker. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application are described clearly and completely. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0015] like Figure 1 As shown, the water level monitoring system includes a monitoring array deployed near the water level gauge. The monitoring array comprises multiple monitoring units interconnected and fixed around the water level gauge within the panoramic image acquisition range, ensuring accurate capture of the indicator lights' status. Each monitoring unit is systematically numbered and includes an indicator light and a location marker. The indicator light's color and brightness change in real-time with the rise and fall of the water level. For example... Figure 1 In this system, multiple monitoring units are connected together and laid on the surface of a canal or well. The entire monitoring array is fixed to the side wall of the canal or well. Figure 2As shown, the upper edge of the outer frame represents the upper edge of the canal or well, and the broken line of the outer frame represents the break line. Outside the break line, there are some identical monitoring units of the array that are not shown. The broken line indicates that only part of the array unit is shown. The entire monitoring array is above the water surface, and the monitoring units in the array vertically span the guarantee line and warning line on the water gauge. The guarantee line corresponds to the guarantee water level (the upper limit water level), and the warning line corresponds to the warning water level (the water level where further rises may lead to seepage, piping, or other dangers, requiring increased vigilance). When the water level approaches the warning line, the water surface begins to contact the monitoring unit. Each monitoring unit is equipped with indicator lights and location markers 14. The indicator lights change color and brightness in real time as the water level rises and falls. For example, a level float rheostat is used (the higher the water level, the lower the resistance). The level float rheostat is connected in series with the base control circuit of a transistor. When the water level rises, the sensor resistance decreases, the base current increases, the transistor conduction becomes stronger, the LED current increases, and the brightness increases. When the water level falls, the resistance increases, the conduction weakens, and the LED dims. Alternatively, a water level sensor can be used to collect analog signals (voltage changes continuously with water level); a microcontroller's ADC reads the water level voltage value; and PWM pulse width modulation maps the water level value to a PWM duty cycle; the higher the water level, the higher the PWM duty cycle, and the brighter the indicator light, perfectly tracking the rise and fall. A submersible level transmitter can also be used. The submersible level transmitter is connected to a PLC, which in turn connects to an analog signal module. The PLC performs internal engineering quantity conversion and outputs an analog signal of 0-10V or an adjustable PWM signal. An external adjustable warning light / LED alarm light is connected to the analog output terminal; the higher the 0-10V voltage, the brighter the light. Position marker 14 is used to identify the absolute height of the monitoring unit indicated by the water gauge. Additionally, multiple monitoring units can be numbered, for example... Figure 1 As shown, the numbers in the first row are A1, A2, A3, A4, A5...; the second row starts with B, the third row with C, the fourth row with D, and so on, all using a similar regular numbering method as the first row. Figure 2 In the water level gauge, the numbers 17, 18, 19, ..., 25, 26 represent height indicators. Since each "E" is 5cm high, multiplying the height indicator number by 10 gives the height of the top of the "E" below that number. For example, the height of the top of the "E" below the number 18 is 18 * 10 = 180cm.

[0016] To achieve real-time color and brightness changes of the indicator lights as the water level rises and falls, a chain of insulating, sequentially connected resistive plates can be installed within the monitoring unit. The chain is vertically inserted into the water, with each indicator light corresponding to one resistive plate. One end of each color indicator light is connected to one end of its corresponding resistive plate, and the other end is connected to a movable conductive plate via a power source. The movable conductive plate contacts the chain and moves vertically along the chain as the water level rises and falls. In one example, the chain is vertically inserted into the water, and the indicator lights are assembled together. The indicator lights are located at the top of the monitoring unit, and the chain is positioned below them. The indicator lights and resistive plates are arranged in a one-to-one correspondence; one end of each color indicator light is connected to one end of its corresponding resistive plate, and the other end is connected to a movable conductive plate via a power source. The movable conductive plate contacts the chain and moves vertically along the chain as the water level rises and falls.

[0017] In another instance, the monitoring unit can be configured as Figure 3 The structure shown is as follows. The monitoring unit includes a transparent cover 1, multiple indicator lights 2, a base plate 3, a support column 7, a buoyancy enhancement component 8, a collar 9, multiple resistive plates 11, and a movable conductive plate 13; Multiple indicator lights 2 are installed on one side of the base plate 3; a transparent cover 1 is installed on the base plate 3, enclosing the multiple indicator lights 2 inside; a support column 7 is installed on the other side of the base plate 3, and multiple resistive plates 11 are installed vertically on the support column 7, with insulating strips 12 between the multiple resistive plates 11; a collar 9 is fitted on the support column 7, and a movable conductive plate 13 is installed inside the collar 9, which contacts the multiple resistive plates 11; a buoyancy booster 8 is installed on the collar 9 to allow the collar 9 to move up and down along the support column 7 as the water level rises and falls; the multiple indicator lights 2 are arranged one-to-one with the multiple resistive plates 11, and the indicator lights 2, the corresponding resistive plates 11, the movable conductive plates 13, and the power supply are connected in series.

[0018] The height of the insulating strip 12 can be set to be equal to the height of the contact end of the movable conductive sheet 13. Figure 3 There are three indicator lights 2 in total, each with a different color. Each indicator light 2 is connected to a resistive plate 11, either at the top or the bottom. Figure 3One end of the indicator light 2 is connected to the upper end of the resistive plate 11. The buoyancy enhancer 8 can drive the collar 9 to float on the water surface. As the water level rises and falls, the collar 9 moves up and down along the support column 7, causing the movable conductive plate 13 to move up and down on the resistive plate 11. Since the length of the resistive plate connected to the indicator light 2 is directly proportional to the brightness of the indicator light 2, the length of the resistive plate connected to the circuit can be deduced from the brightness of the indicator light 2, thus obtaining the position of the movable conductive plate 13, i.e., the water surface position at the location of each monitoring unit. The internal circuit design of the monitoring unit associates each indicator light 2 with a specific resistive plate 11. When the water level changes and causes the movable conductive plate 13 to contact a certain resistive plate 11, the resistive plate 11, the movable conductive plate 13, the corresponding indicator light 2, and the external power supply will form a complete series circuit. Once the circuit is closed and current flows, the corresponding indicator light 2 will be lit or its light emission state (color or brightness) will change, thus intuitively indicating the current water level.

[0019] Through this combination of mechanical and electrical methods, the monitoring unit can transform continuous water level changes into discrete, visually identifiable changes in the status of indicator lights. This physical sensing mechanism provides the image acquisition module with stable, reliable, and intuitive water level indication information, effectively solving the accuracy and robustness problems that may arise from relying solely on image recognition of the water gauge scale. Especially in complex environments such as uneven lighting, water surface fluctuations, or partial obstruction of the water gauge, the system can obtain more accurate relative water level data through the status of the indicator lights of the monitoring unit, thereby improving the accuracy and reliability of the entire water gauge level monitoring system.

[0020] In addition, a ball bearing 10 is installed inside the collar 9, and the ball bearing 10 contacts the side of the support column 7 opposite to the side where the resisting plate 11 is installed; a protrusion is provided at the end of the support column 7 away from the base plate 3, and the protrusion is used to restrict the collar 9 from disengaging from the support column 7.

[0021] The ball bearing 10 can be made of insulating material to reduce friction between the collar 9 and the support 7. Alternatively, the support 7 in the above example can be omitted, and the collar 9 can be directly fitted onto the resist chain, with a protrusion provided at the lower end of the resist chain.

[0022] A float frame 4 can also be installed below the base plate 3 to increase the buoyancy of the entire monitoring unit. Side holes 5 are opened on the side of the float frame 4 and bottom holes 6 are opened at the bottom of the float frame 4 to facilitate water to enter the interior of the float frame 4. The float frame 4 can also eliminate the amplitude of water surface fluctuations, reduce the movement of the collar 9, and make the brightness of the indicator light 2 stable.

[0023] The combination of the above technical solutions not only optimizes the mechanical motion performance of the monitoring unit, but also improves its durability and safety in complex hydrological environments, ensuring that the water level monitoring system can operate stably and accurately for a long time.

[0024] like Figure 4 As shown in the embodiment of this application, a water level monitoring method is provided, including: S1: Obtain a panoramic view of the water gauge and the monitoring array, as well as a top view of the monitoring array. The monitoring array includes multiple monitoring units connected to each other, fixed around the water gauge and within the acquisition range of the panoramic view. Each monitoring unit is numbered systematically. The monitoring unit includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls.

[0025] S2: Preprocess the panoramic and top-down views.

[0026] Preprocessing operations can include adjusting the brightness and contrast of the image, or performing noise removal and sharpening to improve image quality and facilitate subsequent recognition. For example, histogram equalization can be used to enhance image contrast, or Gaussian filtering can be used to smooth the image and reduce noise.

[0027] S3: Identify the water level markings measured by water gauges in multiple pre-processed panoramic images. This identification process can locate the water gauge area using image segmentation technology, and then use optical character recognition (OCR) technology to read the marking values ​​on the water gauge. In another implementation, the markings on the water gauge can be manually labeled beforehand, and these markings can be located in the panoramic image using image matching technology to obtain the water level information.

[0028] S4: If the change in water level scale within a preset time exceeds a preset threshold, identify the real-time color and brightness of the indicator lights on each monitoring unit in the top view. If the change in water level scale within a preset time is less than the preset threshold, directly use the identified water level scale as the absolute water level value.

[0029] Specifically, image processing algorithms can be used to extract the area of ​​each monitoring unit and analyze the pixel color distribution and average brightness value of the indicator lights within that area. In one implementation, water level states corresponding to different colors and brightness levels can be preset, and the determination can be made by comparing the recognition results with the preset values.

[0030] S5: Analyze the relative water level value monitored by each monitoring unit based on the real-time color and brightness. A color-brightness-water level mapping table can be established, and the corresponding relative water level value can be found in this table based on the identified real-time color and brightness. Alternatively, the relative water level value can be calculated using interpolation or fitting methods based on the brightness change curve of the indicator lights.

[0031] S6: Compare the relative water level values ​​of all monitoring units, and determine the maximum and minimum values ​​in each row and column of the monitoring array and their corresponding monitoring unit numbers.

[0032] S7: Based on the maximum and minimum values ​​and the monitoring unit numbers corresponding to the maximum and minimum values, the relative average water level is obtained through analysis.

[0033] Specifically, one approach is to directly calculate the arithmetic mean of the relative water level values ​​from all effective monitoring units to obtain a preliminary average relative water level. Another approach is to average the remaining relative water level values ​​after removing obvious outliers (e.g., values ​​that deviate significantly from the majority). Furthermore, due to the volatility of the water surface, the monitoring array may not cover a complete fluctuation cycle, and the maximum or minimum values ​​detected by the array may not reflect the actual maximum or minimum water surface fluctuations. Therefore, existing monitored values ​​can be used for fitting to calculate the average value.

[0034] S8: Determine the absolute height corresponding to the position markers based on the position markers of the water gauge and monitoring unit in the panoramic image.

[0035] Specifically, the height of each monitoring unit's location marker on the water gauge can be pre-recorded by manual measurement and stored in a database. After the location marker is identified in the image, its absolute height can be obtained by querying the database. Alternatively, image matching technology can be used to identify reference objects with known absolute heights in the panoramic image, and these reference objects can be used to calculate the absolute height of the location marker.

[0036] S9: The absolute water level value is obtained based on the absolute height, relative height, and average relative water level of the location marker. The relative height of the location marker refers to its vertical distance from the reference point on the monitoring unit. The absolute height and average relative water level of the location marker can be calculated, and then corrected using the relative height to obtain the final absolute water level value.

[0037] In this optional embodiment, the relative height of the location marker refers to the vertical height of the location marker relative to a fixed reference point within the monitoring unit. This relative height is typically an inherent parameter determined during the design or manufacturing of the monitoring unit. By combining macroscopic water level information from the water gauge and microscopic water level information from the monitoring array, accurate water level monitoring is achieved. Image preprocessing reduces the impact of weather on the acquired images, improving recognition accuracy. When water gauge recognition is affected by environmental factors (such as water surface fluctuations), leading to a decrease in accuracy, the multi-point, real-time relative water level data provided by the monitoring array can effectively supplement and correct this. In particular, when water level changes drastically, the system can promptly identify and initiate a more refined monitoring process, utilizing the distributed data from the monitoring array to capture details of water surface fluctuations, thereby calculating a more accurate average water level. This multi-source information fusion and dynamic response mechanism effectively overcomes the limitations of single water gauge image recognition in harsh environments, significantly improving the accuracy and reliability of water level monitoring.

[0038] The following is a detailed description of each step.

[0039] S1: Obtain a panoramic view of the water gauge and the monitoring array, as well as a top view of the monitoring array. The monitoring array includes multiple monitoring units connected to each other, fixed around the water gauge and within the acquisition range of the panoramic view. Each monitoring unit is numbered systematically. The monitoring unit includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls.

[0040] S2: Preprocess the panoramic and top-down views.

[0041] S210: Perform dehazing, grayscale conversion, and binarization on the panoramic image to obtain a preprocessed panoramic image.

[0042] S220: Defogging the top view to obtain a pre-processed top view.

[0043] Specifically, in dense fog or low light conditions, color details in captured images change, and some features may become blurred or obscured. To extract effective details from the image without affecting detection accuracy, the acquired degraded image needs to undergo image quality restoration and enhancement processing. The system employs an image enhancement-based dehazing algorithm (histogram equalization). Histogram equalization improves the low contrast of fogged images through global or local equalization algorithms, expanding the image's grayscale range and thus increasing contrast, achieving a dehazing effect. Local histogram processing results show that this algorithm effectively preserves the local features of the original image, such as... Figure 5 As shown, no obvious color distortion was observed, and the dehazing effect was also achieved.

[0044] The process of converting a color image into a grayscale image is called grayscale processing. A captured water level indicator image is composed of red, green, and blue pixels, with each pixel having over 16 million possible variations. When R=G=B, color becomes grayscale; therefore, the color space of a grayscale image changes from three dimensions to one dimension. Grayscale processing uses a weighted average method. For example... Figure 6 As shown, the weighted average method is used to convert the image to grayscale while maintaining image clarity.

[0045] Image binarization refers to setting the grayscale value of pixels in an image to 0 or 255, or making the entire image appear as a single grayscale image with only two distinct levels of black and white, preparing for subsequent recognition of watermark characters. The OTSU method is used for image binarization, such as... Figure 7 As shown.

[0046] During water level monitoring, environmental factors (such as fog, haze, and uneven lighting) can degrade image quality, affecting the accuracy of subsequent image recognition. By dehazing, grayscale conversion, and binarization of the panoramic image, and dehazing the top-down view, image clarity, contrast, and target-background separation can be significantly improved. This provides high-quality image input for accurately identifying water level markings and precisely acquiring the real-time color and brightness of the indicator lights on the monitoring unit. This not only improves the accuracy and reliability of water level monitoring but also reduces the misjudgment rate caused by image quality issues, enabling the entire monitoring system to operate stably even in complex and changing environments.

[0047] S3: Identify the water level scale measured by the water gauge in multiple pre-processed panoramic images.

[0048] S310: Extract the water level gauge area from the preprocessed panoramic image.

[0049] Specifically, to extract the effective water gauge region from the water gauge image and improve the accuracy of water gauge recognition, morphological operations are used to delineate the water gauge region. Image morphological processing can remove irrelevant regions and reduce the computational load of image processing while maintaining the basic shape of the image. After image preprocessing, the image processing speed is improved and the background noise interference factors of the actual water gauge region are reduced. Then, a morphological closure operation is performed on the character region to connect the small regions in the image. Finally, an opening operation is used to smooth the boundaries of large objects. Finally, noise factors are removed, the image is enlarged, and the boundaries are enlarged to initially locate the water gauge region. When determining the water gauge region, its left and right edges are first determined, the background on both sides is removed, and then the top and bottom edges are determined. Finally, the region containing only the water gauge is cropped out.

[0050] S320: Perform tilt correction on the water gauge area and identify the characters on the water gauge from bottom to top to obtain the recognition sequence.

[0051] Specifically, in real-world scenarios, the acquired images will exhibit some tilt distortion. Tilt correction facilitates subsequent character segmentation and water level recognition. The horizontal direction of the water level gauge is corrected using the Hough transform. The water level gauge image has two parallel upper and lower bounds; by detecting these two parallel bounding boxes, the tilt angle of the water level gauge can be determined. By rotating the tilt angle, the image of the water level gauge can be corrected. The Hough transform converts the Cartesian coordinate system to a polar coordinate system, and then counts the number of feature points at each angle; the angle with the most feature points is the tilt angle of the line to be detected.

[0052] Water level gauges typically have the following characteristics: 1) The background color of the water level gauge is white, and the characters are red or blue; 2) The numerical characters are uniformly printed on the left side of the water level gauge, and each numerical character has an "E" to its right, such as... Figure 2 and Figure 5 As shown; 3) The height and width of each "E" are the same. First, the watermark character is segmented into numbers and the letter "E". Then, the character recognition algorithm of the BP neural network is used to recognize the watermark character. The main process of the BP neural network character recognition algorithm is as follows: the input is set to the character image, and the output is set to the corresponding text character. Through repeated learning of the neural network, a network is finally obtained; then, in the working period, the input of the neural network is set to the image of the character to be recognized. By keeping the network connection weights unchanged, the output is obtained, that is, the correct text character.

[0053] S330: If the sequence contains a number and the second character is a complete E, then substitute the number of the third character and the height of the first character into the first water level analysis model to obtain the water level scale.

[0054] S340: If the sequence contains numbers and the second character is a number, then substitute the number of the second character and the height of the first character into the second water level analysis model to obtain the water level scale.

[0055] Specifically, since the first character in contact with the water surface is usually incomplete, the error in calculating the water level by recognizing the first character is too large, but the height of the first character can be calculated to accurately identify the result.

[0056] Each character on the water ruler is the same size and its actual height is 5cm. The height is calculated by measuring the ratio of the last character to the complete character.

[0057] If the recognition result contains a number and the second character is "E", the calculation formula is: In the formula: This is the current draft gauge reading; This indicates the third character identified; M is the height of the complete character, and m represents the height of the last character.

[0058] If the recognition result contains numbers and the second character is a number, the calculation formula is: In the formula: This indicates the second character that was identified.

[0059] The system precisely extracts the water level gauge area from the preprocessed panoramic image, focusing processing on key information. Subsequently, the extracted water level gauge area undergoes tilt correction, effectively eliminating image distortion caused by shooting angle or installation errors, ensuring the vertical or horizontal alignment of the water level gauge scale, laying an accurate foundation for subsequent character recognition. Based on this, the system sequentially recognizes characters from the bottom of the water level gauge upwards, constructing an ordered recognition sequence. This conforms to the conventional reading habits of the water level gauge, avoiding errors caused by disordered reading order. Furthermore, this application adaptively selects different water level analysis models based on the specific pattern of the recognition sequence (e.g., whether it contains the character "E" or a combination of pure numbers). This intelligent model selection mechanism enables the system to flexibly handle water level gauges of different types and marking methods, accurately converting the recognized characters and their relative height information on the water level gauge into actual water level scale values ​​through a preset mathematical model or algorithm. Through the synergistic effect of the above series of steps, this application can overcome challenges such as poor image quality, water gauge tilt, and diversity of scale representation, significantly improving the accuracy and robustness of identifying water gauge scales from images, and providing reliable initial data for subsequent water level monitoring.

[0060] S4: If the change in water level scale exceeds a preset threshold within a preset time, identify the real-time color and brightness of the indicator lights on each monitoring unit in the top view.

[0061] S5: Analyze the relative water level value monitored by each monitoring unit based on real-time color and real-time brightness.

[0062] S510: Based on the real-time color, determine the corresponding brightness peak and reference height. The monitoring unit contains a chain of multiple sequentially connected and insulated resistive plates. The chain is vertically inserted into the water, and indicator lights are positioned one-to-one with the resistive plates. One end of an indicator light of a particular color is connected to one end of its corresponding resistive plate, and the other end is connected to a movable conductive plate via a power source. The movable conductive plate contacts the chain and moves vertically along the chain as the water level rises and falls. Figure 3As shown, assuming the length of each resistive element 11 is L, and L is 20mm, and the height of the insulating tape 12 is 1mm, then from top to bottom, the reference height of the first resistive element 11 is 42mm, the reference height of the second resistive element 11 is 21mm, and the reference height of the third resistive element 11 is 0mm. When one end of the indicator light is connected to the top of the resistive element, the brightness peak can be measured when the monitoring array is installed. The peak value of each color corresponds to the brightness of the indicator light when the moving conductive sheet 13 moves to the top of each resistive element; conversely, the brightness peak is the brightness of the indicator light when the moving conductive sheet 13 moves to the bottom of the resistive element.

[0063] S520: The relative water level value is obtained based on the real-time brightness, peak brightness, reference height, and resistive sheet length.

[0064] Specifically, when one end of the indicator light is connected to the top of the resistive element, the actual length of the resistive element in the circuit is obtained by dividing the real-time brightness by the peak brightness and then multiplying by the resistive element length. The relative water level value is obtained by adding the base height to the resistive element length and then subtracting the actual length. When one end of the indicator light is connected to the bottom of the resistive element, the actual length of the resistive element in the circuit is obtained by dividing the real-time brightness by the peak brightness and then multiplying by the resistive element length. The relative water level value is obtained by adding the base height to the actual length.

[0065] This method directly converts changes in water level into real-time color and brightness changes of the indicator lights on the monitoring units, overcoming the difficulty of accurately quantifying water level through visual observation or simple image processing alone. By introducing a resistive chain, a moving conductive sheet, and corresponding connections between the indicator lights and the resistive sheet, direct conversion between water level and electrical signals is achieved. Furthermore, by combining real-time brightness, peak brightness, reference height, and resistive sheet length for comprehensive analysis, the relative water level value monitored by each monitoring unit can be calculated with high precision, significantly improving the accuracy and reliability of relative water level measurement and laying a solid foundation for the subsequent accurate acquisition of absolute water level values.

[0066] S6: Compare the relative water level values ​​of all monitoring units, and determine the maximum and minimum values ​​in each row and column of the monitoring array and their corresponding monitoring unit numbers.

[0067] S7: Based on the maximum and minimum values ​​and the monitoring unit numbers corresponding to the maximum and minimum values, the relative average water level is obtained through analysis.

[0068] S710: Treat each row or column of monitoring units as a monitoring unit group, and analyze whether the monitoring unit number corresponding to the maximum value or the monitoring unit number corresponding to the minimum value is located at both ends of the monitoring unit group. This analysis is used to determine whether the extreme points (peaks or troughs) of water surface fluctuations occur within the monitoring unit group.

[0069] S720: If not located at both ends of the monitoring unit group, extract the relative water level values ​​(including the maximum and minimum values) of all monitoring units between the monitoring unit number corresponding to the maximum value and the monitoring unit number corresponding to the minimum value, sum them and take the average value to obtain the average relative water level.

[0070] When the extreme points of water surface fluctuations are not located at the two ends of the monitoring unit group, it indicates that the monitoring unit group contains a complete wave crest or trough structure. In this case, the relative water level average can be calculated by taking the arithmetic mean of the relative water level values ​​of all monitoring units between the extreme points (including the two extreme points).

[0071] S730: If located at both ends of the monitoring unit group, the relative water level value corresponding to each monitoring unit in the monitoring unit group is plotted on the coordinate system to obtain a scatter plot, where the horizontal axis of the coordinate system is the position of each monitoring unit and the vertical axis is the relative water level value.

[0072] When the extreme points of water surface fluctuations are located at both ends of the monitoring unit group, it indicates that the monitoring unit group may have only captured a portion of the waveform, requiring extrapolation to estimate the complete waveform. Using the position of the monitoring unit as the x-axis and the corresponding relative water level value as the y-axis, the discrete data points of water surface fluctuations can be visually displayed. For example, the x-axis could be the physical distance of the monitoring unit, and the y-axis could be the relative water level value obtained through real-time color and brightness analysis.

[0073] S740: Based on multiple points in the scatter plot, a wavefront curve is fitted. The wavefront curve is then extended along its increasing or decreasing trend to obtain the estimated maximum or minimum value of the wavefront curve.

[0074] Specifically, mathematical methods are used to reconstruct the continuous pattern of water surface fluctuations from discrete relative water level data, and to estimate missing peaks or troughs through extrapolation. Various mathematical models can be used to fit the wave surface curve, such as polynomial fitting, spline interpolation (e.g., cubic spline interpolation), and Fourier series fitting. Extending the wave surface curve involves extending the fitted curve beyond the monitoring unit group based on its existing growth or decline trend to predict the extreme values ​​of any possible complete peaks or troughs. For example, the trend can be determined based on the derivative information of the fitted curve, and linear or nonlinear extrapolation can be performed along that trend.

[0075] S750: Compare the maximum value with the estimated maximum value and the minimum value with the estimated minimum value to obtain the peak and valley values.

[0076] The peaks and valleys that best represent the complete waveform characteristics are determined by considering both the actual measured extreme values ​​and the estimated extreme values ​​obtained through curve extension. For example, if the estimated maximum value is greater than the actual measured maximum value, the estimated maximum value is taken as the final peak value; otherwise, the actual measured maximum value is used as the peak value. A similar approach is used for valley values.

[0077] S760: The average relative water level is obtained by adding the peak and valley values ​​and the relative water level values ​​corresponding to all monitoring units between them.

[0078] After identifying the complete peaks and troughs, this step yields a more accurate relative average water level by averaging all relevant data points that encompass the complete waveform. This includes the actual measured values ​​from monitoring units, as well as the peak and trough values ​​obtained by extending the curve. For example, these values ​​can be simply averaged arithmetically, or weighted according to their position and importance within the waveform.

[0079] The above-mentioned technical solution effectively addresses the problem of inaccurate water level measurements caused by water surface fluctuations. Especially when the peaks or troughs of water surface fluctuations are located precisely at the edge of the monitoring array, fitting and extending the wave surface curve allows for accurate prediction of the complete waveform extremes, thus avoiding deviations in average water level calculations caused by data truncation. This method results in more accurate and stable relative water level averages, providing reliable water level data even under complex hydrological conditions. It significantly improves the accuracy and robustness of water gauge monitoring, laying a solid foundation for subsequent calculations of absolute water level values.

[0080] S8: Determine the absolute height corresponding to the position markers based on the position markers of the water gauge and monitoring unit in the panoramic image.

[0081] S810: Based on the location markers of the monitoring units in the panoramic view, extend the horizontal line towards the water gauge to obtain the auxiliary marker lines, such as... Figure 2 The auxiliary lines drawn in the diagram are shown.

[0082] S820: In the panoramic image, identify the characters on the water level gauge that are above the marker guide lines to obtain the relative position recognition sequence.

[0083] By limiting the recognition area to the water level mark above the auxiliary lines, the recognition range can be effectively narrowed, improving recognition efficiency and accuracy. This recognition method utilizes Optical Character Recognition (OCR) technology to scan and recognize numbers, letters, and other characters within the water level mark area above the auxiliary lines. The recognized characters can be sorted according to their vertical position on the water level mark, either from bottom to top or from top to bottom, forming a string or character array—a relative position recognition sequence.

[0084] S830: If the relative position identification sequence contains a number and the second character is a complete E, then substitute the number of the third character and the height of the first character into the first water level analysis model to obtain the absolute height corresponding to the position identifier.

[0085] S840: If the relative position identification sequence contains numbers and the second character is a number, then substitute the number of the second character and the height of the first character into the second water level analysis model to obtain the absolute height corresponding to the position identifier.

[0086] Specifically, the S330 and S340 methods are used to calculate the height, obtaining the absolute height corresponding to the location marker. Image recognition technology is utilized to avoid errors that may arise from manual measurement, improving the accuracy and efficiency of data acquisition. Simultaneously, by employing different water level analysis models for different water gauge scale formats, the system's adaptability and robustness are enhanced, making it applicable to various water gauge types. This provides a reliable and accurate benchmark for subsequent absolute water level calculations, significantly improving the accuracy and practicality of the entire water gauge level monitoring method.

[0087] S9: Obtain the absolute water level value based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

[0088] Specifically, the relative height difference is obtained based on the absolute height and relative height of the location marker. The absolute water level value is obtained based on the average relative water level and the relative height difference. The absolute height of the location marker refers to the vertical height of the location marker in the actual geographic coordinate system, determined by analyzing the water level gauge and the location marker of the monitoring unit in the panoramic view, combined with the scale information on the water level gauge. The relative height of the location marker refers to the vertical height of its location marker inside the monitoring unit relative to a fixed reference point within the monitoring unit (e.g., the bottom, top, or bottom or top of support column 7 of the monitoring unit). This relative height is usually an inherent parameter determined during the design or manufacturing of the monitoring unit. The relative height difference essentially represents the actual absolute height of the reference point inside the monitoring unit (e.g., its zero point of relative height) in the absolute geographic coordinate system.

[0089] By introducing the difference between the absolute and relative height of the location markers as a calibration benchmark, the reference differences between different measurement systems are effectively bridged, ensuring that the relative water level data obtained from the distributed monitoring units can be accurately mapped to a unified absolute elevation system. This significantly improves the accuracy and reliability of water level monitoring data, providing more precise and consistent data support for applications such as hydrological management and flood warning, and avoiding measurement errors caused by inconsistent reference systems.

[0090] like Figure 8 As shown in the figure, an embodiment of this application provides a water level monitoring system, comprising: A monitoring array is deployed near the water level gauge. The monitoring array consists of multiple monitoring units, each of which is regularly numbered. Each monitoring unit includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls.

[0091] The image acquisition module is used to acquire panoramic views of the water gauge and monitoring array, as well as top views of the monitoring array.

[0092] The image preprocessing module is used to preprocess panoramic and top-down views.

[0093] The image recognition module is used to identify the water level scales measured by water gauges in multiple pre-processed panoramic images.

[0094] The joint identification module is used to identify the real-time color and brightness of the indicator lights on each monitoring unit in the top view if the change in the water level scale exceeds a preset threshold within a preset time.

[0095] The relative water level analysis module is used to analyze the relative water level value monitored by each monitoring unit based on real-time color and real-time brightness; it is also used to compare the relative water level values ​​of all monitoring units, and in the monitoring array, to determine the maximum and minimum values ​​in each row and column and their corresponding monitoring unit numbers; it is also used to analyze and obtain the average relative water level based on the maximum and minimum values ​​and the monitoring unit numbers corresponding to the maximum and minimum values ​​respectively.

[0096] The image recognition module is also used to determine the absolute height corresponding to the position marker based on the position markers of the water gauge and the monitoring unit in the panoramic image.

[0097] The absolute water level analysis module is used to obtain the absolute water level value based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

[0098] In this optional embodiment, by combining the monitoring array with water level gauge image recognition, and particularly utilizing the characteristic of the indicator lights on the monitoring units changing with the water level, the system automatically switches to a multi-point monitoring mode when the water level fluctuates significantly, effectively overcoming the limitations of a single water level gauge image in harsh environments. When the change in the water level scale exceeds a preset threshold within a preset time, the joint recognition module is activated, recognizing the real-time color and brightness of the indicator lights on each monitoring unit in the top-down view. The relative water level analysis module analyzes the relative water level value monitored by each monitoring unit accordingly, and by comparing the relative water level values ​​of all monitoring units, determines the maximum and minimum values ​​in each row and column of the monitoring array and their corresponding monitoring unit numbers, thereby obtaining the average relative water level. Simultaneously, the image recognition module determines the absolute height corresponding to the position markers based on the position markers of the water level gauge and monitoring units in the panoramic image. Finally, the absolute water level analysis module combines the absolute height of the position markers, the relative height of the position markers, and the average relative water level to calculate the accurate absolute water level value. This technical solution significantly reduces the impact of environmental factors on water level recognition through multi-point monitoring and a dynamic threshold triggering mechanism.

[0099] The system maintains high water level monitoring accuracy even under adverse weather conditions. For example, when the water surface fluctuates violently due to wind and waves, water level gauge image recognition may fail due to glare or blurring. In this case, the system automatically switches to monitoring array mode, using the color and brightness changes of indicator lights to reflect the local water level, and then obtains the average water level through statistical analysis, avoiding random errors from single measurement points. As a specific implementation method, the monitoring array can be arranged in a matrix form. When the maximum and minimum values ​​in a row or column of monitoring units are not located at the ends, the average value of the middle part is directly taken; if they are located at the ends, an extended estimate is made by fitting a wave surface curve, further improving the reliability of data processing. Overall, this application achieves a dual guarantee mechanism for water level monitoring by integrating macroscopic water level gauge recognition and microscopic monitoring array data, effectively improving the system's adaptability and accuracy in complex environments.

[0100] An electronic device provided in this application includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement the water level monitoring method described above when the computer program is executed.

[0101] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the water level monitoring method described above.

[0102] In this embodiment, the beneficial effects of the electronic device and the computer-readable storage medium are similar to those of the water level monitoring method described above, and will not be repeated here.

[0103] The present invention describes electronic devices that can serve as servers or clients of this application, which are examples of hardware devices that can be applied to various aspects of this application. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital assistant devices, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the application described and / or claimed herein.

[0104] Electronic devices include a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM can also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0105] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the separately described modules may or may not be physically separate. Some or all of the modules can be selected to achieve the purpose of the embodiments of this application according to actual needs. Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0106] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0107] The above 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.

Claims

1. A method for monitoring water levels using a water gauge, characterized in that, include: The system acquires a panoramic view of the water level gauge and the monitoring array, as well as a top view of the monitoring array. The monitoring array is deployed near the water level gauge and consists of multiple monitoring units connected to each other. These units are fixed around the water level gauge and within the acquisition range of the panoramic view. Each monitoring unit is numbered systematically and includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. Preprocess the panoramic and top-down views; Identify water level readings from water gauges in multiple pre-processed panoramic images; If the change in water level scale exceeds a preset threshold within a preset time, identify the real-time color and brightness of the indicator lights on each monitoring unit in the top view; Based on real-time color and real-time brightness, analyze the relative water level value monitored by each monitoring unit; Compare the relative water level values ​​of all monitoring units, and determine the maximum and minimum values ​​in each row and column of the monitoring array and their corresponding monitoring unit numbers; Based on the maximum and minimum values, and the monitoring unit numbers corresponding to the maximum and minimum values, the relative average water level is obtained through analysis. Based on the location markers of the water gauge and monitoring unit in the panoramic image, determine the absolute height corresponding to the location markers; The absolute water level value is obtained based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

2. The water level monitoring method according to claim 1, characterized in that, The preprocessing of the panoramic and top-view images includes: The panoramic image is subjected to dehazing, grayscale conversion, and binarization to obtain a preprocessed panoramic image; The top view is dehazed to obtain a pre-processed top view.

3. The water level monitoring method according to claim 1, characterized in that, The water level readings measured by water gauges in the preprocessed panoramic images include: The water level gauge area is obtained by cropping the water level gauge from the preprocessed panoramic image; The tilt of the water gauge area is corrected, and the characters on the water gauge are identified sequentially from bottom to top to obtain the recognition sequence. If the sequence contains a number and the second character is a complete E, then substitute the number of the third character and the height of the first character into the first water level analysis model to obtain the water level scale. If the sequence contains numbers and the second character is a number, then the number of the second character and the height of the first character are substituted into the second water level analysis model to obtain the water level scale.

4. The water level monitoring method according to claim 1, characterized in that, The analysis of the relative water level value monitored by each monitoring unit based on real-time color and real-time brightness includes: Based on the real-time color, the brightness peak and reference height corresponding to the real-time color are determined. The monitoring unit is equipped with a chain of multiple sequentially connected and insulated resistive plates. The chain of resistive plates is vertically inserted into the water, and the indicator lights are set one-to-one with the resistive plates. One end of the indicator light of a certain color is connected to one end of the corresponding resistive plate, and the other end of the indicator light of a certain color is connected to a moving conductive plate through a power supply. The moving conductive plate is in contact with the chain of resistive plates, and the moving conductive plate moves up and down along the vertical direction along the chain of resistive plates as the water level rises and falls. The relative water level value is obtained based on the real-time brightness, peak brightness, reference height, and resistive sheet length.

5. The water level monitoring method according to claim 1, characterized in that, The analysis of the relative water level average value based on the maximum and minimum values, and the monitoring unit numbers corresponding to the maximum and minimum values, includes: Treat each row or column of monitoring units as a monitoring unit group, and analyze whether the monitoring unit number corresponding to the maximum value or the monitoring unit number corresponding to the minimum value is located at both ends of the monitoring unit group; If it is not located at both ends of the monitoring unit group, extract the relative water level values ​​of all monitoring units between the monitoring unit number corresponding to the maximum value and the monitoring unit number corresponding to the minimum value, sum them and take the average value to obtain the average relative water level. If located at both ends of the monitoring unit group, the relative water level value corresponding to each monitoring unit in the monitoring unit group is plotted on the coordinate system to obtain a scatter plot, where the horizontal axis of the coordinate system is the position of each monitoring unit and the vertical axis is the relative water level value; Based on multiple points in the scatter plot, a wavefront curve is fitted. The wavefront curve is then extended along its increasing or decreasing trend to obtain the estimated maximum or minimum value of the wavefront curve. By comparing the maximum value with the estimated maximum value and by comparing the minimum value with the estimated minimum value, the peak value and the trough value are obtained. The average relative water level is obtained by adding the peak and trough values ​​and the relative water level values ​​corresponding to all monitoring units between them.

6. The water level monitoring method according to claim 3, characterized in that, The process of determining the absolute height corresponding to the location marker based on the water level gauge and the location marker of the monitoring unit in the panoramic image includes: Based on the location markings of the monitoring units in the panoramic image, extend the horizontal line towards the water gauge to obtain the marking auxiliary line; In the panoramic image, characters above the marker lines on the water gauge are identified to obtain a relative position identification sequence; If the relative position identification sequence contains a number and the second character is a complete E, then substitute the number of the third character and the height of the first character into the first water level analysis model to obtain the absolute height corresponding to the position identifier; If the relative position identification sequence contains numbers and the second character is a number, then the number of the second character and the height of the first character are substituted into the second water level analysis model to obtain the absolute height corresponding to the position identifier.

7. The water level monitoring method according to claim 6, characterized in that, The process of obtaining the absolute water level value based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level includes: The relative height difference is obtained based on the absolute height and relative height of the location marker. The absolute water level value is obtained based on the relative average water level and the relative height difference.

8. A water level monitoring system, characterized in that, include: A monitoring array is deployed near the water level gauge. The monitoring array consists of multiple monitoring units connected to each other, fixed around the water level gauge and within the panoramic image acquisition range. Each monitoring unit is regularly numbered and includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. The image acquisition module is used to acquire panoramic views of the water gauge and the monitoring array, as well as top views of the monitoring array. The monitoring array includes multiple monitoring units, each of which is regularly numbered. Each monitoring unit includes indicator lights and location markers. The indicator lights change color and brightness in real time as the water level rises and falls. The image preprocessing module is used to preprocess panoramic and top-down views; The image recognition module is used to identify the water level scales measured by water gauges in multiple pre-processed panoramic images; The joint identification module is used to identify the real-time color and real-time brightness of the indicator lights on each monitoring unit in the top view if the change in the water level scale exceeds a preset threshold within a preset time. The relative water level analysis module is used to analyze the relative water level value monitored by each monitoring unit based on real-time color and real-time brightness; it is also used to compare the relative water level values ​​of all monitoring units, and in the monitoring array, to determine the maximum and minimum values ​​in each row and column and their corresponding monitoring unit numbers; it is also used to analyze and obtain the average relative water level based on the maximum and minimum values ​​and the monitoring unit numbers corresponding to the maximum and minimum values ​​respectively. The image recognition module is also used to determine the absolute height corresponding to the position marker based on the position markers of the water gauge and the monitoring unit in the panoramic image; The absolute water level analysis module is used to obtain the absolute water level value based on the absolute height of the location marker, the relative height of the location marker, and the average relative water level. The relative height of the location marker refers to the vertical height of the location marker from the reference point on the monitoring unit.

9. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the water level monitoring method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the water level monitoring method as described in any one of claims 1 to 7.

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