AI water level early warning linkage gate control method and system and medium

Abstract

The invention discloses an AI water level early warning linkage gate control method and system and a medium. The method comprises the steps that S10, a waterlogging area water level gauge image is obtained; step S20, extracting scale features from the water level scale image by using a water level scale identification algorithm, and calculating a water level height; and S30, executing a corresponding gate control strategy according to the calculated water level height. The system can help urban safety and flood control, quickly discover and prevent problems, timely notify a responsibility unit when an alarm occurs, and automatically link a control scheme for automatic control, so that the early warning problem can be handled in the first time; an emergency department is helped to quickly deal with sudden safety accidents, prevent the safety accidents and timely and automatically deal with emergencies, life and property safety of people is guaranteed, and a large amount of manpower and material resource cost is saved.

Description

Technical Field

[0001] This invention relates to the field of flood disaster monitoring technology, and in particular to an AI-based water level early warning and linkage gate control method, system and medium. Background Technology

[0002] Floods are a common natural disaster that not only threatens people's property and safety but also endangers their personal safety, causing irreparable losses in severe cases. Therefore, effective flood prevention and drainage are of great practical significance.

[0003] Current urban safety and flood control solutions cannot automatically control gates based on water levels, cannot quickly detect and prevent problems, and cannot provide real-time early warnings and responses to flooding conditions. Summary of the Invention

[0004] The main objective of this invention is to propose an AI-based water level early warning and linkage gate control method, system, and medium, which aims to assist in urban safety and flood control by enabling rapid detection and prevention of problems, timely notification of responsible units upon alarm occurrence, and automated linkage management schemes for automated management.

[0005] To achieve the above objectives, the present invention provides an AI-based water level early warning and linkage gate control method, the method comprising the following steps:

[0006] Step S10: Obtain the water level gauge image of the flooded area;

[0007] Step S20: Extract scale features from the water level scale image using a water level scale recognition algorithm, and calculate the water level height;

[0008] Step S30: Execute the corresponding gate control strategy based on the calculated water level height.

[0009] A further technical solution of the present invention is that step S20 includes:

[0010] Step S201: Preprocess the water level gauge image;

[0011] Step S202: Extract features from the preprocessed image to obtain the horizontal scale line and scale position of the water level gauge;

[0012] Step S203: Perform scale positioning and recognition based on the extracted features;

[0013] Step S204: Convert the image coordinates into actual physical coordinates using camera calibration parameters, and calculate the water level height based on the ratio of the known length of the water level gauge to the image pixel length.

[0014] A further technical solution of the present invention is that step S201 includes:

[0015] Step S2011, Grayscale conversion: Convert the water level scale image into a grayscale image to reduce computational complexity;

[0016] Step S2012, Filtering and noise reduction: Use Gaussian filtering or median filtering to remove noise;

[0017] Step S2013, binarization: Separate the water level gauge from the background using a threshold segmentation method.

[0018] A further technical solution of the present invention is that step S202 includes:

[0019] Step S2021, Edge Detection: Extract the edges of the water level gauge image using the Canny or Sobel operator;

[0020] Step S2022, Line detection: Use Hough transform to detect the horizontal scale line of the water level gauge;

[0021] Step S2023, Contour Analysis: Locate the contour of the water level gauge area and determine the gauge position.

[0022] A further technical solution of the present invention is that step S203 includes:

[0023] Step S2031, scale line matching: Filter valid scales based on scale line spacing and length;

[0024] Step S2032: Based on the effective scale, the water level value is identified using OCR technology or template matching.

[0025] A further technical solution of the present invention is that step S20 further includes:

[0026] The system adjusts the corresponding illumination changes based on dynamic thresholds, detects the tilt angle of the scale and corrects it through affine transformation, uses YOLO or Mask R-CNN to detect the scale area, and directly outputs the water level value by combining it with a regression model.

[0027] A further technical solution of the present invention is that step S30 includes:

[0028] In step S301, if the water level is higher than or equal to the preset threshold, the gate is opened to release water automatically, and images of the gate opening are captured, video of the case handling process is recorded, and an alarm is issued and the responsible unit is notified.

[0029] A further technical solution of the present invention is that step S30 further includes:

[0030] Step S302: If the water level is lower than the preset threshold, the gate is closed, a picture of the gate being closed is captured, and a video of the water level at the scene is recorded to automatically close the case.

[0031] To achieve the above objectives, the present invention also proposes an AI water level early warning linkage gate control system, the system including a memory, a processor, and an AI water level early warning linkage gate control program stored on the processor, wherein the AI ​​water level early warning linkage gate control program is executed by the processor to perform the steps of the method described above.

[0032] To achieve the above objectives, the present invention also proposes a computer-readable storage medium storing an AI water level early warning linkage gate control program, wherein the AI ​​water level early warning linkage gate control program is executed by a processor to perform the steps of the method described above.

[0033] The beneficial effects of the AI-based water level early warning and linkage gate control method, system, and medium of this invention are:

[0034] This invention achieves an accuracy rate of over 98%, automatically generating water level alarm cases. After platform confirmation, it automatically opens the downstream sluice gate to release water, captures images of the gate opening, and records video of the case handling process. When the water level returns to normal, it automatically closes the gate, captures images of the gate closure, records video of the on-site water level, and automatically closes the case. This can help with urban safety and flood control, enabling rapid detection and prevention of problems. When an alarm occurs, it promptly notifies the responsible unit and automatically links with the management plan for automated management. It can handle early warning issues immediately, helping emergency departments to quickly respond to and prevent sudden safety accidents, and promptly and automatically handle emergencies, protecting people's lives and property and saving a lot of manpower and material costs. Attached Figure Description

[0035] 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 the structures shown in these drawings without creative effort.

[0036] Figure 1 This is a flowchart illustrating a preferred embodiment of the AI ​​water level early warning and linkage gate control method of the present invention;

[0037] Figure 2 This is a detailed flowchart of step S20.

[0038] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0040] This invention proposes an AI-based water level early warning and linkage gate control method, which can be applied to water conservancy monitoring and real-time monitoring of river and reservoir water levels.

[0041] like Figure 1 As shown, a preferred embodiment of the AI ​​water level early warning linkage gate control method of the present invention includes the following steps:

[0042] Step S10: Obtain the water level gauge image of the flooded area.

[0043] In this embodiment, an AI PTZ camera is installed at the water level gauge location in the flooded area, which can capture real-time images of the water level gauge.

[0044] Step S20: Use a water level scale recognition algorithm to extract scale features from the water level scale image and calculate the water level height.

[0045] Step S30: Execute the corresponding gate control strategy based on the calculated water level height.

[0046] Specifically, such as Figure 2 As shown, step S20 includes:

[0047] Step S201: Preprocess the water level gauge image.

[0048] Step S202: Feature extraction is performed on the preprocessed image to obtain the horizontal scale line and scale position of the water level gauge.

[0049] Step S203: Perform scale positioning and recognition based on the extracted features.

[0050] Step S204: Convert the image coordinates into actual physical coordinates using camera calibration parameters, and calculate the water level height based on the ratio of the known length of the water level gauge to the image pixel length.

[0051] Specifically, step S201 includes the following steps:

[0052] Step S2011, Grayscale conversion: Convert the water level scale image into a grayscale image to reduce computational complexity;

[0053] Step S2012, Filtering and noise reduction: Use Gaussian filtering or median filtering to remove noise;

[0054] Step S2013, binarization: Separate the water level gauge from the background using a threshold segmentation method (such as the Otsu algorithm).

[0055] Step S202 specifically includes the following steps:

[0056] Step S2021, Edge Detection: Extract the edges of the water level gauge image using the Canny or Sobel operator;

[0057] Step S2022, Line detection: Use Hough transform to detect the horizontal scale line of the water level gauge;

[0058] Step S2023, Contour Analysis: Locate the contour of the water level gauge area and determine the gauge position.

[0059] Step S203 specifically includes the following steps:

[0060] Step S2031, scale line matching: Filter valid scales based on scale line spacing and length;

[0061] Step S2032: Based on the effective scale, the water level value is identified using OCR technology or template matching.

[0062] In this embodiment, step S20 further includes:

[0063] The system adjusts the corresponding illumination changes based on dynamic thresholds, detects the tilt angle of the scale and corrects it through affine transformation, uses YOLO or Mask R-CNN to detect the scale area, and directly outputs the water level value by combining it with a regression model.

[0064] In this embodiment, step S30 includes:

[0065] In step S301, if the water level is higher than or equal to the preset threshold, the gate is opened to release water automatically, and images of the gate opening are captured, video of the case handling process is recorded, and an alarm is issued and the responsible unit is notified.

[0066] Step S302: If the water level is lower than the preset threshold, the gate is closed, a picture of the gate being closed is captured, and a video of the water level at the scene is recorded to automatically close the case.

[0067] The following provides a further explanation of the AI-based water level early warning and linkage gate control method of the present invention.

[0068] The AI-powered water level early warning and linkage gate control method of this invention can achieve an accuracy of over 98%. It automatically generates water level alarm cases, and after platform confirmation, it automatically opens the downstream gate to release water, captures images of the gate opening, and records video of the case handling process. When the water level returns to normal, it automatically closes the gate, captures images of the gate closure, records video of the on-site water level, and automatically closes the case. This method can help with urban safety and flood control, enabling rapid detection and prevention of problems. When an alarm occurs, it promptly notifies the responsible unit and automatically links with the management plan for automated management. It can handle early warning issues immediately, help emergency departments quickly respond to sudden safety accidents, prevent the occurrence of safety accidents, and promptly and automatically handle emergencies, protecting people's lives and property and saving a lot of manpower and material costs.

[0069] To achieve the above objectives, the present invention also proposes an AI water level early warning linkage gate control system. The system includes a memory, a processor, and an AI water level early warning linkage gate control program stored on the processor. When the AI ​​water level early warning linkage gate control program is run by the processor, it executes the steps of the method described above, which will not be repeated here.

[0070] To achieve the above objectives, the present invention also proposes a computer-readable storage medium, characterized in that the computer-readable storage medium stores an AI water level early warning linkage gate control program, which, when run by a processor, executes the steps of the method described above, which will not be repeated here.

[0071] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for controlling gates with AI-based water level early warning and linkage, characterized in that, The method includes the following steps: Step S10: Obtain the water level gauge image of the flooded area; Step S20: Extract scale features from the water level scale image using a water level scale recognition algorithm, and calculate the water level height; Step S30: Execute the corresponding gate control strategy based on the calculated water level height.

2. The AI-based water level early warning and linkage gate control method according to claim 1, characterized in that, Step S20 includes: Step S201: Preprocess the water level gauge image; Step S202: Extract features from the preprocessed image to obtain the horizontal scale line and scale position of the water level gauge; Step S203: Perform scale positioning and recognition based on the extracted features; Step S204: Convert the image coordinates into actual physical coordinates using camera calibration parameters, and calculate the water level height based on the ratio of the known length of the water level gauge to the image pixel length.

3. The AI-based water level early warning and linkage gate control method according to claim 2, characterized in that, Step S201 includes: Step S2011, Grayscale conversion: Convert the water level gauge image into a grayscale image to reduce computational complexity; Step S2012, Filtering and noise reduction: Use Gaussian filtering or median filtering to remove noise; Step S2013, binarization: Separate the water level gauge from the background using a threshold segmentation method.

4. The AI-based water level early warning and linkage gate control method according to claim 3, characterized in that, Step S202 includes: Step S2021, Edge Detection: Extract the edges of the water level gauge image using the Canny or Sobel operator; Step S2022, Line detection: Use Hough transform to detect the horizontal scale line of the water level gauge; Step S2023, Contour Analysis: Locate the contour of the water level gauge area and determine the gauge position.

5. The AI ​​water level early warning and linkage gate control method according to claim 4, characterized in that, Step S203 includes: Step S2031, scale line matching: Filter valid scales based on scale line spacing and length; Step S2032: Based on the effective scale, the water level value is identified using OCR technology or template matching.

6. The AI-based water level early warning and linkage gate control method according to claim 5, characterized in that, Step S20 further includes: The system adjusts the corresponding illumination changes based on dynamic thresholds, detects the tilt angle of the scale and corrects it through affine transformation, uses YOLO or Mask R-CNN to detect the scale area, and directly outputs the water level value by combining it with a regression model.

7. The AI-based water level early warning and linkage gate control method according to any one of claims 1 to 6, characterized in that, Step S30 includes: In step S301, if the water level is higher than or equal to the preset threshold, the gate is opened to release water automatically, and images of the gate opening are captured, video of the case handling process is recorded, and an alarm is issued and the responsible unit is notified.

8. The AI ​​water level early warning and linkage gate control method according to claim 7, characterized in that, Step S30 further includes: Step S302: If the water level is lower than the preset threshold, the gate is closed, a picture of the gate being closed is captured, and a video of the water level at the scene is recorded to automatically close the case.

9. An AI-based water level early warning and linkage gate control system, characterized in that, The system includes a memory, a processor, and an AI water level early warning and linkage gate control program stored on the processor. The AI ​​water level early warning and linkage gate control program is executed by the processor to perform the steps of the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an AI water level early warning linkage gate control program, which, when executed by a processor, performs the steps of the method as described in any one of claims 1 to 8.

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