A geological disaster monitoring and early warning method and system for a field environment

Abstract

The application provides a geological disaster monitoring and early warning method and system for a field environment, and relates to the technical field of geological disaster monitoring. The method comprises the following steps: acquiring a monitoring check image of a target area, identifying color features in the acquired monitoring check image and judging the main external environment light at the moment, adjusting the light transmittance of an image acquisition device to filter out the main external environment light; acquiring a monitoring initial value image and a monitoring final value image; marking edges and feature points of the acquired images, comparing the displacement changes of the feature point markings in the monitoring initial value image and the monitoring final value image; when the edge marking coincidence rate of the monitoring initial value image and the monitoring final value image is greater than or equal to a first threshold value, if the displacement change amount in the image processing step is greater than or equal to a second threshold value and less than or equal to a third threshold value, a first warning signal is output, and if the displacement change amount in the image processing step is greater than or equal to the third threshold value, a second warning signal is output.

Description

Technical Field

[0001] This application relates to the field of geological disaster monitoring technology, specifically to a method and system for monitoring and early warning of geological disasters in the field environment. Background Technology

[0002] Geological disasters, also known as geological hazards, are natural disasters primarily caused by geological activity or abnormal changes in the geological environment. They have a significant impact on human production and daily life. Among geological disasters, sudden geological disasters (especially landslides) not only occur rapidly but also pose a direct threat to the lives of people in the vicinity.

[0003] Currently, landslide monitoring generally falls into two main categories: contact monitoring, which typically involves establishing observation stations for direct monitoring and using contact measuring instruments; and non-contact monitoring, which generally includes monitoring via satellite remote sensing images and real-time monitoring using image acquisition devices installed outside the landslide body. Contact monitoring suffers from high initial construction costs and generally requires specialized personnel, resulting in substantial upfront investment and high ongoing personnel costs. Non-contact monitoring, on the other hand, suffers from low accuracy due to satellite remote sensing and susceptibility to weather conditions. Real-time monitoring using image acquisition devices installed outside the landslide body offers advantages such as low cost, high accuracy, and less susceptibility to weather conditions.

[0004] In existing related technologies, after the image acquisition device acquires relevant images (the landslide itself and the target set on the landslide), it needs to perform image recognition and processing to obtain the displacement changes of the target over a certain period of time, thereby determining the movement status of the landslide based on these displacement changes. However, since the landslide itself occupies a large portion of the entire image, and only the displacement changes of the target are needed to determine the movement status of the landslide, the recognition and processing of the landslide itself will consume a large amount of computing power during the image recognition and processing process. This will, to some extent, lead to a waste of computing power and result in low efficiency in the image recognition and processing process. Summary of the Invention

[0005] To address the technical problems in related technologies, this application provides a method and system for monitoring and early warning of geological disasters in the field environment.

[0006] To achieve the above objectives, the technical solution adopted in this application includes:

[0007] According to a first aspect of this application, a method for monitoring and early warning of geological hazards in the field environment is provided, specifically for landslide monitoring in the field environment, comprising the following steps:

[0008] Transmittance adjustment: acquire monitoring and verification images of the target area, identify color features in the acquired monitoring and verification images and determine the main ambient light at this time, and adjust the transmittance of the image acquisition device to filter out the main ambient light;

[0009] Image acquisition: Acquire initial and final monitoring images at preset intervals;

[0010] Image processing involves edge marking and feature point marking of the acquired image. Using the edge marking as a reference, the displacement changes of the feature point markings in the initial monitoring image and the final monitoring image are compared. The feature point markings are the position markings of the target.

[0011] Signal output: When the overlap rate of edge markers of the initial monitoring image and the final monitoring image is greater than or equal to the first threshold, if the displacement change in the image processing step is greater than or equal to the second threshold and less than or equal to the third threshold, a first warning signal is output; if the displacement change in the image processing step is greater than or equal to the third threshold, a second warning signal is output.

[0012] Optionally, in the transmittance adjustment step, identifying color features in the monitoring and verification image specifically includes:

[0013] Obtaining the dominant color of the monitoring and verification image using the RGB color space: This involves statistically analyzing the RGB values ​​of all pixels in the image, calculating the frequency of each color, and then determining the dominant color of the image based on the frequency of each color. Alternatively,

[0014] Obtain the dominant color of the monitoring and verification image using the HSV color space: Identify and label the color of each pixel individually, then iterate through all pixels, finding and labeling all pixels within a specific color range. Based on the outline list, determine the dominant color of the image; or...

[0015] The main colors of the monitoring and verification image are obtained through the HSL color space: The values ​​of the hue, saturation and luminance channels of the monitoring and verification image are analyzed respectively. For the hue channel, the main hue type in the monitoring and verification image is obtained. For the saturation channel, the extension with the highest saturation in the monitoring and verification image and its corresponding hue are obtained. For the luminance channel, the color with the highest luminance in the monitoring and verification image and its corresponding hue and saturation are obtained.

[0016] Optionally, in the image processing step, the edge marking specifically includes:

[0017] The acquired image is converted to grayscale and Gaussian filtered. The Canny edge detection method is used to find all edges in the image, and the findContours method is used to obtain closed contours.

[0018] Optionally, in the signal output step, the first threshold is 98%-100%.

[0019] Optionally, in the signal output step, when the overlap rate of edge markers of the initial monitoring image and the final monitoring image is less than a first threshold, the initial monitoring image and the final monitoring image are re-acquired at a preset interval.

[0020] According to a second aspect of this application, a geological disaster monitoring and early warning system for field environments is provided, comprising:

[0021] Image acquisition device, used to acquire monitoring images of the target area;

[0022] A transmittance adjustment device is used to adjust the transmittance of the image acquisition device;

[0023] The control unit is used to process the acquired images and output the first and second warning signals.

[0024] Optionally, the transmittance adjustment device includes:

[0025] The housing has a cavity inside and a light-transmitting port on the housing that communicates with the cavity. The image acquisition device is installed inside the cavity.

[0026] The system includes a switching structure and multiple light-transmitting sheets with different transmittances. The switching structure is installed within the accommodating cavity and located between the image acquisition device and the light-transmitting port. The switching structure includes a drive motor, a mounting frame, a rotating block, and multiple mounting rods. The rotating block is rotatably mounted on the mounting frame. The multiple mounting rods are spaced apart circumferentially along the rotating block, with one end of each rod pointing towards the rotation center of the rotating block. The other ends of the mounting rods are used to mount multiple light-transmitting sheets. The light-transmitting sheets are positioned between the light-transmitting port and the image acquisition device to adjust the transmittance of the image acquisition device.

[0027] Optionally, the light transmittance adjustment device further includes a partition plate disposed within the accommodating cavity to divide the accommodating cavity into a first cavity and a second cavity arranged in a vertical direction.

[0028] The image acquisition device is mounted on the partition plate and located in the first cavity, the control unit is mounted on the housing and / or the partition plate and located in the second cavity, the drive motor is mounted on the partition plate and located in the first cavity, and the drive motor and the image acquisition device are electrically connected to the control unit respectively.

[0029] According to a third aspect of this application, a computer-readable storage medium is also provided, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, it is capable of implementing the steps of the geological disaster monitoring and early warning method for the field environment as described in any of the technical solutions of the first aspect of this application.

[0030] According to a fourth aspect of this application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, is capable of implementing the steps of the geological disaster monitoring and early warning method for the field environment as described in any of the technical solutions of the first aspect of this application.

[0031] Beneficial effects:

[0032] 1. Through the above technical solution, firstly, before performing monitoring image recognition and processing, the transmittance is adjusted. In this way, the image acquired by the image acquisition device can filter out the main external ambient light (i.e., the color of the landslide itself or the vegetation on the landslide), which helps to save computing power in the image processing step and can improve the efficiency of image recognition and processing to a certain extent.

[0033] Second, in this embodiment, after adjusting the transmittance, the initial monitoring image and the final monitoring image of the target area are first obtained through the image acquisition step. Then, the edge markers and feature point markers of the image are obtained through the image processing step. With the edge markers as a reference, the displacement changes of the feature point markers are compared. In this way, the corresponding warning signal can be output to the outside through the signal output step.

[0034] Third, in this embodiment, the judgment of early warning information is only made after the overlap rate of edge markers in the initial monitoring image and the final monitoring image reaches a certain value. This ensures, on the one hand, the correlation and accuracy between the initial and final monitoring images by identifying the overlap rate, thus avoiding false alarms caused by image acquisition errors. On the other hand, dividing the displacement change into two segments, corresponding to the first and second early warning signals respectively, helps ensure the effectiveness and timeliness of the forecast.

[0035] 2. Other beneficial effects or advantages of this application will be described in detail in conjunction with specific structures in the specific embodiments. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In addition, it should be understood that the proportional relationship of each component in the drawings of this specification does not represent the proportional relationship in the actual material selection and design, but is only a schematic diagram of the structure or position, wherein:

[0037] Figure 1 This is a schematic diagram illustrating the steps of a geological disaster monitoring and early warning method for the field environment provided in an exemplary embodiment of this application;

[0038] Figure 2 This is a schematic diagram of the structure of a geological disaster monitoring and early warning system for the field environment provided in an exemplary embodiment of this application;

[0039] Figure 3 This is a three-dimensional structural schematic diagram of a transmittance adjustment device provided in an exemplary embodiment of this application, wherein the sidewalls of the housing are hidden to show the image acquisition device and control unit therein;

[0040] Figure 4 This is a three-dimensional structural schematic diagram of a transmittance adjustment device provided in an exemplary embodiment of this application, wherein the sidewalls of the housing are hidden to show the image acquisition device and control unit therein.

[0041] Explanation of the labels in the attached drawings:

[0042] 100-Geological disaster monitoring and early warning system for field environment; 101-Image acquisition device; 102-Light transmittance adjustment device; 103-Control unit; 1-Housing shell; 11-Accommodation cavity; 111-First cavity; 112-Second cavity; 12-Light transmission port; 2-Switching structure; 21-Drive motor; 22-Mounting bracket; 23-Rotating block; 24-Mounting rod; 25-Separating plate; 3-Light transmission sheet. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of this application, but not all embodiments.

[0044] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0045] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0046] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0047] To facilitate a clearer and more accurate understanding of the technical solution of this application by relevant technical personnel, the following provides a more detailed description of the existing related technologies.

[0048] In existing related technologies, when using contact-based monitoring methods, several reflective or luminous targets are generally set up on the landslide body to be monitored. Then, an image acquisition device is set up at a distance from the landslide body to collect images of the entire landslide body. The movement trend of the landslide body is judged based on the displacement changes of the targets over a certain period of time, so as to issue early warning information a certain period of time before the landslide occurs (or at the moment of occurrence), reminding nearby personnel to take the initiative to avoid or evacuate as soon as possible, so as to ensure the safety of life and property of relevant personnel.

[0049] Generally speaking, the color of a landslide body within a certain range is relatively uniform (generally, there are two situations regarding the color of a landslide body: one is that there is no vegetation on the landslide body, and the color it exhibits is the natural color of the landslide body, such as black or yellow; the other is that there is vegetation on the landslide body, and the color it exhibits is the color of the vegetation, which has different colors in different seasons, for example, it may be light green in spring and yellow in autumn). After the image acquisition device acquires relevant images (the landslide body itself and the targets set on the landslide body), it is necessary to perform image recognition and processing to obtain the displacement changes of the targets over a certain period of time, so that the movement trend of the landslide body can be determined based on the displacement changes.

[0050] However, since the landslide itself occupies a large part of the entire image, and its color may change with the seasons (because in the wild, the vegetation on the landslide may appear in different colors in different seasons, for example, light green in spring, dark green in summer, light yellow in autumn, and dark brownish-gray or white in winter), and only the displacement change of the target is needed to determine the movement of the landslide, the identification and processing of the landslide itself will consume a lot of computing power in the image recognition and processing process. This will cause a certain degree of waste of computing power and make the image recognition and processing process less efficient.

[0051] The following explains some of the related terms and technologies involved in the embodiments of this application.

[0052] 1) The RGB color space is a commonly used method for representing color images. It uses different combinations of three color channels—red (R), green (G), and blue (B)—to represent various colors.

[0053] 2) The HSV color space is a commonly used method for representing color images. It uses different combinations of three color channels—hue (H), saturation (S), and brightness (V)—to represent various colors.

[0054] 3) HSL color space is a commonly used method for representing color images. It uses different combinations of three color channels—hue (H), saturation (S), and brightness (L)—to represent various colors.

[0055] 4) The Canny edge detection method is a method that uses a multi-level edge detection algorithm to detect edges.

[0056] 5) The findContours method is a method for finding contours in digital images.

[0057] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0058] Example 1

[0059] like Figure 1 As shown, a geological disaster monitoring and early warning method for the field environment, specifically for landslide monitoring in the field, includes the following steps:

[0060] Transmittance adjustment: acquire monitoring and verification images of the target area, identify color features in the acquired monitoring and verification images and determine the main ambient light at this time, and adjust the transmittance of the image acquisition device to filter out the main ambient light;

[0061] Image acquisition: Acquire initial and final monitoring images at preset intervals;

[0062] Image processing involves edge marking and feature point marking of the acquired image. Using the edge marking as a reference, the displacement changes of the feature point markings in the initial monitoring image and the final monitoring image are compared. The feature point markings are the position markings of the target.

[0063] Signal output: When the overlap rate of edge markers of the initial monitoring image and the final monitoring image is greater than or equal to the first threshold, if the displacement change in the image processing step is greater than or equal to the second threshold and less than or equal to the third threshold, a first warning signal is output; if the displacement change in the image processing step is greater than or equal to the third threshold, a second warning signal is output.

[0064] The above technical solution achieves the following: First, before monitoring image recognition and processing, the transmittance is adjusted. This allows the image acquired by the image acquisition device to filter out the main external ambient light (i.e., the color of the landslide itself or the vegetation on the landslide), which helps save computing power in the image processing step and can improve the efficiency of image recognition and processing to a certain extent.

[0065] Second, in this embodiment, after adjusting the transmittance, the initial monitoring image and the final monitoring image of the target area are first obtained through the image acquisition step. Then, the edge markers and feature point markers of the image are obtained through the image processing step. With the edge markers as a reference, the displacement changes of the feature point markers are compared. In this way, the corresponding warning signal can be output to the outside through the signal output step.

[0066] Third, in this embodiment, the judgment of early warning information is only made after the overlap rate of edge markers in the initial monitoring image and the final monitoring image reaches a certain value. This ensures, on the one hand, the correlation and accuracy between the initial and final monitoring images by identifying the overlap rate, thus avoiding false alarms caused by image acquisition errors. On the other hand, dividing the displacement change into two segments, corresponding to the first and second early warning signals respectively, helps ensure the effectiveness and timeliness of the forecast.

[0067] It is understood that, in this embodiment, the start time of transmittance adjustment can be adjusted according to actual conditions and needs. For example, in one embodiment, transmittance adjustment can be started at a set time (based on seasonal time or by setting a specific start time). In another embodiment, transmittance adjustment can be started cyclically, that is, after a certain number of monitoring operations (e.g., after acquiring several final monitoring images), a transmittance adjustment step is initiated. This application does not impose specific limitations on this.

[0068] Furthermore, in this embodiment, the specific values ​​of the first threshold, the second threshold, and the third threshold can be selected according to actual needs, and this application does not impose specific limitations on them.

[0069] In the transmittance adjustment step of this application, identifying color features in the monitoring and verification image can be implemented in various ways. For example, in one embodiment of this application, the main color of the monitoring and verification image can be obtained through the RGB color space: by statistically analyzing the RGB values ​​of all pixels in the monitoring and verification image, and then calculating the frequency of each color appearing in the image, the main color of the monitoring and verification image is obtained based on the frequency of each color. In this way, the color exhibited by the landslide body can be accurately obtained, making it easier to filter it out, thereby saving computing power and improving the efficiency of image recognition and processing.

[0070] In another embodiment of this application, the main color of the monitoring and verification image can also be obtained through the HSV color space. Specifically, the color of each pixel is first determined and identified, then all pixels are traversed to find and identify all pixels within a specific color range, and the main color of the image is determined based on the contour list.

[0071] Taking a specific implementation as an example, firstly, each pixel is checked to see if it falls within a certain range and then identified. In the HSV color space, hue (H) can basically determine a certain color, and then combined with saturation (S) and brightness (V) information, it is determined to be greater than a certain threshold. For each pixel, its HSV value needs to be checked to determine whether it belongs to the range of a specific color. In this step, some conditional statements (such as if-else statements) may be used for judgment and identification. All pixels can be traversed to find all pixels within the specific color range and identify them. Specifically, functions in the OpenCV library can be used, such as "cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)", which can find contours in a binary image and return a list of contours. Based on the list of contours, the range of each color region can be found, thereby determining the main color in the image. Specifically, the range of each color region in the image can be determined by the position, size, and other information of the contours, thereby deriving the main color in the image.

[0072] In another embodiment of this application, the main colors of the monitoring and verification image can also be obtained through the HSL color space. First, the values ​​of the hue, saturation, and luminance channels of the monitoring and verification image are analyzed. Specifically, for the hue channel, the main hue type in the monitoring and verification image is obtained; for the saturation channel, the extension with the highest saturation in the monitoring and verification image and its corresponding hue are obtained; and for the luminance channel, the color with the highest luminance in the monitoring and verification image and its corresponding hue and saturation are obtained.

[0073] Taking a specific implementation as an example, the method for identifying the main colors in an image using the HSL color space is as follows:

[0074] In the obtained HSL color space, the values ​​of the three channels, hue (H), saturation (S), and brightness (L), are analyzed.

[0075] a. Analyze the values ​​of the H channel to identify the main color tone types in the image (such as red, blue, green, etc.).

[0076] b. Analyze the values ​​of the S saturation channel to find the color with the highest saturation in the image and its corresponding hue.

[0077] c. Analyze the values ​​of the L channel to find the color with the highest brightness in the image, as well as its corresponding hue and saturation.

[0078] Based on the analysis results, the main colors in the image are extracted.

[0079] a. Sort the values ​​of the H channel of the hue and find the hue type that appears most frequently.

[0080] b. Sort the values ​​of the S saturation channel to find the color with the highest saturation and its corresponding hue.

[0081] c. Sort the values ​​of the L channel for brightness and find the color with the highest brightness, as well as its corresponding hue and saturation.

[0082] After extracting the primary colors, they are categorized and labeled. Different colors can be categorized and labeled as needed, such as red, green, blue, etc.

[0083] In one embodiment of this application, the edge marking in the image processing step specifically includes: converting the acquired image into a grayscale image and performing Gaussian filtering, using the Canny edge detection method to find all edges in the image, and using the findContours method to obtain closed contours.

[0084] Converting the acquired image to grayscale reduces the number of channels. Applying Gaussian filtering to the grayscale image smooths the image, reduces noise, and helps prevent the Canny edge detection method from misinterpreting noise as edges, thus improving edge detection accuracy. Simultaneously, the findContours method can be used to obtain closed contours.

[0085] In one embodiment of this application, the first threshold in the signal output step can be 98%-100%. In this application, the first threshold is used as a prerequisite judgment condition to ensure that the initial monitoring image and the final monitoring image, which serve as the basis for the early warning information, are highly correlated, thereby ensuring the accuracy and effectiveness of the early warning information. Accuracy refers to the degree of accuracy of the judgment result, and effectiveness refers to the degree to which the judgment result conforms to the actual situation.

[0086] Taking a specific practical example, during the time period of acquiring the initial monitoring image and the final monitoring image, the edge markers in the image may change to a certain extent due to human activities (such as felling trees, planting trees, etc.), landslide movement (landslide sliding), or the image acquisition device being blocked or moved. In this way, the introduced first threshold can effectively determine whether the acquired initial monitoring image and the final monitoring image can be used for landslide early warning, which is conducive to ensuring the accuracy of the early warning information.

[0087] Taking another specific practical example, if the initial monitoring image and the final monitoring image are the same image due to an error in the image acquisition device during the time period of acquiring the initial monitoring image and the final monitoring image, then although the warning result is that the landslide body has not moved (in reality, it may or may not have moved), the warning result may not be consistent with the actual situation.

[0088] In one embodiment of this application, during the signal output step, when the overlap rate of edge markers between the initial monitoring image and the final monitoring image is less than a first threshold, the initial monitoring image and the final monitoring image are reacquired at a preset interval. Thus, when the overlap rate of edge markers between the initial monitoring image and the final monitoring image is identified as less than a certain value, the image can be reacquired to ensure the accuracy and effectiveness of the early warning judgment result.

[0089] like Figures 2 to 4As shown, according to a second aspect of this application, a geological disaster monitoring and early warning system 100 for use in the field environment is also provided. The system includes an image acquisition device 101, a transmittance adjustment device 102, and a control unit 103. The image acquisition device 101 is used to acquire monitoring images of a target area; the transmittance adjustment device 102 is used to adjust the transmittance of the image acquisition device 101; and the control unit 103 is used to process the acquired images and output a first early warning signal and a second early warning signal.

[0090] The geological disaster monitoring and early warning system 100 for field environments described in this application can improve the efficiency of image recognition and processing while effectively reducing computing power consumption, thereby improving the timeliness of early warning.

[0091] In one embodiment of this application, such as Figure 3 and Figure 4 As shown, the transmittance adjustment device 102 of this application may include a housing 1, a switching structure 2, and multiple light-transmitting sheets 3 with different transmittances. A receiving cavity 11 is formed inside the housing 1, and a light-transmitting port 12 communicating with the receiving cavity 11 is formed on the housing 1. The image acquisition device 101 is installed inside the receiving cavity 11. The switching structure 2 is installed inside the receiving cavity 11 and located between the image acquisition device 101 and the light-transmitting port 12. The switching structure 2 includes a drive motor 21, a mounting frame 22, a rotating block 23, and multiple mounting rods 24. The rotating block 23 is rotatably mounted on the mounting frame 22. The multiple mounting rods 24 are spaced apart circumferentially along the rotating block 23, and one end of each mounting rod 24 points towards the rotation center of the rotating block 23. The other ends of the mounting rods 24 are used to install multiple light-transmitting sheets 3. The light-transmitting sheets 3 are positioned between the light-transmitting port 12 and the image acquisition device 101 to adjust the transmittance of the image acquisition device 101.

[0092] In this way, during the light transmittance adjustment process, the rotating block 23 can be driven to rotate by the drive motor 21, so that the light transmittance of the light-transmitting sheet 3 installed on different mounting rods 24 can be moved between the light-transmitting port 12 and the image acquisition device 101 to achieve the filtering effect of different main external ambient light.

[0093] In one embodiment of this application, such as Figure 3 and Figure 4As shown, the transmittance adjustment device 102 of this application may further include a partition plate 25, which is disposed in the accommodating cavity 11 to divide the accommodating cavity 11 into a first cavity 111 and a second cavity 112 arranged in the vertical direction; the image acquisition device 101 is mounted on the partition plate 25 and located in the first cavity 111; the control unit 103 is mounted on the housing 1 and / or the partition plate 25 and located in the second cavity 112; the drive motor 21 is mounted on the partition plate 25 and located in the first cavity 111; and the drive motor 21 and the image acquisition device 101 are electrically connected to the control unit 103 respectively.

[0094] In this way, on the one hand, the partition plate 25 can serve as a mounting structure for the image acquisition device 101 and the control unit 103, making it convenient to install the image acquisition device 101 and the control unit 103 onto the partition plate 25 before installing them into the housing 1. This not only improves the ease of installation of the relevant structures but also facilitates the disassembly, assembly, and maintenance of the relevant equipment or structures. On the other hand, the partition plate 25 can separate the image acquisition device 101, the switching structure 2, and the control unit 103 from each other, thereby improving the operational stability of the relevant equipment and structures and reducing mutual interference between multiple devices and structures during operation.

[0095] This application embodiment can divide the geological disaster monitoring and early warning system for field environments into functional modules or functional units according to the above method examples. For example, each function can be divided into its own functional modules or functional units, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or as software functional modules or functional units. The module or unit division in this application embodiment is illustrative and represents only one logical functional division; other division methods may be used in actual implementation.

[0096] According to a third aspect of this application, a computer-readable storage medium is also provided, on which a computer program is stored, characterized in that, when executed by a processor, the computer program is capable of implementing the steps of the geological disaster monitoring and early warning method for the field environment as described in any of the technical solutions of the first aspect of this application.

[0097] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires; portable computer disks; hard disks; random access memory (RAM); read-only memory (ROM); erasable programmable read-only memory (EPROM); registers; hard disks; optical fibers; portable compact disc read-only memory (CD-ROM); optical storage devices; magnetic storage devices; or any suitable combination thereof; or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0098] According to a fourth aspect of this application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it is able to implement the steps of the geological disaster monitoring and early warning method for the field environment as described in any of the technical solutions of the first aspect of this application.

[0099] The processor described above can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0100] In the embodiments provided in this application, it should be understood that the disclosed systems, modules, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0101] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0103] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring and early warning of geological hazards in the field environment, specifically for monitoring landslides in the field environment, characterized in that... Includes the following steps: Transmittance adjustment: acquire monitoring and verification images of the target area, identify color features in the acquired monitoring and verification images and determine the main ambient light at this time, and adjust the transmittance of the image acquisition device to filter out the main ambient light; Image acquisition: Acquire initial and final monitoring images at preset intervals; Image processing involves edge marking and feature point marking of the acquired image. Using the edge marking as a reference, the displacement changes of the feature point markings in the initial monitoring image and the final monitoring image are compared. The feature point markings are the position markings of the target. Signal output: When the overlap rate of edge markers of the initial monitoring image and the final monitoring image is greater than or equal to the first threshold, if the displacement change in the image processing step is greater than or equal to the second threshold and less than or equal to the third threshold, a first warning signal is output; if the displacement change in the image processing step is greater than or equal to the third threshold, a second warning signal is output.

2. The geological disaster monitoring and early warning method for the field environment according to claim 1, characterized in that, In the transmittance adjustment step, identifying color features in the monitoring and verification image specifically includes: Obtaining the dominant color of the monitoring and verification image using the RGB color space: This involves statistically analyzing the RGB values ​​of all pixels in the image, calculating the frequency of each color, and then determining the dominant color of the image based on the frequency of each color. Alternatively, Obtain the dominant color of the monitoring and verification image using the HSV color space: Identify and label the color of each pixel individually, then iterate through all pixels, finding and labeling all pixels within a specific color range. Based on the outline list, determine the dominant color of the image; or... The main colors of the monitoring and verification image are obtained through the HSL color space: The values ​​of the hue, saturation and luminance channels of the monitoring and verification image are analyzed respectively. For the hue channel, the main hue type in the monitoring and verification image is obtained. For the saturation channel, the extension with the highest saturation in the monitoring and verification image and its corresponding hue are obtained. For the luminance channel, the color with the highest luminance in the monitoring and verification image and its corresponding hue and saturation are obtained.

3. The geological disaster monitoring and early warning method for the field environment according to claim 1, characterized in that, In the image processing step, the edge marking specifically includes: The acquired image is converted to grayscale and Gaussian filtered. The Canny edge detection method is used to find all edges in the image, and the findContours method is used to obtain closed contours.

4. The geological disaster monitoring and early warning method for the field environment according to claim 1, characterized in that, In the signal output step, the first threshold is 98%-100%.

5. The geological disaster monitoring and early warning method for the field environment according to claim 1, characterized in that, In the signal output step, when the overlap rate of edge markers between the initial monitoring image and the final monitoring image is less than a first threshold, the initial monitoring image and the final monitoring image are re-acquired at a preset interval.

6. A geological disaster monitoring and early warning system for use in the field environment, characterized in that, include: Image acquisition device (101) is used to acquire monitoring images of the target area; A transmittance adjustment device (102) is used to adjust the transmittance of the image acquisition device (101); The control unit (103) is used to process the acquired images and output the first warning signal and the second warning signal.

7. The geological disaster monitoring and early warning system for field environments according to claim 6, characterized in that, The transmittance adjustment device (102) includes: A housing (1) has a cavity (11) formed inside it, and a light-transmitting port (12) is formed on the housing (1) that communicates with the cavity (11). The image acquisition device (101) is installed inside the cavity (11). The switching structure (2) and multiple light-transmitting sheets (3) with different transmittance are provided. The switching structure (2) is installed in the accommodating cavity (11) and located between the image acquisition device (101) and the light-transmitting port (12). The switching structure (2) includes a drive motor (21), a mounting frame (22), a rotating block (23) and multiple mounting rods (24). The rotating block (23) is rotatably mounted on the mounting frame (22). The multiple mounting rods (24) are arranged at intervals along the circumference of the rotating block (23), and one end of each mounting rod (24) points to the rotation center of the rotating block (23). The other end of each mounting rod (24) is used to install multiple light-transmitting sheets (3). The light-transmitting sheets (3) are arranged between the light-transmitting port (12) and the image acquisition device (101) to adjust the transmittance of the image acquisition device (101).

8. The geological disaster monitoring and early warning system for field environments according to claim 7, characterized in that, The light transmittance adjustment device (102) further includes a partition plate (25), which is disposed in the accommodating cavity (11) to divide the accommodating cavity (11) into a first cavity (111) and a second cavity (112) arranged in the vertical direction. The image acquisition device (101) is mounted on the partition plate (25) and located in the first cavity (111). The control unit (103) is mounted on the housing (1) and / or the partition plate (25) and located in the second cavity (112). The drive motor (21) is mounted on the partition plate (25) and located in the first cavity (111). The drive motor (21) and the image acquisition device (101) are electrically connected to the control unit (103).

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it can implement the steps of the geological disaster monitoring and early warning method for the field environment as described in any one of claims 1-8.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it can implement the steps of the geological disaster monitoring and early warning method for the field environment as described in any one of claims 1-8.

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