Intelligent design method and T-shaped wave-resistant retaining wall

Abstract

The invention provides an intelligent design method and a T-shaped wave-resistant retaining wall. The method comprises the steps that a footpath area located on the periphery of a riverway is determined, and all installation point positions corresponding to all T-shaped wave-resistant retaining walls are determined in the footpath area; wave height acquisition graphs corresponding to the installation point positions are obtained based on different acquisition moments, and the retaining wall heights of the T-shaped wave-resistant retaining walls corresponding to the installation point positions are determined based on the wave height acquisition graphs; based on the irradiation areas corresponding to the street lamps located in the footpath area, the containing attributes corresponding to the containing groove positions of the T-shaped wave-resistant retaining walls are determined, and the containing attributes comprise the green plant attribute and the lamp attribute. The practicability of the T-shaped wave-resistant retaining wall is at least improved.

Description

Technical Field

[0001] This invention relates to data processing technology, and more particularly to an intelligent design method and a T-shaped wave-breaking retaining wall. Background Technology

[0002] In the field of water conservancy engineering and river management, wave-breaking walls, as core facilities for resisting water flow impact and protecting shoreline stability, have expanded their application scenarios from traditional flood control projects to urban waterfront space construction. Currently, the technological development of wave-breaking walls mainly focuses on optimizing structural forms and improving the impact resistance of materials. Flood control reliability is enhanced through methods such as improving the cross-sectional shape of the walls and using high-strength composite materials. However, the overall design still centers on a single flood control function, lacking comprehensive consideration of the diverse needs in actual application scenarios. This results in significant shortcomings in adapting to the surrounding environment and meeting user experience requirements.

[0003] Existing patent documents, including application number CN202210876543.2 ("A Method for Installing and Positioning a Riverbed Wave-Blocking Wall") and application number CN202122345678.9 ("A Riverbed Retaining Wall with Adjustable Height"), focus on determining the installation position of the retaining wall through engineering parameters such as terrain and water flow. The latter focuses on the mechanical adjustment structure design of the retaining wall's height. Both patents optimize the technology around the core flood control function of the retaining wall. However, existing technologies generally suffer from insufficient adaptability to different scenarios. The design process fails to fully consider the special characteristics of waterfront public spaces such as walkways, neglecting the activity habits, usage needs, and synergy with the surrounding environment of users in the walkway area. This results in the retaining wall failing to deeply integrate with the walkway scene after installation, thus failing to achieve a dual improvement in functionality and experience.

[0004] The core technical problem that existing technologies have failed to solve is: how to combine the user behavior characteristics of the trail area with the surrounding environmental conditions to achieve precise selection of the installation points of the wave-breaking retaining wall next to the trail, so that the retaining wall can not only meet the flood protection needs, but also adapt to the actual usage habits of users, thereby improving the practicality and user experience of the wave-breaking retaining wall. Summary of the Invention

[0005] Based on the above problems, the present invention is proposed to provide an intelligent design method and a T-shaped wave-breaking barrier wall that overcomes or at least partially solves the above problems.

[0006] According to one aspect of the present invention, a smart design method is provided, comprising the following steps: Identify the walkway area around the river and determine the installation points for each T-shaped wave-breaking barrier within the walkway area; Based on different acquisition times, wave height acquisition maps corresponding to each installation point are obtained, and based on each wave height acquisition map, the height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined. Based on the illumination area corresponding to each street light in the walkway area, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking barrier is determined, wherein the containment attribute includes green plant attribute and lighting attribute.

[0007] Optionally, in the method according to the invention, determining the walkway area located around the river channel, and determining the installation points corresponding to each T-shaped wave-breaking wall within the walkway area, includes: If the current time is the same as the first preset collection time, control the collection drone to collect images of the river channel, and perform image recognition on the first collected image to obtain the walkway area located in the first collected image; Obtain the length of the walkway area in the direction of its extension along the river channel, and divide the length of the walkway area by the reference length of the corresponding T-shaped wave-breaking wall. The largest integer in the calculation result is determined as the number of points in the corresponding walkway area. The trail area is divided into points based on the number of points along the extension direction of the river, resulting in points for each area. Based on the data collection drone, monitoring tasks are established for each monitoring period corresponding to each regional location, and regional attributes corresponding to each regional location are determined based on the monitoring tasks. The regional attributes include suitable attributes and unsuitable attributes. The locations of each area with the appropriate regional attribute are determined as the corresponding installation locations for each T-shaped wave-breaking retaining wall.

[0008] Optionally, in the method according to the present invention, establishing monitoring tasks based on the data acquisition drone and corresponding monitoring time periods for each area location includes: Obtain the first pixel value corresponding to each image pixel point that makes up the first acquired image, and compare each first pixel value with a preset shadow pixel range; Each image pixel corresponding to each first pixel value that is located in the preset shadow pixel range is determined as a shadow pixel. Based on the first acquired image, each baseline line segment is generated with the midpoint of each area as the midpoint of the line segment and the length of the line segment as the baseline length along the extension direction of the river. If each reference point corresponding to the same baseline segment has a point overlap relationship with different shadow pixels, the first time period corresponding to the daytime sunshine attribute is determined as the monitoring time period of the area point corresponding to the baseline segment. Conversely, the second time period corresponding to dim evening sunlight is determined as the monitoring time period for the area points corresponding to the baseline segment, and the data acquisition drone is controlled to perform each monitoring task for each area point based on the monitoring time period corresponding to each area point, according to the preset monitoring time.

[0009] Optionally, in the method according to the present invention, based on the monitoring task, the regional attributes corresponding to each regional location are determined, wherein the regional attributes include suitable attributes and unsuitable attributes, including: Based on the monitoring task, it is determined that any location in any area has human elements at any monitoring time. The monitoring time of the location is determined as the starting time, and the starting monitoring image corresponding to the starting time is obtained. Determine the termination time with a preset interval after the start time, and acquire the termination monitoring image at the corresponding termination time; The starting monitoring image and the ending monitoring image are compared. If the comparison result shows that the ending monitoring image includes all human elements located in the starting monitoring image, the dwell attribute corresponding to the starting time is determined as a valid dwell time. Based on the preset monitoring time, determine the number of times at each start time of each valid stay for each location in each area. If the number of times is greater than the preset number, the regional attribute corresponding to the regional point will be determined as the appropriate attribute; Conversely, the regional attributes corresponding to the aforementioned regional points are determined as unsuitable attributes.

[0010] Optionally, in the method according to the present invention, acquiring wave height acquisition maps corresponding to each installation point based on different acquisition times, and determining the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on each wave height acquisition map, includes: The number of samples is obtained by directly dividing the preset interval time by the retrieved preset collection interval. Based on each monitoring task corresponding to each installation point, the start time of each valid stay attribute is determined as the collection time of each installation point. Each monitoring task acquires additional time points corresponding to the number of data points at preset intervals after each data acquisition time. Based on the acquisition unit, wave height acquisition images of each installation point at each acquisition time and each additional time are obtained, and wave height acquisition images of the same installation point are sequentially superimposed on each retrieved transparent fusion layer to obtain each acquisition fusion layer. The height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the collected and fused layers.

[0011] Optionally, in the method according to the present invention, determining the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on each acquired and fused layer includes: Retrieve a reference image with the reference height and reference length corresponding to the T-shaped wave-breaking barrier, and determine the downward contour line segment that makes up the image contour of the reference image; Determine the midpoint of the corresponding downlink contour line segment, and overlay the reference image onto each acquisition and fusion layer by overlapping the midpoint of the line segment with each installation point based on each acquisition and fusion layer; Based on the left and right contour segments of the image contour that make up the reference image, the images of each acquisition and fusion layer are cropped respectively, and the reference images are blurred based on each acquisition and fusion layer to obtain each current fusion layer with the horizontal length of the corresponding layer being the reference length. Each current fused layer is binarized to obtain a binarized image, wherein the binarized image includes wave pixels corresponding to the first pixel value and / or noise pixels corresponding to the second pixel value; The binarized image is pixel-wise identified, and the height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the identification results.

[0012] Optionally, in the method according to the present invention, pixel recognition is performed on the binarized image, and the height of each T-shaped wave-breaking barrier corresponding to each installation point is determined based on the recognition result, including: Pixel recognition is performed on the binarized image to obtain the individual image pixels that make up the binarized image; If each image pixel corresponding to the same binarized image includes at least one image pixel corresponding to the first pixel value, then the at least one image pixel is determined as each target pixel. The image coordinate system established with the image center point of the corresponding binarized image as the origin determines the pixel coordinates of each target pixel, and the target pixel is compared based on the vertical coordinate. The target pixel with the maximum vertical coordinate is determined as the limit coordinate point. The vertical distance between the extreme coordinate point and the downward contour line segment determined based on the acquisition and fusion layer corresponding to the binarized image is summed with the retrieved preset growth height to obtain the retaining wall height of the T-shaped wave-breaking retaining wall corresponding to the installation point of the acquisition and fusion layer. If the image pixels corresponding to the same binarized image do not include any image pixel corresponding to the first pixel value, the reference height is determined as the height of the T-shaped wave-breaking barrier wall corresponding to the installation point of the acquisition and fusion layer corresponding to the binarized image.

[0013] Optionally, in the method according to the invention, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking wall is determined based on each illumination area corresponding to each street light located in the walkway area, wherein the containment attribute includes vegetation attributes and lighting attributes, including: Based on the fact that the current time is the same as the second preset acquisition time, the acquisition drone is controlled to acquire images of the river channel to obtain the second acquired image; Acquire the second pixel value corresponding to each image pixel point that makes up the second acquired image, and compare each second pixel value with the preset illumination pixel range; Each image pixel corresponding to each second pixel value that is located in the preset illumination pixel range is determined as each illumination pixel, and each illumination pixel is connected to obtain each illumination area. Based on each irradiation area, the corresponding containment attributes for each containment slot of each T-shaped wave-breaking wall are determined, wherein the containment attributes include plant attributes and lighting attributes.

[0014] Optionally, in the method according to the invention, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking wall is determined based on each irradiation area, wherein the containment attribute includes vegetation attributes and lighting attributes, including: Based on the second acquired image, each installation line segment is generated with the installation point as the midpoint of the line segment and the length of the line segment as the reference length along the extension direction of the river. If each point on the same installation line segment has a point overlap relationship with different light illumination pixels, the accommodation attribute of the T-shaped wave-breaking retaining wall corresponding to the installation point of the installation line segment is determined as the green plant attribute. If any line segment point corresponding to the same installation line segment has a point position that does not have a point position overlap with any lamp illumination pixel point, the accommodating attribute of the accommodating slot of the T-shaped wave-breaking barrier corresponding to the installation point of the installation line segment is determined as the lamp attribute, and the barrier height corresponding to the T-shaped wave-breaking barrier is summed with the retrieved preset lamp height to obtain the updated barrier height.

[0015] According to another aspect of the present invention, a T-shaped wave-breaking barrier is provided, comprising a T-shaped bench, wherein the T-shaped bench includes a T-shaped base and a rectangular barrier wall disposed on the T-shaped base, the rectangular barrier wall being provided with a receiving slot.

[0016] According to the present invention, the server can first accurately determine the walkway area around the river and, combined with visitor lingering habits and sunlight conditions, select the installation locations of the T-shaped wave-breaking walls. This effectively avoids sparsely populated areas, prevents resource waste, and significantly improves the utilization rate and user adaptability of the T-shaped wave-breaking walls. Furthermore, in the wall height design stage, the server integrates wave height data collected at different times to ensure that the determined wall heights of each T-shaped wave-breaking wall corresponding to each installation location guarantee the core performance of the T-shaped wave-breaking walls in resisting water flow impact, while also preventing [further issues]. The high degree of design redundancy leads to additional consumption of materials and construction costs. At the same time, the server determines the slot attributes of the T-shaped wave-breaking barrier based on the illumination area of ​​the pedestrian street lights. When the T-shaped wave-breaking barrier is in a well-lit area, the slot attribute is greenery, which can be configured with greenery to optimize the landscape and ecological environment. When the T-shaped wave-breaking barrier is in a light-blind area, the slot attribute is lighting, which can be configured with lighting to fill the lighting gap. Ultimately, the wave-breaking, landscaping, and lighting functions of the barrier are integrated, significantly enhancing the safety and user experience of the T-shaped wave-breaking barrier. Attached Figure Description

[0017] Figure 1 A flowchart of an intelligent design method according to an embodiment of the present invention is shown; Figure 2 A schematic diagram of the current blended layer according to an embodiment of the present invention is shown; Figure 3 A schematic diagram of the perpendicular distance according to an embodiment of the present invention is shown; Figure 4 A schematic diagram of the structure of a T-shaped wave-breaking barrier wall according to another embodiment of the present invention is shown. Detailed Implementation

[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0019] To address the problems existing in the aforementioned background art, the inventors have proposed the solution of this invention. One embodiment of this invention provides an intelligent design method that can be executed in a computing device.

[0020] Figure 1 A flowchart of an intelligent design method according to an embodiment of the present invention is shown, the method being adapted to be executed in a computing device.

[0021] like Figure 1 As shown, the intelligent design method proposed in this embodiment begins with step S102, which includes the following: Identify the walkway area around the river and determine the installation points for each T-shaped wave-breaking barrier within the walkway area.

[0022] For example, since tourists mostly choose to walk or rest in the walkway area along the river, the T-shaped wave-breaking wall should ideally be installed in the walkway area around the river. Therefore, the server will first determine the walkway area around the river. Since the walkway area is usually quite large, in order to facilitate the practicality of the T-shaped wave-breaking walls to be installed later, the server will further determine the most suitable installation points for each T-shaped wave-breaking wall in the walkway area.

[0023] Furthermore, the aforementioned "determining the walkway area around the river and identifying the installation points for each T-shaped wave-breaking wall within the walkway area" also includes the following steps: If the current time is the same as the first preset collection time, control the collection drone to collect images of the river channel, and perform image recognition on the first collected image to obtain the walkway area located in the first collected image; Obtain the length of the walkway area in the direction of its extension along the river channel, and divide the length of the walkway area by the reference length of the corresponding T-shaped wave-breaking wall. The largest integer in the calculation result is determined as the number of points in the corresponding walkway area. The trail area is divided into points based on the number of points along the extension direction of the river, resulting in points for each area. Based on the data collection drone, monitoring tasks are established for each monitoring period corresponding to each regional location, and regional attributes corresponding to each regional location are determined based on the monitoring tasks. The regional attributes include suitable attributes and unsuitable attributes. The locations of each area with the appropriate regional attribute are determined as the corresponding installation locations for each T-shaped wave-breaking retaining wall.

[0024] For example, in this embodiment, when the current time is the same as the first preset acquisition time, the server will control the acquisition drone to acquire images of the river channel, thereby obtaining the first acquired image. For example, the first preset acquisition time can be 10:00 AM, when the light is relatively sufficient, which can facilitate clearer image recognition of the obtained first acquired image later. Then, the server will perform image recognition on the first captured image to obtain the trail area located in the first captured image; Next, the server will obtain the length of the walkway area in the direction of the river's extension, and then divide the area length by the reference length of the corresponding T-shaped wave-breaking wall. The largest integer in the calculation result will be determined as the number of points in the corresponding walkway area. For example, if the area length is 30 and the reference length is 4, then the number of points is 7. Next, the server will divide the trail area into points according to the number of points along the extension direction of the river, thus obtaining points in each area with equal spacing. In order to more accurately determine which areas are more suitable for installing T-shaped wave-breaking walls, the server will create monitoring tasks for each area and time period based on the data collection drones, and then determine the area attributes corresponding to each area and time period based on the monitoring tasks. The area attributes include suitable attributes and unsuitable attributes. Finally, the server will determine the locations of each area with suitable regional attributes as the corresponding installation points for each T-shaped wave-breaking retaining wall, thereby improving the scientific nature and safety of the retaining wall installation.

[0025] Furthermore, the aforementioned "establishment of monitoring tasks corresponding to monitoring periods for each area location based on data collection drones" also includes the following steps: Obtain the first pixel value corresponding to each image pixel point that makes up the first acquired image, and compare each first pixel value with a preset shadow pixel range; Each image pixel corresponding to each first pixel value that is located in the preset shadow pixel range is determined as a shadow pixel. Based on the first acquired image, each baseline line segment is generated with the midpoint of each area as the midpoint of the line segment and the length of the line segment as the baseline length along the extension direction of the river. If each reference point corresponding to the same baseline segment has a point overlap relationship with different shadow pixels, the first time period corresponding to the daytime sunshine attribute is determined as the monitoring time period of the area point corresponding to the baseline segment. Conversely, the second time period corresponding to dim evening sunlight is determined as the monitoring time period for the area points corresponding to the baseline segment, and the data acquisition drone is controlled to perform each monitoring task for each area point based on the monitoring time period corresponding to each area point, according to the preset monitoring time.

[0026] For example, in this embodiment, it should be noted that tourists usually prefer to rest in the shade during the day when there is plenty of sunlight. Therefore, the server will determine the installation points of the corresponding T-shaped wave-breaking barrier based on this behavioral characteristic so that they can better meet the actual usage needs. First, the server obtains the first pixel value corresponding to each image pixel that makes up the first captured image, and then compares each first pixel value with a preset shadow pixel range. Each pixel value located in the preset shadow pixel range can be understood as the pixel value corresponding to the area without direct sunlight during the day. Therefore, the server will determine each image pixel corresponding to each first pixel value that is located in the preset shadow pixel range as each shadow pixel. That is, each shadow pixel cannot be directly illuminated but is occluded to a certain extent, such as being occluded by large trees or other green plants. Next, the server will use the points in each area as the midpoints of the line segments in the first acquired image to generate baseline line segments with the same length as the baseline length along the extension direction of the river. By generating baseline line segments, the actual coverage area of ​​the T-shaped wave-breaking barrier wall installed at the points in that area can be accurately predicted, providing accurate spatial basis for subsequent judgment. If each reference point corresponding to the same baseline segment has a point overlap relationship with different shadow pixels, it indicates that the T-shaped wave-breaking wall installed at that point may be in a shady place. Therefore, during the day, that point may become an area where tourists are willing to stay. Thus, the server will determine the first time period corresponding to the daytime sunshine attribute (i.e., 9:00 to 11:00 AM or 2:00 to 4:00 PM) as the monitoring time period for the area points corresponding to that baseline segment. During this time period, the lighting is sufficient and the comfort level is high, which can ensure the clarity of the images collected by the drone and accurately capture the behavior of tourists staying in that area. If the reference points corresponding to the same baseline segment do not have a point overlap relationship with different shadow pixels, it means that after installing the T-shaped breakwater wall in that area, the T-shaped breakwater wall may not be completely shaded. Therefore, tourists may be less willing to stay in that area during the day. So, the server will determine the second time period (i.e., 7 pm to 9 pm) with the corresponding dim evening sunlight attribute as the monitoring time period for the area points corresponding to the baseline segment, so as to avoid missing the area points suitable for installing T-shaped breakwater walls. Finally, the server will control the data collection drone to perform various monitoring tasks based on the preset monitoring time according to the monitoring time period corresponding to each area location. This not only reduces the energy consumption and operating cost of the data collection drone, but also ensures that the final determined installation location meets both flood control requirements and the actual usage habits of tourists by accurately matching monitoring needs and time period characteristics.

[0027] Furthermore, the aforementioned "determining the regional attributes corresponding to each regional location based on the monitoring task, wherein the regional attributes include suitable attributes and unsuitable attributes" also includes the following steps: Based on the monitoring task, it is determined that any location in any area has human elements at any monitoring time. The monitoring time of the location is determined as the starting time, and the starting monitoring image corresponding to the starting time is obtained. Determine the termination time with a preset interval after the start time, and acquire the termination monitoring image at the corresponding termination time; The starting monitoring image and the ending monitoring image are compared. If the comparison result shows that the ending monitoring image includes all human elements located in the starting monitoring image, the dwell attribute corresponding to the starting time is determined as a valid dwell time. Based on the preset monitoring time, determine the number of times at each start time of each valid stay for each location in each area. If the number of times is greater than the preset number, the regional attribute corresponding to the regional point will be determined as the appropriate attribute; Conversely, the regional attributes corresponding to the aforementioned regional points are determined as unsuitable attributes.

[0028] For example, in this embodiment, when the server determines that there is a human element at a certain location in any area at a certain monitoring time, it means that there is a tourist at that location at that monitoring time. Therefore, the server will determine the monitoring time of that location as the start time and synchronously acquire the start monitoring image corresponding to that start time. Subsequently, the server will determine the termination time with a preset interval after the start time and acquire the termination monitoring image at the corresponding termination time. The preset interval can be flexibly adjusted according to the pedestrian flow characteristics of the walkway, for example, 30 minutes. Next, the starting monitoring image and the ending monitoring image are compared. If the comparison result shows that the ending monitoring image contains all the human body elements located in the starting monitoring image, it means that the tourist has been staying in the area. Therefore, the server determines the stay attribute corresponding to the starting time as a valid stay. Next, the server will count the number of times each location in each area has a valid stay attribute at each start time within the preset monitoring time, and compare the number of times with the preset number. If the number of time intervals is greater than the preset number, it indicates that the visitor dwell rate at that location is high. Therefore, the server will determine the area attribute corresponding to that location as a suitable attribute. If the number of time intervals is less than or equal to the preset number, it indicates that the visitor dwell rate at that location is low. Therefore, the server will determine the area attribute corresponding to that location as an unsuitable attribute to avoid wasting resources caused by installing T-shaped wave-breaking walls at that location.

[0029] Step S104 includes the following: Based on the wave height acquisition images corresponding to each installation point at different acquisition times, the height of each T-shaped wave barrier wall corresponding to each installation point is determined based on the wave height acquisition images.

[0030] For example, in this embodiment, since the height of the waves is different at different times, the server will acquire wave height acquisition images corresponding to each installation point according to different acquisition times, and determine the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on the wave height acquisition images, so that the final determined height of each barrier wall can be higher than the wave height corresponding to each installation point, thereby improving practicality.

[0031] Furthermore, the aforementioned "acquiring wave height acquisition maps corresponding to each installation point based on different acquisition times, and determining the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on each wave height acquisition map" also includes the following steps: The number of samples is obtained by directly dividing the preset interval time by the retrieved preset collection interval. Based on each monitoring task corresponding to each installation point, the start time of each valid stay attribute is determined as the collection time of each installation point. Each monitoring task acquires additional time points corresponding to the number of data points at preset intervals after each data acquisition time. Based on the acquisition unit, wave height acquisition images of each installation point at each acquisition time and each additional time are obtained, and wave height acquisition images of the same installation point are sequentially superimposed on each retrieved transparent fusion layer to obtain each acquisition fusion layer. The height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the collected and fused layers.

[0032] For example, in this embodiment, the server first performs a direct division calculation between the preset interval time (e.g., 30 minutes) and the preset collection interval (e.g., 10 minutes) to obtain a collection quantity of 3; Next, the server will determine the start time of each valid stay attribute based on each monitoring task at each installation point as the collection time for each installation point. Then, after each collection time, the server will obtain the corresponding number of additional times at each preset collection interval. For example, if the collection time is 10:00, the additional times will be 10:10, 10:20, and 10:30. Next, the server controls the acquisition unit (such as a high-definition camera) to acquire images at each acquisition time and additional time based on each installation point, obtaining various wave height acquisition images. The server will overlay all wave height acquisition images corresponding to the same installation point onto the retrieved transparent fusion layer to obtain various acquisition fusion layers. Based on the acquisition fusion layers, the maximum wave height and the trend of change can be intuitively presented, which is convenient for providing accurate data for the subsequent determination of the height of each T-shaped wave-breaking barrier corresponding to each installation point, greatly improving the efficiency of data acquisition.

[0033] Furthermore, the aforementioned "determining the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on each collected and fused layer" also includes the following steps: Retrieve a reference image with the reference height and reference length corresponding to the T-shaped wave-breaking barrier, and determine the downward contour line segment that makes up the image contour of the reference image; Determine the midpoint of the corresponding downlink contour line segment, and overlay the reference image onto each acquisition and fusion layer by overlapping the midpoint of the line segment with each installation point based on each acquisition and fusion layer; Based on the left and right contour segments of the image contour that make up the reference image, the images of each acquisition and fusion layer are cropped respectively, and the reference images are blurred based on each acquisition and fusion layer to obtain each current fusion layer with the horizontal length of the corresponding layer being the reference length. Each current fused layer is binarized to obtain a binarized image, wherein the binarized image includes wave pixels corresponding to the first pixel value and / or noise pixels corresponding to the second pixel value; The binarized image is pixel-wise identified, and the height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the identification results.

[0034] For example, in this embodiment, the server first retrieves a preset reference image, which includes a reference height (e.g., 1.2 meters) and a reference length (e.g., 3 meters) that matches the T-shaped wave-breaking barrier to be installed. The server will determine the downward contour line segment that makes up the image outline of the reference image. This downward contour line segment can be understood as the boundary between the bottom of the barrier and the ground, providing a reference for the subsequent calculation of the barrier height. Next, the server will determine the midpoint of the downlink contour line segment and, according to the overlap between the midpoint and the installation point, will overlay the reference image onto each acquisition and fusion layer, such as... Figure 2 As shown, the left and right contour segments of the baseline image are then used as boundaries to crop the images of each acquired and fused layer, that is, only the area corresponding to the baseline length of the retaining wall is retained, such as... Figure 2The bolded rectangle shown facilitates the accurate determination of the retaining wall height and also reduces the amount of data processing required by the server. Next, the server will blur the stacked reference image to avoid the reference image interfering with the subsequent wave pixel recognition, and finally obtain each current fused layer with the same horizontal length as the reference. Next, the server performs binarization on each of the current fused layers to obtain each binarized image. The binarized image may include wave pixels corresponding to the first pixel value and / or noise pixels corresponding to the second pixel value. Finally, the server performs pixel recognition on the binarized image and determines the height of each T-shaped wave barrier corresponding to each installation point based on the recognition results. This ensures that the final determined barrier height can effectively resist the impact of high waves while avoiding resource waste caused by redundant height design.

[0035] Furthermore, the aforementioned "performing pixel recognition on the binarized image and determining the height of each T-shaped wave-breaking barrier wall corresponding to each installation point based on the recognition results" also includes the following steps: Pixel recognition is performed on the binarized image to obtain the individual image pixels that make up the binarized image; If each image pixel corresponding to the same binarized image includes at least one image pixel corresponding to the first pixel value, then the at least one image pixel is determined as each target pixel. The image coordinate system established with the image center point of the corresponding binarized image as the origin determines the pixel coordinates of each target pixel, and the target pixel is compared based on the vertical coordinate. The target pixel with the maximum vertical coordinate is determined as the limit coordinate point. The vertical distance between the extreme coordinate point and the downward contour line segment determined based on the acquisition and fusion layer corresponding to the binarized image is summed with the retrieved preset growth height to obtain the retaining wall height of the T-shaped wave-breaking retaining wall corresponding to the installation point of the acquisition and fusion layer. If the image pixels corresponding to the same binarized image do not include any image pixel corresponding to the first pixel value, the reference height is determined as the height of the T-shaped wave-breaking barrier wall corresponding to the installation point of the acquisition and fusion layer corresponding to the binarized image.

[0036] For example, in this embodiment, the server will perform pixel recognition on the binarized image to accurately extract all the image pixels that make up the binarized image, providing a complete data foundation for subsequent judgment; If all image pixels corresponding to the same binarized image contain at least one image pixel corresponding to the first pixel value, the server will directly determine these image pixels as each target pixel. Subsequently, the server establishes a two-dimensional image coordinate system with the center point of the binarized image as the origin, and then determines the pixel coordinates of each target pixel according to the image coordinate system. The server then performs a coordinate comparison of each target pixel based on the vertical coordinate. The target pixel with the maximum vertical coordinate corresponds to the highest impact position of the wave, so the server will determine the target pixel as the extreme coordinate point. Next, the server will determine the perpendicular distance between the extreme coordinate points and the descending contour line segment based on the acquisition and fusion layer corresponding to the binarized image, such as... Figure 3 As shown, since the wave height may fluctuate slightly at different times, in order to ensure that the determined retaining wall height can withstand the impact of extreme wave height, the server will sum the vertical distance with the retrieved preset growth height to calculate the retaining wall height of the T-shaped wave-breaking retaining wall corresponding to the installation point corresponding to the data collection and fusion layer. If there is no image pixel corresponding to the first pixel value among all image pixels of the same binarized image, it means that the wave height during the monitoring period corresponding to the installation point is low and has not reached the reference height corresponding to the reference image. Since the reference height can be understood as being set by the management end based on historical wave height data, when there is no image pixel corresponding to the first pixel value among all image pixels corresponding to the same binarized image, the server will directly determine the preset reference height as the height of the T-shaped wave-breaking barrier wall corresponding to the installation point of the acquisition and fusion layer corresponding to the binarized image. This avoids the waste of materials and construction costs caused by over-design and achieves a balance between engineering economy and practicality.

[0037] Step S106 includes the following: Based on the illumination area corresponding to each street light in the walkway area, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking barrier is determined, wherein the containment attribute includes green plant attribute and lighting attribute.

[0038] For example, in this embodiment, the design of the receiving slots of the T-shaped wave-breaking barrier is both functional and practical. The server will further determine the receiving attributes corresponding to each receiving slot of each T-shaped wave-breaking barrier by analyzing the illumination area of ​​the street lights in the walkway area. The receiving attributes include green plant attributes and lighting attributes.

[0039] Furthermore, the aforementioned "determining the accommodation attributes corresponding to each accommodation slot of each T-shaped wave-breaking barrier based on each illumination area corresponding to each street light located in the walkway area, wherein the accommodation attributes include vegetation attributes and lighting attributes" also includes the following steps: Based on the fact that the current time is the same as the second preset acquisition time, the acquisition drone is controlled to acquire images of the river channel to obtain the second acquired image; Acquire the second pixel value corresponding to each image pixel point that makes up the second acquired image, and compare each second pixel value with the preset illumination pixel range; Each image pixel corresponding to each second pixel value that is located in the preset illumination pixel range is determined as each illumination pixel, and each illumination pixel is connected to obtain each illumination area. Based on each irradiation area, the corresponding containment attributes for each containment slot of each T-shaped wave-breaking wall are determined, wherein the containment attributes include plant attributes and lighting attributes.

[0040] For example, in this embodiment, the second preset collection time can be a fixed time after the streetlights are fully turned on in the evening (such as 20:00), at which time the illumination is stable and can accurately reflect the actual illumination effect of the streetlights; When the current time reaches the second preset acquisition time, the server controls the acquisition drone to acquire images of the river channel and obtain the second acquired image. Subsequently, the server will obtain the second pixel value corresponding to each image pixel that makes up the second captured image, and compare each second pixel value with the preset lighting pixel range. The server will identify each image pixel that corresponds to each second pixel value that is located in the preset illumination pixel range as an illumination pixel, and connect each illumination pixel to obtain each illumination area. Finally, the server will determine the corresponding accommodation attributes of each accommodation slot in each T-shaped wave barrier according to each irradiated area. This will not only make full use of the slot space to improve resource utilization, but also make up for the shortcomings of walkway lighting or optimize the landscape effect, further improving the user experience and aesthetics of the T-shaped wave barrier.

[0041] Furthermore, the aforementioned "determining the accommodation attributes corresponding to each accommodation slot of each T-shaped wave-breaking wall based on each irradiation area, wherein the accommodation attributes include plant attributes and lighting attributes" also includes the following steps: Based on the second acquired image, each installation line segment is generated with the installation point as the midpoint of the line segment and the length of the line segment as the reference length along the extension direction of the river. If each point on the same installation line segment has a point overlap relationship with different light illumination pixels, the accommodation attribute of the T-shaped wave-breaking retaining wall corresponding to the installation point of the installation line segment is determined as the green plant attribute. If any line segment point corresponding to the same installation line segment has a point position that does not have a point position overlap with any lamp illumination pixel point, the accommodating attribute of the accommodating slot of the T-shaped wave-breaking barrier corresponding to the installation point of the installation line segment is determined as the lamp attribute, and the barrier height corresponding to the T-shaped wave-breaking barrier is summed with the retrieved preset lamp height to obtain the updated barrier height.

[0042] For example, in this embodiment, the server will generate each installation line segment in the second acquired image with each installation point as the midpoint of the line segment along the extension direction of the river channel. The installation line segments can accurately correspond to the actual coverage area of ​​the T-shaped wave barrier after installation. If all points on the same installation line segment coincide with different light-emitting pixels, it means that the retaining wall area is completely within the illumination range of the streetlights and the lighting conditions are sufficient. There is no need to add lights to the corresponding slots of the T-shaped wave-breaking retaining wall. Therefore, the server will determine the accommodation attribute of the slot of the T-shaped wave-breaking retaining wall corresponding to the installation point of the installation line segment as the green plant attribute. That is, ornamental green plants (such as liriope and ivy) can be planted in the slot of the T-shaped wave-breaking retaining wall, which can beautify the walkway environment, purify the air and reduce noise, and enhance the ecological value of the T-shaped wave-breaking retaining wall. If there are line segments that do not overlap with any lighting pixels in all line segments corresponding to the same installation line segment, it indicates that there is a blind spot in the retaining wall area and the lighting conditions are insufficient. Therefore, the server will determine the accommodation attribute of the T-shaped wave-breaking retaining wall corresponding to the installation point of the installation line segment as the lighting attribute. To avoid the risk of electric shock caused by waves wetting the lights after they are installed in the storage slots, the server will sum the height of the T-shaped wave barrier corresponding to the barrier wall with the preset height of the lights to obtain the updated barrier height. This not only accurately fills the blind spots with the added lights to ensure the safety of the walkway at night, but also ensures the safety of the lights after installation by adjusting the barrier height synchronously.

[0043] According to the present invention, the server can first accurately determine the walkway area around the river and, combined with visitor lingering habits and sunlight conditions, select the installation locations of the T-shaped wave-breaking walls. This effectively avoids sparsely populated areas, prevents resource waste, and significantly improves the utilization rate and user adaptability of the T-shaped wave-breaking walls. Furthermore, in the wall height design stage, the server integrates wave height data collected at different times to ensure that the determined wall heights of each T-shaped wave-breaking wall corresponding to each installation location guarantee the core performance of the T-shaped wave-breaking walls in resisting water flow impact, while also preventing [further issues]. The high degree of design redundancy leads to additional consumption of materials and construction costs. At the same time, the server determines the slot attributes of the T-shaped wave-breaking barrier based on the illumination area of ​​the pedestrian street lights. When the T-shaped wave-breaking barrier is in a well-lit area, the slot attribute is greenery, which can be configured with greenery to optimize the landscape and ecological environment. When the T-shaped wave-breaking barrier is in a light-blind area, the slot attribute is lighting, which can be configured with lighting to fill the lighting gap. Ultimately, the wave-breaking, landscaping, and lighting functions of the barrier are integrated, significantly enhancing the safety and user experience of the T-shaped wave-breaking barrier.

[0044] Another embodiment of the present invention provides a T-shaped wave-breaking barrier. Figure 4 According to its corresponding system block diagram, the T-shaped wave-breaking barrier includes a T-shaped bench, wherein the T-shaped bench includes a T-shaped base and a rectangular barrier wall disposed on the T-shaped base, and the rectangular barrier wall is provided with a receiving slot.

[0045] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used with the examples of this invention. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing preferred embodiments of the invention.

[0046] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0047] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof.

[0048] Those skilled in the art will understand that modules, units, or components of the devices disclosed in the examples herein can be arranged in the devices described in this embodiment, or alternatively, can be located in one or more devices different from the devices in this example. The modules in the foregoing examples can be combined into a single module or further divided into multiple sub-modules.

[0049] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components.

[0050] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of the invention and form different embodiments.

[0051] Furthermore, some of the embodiments described herein are methods or combinations of method elements that can be implemented by a processor of a computer system or by other means of performing the functions. Therefore, a processor having the necessary instructions for implementing the methods or method elements forms means for implementing the methods or method elements. Furthermore, the elements described herein in the apparatus embodiments are examples of means for implementing the functions performed by elements for the purposes of carrying out the invention.

[0052] As used herein, unless otherwise specified, the use of ordinal numbers such as “first,” “second,” “third,” etc., to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects being described must have a given order in time, space, ordering, or any other manner.

[0053] Although the invention has been described with respect to a limited number of embodiments, those skilled in the art will understand from the foregoing description that other embodiments are conceivable within the scope of the invention described herein. Furthermore, it should be noted that the language used in this specification has been chosen primarily for readability and edibility purposes, and not for the purpose of explaining or limiting the subject matter of the invention.

Claims

1. An intelligent design method, characterized in that, Includes the following steps: Identify the walkway area around the river and determine the installation points for each T-shaped wave-breaking barrier within the walkway area; Based on different acquisition times, wave height acquisition maps corresponding to each installation point are obtained, and based on each wave height acquisition map, the height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined. Based on the illumination area corresponding to each street light in the walkway area, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking barrier is determined, wherein the containment attribute includes green plant attribute and lighting attribute.

2. The method according to claim 1, characterized in that, Identify the walkway area surrounding the river channel, and within the walkway area, determine the installation locations for each T-shaped wave-breaking wall, including: If the current time is the same as the first preset collection time, control the collection drone to collect images of the river channel, and perform image recognition on the first collected image to obtain the walkway area located in the first collected image; Obtain the length of the walkway area in the direction of its extension along the river channel, and divide the length of the walkway area by the reference length of the corresponding T-shaped wave-breaking wall. The largest integer in the calculation result is determined as the number of points in the corresponding walkway area. The trail area is divided into points based on the number of points along the extension direction of the river, resulting in points for each area. Based on the data collection drone, monitoring tasks are established for each monitoring period corresponding to each regional location, and regional attributes corresponding to each regional location are determined based on the monitoring tasks. The regional attributes include suitable attributes and unsuitable attributes. The locations of each area with the appropriate regional attribute are determined as the corresponding installation locations for each T-shaped wave-breaking retaining wall.

3. The method according to claim 2, characterized in that, Based on the data collection drones, various monitoring tasks were established for each monitoring point in each region and corresponding monitoring time period, including: Obtain the first pixel value corresponding to each image pixel point that makes up the first acquired image, and compare each first pixel value with a preset shadow pixel range; Each image pixel corresponding to each first pixel value that is located in the preset shadow pixel range is determined as a shadow pixel. Based on the first acquired image, each baseline line segment is generated with the midpoint of each area as the midpoint of the line segment and the length of the line segment as the baseline length along the extension direction of the river. If each reference point corresponding to the same baseline segment has a point overlap relationship with different shadow pixels, the first time period corresponding to the daytime sunshine attribute is determined as the monitoring time period of the area point corresponding to the baseline segment. Conversely, the second time period corresponding to dim evening sunlight is determined as the monitoring time period for the area points corresponding to the baseline segment, and the data acquisition drone is controlled to perform each monitoring task for each area point based on the monitoring time period corresponding to each area point, according to the preset monitoring time.

4. The method according to claim 3, characterized in that, Based on the monitoring task, the regional attributes corresponding to each regional location are determined, wherein the regional attributes include suitable attributes and unsuitable attributes, including: Based on the monitoring task, it is determined that any location in any area has human elements at any monitoring time. The monitoring time of the location is determined as the starting time, and the starting monitoring image corresponding to the starting time is obtained. Determine the termination time with a preset interval after the start time, and acquire the termination monitoring image at the corresponding termination time; The starting monitoring image and the ending monitoring image are compared. If the comparison result shows that the ending monitoring image includes all human elements located in the starting monitoring image, the dwell attribute corresponding to the starting time is determined as a valid dwell time. Based on the preset monitoring time, determine the number of times at each start time of each valid stay for each location in each area. If the number of times is greater than the preset number, the regional attribute corresponding to the regional point will be determined as the appropriate attribute; Conversely, the regional attributes corresponding to the aforementioned regional points are determined as unsuitable attributes.

5. The method according to claim 4, characterized in that, Based on the wave height acquisition images obtained at different acquisition times for each installation point, and based on the wave height acquisition images, the height of each T-shaped wave-breaking retaining wall corresponding to each installation point is determined, including: The number of samples is obtained by directly dividing the preset interval time by the retrieved preset collection interval. Based on each monitoring task corresponding to each installation point, the start time of each valid stay attribute is determined as the collection time of each installation point. Each monitoring task acquires additional time points corresponding to the number of data points at preset intervals after each data acquisition time. Based on the acquisition unit, wave height acquisition images of each installation point at each acquisition time and each additional time are obtained, and the wave height acquisition images of the same installation point are sequentially superimposed on the retrieved transparent fusion layers to obtain each acquisition fusion layer. The height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the collected and fused layers.

6. The method according to claim 5, characterized in that, Based on the data acquisition and fusion layers, the heights of each T-shaped wave-breaking retaining wall corresponding to each installation point are determined, including: Retrieve a reference image with the reference height and reference length corresponding to the T-shaped wave-breaking barrier, and determine the downward contour line segment that makes up the image contour of the reference image; Determine the midpoint of the corresponding downlink contour line segment, and overlay the reference image onto each acquisition and fusion layer by overlapping the midpoint of the line segment with each installation point based on each acquisition and fusion layer; Based on the left and right contour segments of the image contour that make up the reference image, each acquisition and fusion layer is cropped, and each reference image is blurred based on each acquisition and fusion layer to obtain each current fusion layer with a horizontal length of the reference length. Each current fused layer is binarized to obtain a binarized image, wherein the binarized image includes wave pixels corresponding to the first pixel value and / or noise pixels corresponding to the second pixel value; The binarized image is pixel-wise identified, and the height of each T-shaped wave-breaking barrier wall corresponding to each installation point is determined based on the identification results.

7. The method according to claim 6, characterized in that, Pixel recognition is performed on the binarized image, and the height of each T-shaped wave-breaking barrier corresponding to each installation point is determined based on the recognition results, including: Pixel recognition is performed on the binarized image to obtain the individual image pixels that make up the binarized image; If each image pixel corresponding to the same binarized image includes at least one image pixel corresponding to the first pixel value, then the at least one image pixel is determined as each target pixel. The image coordinate system established with the image center point of the corresponding binarized image as the origin determines the pixel coordinates of each target pixel, and the target pixel is compared based on the vertical coordinate. The target pixel with the maximum vertical coordinate is determined as the limit coordinate point. The vertical distance between the extreme coordinate point and the downward contour line segment determined based on the acquisition and fusion layer corresponding to the binarized image is summed with the retrieved preset growth height to obtain the retaining wall height of the T-shaped wave-breaking retaining wall corresponding to the installation point of the acquisition and fusion layer. If the image pixels corresponding to the same binarized image do not include any image pixel corresponding to the first pixel value, the reference height is determined as the height of the T-shaped wave-breaking barrier wall corresponding to the installation point of the acquisition and fusion layer corresponding to the binarized image.

8. The method according to claim 7, characterized in that, Based on the illumination areas corresponding to each street light located in the walkway area, each containment attribute corresponding to each containment slot of each T-shaped wave-breaking barrier is determined. The containment attributes include vegetation attributes and lighting attributes, including: Based on the fact that the current time is the same as the second preset acquisition time, the acquisition drone is controlled to acquire images of the river channel to obtain the second acquired image; Acquire the second pixel value corresponding to each image pixel point that makes up the second acquired image, and compare each second pixel value with the preset illumination pixel range; Each image pixel corresponding to each second pixel value that is located in the preset illumination pixel range is determined as an illumination pixel, and each illumination pixel is connected to obtain each illumination area. Based on each irradiation area, the corresponding containment attributes for each containment slot of each T-shaped wave-breaking wall are determined, wherein the containment attributes include plant attributes and lighting attributes.

9. The method according to claim 8, characterized in that, Based on each irradiation area, the corresponding containment attributes for each containment slot of each T-shaped wave-breaking wall are determined. These containment attributes include plant attributes and lighting attributes, including: Based on the second acquired image, each installation line segment is generated with the installation point as the midpoint of the line segment and the length of the line segment as the reference length along the extension direction of the river. If each point on the same installation line segment has a point overlap relationship with different light illumination pixels, the accommodation attribute of the T-shaped wave-breaking retaining wall corresponding to the installation point of the installation line segment is determined as the green plant attribute. If any line segment point corresponding to the same installation line segment has a point position that does not have a point position overlap with any lamp illumination pixel point, the accommodating attribute of the accommodating slot of the T-shaped wave-breaking barrier corresponding to the installation point of the installation line segment is determined as the lamp attribute, and the barrier height corresponding to the T-shaped wave-breaking barrier is summed with the retrieved preset lamp height to obtain the updated barrier height.

10. A T-shaped wave-breaking retaining wall based on the intelligent design method according to any one of claims 1 to 9, characterized in that, The invention includes a T-shaped stool, wherein the T-shaped stool includes a T-shaped base and a rectangular retaining wall disposed on the T-shaped base, and the rectangular retaining wall is provided with a receiving slot.

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