Ecological environment data real-time monitoring method based on big data processing

Abstract

The application provides an ecological environment data real-time monitoring method based on big data processing. The method comprises the following steps: determining a rectangular cleaning area surrounding the floating garbage according to the patrol data; determining the extension direction corresponding to the rectangular cleaning area as the cleaning moving direction, and determining the area contour line perpendicular to the cleaning moving direction and constituting the rectangular cleaning area as the starting cleaning line and the ending cleaning line; determining the end point of the starting cleaning line as the first cleaning point and the second cleaning point, and controlling the first ship and the second ship to move towards the first cleaning point and the second cleaning point; and controlling the first ship and the second ship to clean the floating garbage to the ending cleaning line along the cleaning moving direction. The application at least improves the salvage efficiency.

Description

Technical Field

[0001] This invention relates to data processing technology, and more particularly to a method for real-time monitoring of ecological and environmental data based on big data processing. Background Technology

[0002] In ecologically sensitive areas, garbage acts like a lurking "killer," posing a serious threat to ecological balance and stability. Timely garbage cleanup is of great significance. Taking wetland ecosystems around cities as an example, regular garbage cleanup can significantly improve the water quality of wetlands. Previously turbid and smelly water becomes clear, and the breeding of mosquitoes in the surrounding area is greatly reduced, improving the living environment of residents. From an ecological perspective, this can prevent harmful substances in garbage from seeping into the soil and water, protect the living space of wetland plants and animals, maintain ecological balance and stability, prevent the decline of wetland ecological functions due to garbage accumulation, and reduce potential ecological damage risks such as biodiversity loss.

[0003] However, the current state of waste cleanup in ecological and environmental areas is far from satisfactory. Through in-depth research, the inventors discovered that most waste cleanup work still relies on manual labor. In some river areas, workers must manually pick up floating debris. Each effort to retrieve trash involves significant time and energy; moreover, cleaning large areas requires the collaboration of numerous workers, which not only consumes a large amount of manpower but also necessitates the use of appropriate tools and equipment, resulting in extremely high material costs. Over time, the contradiction between the high investment of manpower and resources and the inefficiency of the cleanup work becomes increasingly prominent.

[0004] Therefore, there is an urgent need for a real-time monitoring method for ecological and environmental data based on big data processing that can improve salvage efficiency. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a real-time monitoring method for ecological and environmental data based on big data processing to overcome or at least partially solve the above problems.

[0006] According to one aspect of the present invention, a method for real-time monitoring of ecological and environmental data based on big data processing is provided, comprising the following steps:

[0007] The rectangular collection area surrounding the floating garbage was determined based on the patrol data;

[0008] The extension direction corresponding to the rectangular cleaning area is determined as the cleaning movement direction, and the outline of the area that makes up the rectangular cleaning area and is perpendicular to the cleaning movement direction is determined as the starting cleaning line and the ending cleaning line.

[0009] The extension direction corresponding to the rectangular cleaning area is determined as the cleaning moving direction, and the area contour line of the area constituting the rectangular cleaning area and perpendicular to the cleaning moving direction is determined as the starting cleaning line and the ending cleaning line;

[0010] The end point of the starting cleaning line is determined as the first cleaning point and the second cleaning point, and the first ship and the second ship are controlled to move towards the first cleaning point and the second cleaning point;

[0011] The first ship and the second ship are controlled to clean the floating garbage to the ending cleaning line along the cleaning moving direction.

[0012] Optionally, in the method according to the present application, the rectangular cleaning area surrounding the floating garbage is determined according to the patrol data, comprising:

[0013] The image acquisition size corresponding to the unmanned aerial vehicle is obtained, and the ecological area is arrayed to obtain each ecological sub-area corresponding to the image acquisition size;

[0014] Each area center point corresponding to each ecological sub-area is obtained, and the unmanned aerial vehicle is configured with a patrol task based on each area center point;

[0015] In response to the unmanned aerial vehicle flying to any area center point, the unmanned aerial vehicle is triggered to perform flow rate measurement to obtain the water flow rate corresponding to the ecological area;

[0016] The ecological area attribute is determined based on the comparison result between the water flow rate and the preset flow rate, and different preset floating garbage identification strategies are configured based on different ecological area attributes, wherein the ecological area attribute includes a stable attribute and a turbulent attribute;

[0017] Each ecological sub-area is identified based on the preset floating garbage identification strategy, and each ecological sub-area corresponding to the existence of floating garbage is determined as a set of to-be-cleaned.

[0018] Based on the mutual positional relationship between each ecological sub-area in the set of to-be-cleaned, the ecological sub-areas are merged to obtain the rectangular cleaning area.

[0019] Optionally, in the method according to the present application, each ecological sub-area is identified based on the preset floating garbage identification strategy, and each ecological sub-area corresponding to the existence of floating garbage is determined as a set of to-be-cleaned, comprising:

[0020] In response to the ecological area attribute being a stable attribute, the unmanned aerial vehicle is controlled to hover for a preset time, and the ecological sub-area is photographed for a preset number of frames at intervals of the same period within the preset time to obtain an ecological area image composed of image frames corresponding to different frame sequences.

[0021] respectively, to obtain each image pixel point respectively constituting the same binary image;

[0022] Each water area pixel point corresponding to a water area pixel value is determined in each image pixel point, and each pixel point other than each water area pixel point is determined as each clean-up pixel point;

[0023] A pixel ratio between each clean-up pixel point and each image pixel point located in the same binary image is obtained, and each pixel ratio corresponding to each binary image is compared in proportion;

[0024] The pixel ratio corresponding to the smallest pixel ratio is determined as the pixel ratio corresponding to the ecological region image, and each ecological sub-region corresponding to a pixel ratio greater than or equal to a preset ratio is determined as the set to be cleaned up.

[0025] Optionally, in the method according to the present application, each ecological sub-region is identified based on the preset floating garbage identification strategy, and each ecological sub-region corresponding to the presence of floating garbage is determined as the set to be cleaned up, comprising:

[0026] When the ecological region attribute of the ecological region is a turbulent attribute, the unmanned aerial vehicle is controlled to take one image of the ecological sub-region to obtain an ecological region image;

[0027] The ecological region image is subjected to binaryzation processing, and each image pixel point constituting the binary image is obtained by performing pixel recognition on the obtained binary image;

[0028] Each water area pixel point corresponding to a water area pixel value is determined in each image pixel point, and each pixel point other than each water area pixel point is determined as each clean-up pixel point;

[0029] A pixel ratio between each clean-up pixel point and each image pixel point located in the same binary image is obtained, and each ecological sub-region corresponding to a pixel ratio greater than or equal to a preset ratio is determined as the set to be cleaned up.

[0030] Optionally, in the method according to the present application, each ecological sub-region is regionally merged based on the mutual positional relationship between each ecological sub-region located in the set to be cleaned up, to obtain the rectangular clean-up region, comprising:

[0031] Each regional position of each ecological sub-region located in the set to be cleaned up in the ecological region is determined, and each ecological sub-region exhibiting continuity connection is divided into the same regional division group based on each regional position, and each remaining ecological sub-region is divided into different regional division groups, to obtain each regional division group;

[0032] establish a regional coordinate system corresponding to the ecological region, and obtain coordinates of each clean-up pixel point corresponding to each ecological sub-region in the same regional division group, to obtain each clean-up coordinate point corresponding to each clean-up pixel point;

[0033] determine an X-axis extreme coordinate point corresponding to an X-axis and a Y-axis extreme coordinate point corresponding to a Y-axis based on each clean-up coordinate point, and form a rectangular clean-up region covering at least any one of the X-axis extreme coordinate point and the Y-axis extreme coordinate point and surrounding all the remaining clean-up coordinate points based on a minimum circumscribed rectangle algorithm.

[0034] Optionally, in the method according to the present application, an extension direction corresponding to the rectangular clean-up region is determined as a clean-up moving direction, and a region contour line constituting the rectangular clean-up region and perpendicular to the clean-up moving direction is determined as a starting clean-up line and a terminal clean-up line, comprising:

[0035] obtaining each region contour line constituting the rectangular clean-up region, and obtaining a distance between each region contour line and a ship berthing line corresponding to the ship wharf to obtain each moving distance;

[0036] determining an extension direction perpendicular to the region contour line corresponding to the smallest moving distance as the clean-up moving direction, and obtaining a first contour size and a second contour size corresponding to the contour of the rectangular clean-up region in a direction perpendicular to and parallel to the clean-up moving direction;

[0037] comparing the first contour size and the second contour size with a fence size corresponding to the trawl fence respectively, and determining a direction adjustment coefficient based on the comparison result;

[0038] in response to the direction adjustment coefficient being greater than or equal to a preset coefficient, determining an extension direction perpendicular to the clean-up moving direction as an updated clean-up moving direction;

[0039] obtaining each region contour line perpendicular to the clean-up moving direction, and determining the region contour line corresponding to the smallest moving distance as the terminal clean-up line and the region contour line corresponding to the largest moving distance as the starting clean-up line.

[0040] Optionally, in the method according to the present application, the first contour size and the second contour size are compared with the fence size corresponding to the trawl fence respectively, and a direction adjustment coefficient is determined based on the comparison result, comprising:

[0041] when the first contour size is the same as the second contour size, determining a first reference coefficient as the direction adjustment coefficient, wherein the first reference coefficient is smaller than the preset coefficient;

[0042] or,

[0043] When the first profile size and the second profile size are different, the first profile size and the second profile size are respectively subtracted from the size of the corresponding net fence to obtain a first difference value corresponding to the first profile size and a second difference value corresponding to the second profile size;

[0044] When the first difference value and the second difference value are both non-positive numbers, the first reference coefficient retrieved is determined as the direction adjustment coefficient;

[0045] When the first difference value is positive and the second difference value is non-positive, the second reference coefficient retrieved is determined as the direction adjustment coefficient, wherein the second reference coefficient is greater than or equal to the preset coefficient;

[0046] When the first difference value and the second difference value are both positive, the direction adjustment coefficient is determined by the following formula:

[0047]

[0048] wherein C is the direction adjustment coefficient, k is the size normalization value, X1 is the first difference value, and X2 is the second difference value.

[0049] Optionally, in the method according to the present application, the first ship and the second ship are controlled to clean up the floating garbage to a termination cleaning line along a cleaning movement direction, comprising:

[0050] In response to the real-time monitoring data, it is determined that the first ship and the second ship respectively arrive at the first cleaning point and the second cleaning point, a center point of a line segment corresponding to the starting cleaning line is obtained, and the unmanned aerial vehicle is controlled to fly to the center point of the line segment;

[0051] In response to the unmanned aerial vehicle flying to the center point of the line segment, the unmanned aerial vehicle is triggered to perform flow direction measurement of the ecological area to obtain a water area flow direction corresponding to the ecological area;

[0052] A direction included angle between the cleaning movement direction and the water area flow direction is determined, and an included angle influence value is determined based on the direction included angle;

[0053] A cleaning proportion corresponding to the rectangular cleaning area is determined based on the number of pixels of each cleaning pixel point located in the rectangular cleaning area, and a proportion influence value is determined based on the cleaning proportion;

[0054] A cleaning buffer length is determined based on the included angle influence value and the proportion influence value, and the rectangular cleaning area is extended in an area corresponding to the cleaning buffer length along the termination cleaning line away from the starting cleaning line to obtain an updated rectangular cleaning area and a termination cleaning line;

[0055] Controlling the first ship and the second ship to clean up the floating garbage located in the rectangular cleaning area to the termination cleaning line along the cleaning movement direction.

[0056] Optionally, in the method according to the present application, the cleaning buffer length is determined by the following formula:

[0057]

[0058] wherein, the L s is the cleaning buffer length, the A z is the direction angle, the α1 is the angle weight, the k z is the angle normalization value, the P n is the pixel number, the P a is the pixel area, the R a is the area of the rectangular cleaning area, the β1 is the proportion weight, and the k a is the proportion normalization value.

[0059] Optionally, in the method according to the present application,

[0060] The method further comprises:

[0061] acquiring an actual buffer length sent by the management end based on the rectangular cleaning area, and comparing the actual buffer length with the cleaning buffer length;

[0062] If the actual buffer length is greater than the cleaning buffer length, the angle weight and the proportion weight are respectively increased and trained;

[0063] If the actual buffer length is less than the cleaning buffer length, the angle weight and the proportion weight are respectively decreased and trained;

[0064] The trained angle weight and the proportion weight are obtained by the following formula:

[0065]

[0066] wherein, the q + is the number of times of increasing training of the angle weight α1, the ∈ is the training constant value of the angle weight α1, the q - is the number of times of decreasing training of the angle weight α1, the α2 is the trained angle weight, the v + is the number of times of increasing training of the proportion weight β1, the δ is the training constant value of the proportion weight β1, the v - is the number of times of decreasing training of the proportion weight β1, and the β2 is the trained proportion weight.

[0067] Optionally, in the method according to the present application,

[0068] The method further comprises:

[0069] determining an extension length corresponding to the rectangular collection area along a collection moving direction, and determining a collection attribute corresponding to the rectangular collection area based on a length comparison between the extension length and a preset length, wherein the collection attribute comprises a one-way attribute and a two-way attribute;

[0070] in response to the extension length being greater than or equal to the preset length, determining the rectangular collection area as a two-way attribute, and determining a region center line located at a center of the rectangular collection area and parallel to the terminal collection line;

[0071] determining the starting collection line and the terminal collection line as an updated first starting collection line and a second starting collection line respectively, and determining the region center line as an updated terminal collection line,

[0072] controlling a first ship and a second ship located in different collection ship groups to move towards the first starting collection line and the second starting collection line respectively, and determining a collection ship group located at the first starting collection line as a first ship group and a collection ship group located at the second starting collection line as a second ship group;

[0073] controlling each ship located in the first ship group to move along the collection moving direction and each ship located in the second ship group to move in a direction opposite to the collection moving direction to collect the floating garbage located in the rectangular collection area to the terminal collection line.

[0074] According to still another aspect of the present application, an ecological environment data real-time monitoring system based on big data processing is provided, comprising:

[0075] an ecological patrol module configured to determine a rectangular collection area surrounding the floating garbage according to patrol data;

[0076] a direction determination module configured to determine an extension direction corresponding to the rectangular collection area as a collection moving direction, and determine a region contour line constituting the rectangular collection area and perpendicular to the collection moving direction as a starting collection line and a terminal collection line;

[0077] a moving control module configured to determine an end point of the starting collection line as a first collection point and a second collection point, and control a first ship and a second ship to move towards the first collection point and the second collection point;

[0078] a collection control module configured to control the first ship and the second ship to move along the collection moving direction to collect the floating garbage to the terminal collection line.

[0079] According to the scheme of the present application, the server controls the UAV to fly along the extension direction of the ecological region to determine whether there is floating garbage on the ecological region, and then determines a rectangular cleaning area surrounding the floating garbage, so that the subsequent ship can accurately salvage the floating garbage. Then, the server obtains the rectangular center point corresponding to the rectangular cleaning area, and controls the UAV to move to the rectangular center point to monitor the rectangular cleaning area, so that the server can determine whether the ship reaches the corresponding point and clean the floating garbage according to the obtained real-time monitoring data. Then, the server determines the extension direction corresponding to the rectangular cleaning area as the cleaning moving direction, and then determines the two region contour lines of the rectangular cleaning area perpendicular to the cleaning moving direction as the starting cleaning line and the ending cleaning line. Then, the server determines the two end points of the starting cleaning line as the first cleaning point and the second cleaning point, and controls the first ship and the second ship in the same cleaning ship group to move towards the first cleaning point and the second cleaning point, respectively. When the server determines that the first ship and the second ship reach the first cleaning point and the second cleaning point, respectively, through real-time monitoring data, the server controls the first ship and the second ship to clean the floating garbage in the rectangular cleaning area along the cleaning moving direction. The present application can reduce the time for salvaging floating garbage, thereby improving the salvaging efficiency, and can repair the ecological region to a certain extent. BRIEF DESCRIPTION OF DRAWINGS

[0080] Figure 1 A flow chart of the real-time monitoring method of ecological environment data based on big data processing according to an embodiment of the present application is shown;

[0081] Figure 2 A schematic diagram of the cleaning moving direction in the present embodiment is shown;

[0082] Figure 3 A schematic diagram of the ship cleaning the floating garbage in the rectangular cleaning area in the present embodiment is shown;

[0083] Figure 4 A structural block diagram of the real-time monitoring system of ecological environment data based on big data processing according to another embodiment of the present application is shown. DETAILED DESCRIPTION

[0084] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0085] To solve the problems in the background art, the inventors propose the solutions of the present application. One embodiment of the present application provides a real-time monitoring method for ecological environment data based on big data processing, which can be executed in a computing device.

[0086] Figure 1 A flowchart of the real-time monitoring method for ecological environment data based on big data processing according to one embodiment of the present application is shown, which is suitable for execution in a computing device.

[0087] As shown in Figure 1 The purpose of the present embodiment is to implement a real-time monitoring method for ecological environment data based on big data processing, which starts from step S101, in which the following steps are included:

[0088] A rectangular clean-up area surrounding the floating garbage is determined according to the patrol data.

[0089] For example, in the present embodiment, the server controls the UAV to fly along the extension direction of the ecological area to patrol the ecological area and determine whether there is floating garbage such as a garbage bag on the ecological area.

[0090] Since the subsequent ship uses a trawl fence to salvage the floating garbage, and the fence surface shape of the trawl fence is mostly rectangular, when the UAV discovers floating garbage on the ecological area during the patrol process, the server determines a rectangular area surrounding the floating garbage, i.e., a rectangular clean-up area, so that the subsequent ship can accurately salvage the floating garbage.

[0091] It should be noted that when the ship uses the trawl fence to salvage the floating garbage, two ships are generally arranged to move to two adjacent vertices of the rectangular clean-up area, and then move synchronously along the extension direction of the rectangular clean-up area. When the two ships move to the trawl fence to surround all the floating garbage, the two ships move towards each other to cross, so that the trawl fence is driven to change from an "open state" to a corresponding "closed state" to complete the salvage work of the floating garbage.

[0092] Further, the above-mentioned "determining a rectangular clean-up area surrounding the floating garbage according to the patrol data" further includes the following steps:

[0093] An image acquisition size corresponding to the UAV is obtained, and the ecological area is arrayed to obtain each ecological sub-area corresponding to the image acquisition size;

[0094] acquire each regional center point corresponding to each ecological sub-region respectively, and configure the unmanned aerial vehicle with a patrol task based on each regional center point;

[0095] In response to the unmanned aerial vehicle flying to any regional center point, trigger the unmanned aerial vehicle to perform flow rate measurement to obtain the water flow rate corresponding to the ecological region;

[0096] Based on the comparison result between the water flow rate and the retrieved preset flow rate, determine the ecological region attribute, and configure different preset floating garbage identification strategies based on different ecological region attributes, wherein the ecological region attribute includes a steady attribute and a turbulent attribute;

[0097] Based on the preset floating garbage identification strategy, identify each ecological sub-region, and determine each ecological sub-region with floating garbage as the collection to be cleaned up;

[0098] Based on the mutual positional relationship between each ecological sub-region in the collection to be cleaned up, merge the regions to obtain the rectangular cleaning region.

[0099] For example, in this embodiment, the server will first acquire the image acquisition size of the unmanned aerial vehicle, and then array the ecological region along the extension direction of the ecological region according to the image acquisition size, thereby obtaining each ecological sub-region corresponding to the image acquisition size of the unmanned aerial vehicle. Then, the server will acquire the regional center point of each ecological sub-region, and configure the unmanned aerial vehicle with a patrol task based on each regional center point, so that the unmanned aerial vehicle can subsequently reach each regional center point to perform the corresponding patrol task.

[0100] When the unmanned aerial vehicle flies to any regional center point according to the patrol task, the unmanned aerial vehicle will trigger to measure the flow rate of the ecological region, thereby obtaining the water flow rate of the ecological region. At this time, the server will retrieve the preset flow rate and compare the water flow rate with the preset flow rate, thereby determining the ecological region attribute according to the comparison result. When the water flow rate is greater than the preset flow rate, it indicates that the water flow rate of the current ecological region is too fast, and the corresponding ecological region attribute is turbulent attribute. When the water flow rate is less than or equal to the preset flow rate, it indicates that the water flow rate of the current ecological region is relatively slow, and the corresponding ecological region attribute is steady attribute. Then, the server will configure different preset floating garbage identification strategies for different ecological region attributes.

[0101] Then, the server will control the unmanned aerial vehicle to identify whether there is floating garbage in each ecological sub-region based on the preset floating garbage identification strategy, and determine each ecological sub-region with floating garbage as the collection to be cleaned up.

[0102] In order to reduce the number of fishing times and fishing time, the server will merge the adjacent floating garbage according to the mutual position relationship between each ecological sub-region in the collection to be cleaned, that is, to merge the regions corresponding to each ecological sub-region, so as to obtain a rectangular cleaning region.

[0103] Further, the above "identifying each ecological sub-region based on the preset floating garbage identification strategy, and determining each ecological sub-region with floating garbage as the collection to be cleaned" further comprises the following steps:

[0104] In response to the ecological region attribute being a stable attribute, the server controls the unmanned aerial vehicle to hover for a preset time, and performs image shooting of a preset number of frames on the ecological sub-region in a same interval period for a preset time, to obtain an ecological region image composed of image frames corresponding to different frame sequences.

[0105] Each image frame is subjected to binarization processing, and each binarized image obtained is subjected to pixel recognition, to obtain each image pixel point respectively constituting the same binarized image.

[0106] Each water area pixel point corresponding to a water area pixel value is determined in each image pixel point, and each pixel point other than each water area pixel point is determined as each cleaning pixel point.

[0107] The pixel proportion between each cleaning pixel point and each image pixel point in the same binarized image is obtained, and each pixel proportion corresponding to each binarized image is compared in proportion.

[0108] The pixel proportion corresponding to the smallest pixel proportion is determined as the pixel proportion corresponding to the ecological region image, and each ecological sub-region with a pixel proportion greater than or equal to a preset proportion is determined as the collection to be cleaned.

[0109] For example, in the present embodiment, when the ecological region attribute of the ecological region is a stable attribute, it indicates that the water flow velocity of the current ecological region is small, so the floating garbage will not move to a farther region in a short time, but when the image of the ecological sub-region is collected, it is possible to shoot the passing fish or bird group, thereby causing a certain influence on the subsequent identification of the floating garbage. Therefore, the server controls the unmanned aerial vehicle to hover at the region center point for a preset time, and performs image shooting of a preset number of frames on the ecological sub-region in a same interval period for a preset time, to obtain an ecological region image composed of image frames corresponding to different frame sequences. For example, the preset time is 10 seconds, and the preset number of frames is 5, so the server controls the unmanned aerial vehicle to hover at the region center point for 10 seconds, and performs image shooting of the ecological sub-region every two seconds, to obtain 5 ecological region images.

[0110] Then, the server performs binarization processing on each image frame respectively to obtain each binarization image, and performs pixel recognition on each binarization image respectively to obtain each image pixel point respectively constituting one binarization image. At this time, the server determines each water area pixel point corresponding to a water area pixel value in each image pixel point, and determines each pixel point other than each water area pixel point as each clean-up pixel point.

[0111] Then, the server obtains a pixel ratio between each clean-up pixel point and each image pixel point in one binarization image, and compares each pixel ratio corresponding to each binarization image in proportion. The smaller the pixel ratio, the smaller the influence of the bird group or fish group in the area corresponding to the pixel ratio. Therefore, the server determines the smallest pixel ratio as the pixel ratio corresponding to the ecological area image.

[0112] The server has a preset ratio in advance. When the pixel ratio is greater than or equal to the preset ratio, it indicates that the range of floating garbage in the ecological sub-area corresponding to the pixel ratio is large. Therefore, the server determines each ecological sub-area corresponding to the pixel ratio greater than or equal to the preset ratio as the set to be cleaned up. When the pixel ratio is less than the preset ratio, it indicates that the range of floating garbage in the ecological sub-area corresponding to the pixel ratio is small. Therefore, it is not necessary to use a ship to clean up the floating garbage, which can reduce certain manpower and resources.

[0113] The embodiment can perform multi-frame image shooting on the ecological sub-area of the ecological area with a stable attribute, avoid the influence of the affected bird group or fish group when identifying the floating garbage later, and determine the set to be cleaned up through the pixel ratio, which has a certain accuracy.

[0114] Further, the above-mentioned "identifying each ecological sub-area based on the preset floating garbage identification strategy, and determining each ecological sub-area corresponding to the existence of floating garbage as the set to be cleaned up" further includes the following steps:

[0115] When the ecological area attribute of the ecological area is a turbulent attribute, the server controls the unmanned aerial vehicle to perform one-time image shooting on the ecological sub-area to obtain an ecological area image;

[0116] Performing binarization processing on the ecological area image, and performing pixel recognition on the obtained binarization image to obtain each image pixel point constituting the binarization image;

[0117] Determining each water area pixel point corresponding to a water area pixel value in each image pixel point, and determining each pixel point other than each water area pixel point as each clean-up pixel point;

[0118] The pixel proportion between each clean-up pixel point and each image pixel point in the same binary image is obtained, and each ecological sub-region with a pixel proportion greater than or equal to a preset proportion is determined as the set of ecological sub-regions to be cleaned up.

[0119] For example, in the present embodiment, when the ecological region attribute of the ecological region is a turbulent attribute, it indicates that the water flow speed of the current ecological region is fast. If the server controls the unmanned aerial vehicle to take a second image of the ecological sub-region after a first image is taken at a first time, the floating garbage may have moved to other ecological sub-regions along with the turbulent river water. Therefore, when the ecological region attribute of the ecological region is a turbulent attribute, the ecological sub-region does not need to be taken multiple images. Therefore, the server only needs to control the unmanned aerial vehicle to take one image of the ecological sub-region to obtain the ecological region image.

[0120] Next, the server performs binaryzation processing on the ecological region image, and performs pixel recognition on the obtained binary image to obtain each image pixel point constituting the binary image. Each water area pixel point corresponding to the water area pixel value is determined in each image pixel point, and each pixel point other than each water area pixel point is determined as each clean-up pixel point. Then, the server obtains the pixel proportion between each clean-up pixel point and each image pixel point in the same binary image, and determines each ecological sub-region with a pixel proportion greater than or equal to a preset proportion as the set of ecological sub-regions to be cleaned up.

[0121] Furthermore, the above-mentioned "based on the mutual positional relationship between each ecological sub-region in the set of ecological sub-regions to be cleaned up, merging each ecological sub-region to obtain the rectangular clean-up region" further includes the following steps:

[0122] determining the region position of each ecological sub-region in the ecological region, and based on the region position, dividing each ecological sub-region showing continuous connection to the same region division group, and dividing the remaining ecological sub-regions to different region division groups to obtain each region division group;

[0123] establishing a region coordinate system corresponding to the ecological region, and obtaining the coordinates of each clean-up pixel point corresponding to each ecological sub-region in the same region division group to obtain each clean-up coordinate point corresponding to each clean-up pixel point;

[0124] determining the X-axis extreme coordinate point corresponding to the X-axis and the Y-axis extreme coordinate point corresponding to the Y-axis based on each clean-up coordinate point, and forming a rectangular clean-up region covering at least any one of the X-axis extreme coordinate point and the Y-axis extreme coordinate point and surrounding all the remaining clean-up coordinate points based on the minimum circumscribed rectangle algorithm.

[0125] For example, in the embodiment, the server determines the area positions of each ecological sub-region in the ecological region, divides the ecological sub-regions that present continuity into the same area division group according to the area positions, and divides the remaining ecological sub-regions into different area division groups, thereby obtaining each area division group.

[0126] Then, the server establishes an area coordinate system corresponding to the ecological region, obtains the coordinates of each collection pixel point corresponding to each ecological sub-region in the same area division group, thereby obtaining each collection coordinate point corresponding to each collection pixel point. Then, the X-axis extreme coordinate point corresponding to the X-axis and the Y-axis extreme coordinate point corresponding to the Y-axis are determined in all collection coordinate points, and a rectangular collection region that surrounds all collection coordinate points except the X-axis extreme coordinate point and the Y-axis extreme coordinate point and covers at least the X-axis extreme coordinate point or the Y-axis extreme coordinate point is formed according to the existing minimum enclosing rectangle algorithm.

[0127] The embodiment can divide the ecological sub-regions that present continuity into the same area division group, reduce the number of subsequent salvage times, generate a rectangular collection region according to the area coordinate system, and facilitate the use of trawl by subsequent ships to salvage floating garbage.

[0128] In step S102, the following contents are included:

[0129] The extension direction corresponding to the rectangular collection region is determined as the collection movement direction, and the area contour line that constitutes the rectangular collection region and is perpendicular to the collection movement direction is determined as the starting collection line and the ending collection line.

[0130] For example, in the embodiment, after determining the rectangular collection region, the server first obtains the rectangular center point corresponding to the rectangular collection region, and controls the unmanned aerial vehicle to move to the rectangular center point to perform area monitoring on the rectangular collection region, thereby facilitating the server to determine whether the ship responsible for collection reaches the corresponding point according to the obtained real-time monitoring data and to perform corresponding collection on the floating garbage.

[0131] In step S103, the following contents are included:

[0132] The extension direction corresponding to the rectangular collection region is determined as the collection movement direction, and the area contour line that constitutes the rectangular collection region and is perpendicular to the collection movement direction is determined as the starting collection line and the ending collection line.

[0133] For example, in this embodiment, if the rectangular cleaning area is rectangular in shape, the ship can move in two directions when cleaning up floating garbage, namely, two cleaning movement directions: one is to move along the extension direction of the longer area outline of the rectangular cleaning area, and the other is to move along the extension direction of the shorter area outline of the rectangular cleaning area.

[0134] Therefore, the server will determine the extension direction corresponding to the rectangular cleaning area as the cleaning movement direction based on the actual situation, and then determine the outlines of the two areas that make up the rectangular cleaning area and are perpendicular to the cleaning movement direction as the starting cleaning line and the ending cleaning line, respectively.

[0135] Furthermore, the aforementioned "determining the extension direction corresponding to the rectangular cleaning area as the cleaning movement direction, and determining the outline of the area constituting the rectangular cleaning area and perpendicular to the cleaning movement direction as the starting cleaning line and the ending cleaning line" also includes the following steps:

[0136] Obtain the outline of each area that makes up the rectangular cleaning area, and obtain the distance between each area outline and the ship berthing line of the corresponding ship dock to obtain each movement distance;

[0137] The direction of extension perpendicular to the outline of the area with the smallest corresponding moving distance is determined as the cleaning and transportation moving direction, and the first outline size and the second outline size corresponding to the outline of the rectangular cleaning and transportation area are obtained in the direction perpendicular to and parallel to the cleaning and transportation moving direction.

[0138] The first and second outline dimensions are compared with the corresponding trawl fence dimensions, and the direction adjustment coefficient is determined based on the comparison results.

[0139] When the direction adjustment coefficient is greater than or equal to the preset coefficient, the extension direction perpendicular to the cleaning movement direction is determined as the updated cleaning movement direction;

[0140] Obtain the outlines of each area perpendicular to the cleaning and transportation direction, and determine the outline of the area with the smallest corresponding movement distance as the termination cleaning line, and determine the outline of the area with the largest corresponding movement distance as the starting cleaning line.

[0141] For example, in this embodiment, the server acquires the outlines of each area that makes up the rectangular cleaning area, and obtains the distance between each area outline and the corresponding ship berthing line at the dock, thus obtaining each movement distance. Next, the server determines the direction of movement of the cleaning operation perpendicular to the outline of the area with the smallest movement distance. Figure 2 As shown, this allows ships to move in a predetermined direction to remove floating debris, saving time and reducing fuel consumption.

[0142] In order to reduce the number of fishing operations as much as possible when the ship is collecting floating garbage, the server obtains a first profile size and a second profile size corresponding to the rectangular collection area profile in a direction perpendicular to the collection moving direction and a direction parallel to the collection moving direction, respectively, and then compares the first profile size and the second profile size with the size of the net fence, so as to determine the direction adjustment coefficient according to the comparison result.

[0143] When the direction adjustment coefficient is greater than or equal to a preset coefficient, it indicates that the server needs to change the collection moving direction, so the server determines the extension direction perpendicular to the collection moving direction as the updated collection moving direction. At this time, the server obtains each area profile line perpendicular to the collection moving direction, and determines the area profile line corresponding to the minimum moving distance as the termination collection line, and determines the area profile line corresponding to the maximum moving distance as the starting collection line.

[0144] Further, the above-mentioned "comparing the first profile size and the second profile size with the size of the corresponding net fence, and determining the direction adjustment coefficient based on the comparison result" further includes the following steps:

[0145] When the first profile size is the same as the second profile size, the first reference coefficient is determined as the direction adjustment coefficient, wherein the first reference coefficient is less than the preset coefficient;

[0146] Or,

[0147] When the first profile size is different from the second profile size, the first profile size and the second profile size are respectively subjected to difference calculation with the size of the corresponding net fence, to obtain a first difference value corresponding to the first profile size and a second difference value corresponding to the second profile size;

[0148] When the first difference value and the second difference value are both non-positive numbers, the first reference coefficient is determined as the direction adjustment coefficient;

[0149] When the first difference value is positive and the second difference value is non-positive, the second reference coefficient is determined as the direction adjustment coefficient, wherein the second reference coefficient is greater than or equal to the preset coefficient;

[0150] When the first difference value and the second difference value are both positive, the direction adjustment coefficient is determined by the following formula:

[0151]

[0152] Wherein, C is the direction adjustment coefficient, k is the size normalization value, X1 is the first difference value, and X2 is the second difference value.

[0153] For example, in the embodiment, when the first profile size is the same as the second profile size, i.e. no adjustment is needed for the moving direction of the collection and transportation, the server determines the first reference coefficient less than the preset coefficient as the direction adjustment coefficient.

[0154] When the first profile size is different from the second profile size, the server calculates the difference between the first profile size and the fence size and the difference between the second profile size and the fence size, respectively, to obtain a first difference corresponding to the first profile size and a second difference corresponding to the second profile size. When both the first difference and the second difference are non-positive numbers, it indicates that both the first profile size and the second profile size are less than the fence size, so no adjustment is needed for the moving direction of the collection and transportation, and the server determines the first reference coefficient as the direction adjustment coefficient. When the first difference is positive and the second difference is non-positive, it indicates that the first profile size is greater than the fence size, so the ship cannot complete the salvage of the floating garbage at one time according to the original moving direction of the collection and transportation, but the second profile size is less than the fence size, so the server determines the second reference coefficient greater than or equal to the preset coefficient as the direction adjustment coefficient, so that the ship can complete the salvage of the floating garbage at one time according to the updated moving direction of the collection and transportation. When both the first difference and the second difference are positive, it indicates that both the first profile size and the second profile size are greater than the fence size, so the ship cannot complete the salvage of the floating garbage at one time according to the original moving direction of the collection and transportation or the updated moving direction of the collection and transportation, but the server can determine the direction adjustment coefficient through the formula to reduce the number of salvages of the ship according to the updated moving direction of the collection and transportation as much as possible.

[0155] The embodiment can determine different direction adjustment coefficients according to different difference values of the first profile size and the second profile size, so as to reduce the number of salvages of the ship, thereby reducing certain costs and improving the corresponding salvage efficiency.

[0156] In step S104, the following contents are included:

[0157] The end point positions of the starting collection and transportation line are determined as the first collection and transportation point position and the second collection and transportation point position, and the first ship and the second ship are controlled to move towards the first collection and transportation point position and the second collection and transportation point position.

[0158] For example, in the embodiment, the server determines the two end point positions of the starting collection and transportation line as the first collection and transportation point position and the second collection and transportation point position, respectively, and controls two ships in the same collection and transportation ship group to move towards the two collection and transportation point positions, i.e. controls the first ship and the second ship to move towards the first collection and transportation point position and the second collection and transportation point position, respectively.

[0159] In step S105, the following is included:

[0160] The first ship and the second ship are controlled to clean up the floating garbage in the rectangular cleaning area to the termination cleaning line along the cleaning moving direction.

[0161] For example, in the present embodiment, when the server determines that the first ship and the second ship arrive at the first cleaning point and the second cleaning point respectively by monitoring the real-time monitoring data in real time, the first ship and the second ship are controlled to clean up the floating garbage in the rectangular cleaning area along the cleaning moving direction.

[0162] Further, the above-mentioned "controlling the first ship and the second ship to clean up the floating garbage in the rectangular cleaning area to the termination cleaning line along the cleaning moving direction" further includes the following steps:

[0163] In response to the real-time monitoring data determining that the first ship and the second ship arrive at the first cleaning point and the second cleaning point respectively, a line segment center point corresponding to the starting cleaning line is obtained, and the unmanned aerial vehicle is controlled to fly to the line segment center point;

[0164] In response to the unmanned aerial vehicle flying to the line segment center point, the unmanned aerial vehicle is triggered to perform flow direction measurement of the ecological area to obtain a water area flow direction corresponding to the ecological area;

[0165] A direction included angle between the cleaning moving direction and the water area flow direction is determined, and an included angle influence value is determined based on the direction included angle;

[0166] A cleaning ratio corresponding to the rectangular cleaning area is determined based on the pixel number of each cleaning pixel point located in the rectangular cleaning area, and a ratio influence value is determined based on the cleaning ratio;

[0167] A cleaning buffer length is determined based on the included angle influence value and the ratio influence value, and the rectangular cleaning area is extended by a region corresponding to the cleaning buffer length along the termination cleaning line away from the starting cleaning line to obtain an updated rectangular cleaning area and termination cleaning line;

[0168] The first ship and the second ship are controlled to clean up the floating garbage in the rectangular cleaning area to the termination cleaning line along the cleaning moving direction.

[0169] For example, in the actual operation process of the embodiment, the floating garbage is transported by the trawl fence arranged between the first ship and the second ship to realize the corresponding cleaning and transporting process. During the transportation, the trawl fence causes a certain surface thrust to the floating garbage, so that the floating garbage is gathered in the trawl fence. Due to the generation of the surface thrust, the floating garbage has a moving speed towards the cleaning and transporting direction. Therefore, by only controlling the first ship and the second ship to move to the terminal cleaning line of the corresponding rectangular cleaning area, the floating garbage cannot be fully gathered, thereby causing the corresponding omission phenomenon.

[0170] In order to solve the above problem, the rectangular cleaning area needs to be correspondingly extended, and the new terminal cleaning line is obtained based on the updated rectangular cleaning area. The corresponding method steps can be as follows:

[0171] Firstly, it can be known that the influence dimension of the moving speed of the floating garbage includes the water flow direction and the area proportion of the corresponding floating garbage. Therefore, in order to respond to different data of the two dimensions, after the first ship and the second ship respectively reach the corresponding first cleaning point and second cleaning point, the line segment center point of the corresponding starting cleaning line is obtained, and the unmanned aerial vehicle is further controlled to fly to the line segment center point.

[0172] Then, the unmanned aerial vehicle can be controlled to measure the flow direction of the ecological area to obtain the water flow direction of the corresponding ecological area. When the floating garbage is cleaned and transported, the trawl fence drives the floating garbage to move towards the cleaning and transporting direction. In the natural scene, the floating garbage moves according to the naturally generated water flow direction. Therefore, in order to judge the influence of the water flow direction on the moving speed of the floating garbage, the direction angle between the water flow direction and the cleaning and transporting direction is determined, and the corresponding angle influence value is further determined based on the direction angle.

[0173] Further, in the above process, since the cleaning pixel points corresponding to each ecological sub-area in the to-be-cleaned collection are determined, the pixel number of all cleaning pixel points in the rectangular cleaning area can be obtained by adding the values. The cleaning area of all cleaning pixel points is obtained by multiplying the pixel number by the pixel area occupied by one pixel point. The cleaning ratio is obtained by ratio calculation of the cleaning area and the area of the rectangular cleaning area. The ratio influence value is further determined based on the cleaning ratio.

[0174] Then, the corresponding cleaning buffer length can be determined according to the obtained angle influence value and the proportion influence value, and the rectangular cleaning area is extended by the corresponding cleaning buffer length away from the starting cleaning line along the original termination line, so as to obtain the updated rectangular cleaning area including the buffer extension area and the termination cleaning line. Figure 3 Figure 3 It is shown that the corresponding ship cleans the floating garbage in the rectangular cleaning area. It can be seen from the content that the corresponding rectangular cleaning area includes the buffer extension area. Figure 3

[0175] Finally, the first ship and the second ship can be controlled to clean the floating garbage along the cleaning direction, that is, the corresponding cleaning buffer length is set to ensure that all floating garbage can be cleaned as much as possible, and the cleaning buffer length is obtained based on multi-dimensional data, which has certain data accuracy.

[0176] Further, in the embodiment, the cleaning buffer length can be obtained by the following formula:

[0177]

[0178] wherein, the L s is the cleaning buffer length, the A z is the direction angle, the a1 is the angle weight, the k z is the angle normalization value, the P n is the pixel number, the P a is the pixel area, the R a is the area of the corresponding rectangular cleaning area, the b1 is the proportion weight, and the k a is the proportion normalization value.

[0179] It should be noted that in the embodiment, the angle weight, pixel area, proportion weight, angle normalization value and proportion normalization value are pre-set and stored in the corresponding storage device, for example, in the server.

[0180] ​​Here, it can be known from the above that the above-mentioned cleaning buffer length is obtained based on the angle influence value and the proportion influence value, the angle influence value is obtained by multiplying the direction angle and the angle weight, and the proportion influence value is obtained by multiplying the cleaning proportion and the proportion weight. Based on this, since the morphological attribute determined by the numerical comparison result may have a certain deviation from the actual situation, in order to improve the corresponding determination accuracy, the respective weights can be updated and trained in real time to realize the process of updating and iterating the respective weights, and thus the corresponding determination accuracy can be continuously improved.

[0181] Here, the updating and iteration of the respective weights can be realized through the following scheme steps:

[0182] The method further comprises:

[0183] The actual buffer length sent by the management end based on the rectangular cleaning area is obtained, and the actual buffer length is compared with the cleaning buffer length;

[0184] If the actual buffer length is greater than the cleaning buffer length, the angle weight and the proportion weight are respectively increased and trained;

[0185] If the actual buffer length is less than the cleaning buffer length, the angle weight and the proportion weight are respectively decreased and trained;

[0186] The trained angle weight and proportion weight are obtained through the following formula:

[0187]

[0188] Wherein, q + is the number of times of increasing training of the angle weight α1, ∈ is the training constant value of the angle weight α1, q - is the number of times of decreasing training of the angle weight α1, α2 is the trained angle weight, v + is the number of times of increasing training of the proportion weight β1, δ is the training constant value of the proportion weight β1, v - is the number of times of decreasing training of the proportion weight β1, β2 is the trained proportion weight.

[0189] It should be noted that in the present embodiment, based on the above scheme steps, the floating garbage can be cleaned by the first ship and the second ship in the same cleaning ship group, and if the extension length of the corresponding rectangular cleaning area is too long, a long cleaning time will be generated, thereby reducing the cleaning efficiency. Therefore, the following method steps can be used to improve the cleaning efficiency:

[0190] determining an extension length corresponding to the rectangular collection region along the collection moving direction, and determining a collection attribute corresponding to the rectangular collection region based on a length comparison between the extension length and a preset length, wherein the collection attribute comprises a one-way attribute and a two-way attribute;

[0191] in response to the extension length being greater than or equal to the preset length, determining the rectangular collection region as a two-way attribute, and determining a region center line located at the center of the rectangular collection region and parallel to the terminal collection line;

[0192] determining the starting collection line and the terminal collection line as an updated first starting collection line and a second starting collection line respectively, and determining the region center line as an updated terminal collection line;

[0193] respectively controlling a first ship and a second ship located in different collection ship groups to move towards the first starting collection line and the second starting collection line respectively, and determining a collection ship group located at the first starting collection line as a first ship group and a collection ship group located at the second starting collection line as a second ship group;

[0194] respectively controlling each ship located in the first ship group to move along the collection moving direction and each ship located in the second ship group to move in a direction opposite to the collection moving direction to collect the floating garbage located in the rectangular collection region to the terminal collection line.

[0195] For example, in the present embodiment, when the obtained extension length is less than the preset length, it indicates that the extension length of the rectangular collection region is relatively short, that is, one collection ship group can meet the corresponding efficiency condition, and therefore, the collection attribute of the rectangular collection region can be determined as a one-way attribute. If the obtained extension length is greater than or equal to the preset length, it indicates that the extension length of the rectangular collection region is too long, that is, a longer collection time will be generated when one collection ship group is used to collect the floating garbage, and therefore, the collection attribute of the rectangular collection region can be determined as a two-way attribute, and two collection ship groups can be used to jointly collect the floating garbage located in the rectangular collection region.

[0196] That is, when the extension length is greater than or equal to the preset length, a region center line located at the center of the rectangular collection region and parallel to the terminal collection line can be determined, so that the starting collection line and the terminal collection line are determined as the updated first starting collection line and the second starting collection line, respectively, and the region center line is determined as the updated terminal collection line; after the update of the starting collection line and the terminal collection line is completed, two different collection ship groups can be controlled to move to the first starting collection line and the second starting collection line, respectively, to obtain a first ship group located at the first starting collection line and a second ship group located at the second starting collection line; finally, each ship in the first ship group and the second ship group can be controlled to move towards the terminal collection line while using different trawl fences, so as to collect the floating garbage in the rectangular collection region to the terminal collection line, so that the trawl fence can surround the floating garbage and complete the collection of the floating garbage, thereby improving the collection efficiency.

[0197] In summary, in the embodiment, the server controls the UAV to fly along the extension direction of the ecological region to determine whether there is floating garbage on the ecological region, and then determines a rectangular collection region surrounding the floating garbage, so that subsequent ships can accurately salvage the floating garbage. Then, the server obtains a rectangular center point corresponding to the rectangular collection region, and controls the UAV to move to the rectangular center point to monitor the rectangular collection region, so that the server can determine whether the ships reach the corresponding point and collect the floating garbage according to the obtained real-time monitoring data. Then, the server determines the extension direction corresponding to the rectangular collection region as a collection moving direction, and then determines two region contour lines perpendicular to the collection moving direction as a starting collection line and a terminal collection line, respectively. Then, the server determines two end point positions of the starting collection line as a first collection point and a second collection point, respectively, and controls a first ship and a second ship in the same collection ship group to move towards the first collection point and the second collection point, respectively. When the server determines that the first ship and the second ship reach the first collection point and the second collection point, respectively, through real-time monitoring data, the first ship and the second ship are controlled to collect the floating garbage in the rectangular collection region along the collection moving direction. The present application can reduce the time for salvaging floating garbage, thereby improving the salvaging efficiency, and can repair the ecological region to a certain extent.

[0198] Another embodiment of the present application provides an ecological environment data real-time monitoring system based on big data processing, Figure 4 The system includes:

[0199] The ecological patrol module is configured to determine a rectangular clean-up area surrounding the floating garbage according to the patrol data;

[0200] The direction determination module is configured to determine an extension direction corresponding to the rectangular clean-up area as a clean-up moving direction, and determine a region contour line of a region constituting the rectangular clean-up area and being perpendicular to the clean-up moving direction as a starting clean-up line and an ending clean-up line;

[0201] The movement control module is configured to determine an end point of the starting clean-up line as a first clean-up point and a second clean-up point, and control the first ship and the second ship to move towards the first clean-up point and the second clean-up point;

[0202] The clean-up control module is configured to control the first ship and the second ship to clean up the floating garbage to the ending clean-up line along the clean-up moving direction.

[0203] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

[0204] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

[0205] Similarly, it is to be understood that the various features of the inventive aspects sometimes described in the description of the exemplary embodiments of the application are to be considered individually or in any combination, as appropriate.

[0206] Those skilled in the art will understand that the modules or units or components of the devices in the examples disclosed herein can be arranged in a device as described in the examples, or alternatively can be located in one or more devices different from the devices in the examples. The modules in the foregoing examples can be combined as one module or further divided into multiple sub-modules.

[0207] Those skilled in the art will appreciate that the modules in the apparatuses in the embodiments can be adapted and placed in one or more apparatuses other than the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and furthermore can be divided into multiple sub-modules or sub-units or sub-components.

[0208] Furthermore, those skilled in the art will appreciate that the features of the various embodiments described herein are not mutually exclusive and can be combined in different embodiments.

[0209] Furthermore, some of the embodiments described herein are described as a method or combination of elements of a method implementable by a processor of a computer system or by other means of carrying out the function described by the method elements. Accordingly, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element of a method described herein functionally implements a means for implementing the corresponding function that is performed by an element of the method for the purpose of carrying out the invention.

[0210] As used herein, the ordinal numbers "first", "second", "third", etc. to describe common objects merely mean different instances of similar objects and are not intended to imply that the objects described must have a given order in time, space, ranking, or in any other manner, unless otherwise specified.

[0211] Although the present application is described in terms of limited number of embodiments, those skilled in the art will appreciate that other embodiments are contemplated in the scope of the present application described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes and can not have been selected to expressly convey the scope of the inventive subject matter.

Claims

1. A real-time monitoring method for ecological and environmental data based on big data processing, characterized in that, Includes the following steps: The rectangular collection area surrounding the floating garbage was determined based on the patrol data; The extension direction corresponding to the rectangular cleaning area is determined as the cleaning movement direction, and the outline of the area that makes up the rectangular cleaning area and is perpendicular to the cleaning movement direction is determined as the starting cleaning line and the ending cleaning line. The endpoints of the starting cleaning line are designated as the first and second cleaning points, and the first and second vessels are controlled to move toward the first and second cleaning points. Control the first and second vessels to move along the cleaning direction and transport the floating garbage to the termination cleaning line; Specifically, the extension direction corresponding to the rectangular cleaning area is defined as the cleaning movement direction, and the outline of the area constituting the rectangular cleaning area and perpendicular to the cleaning movement direction is defined as the starting cleaning line and the ending cleaning line, including: Obtain the outline of each area that makes up the rectangular cleaning area, and obtain the distance between each area outline and the ship berthing line of the corresponding ship dock to obtain each movement distance; The direction of extension perpendicular to the outline of the area with the smallest corresponding moving distance is determined as the cleaning and transportation moving direction, and the first outline dimension and the second outline dimension corresponding to the outline of the rectangular cleaning and transportation area are obtained in the direction perpendicular to and parallel to the cleaning and transportation moving direction. The first and second outline dimensions are compared with the corresponding trawl fence dimensions, and the direction adjustment coefficient is determined based on the comparison results. When the direction adjustment coefficient is greater than or equal to the preset coefficient, the extension direction perpendicular to the cleaning movement direction is determined as the updated cleaning movement direction; Obtain the outlines of each region perpendicular to the cleaning and transportation direction, and determine the outline of the region with the smallest corresponding movement distance as the termination cleaning line, and determine the outline of the region with the largest corresponding movement distance as the starting cleaning line; Specifically, the first and second contour dimensions are compared with the corresponding fencing dimensions of the trawl net fence, and a direction adjustment coefficient is determined based on the comparison results, including: When the first contour size is the same as the second contour size, the retrieved first reference coefficient is determined as the direction adjustment coefficient, wherein the first reference coefficient is less than the preset coefficient; or, When the first outline dimension is different from the second outline dimension, the difference between the first outline dimension and the second outline dimension and the fence dimension of the corresponding trawl fence is calculated to obtain the first difference corresponding to the first outline dimension and the second difference corresponding to the second outline dimension. When both the first difference and the second difference are non-positive, the retrieved first reference coefficient is determined as the direction adjustment coefficient; When the first difference is positive and the second difference is non-positive, the retrieved second reference coefficient is determined as the direction adjustment coefficient, wherein the second reference coefficient is greater than or equal to the preset coefficient; When both the first difference and the second difference are positive, the direction adjustment coefficient is determined by the following formula: ， in, This is the direction adjustment coefficient. This is the normalized value for the size. The first difference, The second difference; This includes controlling the first and second vessels to transport the floating debris along the removal direction to the termination line, including: In response to real-time monitoring data, the system determines that the first vessel and the second vessel have arrived at the first and second cleaning points, respectively. It then obtains the center point of the line segment corresponding to the starting cleaning line and controls the drone to fly to the center point of the line segment. When the drone flies to the center point of the line segment, it is triggered to perform flow direction measurement of the ecological area to obtain the water flow direction corresponding to the ecological area. Determine the directional angle between the cleaning and transport direction and the water flow direction, and determine the influence value of the directional angle based on the directional angle; The cleaning ratio corresponding to the rectangular cleaning area is determined based on the number of pixels of each cleaning pixel in the rectangular cleaning area, and the ratio influence value is determined based on the cleaning ratio. The cleaning buffer length is determined based on the included angle influence value and the proportional influence value, and the rectangular cleaning area is extended along the termination cleaning line away from the starting cleaning line in a manner corresponding to the cleaning buffer length, so as to obtain the updated rectangular cleaning area and the termination cleaning line. Control the first and second vessels to move along the designated cleaning direction and transport the floating garbage located in the rectangular cleaning area to the termination cleaning line.

2. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 1, characterized in that, Based on the patrol data, a rectangular collection area surrounding the floating debris was determined, including: Obtain the image acquisition size corresponding to the UAV, and perform array processing on the ecological region to obtain each ecological sub-region corresponding to the image acquisition size; Obtain the center point of each ecological sub-region and configure the UAV to perform patrol tasks based on the center points of each region; When the drone flies to the center point of any area, it is triggered to perform flow velocity measurement to obtain the water flow velocity corresponding to the ecological area. The ecological region attributes are determined based on the comparison between the water flow velocity and the retrieved preset flow velocity, and different preset floating debris identification strategies are configured based on different ecological region attributes. The ecological region attributes include stable attributes and turbulent attributes. Based on the preset floating waste identification strategy, each ecological sub-region is identified, and each ecological sub-region with floating waste is determined as a set to be cleared. Based on the relative positions of the ecological sub-regions located in the set to be cleared, the ecological sub-regions are merged to obtain the rectangular clearing area.

3. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 2, characterized in that, Based on the preset floating debris identification strategy, each ecological sub-region is identified, and each ecological sub-region containing floating debris is determined as a set to be cleared, including: When the ecological region attribute is stable, the drone is controlled to hover for a preset time and take a preset number of images of the ecological sub-region at the same time intervals within the preset time, so as to obtain an ecological region image composed of image frames with different corresponding frame orders. Each image frame is binarized, and each binarized image is pixel-recognized to obtain the individual image pixels that make up the same binarized image. In each image pixel, the corresponding water area pixel value is determined, and all other pixels except the water area pixel are determined as the cleaning pixel. Obtain the pixel ratio between each cleaning pixel in the same binarized image and each image pixel, and compare the ratio with the corresponding pixel ratios of each binarized image. The pixel ratio with the smallest corresponding pixel ratio is determined as the pixel ratio of the corresponding ecological area image, and each ecological sub-region with a corresponding pixel ratio greater than or equal to a preset ratio is determined as the set to be cleaned up.

4. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 2, characterized in that, Based on the preset floating debris identification strategy, each ecological sub-region is identified, and each ecological sub-region containing floating debris is determined as a set to be cleared, including: When the ecological region attribute of the ecological region is turbulent, the UAV is controlled to take an image of the ecological sub-region to obtain an image of the ecological region. The ecological area image is binarized, and the resulting binarized image is pixel-recognized to obtain the individual image pixels that make up the binarized image. In each image pixel, the corresponding water area pixel value is determined, and all other pixels except the water area pixel are determined as the cleaning pixel. Obtain the pixel ratio between each cleaning pixel in the same binarized image and each image pixel, and determine each ecological sub-region with a corresponding pixel ratio greater than or equal to a preset ratio as the set to be cleaned.

5. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 3 or 4, characterized in that, Based on the relative positions of the ecological sub-regions within the set to be cleared, the ecological sub-regions are merged to obtain the rectangular clearing area, including: Determine the location of each ecological sub-region in the ecological region within the set to be cleared, and based on the location of each region, divide the ecological sub-regions that are continuously connected into the same region division group, and divide the remaining ecological sub-regions into different region division groups to obtain each region division group; Establish a regional coordinate system corresponding to the ecological region, and obtain the coordinates of each cleaning pixel point corresponding to each ecological sub-region located in the same regional division group to obtain each cleaning coordinate point corresponding to each cleaning pixel point. Based on each cleaning coordinate point, the corresponding X-axis extreme coordinate point and the corresponding Y-axis extreme coordinate point are determined respectively. Based on the minimum bounding rectangle algorithm, a rectangular cleaning area is formed that covers at least one of the X-axis extreme coordinate points and the Y-axis extreme coordinate points and surrounds all the remaining cleaning coordinate points.

6. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 1, characterized in that, The length of the waste removal buffer is determined using the following formula: ， Among them, the For the length of the clearance buffer, the The angle between directions, the The angle weights to be retrieved, the The angle is the normalized value, the For the number of pixels, the For the pixel area, the For the area corresponding to the rectangular cleaning area, the For the proportional weighting to be retrieved, the This is the proportionally normalized value.

7. The method for real-time monitoring of ecological and environmental data based on big data processing according to claim 1, characterized in that, The method further includes: An extension length corresponding to the rectangular cleaning area is determined along the cleaning movement direction, and a cleaning attribute corresponding to the rectangular cleaning area is determined based on a length comparison between the extension length and a preset length, wherein the cleaning attribute includes a unidirectional attribute and a bidirectional attribute; In response to the extension length being greater than or equal to the preset length, the rectangular cleaning area is determined to have a bidirectional attribute, and the center line of the area located at the center of the rectangular cleaning area and parallel to the termination cleaning line is determined; The starting and ending waste collection lines are respectively designated as the updated first and second starting waste collection lines, and the center line of the area is designated as the updated ending waste collection line. The first and second vessels located in different cleaning vessel groups are controlled to move toward the first starting cleaning line and the second starting cleaning line, respectively, and the cleaning vessel group located at the first starting cleaning line is designated as the first vessel group and the cleaning vessel group located at the second starting cleaning line is designated as the second vessel group. Each vessel in the first vessel group is controlled to move along the cleaning direction, and each vessel in the second vessel group is controlled to move along the opposite direction to the cleaning direction, so as to clean up the floating garbage in the rectangular cleaning area to the termination cleaning line.

Images