Methods, apparatus, equipment and computer storage media for the analysis and disposal of floating debris

Abstract

This application discloses a method, apparatus, equipment, computer storage medium, and program product for analyzing and disposing of floating debris. The method includes: acquiring river and lake hydrological data, monitoring images, and acquisition coordinates; extracting and identifying features from the images to obtain the type, volume, and distance from the riverbank of the floating debris; calculating the flow velocity and direction of the water body based on the relationship between the river and lake hydrological data and the flow velocity and direction; simulating the movement process of the floating debris based on its acquisition coordinates, distance from the riverbank, and the flow velocity and direction of the water body to obtain its trajectory; inputting the river and lake hydrological data, floating debris volume, trajectory, flow velocity and direction, and floating debris type into a flood control analysis model and a water quality analysis model, respectively, to obtain the flood control impact area and the water quality impact area; and obtaining the disposal location and disposal time of the floating debris based on its trajectory, the flood control impact area, and the water quality impact area. The embodiments of this application achieve intelligent determination of the impact range and disposal method of floating debris.

Description

Technical Field

[0001] This application belongs to the field of river monitoring technology, and in particular relates to a method, device, equipment, computer storage medium, and program product for analyzing and disposing of floating debris. Background Technology

[0002] Floating debris in rivers and lakes is a prominent issue in river and lake management. It not only affects the aesthetics and ecological environment of rivers and lakes, but may also negatively impact water quality and flood control functions. Therefore, it is necessary to analyze and treat the floating debris in rivers and lakes.

[0003] Existing technologies for monitoring floating objects in rivers and lakes often rely on manual analysis and treatment or semi-intelligent analysis and treatment. Manual analysis and treatment methods involve manual patrols to analyze and treat floating objects, while semi-intelligent analysis and treatment methods involve video monitoring to detect floating objects and notify monitoring personnel for treatment. This solves the problem of detecting floating objects, but there are many types of floating objects and different impact ranges, making it difficult to intelligently determine the impact range and treatment methods of floating objects. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, computer storage medium, and program product for analyzing and disposing of floating objects, in order to solve the problem that the prior art is unable to intelligently determine the impact range and disposal method of floating objects.

[0005] In a first aspect, embodiments of this application provide a method for analyzing and disposing of floating debris, the method comprising:

[0006] Acquire floating object monitoring information and river and lake hydrological data. Floating object monitoring information includes floating object monitoring images and acquisition coordinates.

[0007] Extract and identify image features from floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating objects;

[0008] Calculate the flow velocity and flow direction at various points in the water body based on the relationship between river and lake hydrological data and water flow velocity and direction.

[0009] The motion process of the floating object is simulated by acquiring its coordinates from the image, its distance from the riverbank, and the flow velocity and direction at various points in the water body, thus obtaining the trajectory of the floating object.

[0010] River and lake hydrological data, floating object volume, and floating object movement trajectory are input into a preset flood discharge analysis model to obtain information on the flood discharge impact area;

[0011] By inputting river and lake hydrological data, flow velocity and direction at various points in the water body, type of floating objects and their movement trajectory into a preset water quality analysis model, information on the water quality impact area can be obtained.

[0012] The location and time for handling floating objects are determined based on their movement trajectory, information on the flood-affected area, and information on the water quality-affected area.

[0013] Secondly, embodiments of this application provide a floating matter analysis and disposal device, the device comprising:

[0014] The acquisition module is used to acquire floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and acquisition coordinates.

[0015] The identification module is used to extract and identify image features of floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating object;

[0016] The calculation module is used to calculate the flow velocity and flow direction at various points in a water body based on the relationship between river and lake hydrological data, water flow velocity, and flow direction.

[0017] The simulation module is used to simulate the movement of the floating object based on the image acquisition coordinates, distance from the riverbank, and flow velocity and direction at various points in the water, thereby obtaining the trajectory of the floating object.

[0018] The aggregation module is used to input river and lake hydrological data, floating object volume, and floating object movement trajectory into a preset flood control analysis model to obtain information on the flood control impact area;

[0019] The analysis module is used to input river and lake hydrological data, flow velocity and direction at various points in the water body, floating object type and movement trajectory into a preset water quality analysis model to obtain information on the water quality impact area;

[0020] The processing module is used to obtain the disposal location and disposal time of floating objects based on the movement trajectory of the floating objects, information on the flood impact area, and information on the water quality impact area.

[0021] Thirdly, embodiments of this application provide a terminal device, the device including: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the floating object analysis and disposal method as described in the first aspect.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the floating object analysis and disposal method as described in the first aspect.

[0023] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform the floating matter analysis and disposal method as described in the first aspect.

[0024] This application provides a method, apparatus, equipment, computer storage medium, and program product for analyzing and handling floating debris. It acquires floating debris monitoring information and river / lake hydrological data. The floating debris monitoring information includes floating debris monitoring images and acquisition coordinates, providing necessary basic data for subsequent floating debris movement simulation and water quality analysis. It extracts and identifies image features from the floating debris monitoring images to obtain the type, volume, and distance of the floating debris from the riverbank, accurately and quickly determining the type, volume, and distance of the floating debris, improving data processing efficiency and accuracy. It calculates the flow velocity and direction at various points in the water body based on the relationship between river / lake hydrological data, water flow velocity, and flow direction. Finally, it calculates the image acquisition coordinates of the floating debris, its distance from the riverbank, and the coordinates of various points in the water body. The flow velocity and direction are simulated to obtain the movement process of floating objects and their trajectories. River and lake hydrological data, floating object volume, and floating object trajectory are input into a preset flood control analysis model to obtain information on the flood control impact area. River and lake hydrological data, flow velocity and direction at various points in the water body, floating object type, and floating object trajectory are input into a preset water quality analysis model to obtain information on the water quality impact area. Based on the floating object trajectory, flood control impact area information, and water quality impact area information, the disposal location and disposal time of floating objects are obtained. This can optimize the allocation of cleanup resources and the disposal efficiency of floating objects, and enable targeted disposal of floating objects with different impacts, realizing intelligent determination of the impact range and disposal method of floating objects. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the system structure that can implement the floating matter analysis and disposal method provided in the embodiments of this application;

[0027] Figure 2 This is a schematic flowchart of the floating matter analysis and disposal method provided in the embodiments of this application;

[0028] Figure 3 This is a schematic diagram of river segment division provided in the embodiments of this application.

[0029] Figure 4 This is a schematic diagram of the structure of the floating matter analysis and disposal device provided in the embodiment of the North Application;

[0030] Figure 5 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0031] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0033] The existing management of floating debris in rivers and lakes faces several problems: Firstly, there are many types of floating debris, including garbage, small structures, algal blooms, water hyacinth, and various plants and animals, with diverse forms, making it difficult to automatically identify the different impact areas. For example, small garbage may affect the residential environment and water quality, small structures may cause river blockages, algal blooms and water hyacinths may affect water quality, and plants and animals may also impact water quality. Secondly, floating debris gradually accumulates with the flow of water, changing its shape or decomposing, significantly impacting water quality maintenance and flood control. Thirdly, the disposal of floating debris is difficult to determine precisely; it is challenging to intelligently determine when to clean it up, which section of the river is responsible for cleaning it, given its movement.

[0034] The analysis and handling of floating debris in rivers and lakes mainly includes manual analysis and handling and semi-automatic analysis and handling. Manual analysis and handling involves manual river patrols. When floating debris is found, historical experience is used to determine the type of floating debris, the potential problems it may cause, and the best handling method. However, problems can only be discovered through manual patrols, and floating debris is constantly moving, making it even more difficult to spot. Whether floating debris affects water quality, whether it will gradually accumulate to form larger pieces, and whether it will affect flood control are all subject to change as the floating debris moves and its shape changes, making precise judgment difficult. Rivers often span districts, cities, and even provinces, and river management is generally divided into multiple river sections, each with different responsible persons. Floating debris is constantly moving with the water flow, changing continuously as the flow rate varies from river to river and from river section to river section. Therefore, it is difficult to accurately determine which river section and at which time the floating debris should be intercepted. Semi-intelligent analysis and handling involves establishing video perception at the river's upstream end, automatically identifying floating objects and generating warnings through video AI analysis, and then manually analyzing the warning situation and analyzing the potential problems and best handling methods based on historical experience. However, the problems of accurately determining the scope of impact and the optimal handling location and time still exist.

[0035] The following section first illustrates a system framework for applying the floating matter analysis and disposal method provided in the embodiments of this application.

[0036] like Figure 1 As shown, the system may include a perception module, an AI recognition module, a model calculation module, a space management module, a basic information management module, and an intelligent analysis and processing module; the perception module is connected to the AI ​​recognition module and the model calculation module, the AI ​​recognition module is connected to the model calculation module, the model calculation module is connected to the space management module, the basic information management module, and the intelligent analysis and processing module, and the intelligent analysis and processing module is connected to the basic information management module and the space management module.

[0037] The perception module includes a video perception unit, a water level perception unit, a water quality perception unit, and a water flow perception unit, used to capture real-time video images of the river, detect the river's water level, water quality, and the speed and direction of the water flow, respectively. The AI ​​recognition module includes a general floating object recognition unit, a floating object volume recognition unit, a floating object type recognition unit, and a river / lake distance recognition unit, used to identify floating objects, their volume, type, and distance from the riverbank or lake shore, respectively. The model calculation module includes a hydrodynamic algorithm unit, a floating object accumulation algorithm unit, a flood discharge algorithm unit, a water quality impact algorithm unit, a floating object flow algorithm unit, and an algal bloom diffusion algorithm unit, used to simulate hydrodynamics, predict floating object accumulation, assess the impact of floating objects on floods, assess the impact of floating objects on water quality, simulate the trajectory of floating objects, and simulate the diffusion impact of phytoplankton, respectively. The spatial management module includes a river channel demarcation spatial management unit, a river segment demarcation spatial management unit, a flood control point spatial management unit, and a perception spatial management unit, used to demarcate river channels, demarcate river segments, determine key locations for flood control, and manage sensing equipment, respectively. The basic information management module includes a river / lake section basic information unit, a responsible person basic information unit, and a river section responsible person relationship unit, which are used to store information about the river section, basic information about the responsible person, and the relationship between the responsible person and the corresponding river section, respectively. The intelligent analysis and disposal module includes an impact type analysis unit, an impact range analysis unit, a disposal responsible person analysis unit, an optimal disposal time analysis unit, and an optimal disposal location analysis unit, which are used to determine the impact type, impact range, responsible person for disposal, and the time and location of disposal of the floating debris, respectively.

[0038] To address the shortcomings of existing technologies, this application provides a method for analyzing and handling floating debris. The method involves acquiring floating debris monitoring information and river / lake hydrological data. The floating debris monitoring information includes monitoring images and acquisition coordinates, providing necessary foundational data for subsequent floating debris movement simulation and water quality analysis. Image features of the floating debris monitoring images are extracted and identified to obtain the type, volume, and distance of the floating debris from the riverbank. This allows for accurate and rapid determination of the floating debris's type, volume, and distance, improving data processing efficiency and accuracy. The method calculates the flow velocity and direction at various points in the water body based on the relationship between river / lake hydrological data, water flow velocity, and flow direction. Finally, the method uses the image acquisition coordinates of the floating debris, its distance from the riverbank, and the flow velocity and direction at various points in the water body as the basis for its analysis. The system simulates the movement of floating objects to obtain their trajectories. River and lake hydrological data, floating object volume, and trajectories are input into a pre-defined flood control analysis model to obtain information on the flood impact area. Similarly, river and lake hydrological data, flow velocity and direction at various points in the water body, floating object type, and trajectories are input into a pre-defined water quality analysis model to obtain information on the water quality impact area. Based on the floating object trajectories, flood impact area information, and water quality impact area information, the system determines the disposal location and time for floating objects. This optimizes the allocation of cleanup resources and the efficiency of floating object disposal, enabling targeted disposal of floating objects with different impacts and achieving intelligent determination of the impact range and disposal methods.

[0039] The following describes the floating matter analysis and disposal method provided in the embodiments of this application.

[0040] Figure 2 A schematic flowchart of a floating debris analysis and disposal method according to an embodiment of this application is shown. Figure 2 As shown, the method may include the following steps: S201 to S207.

[0041] S201, acquire floating object monitoring information and river and lake hydrological data. Floating object monitoring information includes floating object monitoring images and acquisition coordinates.

[0042] In some embodiments, images of floating objects can be acquired via drones, satellites, or fixed cameras.

[0043] S202, extract and identify image features from the floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating object.

[0044] In some embodiments, before extracting and identifying image features of the floating object monitoring image, the detection image is preprocessed, which may include operations such as noise reduction, contrast enhancement, color correction, and background removal.

[0045] In some embodiments, image features of floating object monitoring images can be extracted and identified using a Mask R-CNN, a YOLO model, or a U-Net.

[0046] S203, calculate the flow velocity and flow direction at various points in the water body based on the relationship between river and lake hydrological data and water flow velocity and direction.

[0047] In some embodiments, when calculating the velocity and direction of water at various points in a water body based on river and lake hydrological data and the relationship between water velocity and direction, the Saint-Venant equation or shallow water equation can be used to simulate the flow process of the water body and obtain the velocity and direction of water at various points in the water body.

[0048] S204. Based on the image acquisition coordinates of the floating object, its distance from the riverbank, and the flow velocity and direction at various points in the water, the motion process of the floating object is simulated to obtain its trajectory.

[0049] By considering the flow velocity and direction at various points in the water body, the movement of floating objects with the water flow can be dynamically simulated. Using image acquisition coordinates and actual measurement data from the riverbank, the trajectory of floating objects can be predicted, thus improving the accuracy of the simulation.

[0050] S205 inputs river and lake hydrological data, floating object volume, and floating object movement trajectory into a preset flood discharge analysis model to obtain information on the flood discharge impact area.

[0051] By combining the volume and trajectory of floating debris, the impact on the flood discharge capacity of rivers can be simulated, and areas that may have increased flood risk due to the accumulation of floating debris can be identified, which can provide decision support for flood emergency management.

[0052] S206 inputs river and lake hydrological data, flow velocity and direction at various points in the water body, floating object type and movement trajectory into a preset water quality analysis model to obtain information on the water quality impact area.

[0053] By combining river and lake hydrological data, water flow velocity and direction, and information on floating objects, water quality analysis models can accurately predict the areas affected by floating objects and help identify the affected water areas.

[0054] S207: Based on the movement trajectory of the floating object, information on the flood-affected area, and information on the water quality-affected area, the disposal location and disposal time of the floating object are obtained.

[0055] In some embodiments, based on the movement trajectory of the floating object, the upstream location of a set distance between the flood impact area and the water quality impact area is determined as the disposal location of the floating object, and the time when the floating object moves to the disposal location is predicted based on the movement trajectory of the floating object as the disposal time.

[0056] In some embodiments, if floating objects are not disposed of in a timely manner at the disposal time and disposal location, the tracking and analysis continue to obtain the next disposal time and disposal location until disposal is completed.

[0057] The floating debris analysis and disposal method provided in this application acquires floating debris monitoring information and river and lake hydrological data. The floating debris monitoring information includes floating debris monitoring images and acquisition coordinates, providing necessary basic data for subsequent floating debris movement simulation and water quality analysis. The method extracts and identifies image features from the floating debris monitoring images to obtain the type, volume, and distance of the floating debris from the riverbank, enabling accurate and rapid determination of the type, volume, and distance of the floating debris, thus improving data processing efficiency and accuracy. Based on the relationship between river and lake hydrological data, water flow velocity, and flow direction, the method calculates the flow velocity and flow direction at various points in the water body. Finally, the method simulates the floating debris based on the image acquisition coordinates, distance from the riverbank, and flow velocity and flow direction at various points in the water body. During the movement process, the trajectory of the floating object is obtained; river and lake hydrological data, floating object volume, and floating object trajectory are input into a preset flood control analysis model to obtain information on the flood control impact area; river and lake hydrological data, flow velocity and direction at various points in the water body, floating object type, and floating object trajectory are input into a preset water quality analysis model to obtain information on the water quality impact area; based on the floating object trajectory, flood control impact area information, and water quality impact area information, the disposal location and disposal time of the floating object are obtained, which can optimize the allocation of cleanup resources and the disposal efficiency of floating objects, and enable targeted disposal of floating objects with different impacts, realizing intelligent determination of the impact range and disposal method of floating objects.

[0058] In some embodiments, image features of floating object monitoring images are extracted and identified to obtain the type, volume, and distance from the riverbank of the floating object, including:

[0059] A convolutional neural network is used to extract features from and identify floating object monitoring images to determine the type of floating object.

[0060] Segment the outline of the floating object and generate a pixel-level mask for the floating object. The pixel-level mask represents the two-dimensional outline information of the floating object.

[0061] The volume of the floating object is obtained by reconstructing its 3D model based on the pixel-level mask of the floating object.

[0062] Based on the position of the floating object in the image and the preset pixel depth value, a three-dimensional reconstruction of the space where the floating object is located is performed to obtain the distance of the floating object from the shore. The pixel depth value represents the straight-line distance from the camera that took the image to each point in the image.

[0063] By automating image recognition and analysis, the system can quickly process large amounts of data, reducing the time and cost of manual monitoring. By generating pixel-level masks and 3D reconstruction, the system can provide detailed outlines, volume information, and distance information from the riverbank of floating objects, thus improving recognition accuracy.

[0064] In some embodiments, the volume of the floating object is obtained by reconstructing a 3D model of the floating object based on a pixel-level mask.

[0065] Convert pixels to actual physical size based on a preset relationship between pixels and actual physical size;

[0066] Based on pixel-level masks, each pixel in an image is converted into a point cloud in three-dimensional space, and each point cloud represents the corresponding position of the pixel in three-dimensional space.

[0067] Reconstructing a 3D model of a floating object using a 3D reconstruction algorithm based on point cloud;

[0068] The volume of the floating object is obtained by calculating the volume of the reconstructed 3D model.

[0069] By converting pixel-level masks to actual physical dimensions, precise positioning and size measurement of floating objects can be achieved, enabling a more comprehensive reconstruction of the three-dimensional model of the floating objects.

[0070] In some embodiments, river and lake hydrological data includes topographic information, water depth, initial flow velocity, and initial flow direction of the water body. Calculating the flow velocity and flow direction at various points in the water body based on the relationship between the river and lake hydrological data and the flow velocity and flow direction includes:

[0071] The water body is divided into multiple calculation units based on its topographic information.

[0072] A set of hydrodynamic equations is established for each computational unit based on the topographic information, water depth, initial flow velocity, and initial flow direction of the water body.

[0073] Solving the system of hydrodynamic equations yields the velocity and direction of flow at various points in the water body.

[0074] By considering factors such as topographic information, water depth, initial flow velocity, and initial flow direction of the water body, the flow velocity and flow direction at various points in the water body can be calculated more accurately. This method is applicable to different types of water bodies and improves the accuracy of the simulation results.

[0075] In some embodiments, the topographic information of a water body can be divided into deep water areas, shallow waters, riverbanks, etc.

[0076] In one example, such as Figure 3As shown, the river is divided into three sections, A, B, and C, based on different water topographic information. The dark areas in the figure represent deeper terrain. Sections AC are meandering sections of the river, with faster flow speeds and more complex flow directions. The terrain is deeper on the convex bank and shallower on the concave bank. This section is more prone to the accumulation and diffusion of drifting debris. Section B is a straight section with relatively uniform flow speeds and a consistent flow direction along the river channel, without local acceleration caused by topography.

[0077] In some embodiments, a set of hydrodynamic equations is established for each computational unit based on the topographic information, water depth, initial flow velocity, and initial flow direction of the water body. This can be:

[0078]

[0079] Where h is the water depth, u is the flow velocity, t is the time, x is the spatial coordinate, g is the gravitational acceleration, f is the set damping coefficient, α is the initial flow direction of the water body, and θ is the flow direction angle of the water body.

[0080] In some embodiments, the motion process of the floating object is simulated based on the image acquisition coordinates of the floating object, its distance from the riverbank, and the flow velocity and direction at various points in the water body to obtain the trajectory of the floating object, including:

[0081] Based on the image acquisition coordinates of the floating object and its distance from the riverbank, initialize the initial position, initial velocity, and initial direction of the Lagrange particles representing the floating object in the water.

[0082] The velocity, direction, initial position, initial velocity, and initial direction of the particles at each point in the water body are used to determine the particle's velocity, direction, and position at the next time point.

[0083] The position of the particle at each time point is repeatedly calculated and updated to the next time point, based on the particle's position, velocity, direction, and the flow velocity and direction of the water at each point in the body, thus obtaining the trajectory of the floating object.

[0084] Taking into account multiple factors such as the location of floating objects, water flow velocity, and flow direction, the movement of floating objects can be comprehensively analyzed. By continuously updating the position, velocity, and direction of particles at the next time point, the movement trajectory of floating objects can be tracked in real time, and the location information of floating objects can be fed back in a timely manner.

[0085] In some embodiments, river and lake hydrological data, floating object volume, and floating object trajectory are input into a preset flood control analysis model to obtain the flood impact area, including:

[0086] The location of a floating object is determined based on its motion trajectory.

[0087] Cluster the locations of all floating objects to obtain the water areas where floating objects gather.

[0088] The area where the volume of floating debris in the water body exceeds a set threshold is designated as the flood impact area.

[0089] By obtaining the location of floating objects based on their movement trajectories, it is possible to accurately determine the location where floating objects gather, thereby more precisely identifying the flood-affected area and providing early warning of the potential flood impact range.

[0090] In some embodiments, river and lake hydrological data, flow velocity and direction at various points in the water body, types of floating objects, and the movement trajectories of floating objects are input into a preset water quality analysis model to obtain the water quality impact area, including:

[0091] When the floating matter is a pollutant, the pollutant diffusion amount is calculated based on the relationship between the pollutant concentration at each time point, the flow velocity at each point in the water body, and the pollutant diffusion amount.

[0092] Water bodies with pollutant diffusion rates exceeding a set threshold are designated as water quality impact zones.

[0093] By comprehensively utilizing information such as river and lake hydrological data, water flow velocity, flow direction, and the movement trajectory of floating objects, the propagation process of pollutants in water bodies can be fully analyzed, providing comprehensive data support for water quality analysis. This allows for accurate calculation of the diffusion of pollutants in water bodies and improves the accuracy of the water quality impact area.

[0094] In some embodiments, the relationship between pollutant concentration, flow velocity at various points in the water body, and pollutant diffusion rate is as follows:

[0095]

[0096] Where J is the amount of pollutant diffusion, D is the pollutant diffusion coefficient, C is the pollutant concentration, x is the spatial coordinate, and v is the water flow velocity.

[0097] In some embodiments, the river and lake hydrological data further include light intensity, temperature, pH value, and nutrient concentration. When the pollutant is phytoplankton, before calculating the pollutant diffusion amount based on the relationship between pollutant concentration at each time point, flow velocity at each point in the water body, and pollutant diffusion amount, the method includes:

[0098] The pollutant concentration at each time point was calculated based on the relationship between light intensity, temperature, pH value, nutrient concentration and pollutant concentration. The pollutant concentration is the phytoplankton concentration.

[0099] By calculating phytoplankton concentration based on the relationship between pollutant concentration and hydrological factors, we can predict the spread of phytoplankton, assess potential phytoplankton aggregation areas in water bodies, and identify potential water quality risks in advance.

[0100] In some embodiments, the relationship between light intensity, temperature, pH value, nutrient concentration, and pollutant concentration can be:

[0101]

[0102] Where C is the pollutant concentration, μ is the preset photosynthetic rate, I is the light intensity, γ is the natural mortality rate, λ is the influence coefficient of the preset nutrient concentration, N is the nutrient concentration, α is the temperature influence coefficient, T is the temperature, β is the pH influence coefficient, and Ph is the pH value of the water body.

[0103] In some embodiments, obtaining the disposal location and disposal time of the floating object based on the movement trajectory of the floating object, information on the flood impact area, and information on the water quality impact area further includes:

[0104] Obtain basic data on those responsible for river and lake management, as well as data on the relationship between river sections and those responsible. By analyzing the relationship between those responsible for river and lake management and their corresponding river sections, the location and time of any action to be taken will be sent to the relevant responsible party for processing.

[0105] Figure 4 This is a schematic diagram of a floating debris analysis and disposal device provided in an embodiment of this application. Figure 4 As shown, the device may include an acquisition module 401, an identification module 402, a calculation module 403, a simulation module 404, an aggregation module 405, an analysis module 406, and a processing module 407.

[0106] The acquisition module 401 is used to acquire floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and acquisition coordinates.

[0107] The identification module 402 is used to extract and identify image features of floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating object;

[0108] Calculation module 403 is used to calculate the flow velocity and flow direction at various points in the water body based on the relationship between river and lake hydrological data, water flow velocity and flow direction;

[0109] The simulation module 404 is used to simulate the motion process of the floating object based on the image acquisition coordinates, distance from the riverbank, and flow velocity and direction at various points in the water body, and to obtain the motion trajectory of the floating object.

[0110] The aggregation module 405 is used to input river and lake hydrological data, floating object volume, and floating object movement trajectory into a preset flood control analysis model to obtain information on the flood control impact area;

[0111] Analysis module 406 is used to input river and lake hydrological data, flow velocity and direction at various points in the water body, floating object type and movement trajectory of floating object into a preset water quality analysis model to obtain information on the water quality impact area;

[0112] The processing module 407 is used to obtain the disposal location and disposal time of the floating object based on the movement trajectory of the floating object, the information of the flood impact area, and the information of the water quality impact area.

[0113] In some embodiments, the identification module is further configured to use a convolutional neural network to extract and identify features from floating object monitoring images to obtain the type of floating object;

[0114] The recognition module is also used to segment the outline of the floating object and generate a pixel-level mask of the floating object. The pixel-level mask represents the two-dimensional outline information of the floating object.

[0115] The calculation module is also used to reconstruct the 3D model of the floating object based on the pixel-level mask of the floating object, and obtain the volume of the floating object;

[0116] The calculation module is also used to perform three-dimensional reconstruction of the space where the floating object is located based on the position of the floating object in the image and the preset pixel depth value, and to obtain the distance of the floating object from the shore. The pixel depth value represents the straight-line distance from the camera that took the image to each point in the image.

[0117] In some embodiments, the river and lake hydrological data includes the topographic information of the water body, water depth, initial flow velocity and initial flow direction, and the calculation module is also used to divide the water body into multiple calculation units according to the topographic information of the water body;

[0118] The calculation module is also used to establish a set of hydrodynamic equations for each calculation unit based on the topographic information, water depth, initial flow velocity, and initial flow direction of the water body;

[0119] The calculation module is also used to solve the hydrodynamic equations to obtain the flow velocity and direction at various points in the water body.

[0120] In some embodiments, the simulation module is further configured to initialize the initial position, initial velocity, and initial direction of the Lagrange particles representing the floating objects in the water body based on the image acquisition coordinates of the floating objects and their distance from the riverbank.

[0121] The calculation module is also used to determine the velocity, direction and position of the particles at the next time point based on the flow velocity, flow direction, initial position, initial velocity and initial direction of the particles at each point in the water body;

[0122] The calculation module is also used to repeatedly calculate and update the position of the particle at the next time point based on the particle's position, velocity, direction, and the flow velocity and direction at various points in the water body at each time point, so as to obtain the trajectory of the floating object.

[0123] In some embodiments, the acquisition module is further configured to acquire the position where the floating object stops based on the motion trajectory of the floating object;

[0124] The aggregation module is also used to cluster the locations where all floating objects remain to obtain the water areas where floating objects gather.

[0125] The analysis module is also used to identify areas where the volume of floating debris in a water body exceeds a set threshold as areas affected by flooding.

[0126] In some embodiments, the calculation module is also used to calculate the amount of pollutant diffusion based on the relationship between pollutant concentration at each time point, flow velocity at each point in the water body, and pollutant diffusion when the floating object type is a pollutant.

[0127] The analysis module is also used to identify water bodies where the amount of pollutant diffusion exceeds a set threshold as areas affected by water quality.

[0128] In some embodiments, the river and lake hydrological data also include light intensity, temperature, pH value and nutrient concentration. When the pollutant is phytoplankton, the calculation module is also used to calculate the pollutant concentration at each time point based on the relationship between light intensity, temperature, pH value, nutrient concentration and pollutant concentration, where the pollutant concentration is the phytoplankton concentration.

[0129] Figure 4 The various modules in the illustrated device can achieve Figure 2 The various steps involved, and the corresponding technical effects achieved, will not be elaborated upon here for the sake of brevity.

[0130] Figure 5 A schematic diagram of the hardware structure of the terminal device provided in an embodiment of this application is shown.

[0131] The terminal device may include a processor 501 and a memory 502 storing computer program instructions.

[0132] Specifically, the processor 501 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0133] Memory 502 may include mass storage for data or instructions. For example, and not limitingly, memory 502 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 502 may include removable or non-removable (or fixed) media, or memory 502 may be non-volatile solid-state storage. Memory 502 may be internal or external to the integrated gateway disaster recovery device.

[0134] In one example, memory 502 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the floating object analysis and disposal method according to this disclosure.

[0135] The processor 501 reads and executes computer program instructions stored in the memory 502 to achieve... Figure 2 The floating debris analysis and disposal method in the illustrated embodiment.

[0136] In one example, the terminal device may also include a communication interface 503 and a bus 504. Wherein, for example... Figure 5 As shown, the processor 501, memory 502, and communication interface 503 are connected through bus 504 and complete communication with each other.

[0137] The communication interface 503 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0138] Bus 504 includes hardware, software, or both, that couples components of an end device together. For example, and not as a limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 504 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0139] Furthermore, in conjunction with the floating debris analysis and disposal methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the floating debris analysis and disposal methods in the above embodiments.

[0140] This application also provides a computer program product, including a computer program, which, when executed, implements any of the floating debris analysis and disposal methods described in the above embodiments.

[0141] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0142] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or text segments used to perform the required tasks. Programs or text segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Text segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0143] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0144] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0145] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for analyzing and disposing of floating debris, characterized in that, include: Acquire floating object monitoring information and river and lake hydrological data, wherein the floating object monitoring information includes floating object monitoring images and the image acquisition coordinates of the floating objects; Extract and identify image features from floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating objects; Calculate the flow velocity and flow direction at various points in the water body based on the relationship between river and lake hydrological data and water flow velocity and direction. The motion process of the floating object is simulated by acquiring its coordinates from the image, its distance from the riverbank, and the flow velocity and direction at various points in the water body, thus obtaining the trajectory of the floating object. By inputting river and lake hydrological data, the volume of floating objects, and the movement trajectory of floating objects into a preset flood discharge analysis model, information on the flood discharge impact area can be obtained. By inputting river and lake hydrological data, flow velocity and direction at various points in the water body, type of floating objects and their movement trajectory into a preset water quality analysis model, information on the water quality impact area can be obtained. The location and time for handling floating objects are determined based on their movement trajectory, information on the flood-affected area, and information on the water quality-affected area.

2. The method for analyzing and disposing of floating debris according to claim 1, characterized in that, Extract and identify image features from floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating objects, including: A convolutional neural network is used to extract and identify image features from floating object monitoring images to determine the type of floating object. The outline of the floating object is segmented to generate a pixel-level mask of the floating object, wherein the pixel-level mask represents the two-dimensional outline information of the floating object; The volume of the floating object is obtained by reconstructing its 3D model based on the pixel-level mask of the floating object. Based on the position of the floating object in the floating object monitoring image and the preset pixel depth value, a three-dimensional reconstruction of the space where the floating object is located is performed to obtain the distance of the floating object from the riverbank. The pixel depth value represents the straight-line distance from the camera that took the image to each point in the image.

3. The method for analyzing and disposing of floating matter according to claim 1, characterized in that, The river and lake hydrological data includes topographic information, water depth, initial flow velocity, and initial flow direction of the water body. Based on the relationship between the river and lake hydrological data and the flow velocity and direction of the water body, the flow velocity and direction at various points in the water body are calculated, including: The water body is divided into multiple calculation units based on its topographic information. A set of hydrodynamic equations is established for each computational unit based on the topographic information, water depth, initial flow velocity, and initial flow direction of the water body. Solving the set of hydrodynamic equations yields the flow velocity and direction at various points in the water body.

4. The method for analyzing and disposing of floating debris according to claim 1, characterized in that, The process of simulating the movement of a floating object by acquiring its image coordinates, distance from the riverbank, and the flow velocity and direction at various points in the water body, thereby obtaining the object's trajectory, includes: Based on the image acquisition coordinates of the floating object and its distance from the riverbank, initialize the initial position, initial velocity, and initial direction of the Lagrange particles representing the floating object in the water. The velocity, direction, initial position, initial velocity, and initial direction of the particles at each point in the water body are used to determine the particle's velocity, direction, and position at the next time point. The position of the particle at each time point is repeatedly calculated and updated to the next time point, based on the particle's position, velocity, direction, and the flow velocity and direction of the water at each point in the body, thus obtaining the trajectory of the floating object.

5. The method for analyzing and disposing of floating matter according to claim 1, characterized in that, River and lake hydrological data, the volume of floating debris, and the trajectory of floating debris are input into a pre-set flood control analysis model to obtain the flood impact area, including: The location of a floating object is determined based on its motion trajectory. Clustering is performed based on the location of all floating objects to obtain the water body areas where floating objects gather. The area where the volume of floating debris in the water body exceeds a set threshold is designated as the flood impact area.

6. The method for analyzing and disposing of floating debris according to claim 1, characterized in that, The process involves inputting river and lake hydrological data, flow velocity and direction at various points in the water body, type of floating debris, and the trajectory of floating debris into a preset water quality analysis model to obtain the water quality impact area, including: When the floating matter is a pollutant, the pollutant diffusion amount is calculated based on the relationship between the pollutant concentration at each time point, the flow velocity at each point in the water body, and the pollutant diffusion amount. Water bodies with pollutant diffusion rates exceeding a set threshold are designated as water quality impact zones.

7. The method for analyzing and disposing of floating matter according to claim 6, characterized in that, The river and lake hydrological data also include light intensity, temperature, pH value, and nutrient concentration. When the pollutant is phytoplankton, before calculating the pollutant diffusion amount based on the relationship between pollutant concentration at each time point, flow velocity at various points in the water body, and pollutant diffusion amount, the method includes: The pollutant concentration at each time point was calculated based on the relationship between light intensity, temperature, pH value, nutrient concentration and pollutant concentration, and the pollution concentration was the phytoplankton concentration.

8. A floating matter analysis and disposal device, characterized in that, The device includes: The acquisition module is used to acquire floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and the image acquisition coordinates of the floating objects. The identification module is used to extract and identify image features of floating object monitoring images to obtain the type, volume, and distance from the riverbank of the floating object; The calculation module is used to calculate the flow velocity and flow direction at various points in a water body based on the relationship between river and lake hydrological data, water flow velocity, and flow direction. The simulation module is used to simulate the movement of the floating object based on the image acquisition coordinates, distance from the riverbank, and flow velocity and direction at various points in the water, thereby obtaining the trajectory of the floating object. The aggregation module is used to input river and lake hydrological data, the volume of floating objects, and the movement trajectory of floating objects into a preset flood control analysis model to obtain information on the flood control impact area; The analysis module is used to input river and lake hydrological data, flow velocity and direction at various points in the water body, type of floating objects and movement trajectory of floating objects into a preset water quality analysis model to obtain information on the water quality impact area; The processing module is used to obtain the disposal location and disposal time of floating objects based on the movement trajectory of the floating objects, information on the flood impact area, and information on the water quality impact area.

9. A terminal device, characterized in that, The device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the floating debris analysis and disposal method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the floating debris analysis and disposal method as described in any one of claims 1-7.

11. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the floating matter analysis and disposal method as described in any one of claims 1-7.

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