Floating object analysis and disposal method, device and equipment and computer storage medium

Abstract

The invention discloses a floating object analysis and disposal method, device and equipment, a computer storage medium and a program product. The method comprises the steps that river and lake hydrograph data, monitoring images and acquisition coordinates are acquired; extracting and identifying the features of the image to obtain the type and volume of the floating object and the distance from the floating object to the river bank; calculating the flow velocity and flow direction of the water according to the river and lake hydrograph data and the relationship between the flow velocity and flow direction of the water; simulating the movement process of the floaters according to the collection coordinates of the floaters, the distance from the river bank and the water flow velocity and flow direction to obtain the movement track of the floaters; respectively inputting the river and lake hydrograph data, the volume and the motion trail of the floating object, the flow velocity and the flow direction of the water body and the type of the floating object into a flood discharge analysis model and a water quality analysis model to obtain a flood discharge influence area and a water quality influence area; and obtaining the disposal position and the disposal time of the floating object according to the floating object movement track, the flood discharge influence area and the water quality influence area. According to the embodiment of the invention, intelligent judgment of the influence range and the disposal mode of the floating object is realized.

Description

Technical Field

[0001] The present application belongs to the field of river monitoring technology, and in particular, relates to a floating object analysis and disposal method, device, equipment, computer storage medium, and program product. Background Art

[0002] Floating objects in rivers and lakes are a more prominent problem in river and lake management. They not only affect the beauty and ecological environment of rivers and lakes, but may also have a negative impact on water quality and flood control functions. Therefore, it is necessary to analyze and deal with floating objects in rivers and lakes.

[0003] Existing technologies often use manual analysis and disposal and semi-intelligent analysis and disposal to monitor floating objects in rivers and lakes. The manual analysis and disposal method analyzes and disposes of floating objects through manual inspections, and the semi-intelligent analysis and disposal method detects floating objects through video monitoring and notifies monitoring personnel for disposal, which solves the problem of detecting floating objects. However, there are many types of floating objects and their impact ranges are different, making it difficult to make intelligent judgments on the impact range and disposal methods of floating objects. Summary of the invention

[0004] The embodiments of the present application provide a floating object analysis and disposal method, device, equipment, computer storage medium, and program product to solve the problem that it is difficult to intelligently determine the impact range and disposal method of floating objects in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a floating object analysis and disposal method, the method comprising:

[0006] Obtain floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and collection coordinates;

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

[0008] Calculate the flow velocity and direction of each point in the water body based on the relationship between river and lake hydrological data and water flow velocity and direction;

[0009] The movement process of floating objects is simulated according to the image acquisition coordinates of floating objects, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of floating objects;

[0010] Input river and lake hydrological data, floating object volume, and floating object movement trajectory into the preset flood analysis model to obtain information on the flood-affected area;

[0011] Input the river and lake hydrological data, flow velocity and direction at each point in the water body, the type of floating objects and the movement trajectory of floating objects into the preset water quality analysis model to obtain information on the water quality impact area;

[0012] The disposal location and time of floating objects are obtained based on the movement trajectory of floating objects, the information of flood-affected areas and the information of water quality-affected areas.

[0013] In a second aspect, an embodiment of the present application provides a floating object analysis and disposal device, the device comprising:

[0014] The acquisition module is used to obtain 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 recognition module is used to extract and recognize the image features of the floating object monitoring image to obtain the type, volume and distance from the river bank of the floating object;

[0016] A calculation module is used to calculate the flow velocity and flow direction of each point in the water body based on the hydrological data of rivers and lakes and the relationship between the flow velocity and flow direction of the water body;

[0017] The simulation module is used to simulate the movement process of floating objects according to the image acquisition coordinates of floating objects, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of the floating objects;

[0018] Aggregation module, used to input river and lake hydrological data, floating object volume, and floating object movement trajectory into the preset flood analysis model to obtain information on the flood-affected area;

[0019] The analysis module is used to input the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects into the preset water quality analysis model to obtain the information of the water quality impact area;

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

[0021] In a third aspect, an embodiment of the present application provides a terminal device, comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the floating object analysis and disposal method as in the first aspect is implemented.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the floating object analysis and disposal method according to the first aspect is implemented.

[0023] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the floating object analysis and disposal method of the first aspect.

[0024] The embodiments of the present application provide a floating object analysis and disposal method, device, equipment, computer storage medium, and program product, which obtain floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and acquisition coordinates, which provide necessary basic data for subsequent floating object movement simulation and water quality analysis; extract and identify image features of floating object monitoring images, obtain the type, volume, and distance from the river bank of the floating object, and can accurately and quickly determine the type, volume, and distance of the floating object, thereby improving data processing efficiency and accuracy; calculate the flow velocity and flow direction of each point in the water body according to the relationship between river and lake hydrological data and the flow velocity and flow direction of the water body; and obtain the floating object image acquisition coordinates, the distance from the river bank, and the distance from the river bank to each point in the water body. The flow velocity and direction simulate the movement process of floating objects to obtain the movement trajectory of the floating objects; the river and lake hydrological data, the volume of floating objects, and the movement trajectory of floating objects are input into the preset flood analysis model to obtain the information of the flood impact area; the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects are input into the preset water quality analysis model to obtain the information of the water quality impact area; the disposal location and disposal time of floating objects are obtained according to the movement trajectory of floating objects, the information of the flood impact area and the information of the water quality impact area, which can optimize the allocation of cleaning resources and the disposal efficiency of floating objects, and carry out targeted disposal of floating objects with different impacts, thereby realizing the intelligent judgment of the impact range and disposal method of floating objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0026] Figure 1 It is a schematic diagram of the system structure that can implement the floating object analysis and disposal method provided in the embodiment of the present application;

[0027] Figure 2 It is a schematic diagram of the process of the floating object analysis and disposal method provided in the embodiment of the present application;

[0028] Figure 3 This is a schematic diagram of river section division provided in an embodiment of the present application.

[0029] Figure 4 It is a structural schematic diagram of a floating object analysis and disposal device provided in an embodiment of the northern application;

[0030] Figure 5 It is a schematic diagram of the structure of the terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0032] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0033] There are several main problems in the existing management of floating objects in rivers and lakes: there are many types of floating objects, such as garbage, small buildings, water blooms, water hyacinths, animals and plants, etc., with different shapes, and it is not easy to automatically identify the different impact ranges of floating objects. For example, small garbage may affect the residential environment and water quality and water bodies, small buildings may affect river blockages, water blooms and water hyacinths may affect water quality changes, and animals and plants may affect water quality, etc.; floating objects will gradually gather with the flow of water bodies, change their shapes or deteriorate and rot, which will have a great impact on water quality maintenance and river flooding; the disposal method of floating objects is difficult to accurately determine the time period when the floating objects are flowing and which river section person in charge will clean them up, which is difficult to intelligently judge.

[0034] When analyzing and handling the floating objects in rivers and lakes, it mainly includes manual analysis and disposal and semi-intelligent analysis and disposal. Manual analysis and disposal involves manual river patrols. When floating objects are found, the type of floating objects, possible problems, and the best disposal methods are judged based on historical experience. However, problems can only be discovered during manual river patrols, and floating objects are mobile, making them even more difficult to discover. Whether floating objects affect water quality, whether they will gradually accumulate to form larger floating objects, and whether they affect river flooding will also change with the flow and shape of floating objects, making it difficult to accurately determine. Most rivers are cross-regional, cross-city, and even cross-provincial, and river management is generally divided into multiple river sections, with different people in charge of each river section. Floating objects flow with the water all the time, constantly changing during the flow process. The flow rate of the water varies in each river and each river section, so it is not easy to accurately determine which river section and time point the floating objects are intercepted. Semi-intelligent analysis and disposal establishes video perception at the front end of the river, automatically identifies floating objects through video AI analysis, generates warnings, manually analyzes the warning situation, and then analyzes possible problems and the best disposal methods based on historical experience. However, the problems of accurately determining the impact range and the best disposal location and time still exist.

[0035] The following first describes an example of a system framework to which the floating object analysis and disposal method provided in the embodiments of the present application can be applied.

[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 disposal 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 disposal module, and the intelligent analysis and disposal 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, which are used to capture real-time video images of the river, detect the water level, water quality and speed and direction of the river flow. 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, which are used to identify floating objects, the volume of floating objects, the type of floating objects and the distance of floating objects from the river bank or lake bank. The model calculation module includes a hydrodynamic algorithm unit, a floating object gathering 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, which are used to simulate water flow dynamics, predict floating object gathering, evaluate the impact of floating objects on floods, evaluate the impact of floating objects on water quality, simulate the movement trajectory of floating objects and simulate the diffusion impact of phytoplankton. The spatial management module includes a river demarcation spatial management unit, a river section demarcation spatial management unit, a flood discharge control point spatial management unit and a perception spatial management unit, which are used to demarcate the river channel, demarcate the river section, determine the key locations for flood control and manage perception equipment. The basic information management module includes the basic information unit of river and lake sections, the basic information unit of responsible persons and the relationship unit of river section responsible persons, which are used to store the information of river sections, the basic information of responsible persons and the relationship between responsible persons and corresponding river sections respectively. The intelligent analysis and disposal module includes the impact type analysis unit, the impact range analysis unit, the disposal responsible person analysis unit, the best disposal time analysis unit and the best disposal location analysis unit, which are used to determine the impact type, impact range, responsible person for disposal of floating objects, time and location for disposal of floating objects respectively.

[0038] In order to solve the existing technology, the embodiment of the present application provides a method for analyzing and disposing of floating objects, obtains floating object monitoring information and river and lake hydrological data, the floating object monitoring information includes floating object monitoring images and acquisition coordinates, and provides necessary basic data for subsequent floating object movement simulation and water quality analysis; extracts and identifies image features of floating object monitoring images, obtains the type, volume and distance from the river bank of the floating objects, and can accurately and quickly determine the type, volume and distance of the floating objects, thereby improving data processing efficiency and accuracy; calculates the flow velocity and flow direction of each point in the water body according to the relationship between river and lake hydrological data, water flow velocity and flow direction; and calculates the flow velocity and flow direction of each point in the water body according to the image acquisition coordinates of the floating objects, the distance from the river bank and the flow velocity and flow direction of each point in the water body. The movement process of floating objects is simulated to obtain the movement trajectory of floating objects; the river and lake hydrological data, the volume of floating objects, and the movement trajectory of floating objects are input into the preset flood analysis model to obtain the information of the flood impact area; the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects are input into the preset water quality analysis model to obtain the information of the water quality impact area; the disposal location and disposal time of floating objects are obtained according to the movement trajectory of floating objects, the information of the flood impact area and the information of the water quality impact area, which can optimize the allocation of cleaning resources and the disposal efficiency of floating objects, and carry out targeted disposal of floating objects with different impacts, thereby realizing the intelligent determination of the impact range and disposal method of floating objects.

[0039] The following is an introduction to the floating object analysis and disposal method provided in the embodiments of the present application.

[0040] Figure 2 FIG. 1 is a flow chart of a floating object analysis and disposal method provided by an embodiment of the present application. Figure 2 As shown, the method may include the following steps: S201 to S207.

[0041] S201, obtaining floating object monitoring information and river and lake hydrological data, wherein the floating object monitoring information includes floating object monitoring images and collection coordinates.

[0042] In some embodiments, floating object monitoring images can be acquired via drones, satellites, or fixed-mounted cameras.

[0043] S202, extracting and identifying image features of the floating object monitoring image to obtain the type, volume and distance of the floating object from the river bank.

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

[0045] In some embodiments, a Mask R-CNN, a YOLO model, or a U-Net convolutional neural network (U-Net) may be used to extract and identify image features of floating object monitoring images.

[0046] S203, calculating the flow velocity and flow direction of each point in the water body according to the relationship between the river and lake hydrological data and the water body flow velocity and flow direction.

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

[0048] S204, simulating the movement process of the floating object according to the image acquisition coordinates of the floating object, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of the floating object.

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

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

[0051] Combining the volume and movement trajectory of floating objects, simulating their impact on the river's flood-carrying capacity and identifying areas where flood risks may increase due to the accumulation of floating objects can provide decision support for flood emergency management.

[0052] S206, inputting river and lake hydrological data, flow velocity and direction of each point 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.

[0053] By combining river and lake hydrological data, water flow velocity and direction, and floating object information, the water quality analysis model can accurately predict the area where floating objects affect water quality and help identify the affected water area.

[0054] S207, obtaining the disposal location and disposal time of the floating objects according to the movement trajectory of the floating objects, the information of the flood impact area and the information of the water quality impact area.

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

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

[0057] The floating object analysis and disposal method provided in the embodiment of the present application obtains floating object monitoring information and river and lake hydrological data. The floating object monitoring information includes floating object monitoring images and acquisition coordinates, which provide necessary basic data for subsequent floating object movement simulation and water quality analysis; extracts and identifies image features of floating object monitoring images, obtains the type, volume and distance from the river bank of the floating object, and can accurately and quickly determine the type, volume and distance of the floating object, thereby improving data processing efficiency and accuracy; calculates the flow velocity and flow direction of each point in the water body according to the relationship between river and lake hydrological data and the flow velocity and flow direction of the water body; simulates floating objects according to the image acquisition coordinates of the floating objects, the distance from the river bank and the flow velocity and flow direction of each point in the water body; The movement process can obtain the movement trajectory of floating objects; the river and lake hydrological data, the volume of floating objects, and the movement trajectory of floating objects are input into the preset flood analysis model to obtain the information of the flood impact area; the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects are input into the preset water quality analysis model to obtain the information of the water quality impact area; the disposal location and disposal time of floating objects are obtained according to the movement trajectory of floating objects, the information of the flood impact area and the information of the water quality impact area, which can optimize the allocation of cleaning resources and the disposal efficiency of floating objects, and carry out targeted disposal of floating objects with different impacts, thereby realizing the intelligent judgment of the impact range and disposal method of floating objects.

[0058] In some embodiments, extracting image features of the floating object monitoring image and identifying it to obtain the type, volume and distance from the riverbank of the floating object includes:

[0059] Convolutional neural network is used to extract and identify the features of floating object monitoring images to obtain the type of floating objects;

[0060] Segment the outline of the floating object and generate a pixel-level mask of the floating object, wherein the pixel-level mask represents the two-dimensional outline information of the floating object;

[0061] A three-dimensional model of the floating object is reconstructed based on the pixel-level mask of the floating object to obtain the volume of the floating object;

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

[0063] By automatically identifying and analyzing images, the system can quickly process large amounts of data and reduce the time and cost of manual monitoring. By generating pixel-level masks and three-dimensional reconstruction, the system can provide detailed contours, volume information and distance information from the river bank of floating objects, thereby improving recognition accuracy.

[0064] In some embodiments, reconstructing a three-dimensional model of the floating object based on the pixel-level mask of the floating object to obtain the volume of the floating object includes:

[0065] Converting pixels to actual physical dimensions according to a preset relationship between pixels and actual physical dimensions;

[0066] Based on the pixel-level mask, each pixel in the 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] Reconstruct the 3D model of the floating object using the 3D reconstruction algorithm based on the point cloud;

[0068] The volume of the floating object is obtained by calculating the volume of the reconstructed three-dimensional model.

[0069] Through the conversion of pixel-level masks and actual physical sizes, the precise positioning and size measurement of floating objects can be achieved, and the three-dimensional model of floating objects can be restored more comprehensively.

[0070] In some embodiments, the river and lake hydrological data includes topographic information, water depth, initial flow velocity and initial flow direction of the water body, and the flow velocity and flow direction of each point of the water body are calculated based on the river and lake hydrological data and the relationship between the flow velocity and flow direction of the water body, including:

[0071] Divide the water body into multiple calculation units according to the topographic information of the water body;

[0072] A group of water body dynamic equations is established for each calculation unit according to the topographic information, water depth, initial flow velocity and initial flow direction of the water body;

[0073] Solving the hydrodynamic equations, we can obtain the flow velocity and direction at each point in the water body.

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

[0075] In some embodiments, the terrain information of the water body may be divided into deep water areas, shallows, river banks, etc.

[0076] In one example, if Figure 3As shown in the figure, this section of the river is divided into three sections, A, B, and C, according to different water body terrain information. The dark area in the figure is the deeper terrain. Section AC is the curved section of the river, with a faster flow rate and a more complex flow direction. There is a deeper terrain on the convex bank side and a shallower terrain on the concave bank. In this section, it is more likely for drifting objects to accumulate and diffuse. Section B is a direct flow section with a relatively uniform flow rate and a consistent flow direction along the river channel. There is no local acceleration caused by the terrain.

[0077] In some embodiments, a group of water body dynamic equations is established for each calculation unit according to the topographic information, water depth, initial flow velocity and initial flow direction of the water body, which may be:

[0078]

[0079] Among them, 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 angle of the water body.

[0080] In some embodiments, the movement process of the floating object is simulated according to the image acquisition coordinates of the floating object, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of the floating object, including:

[0081] Initialize the initial position, initial velocity and initial direction of the Lagrangian particles representing the floating objects in the water body according to the image acquisition coordinates of the floating objects and the distance from the river bank;

[0082] Determine the movement speed, direction and position of the particle at the next time point based on the flow velocity, flow direction, initial position, initial velocity and initial direction of each point in the water body;

[0083] According to the position, speed, direction of the particle at each time point, the flow velocity and flow direction of each point in the water body, the position of the particle at the next time point is repeatedly calculated and updated to obtain the movement trajectory of the floating object.

[0084] By comprehensively considering multiple factors such as the location of floating objects, water flow rate, flow direction, etc., the movement of floating objects can be comprehensively analyzed. By continuously updating the position, speed 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 promptly fed back.

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

[0086] Obtaining the location of the floating object based on the movement trajectory of the floating object;

[0087] Cluster the locations of all floating objects and obtain the water area where floating objects gather;

[0088] The area where the volume of floating objects in the floating object accumulation water area exceeds the set threshold is regarded as the flood discharge impact area.

[0089] By obtaining the resting position of floating objects based on their movement trajectories, it is possible to accurately determine the locations where floating objects gather, thereby more accurately determining the flood-affected areas, and providing early warning of the possible flood impact range.

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

[0091] When the floating material is 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] The water area where the pollutant diffusion amount is greater than the set threshold is regarded as the water quality impact area.

[0093] By comprehensively utilizing river and lake hydrological data, water flow velocity, flow direction, and the movement trajectory of floating objects, we can comprehensively analyze the propagation process of pollutants in water bodies, provide comprehensive data support for water quality analysis, accurately calculate the diffusion of pollutants in water bodies, and improve the accuracy of water quality impact areas.

[0094] In some embodiments, the relationship between the pollutant concentration, the flow velocity at each point in the water body, and the pollutant diffusion amount is:

[0095]

[0096] Among them, J is the diffusion amount of pollutants, D is the diffusion coefficient of pollutants, C is the concentration of pollutants, x is the spatial coordinate, and v is the flow velocity of the water body.

[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 according to the relationship between the pollutant concentration at each time point, the flow velocity at each point of the water body and the pollutant diffusion amount, the method includes:

[0098] The pollutant concentration at each time point is 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 the phytoplankton concentration based on the relationship between pollutant concentration and hydrological factors, the spread of phytoplankton can be predicted, the areas where phytoplankton may accumulate in the water body can be evaluated, and potential water quality risks can be identified in advance.

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

[0101]

[0102] Among them, C is the pollutant concentration, μ is the preset photosynthesis 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 value 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 objects according to the movement trajectory of the floating objects, the information of the flood-affected area, and the information of the water quality-affected area also includes:

[0104] Obtain the basic data of river and lake management responsible persons and the relationship data between river sections and responsible persons. By analyzing the relationship between river and lake management responsible persons and corresponding river sections, the disposal location and disposal time are sent to the corresponding responsible persons for processing.

[0105] Figure 4 Schematic diagram of the structure of a floating object analysis and disposal device provided in an embodiment of the present application. Figure 4 As shown, the apparatus 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 recognition module 402 is used to extract and recognize the image features of the floating object monitoring image to obtain the type, volume and distance from the river bank of the floating object;

[0108] The calculation module 403 is used to calculate the flow velocity and flow direction of each point in the water body according to the river and lake hydrological data and the relationship between the flow velocity and flow direction of the water body;

[0109] The simulation module 404 is used to simulate the movement process of the floating object according to the image acquisition coordinates of the floating object, the distance from the river bank, and the flow velocity and flow direction of each point of the water body to obtain the movement trajectory of the floating object;

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

[0111] The analysis module 406 is used to input the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of the floating objects into the preset water quality analysis model to obtain the information of the water quality impact area;

[0112] The processing module 407 is used to obtain the disposal location and disposal time of the floating objects according to the movement trajectory of the floating objects, the information of the flood-affected area and the information of the water quality-affected area.

[0113] In some embodiments, the recognition module is further used to extract and recognize features of the floating object monitoring image using a convolutional neural network to obtain the type of the floating object;

[0114] The recognition module is also used to segment the outline of floating objects and generate pixel-level masks of floating objects. The pixel-level masks represent the two-dimensional outline information of floating objects.

[0115] The calculation module is also used to reconstruct a three-dimensional model of the floating object based on the pixel-level mask of the floating object to 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 obtain the distance of the floating object from the shore. The pixel depth value represents the straight-line distance from the camera that takes the image to each point in the image.

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

[0118] The calculation module is also used to establish a group of water body dynamic equations for each calculation unit according to 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 of each point in the water body.

[0120] In some embodiments, the simulation module is further used to initialize the initial position, initial velocity and initial direction of the Lagrangian particles representing the floating object in the water body according to the image acquisition coordinates of the floating object and the distance from the river bank;

[0121] The calculation module is also used to determine the movement speed, direction and position of the particle at the next time point based on the flow speed, flow direction, initial position, initial speed and initial direction of the particle at each point of 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 position, speed, direction of the particle at each time point, the flow velocity and flow direction of each point in the water body, and obtain the movement trajectory of the floating object.

[0123] In some embodiments, the acquisition module is further used to acquire the resting position of the floating object based on the movement trajectory of the floating object;

[0124] The aggregation module is also used to cluster the resting positions of all floating objects and obtain the water area where floating objects gather;

[0125] The analysis module is also used to take the area where the volume of floating objects in the floating object gathering water area exceeds a set threshold as the flood discharge impact area.

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

[0127] The analysis module is also used to define water areas where the pollutant diffusion amount is greater than a set threshold as water quality impact areas.

[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 device shown can be implemented Figure 2 Each step in the above steps can achieve the corresponding technical effect, which will not be repeated here for the sake of brevity.

[0130] Figure 5 A schematic diagram of the hardware structure of a terminal device provided in an embodiment of the present 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), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0133] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In one example, the memory 502 may include a removable or non-removable (or fixed) medium, or the memory 502 is a non-volatile solid-state memory. The memory 502 may be inside or outside the integrated gateway disaster recovery device.

[0134] In one example, the memory 502 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) 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 the present disclosure.

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

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

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

[0138] Bus 504 includes hardware, software or both, and the components of terminal equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics bus, enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) bus, front side bus (Front Side Bus, FSB), Hyper Transport (Hyper Transport, HT) interconnection, industry standard architecture (Industry Standard Architecture, ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 504 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0139] In addition, in combination with the floating object analysis and disposal method in the above embodiments, the present application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the floating object analysis and disposal methods in the above embodiments is implemented.

[0140] The embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is processed and executed, any one of the floating matter analysis and disposal methods in the above embodiments is implemented.

[0141] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0142] The functional blocks shown in the structural block diagram described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), appropriate firmware, plug-in, function card, etc. When implemented in software, the elements of the present application are programs or text segments used to perform the required tasks. The program or text segment can be stored in a machine-readable medium, or transmitted on a transmission medium or communication link via a data signal carried in a carrier. "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 memories (Read-Only Memory, ROM), flash memory, erasable read-only memories (Erasable ReadOnly Memory, EROM), floppy disks, compact discs (Compact Disc Read-Only Memory, CD-ROM), optical discs, hard disks, optical fiber media, radio frequency (Radio Frequency, RF) links, etc. The text segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0143] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. 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 embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0144] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram 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 device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. 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 can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0145] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for analyzing and disposing floating objects, It is characterized in that include: Obtaining floating object monitoring information and river and lake hydrological data, wherein the floating object monitoring information includes floating object monitoring images and acquisition coordinates; Extract and identify the image features of floating object monitoring images to obtain the type, volume and distance from the river bank of the floating objects; Calculate the flow velocity and direction of each point in the water body based on the relationship between river and lake hydrological data and water flow velocity and direction; The movement process of floating objects is simulated according to the image acquisition coordinates of floating objects, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of floating objects; Input river and lake hydrological data, floating object volume, and floating object movement trajectory into the preset flood analysis model to obtain information on the flood-affected area; Input the river and lake hydrological data, flow velocity and direction at each point in the water body, the type of floating objects and the movement trajectory of floating objects into the preset water quality analysis model to obtain information on the water quality impact area; The disposal location and time of floating objects are obtained based on the movement trajectory of floating objects, the information of flood-affected areas and the information of water quality-affected areas.

2. The floating matter analysis and disposal method according to claim 1, It is characterized in that Extract image features of floating object monitoring images and identify them to obtain the type, volume and distance from the river bank of floating objects, including: Convolutional neural network is used to extract and identify the features of floating object monitoring images to obtain the type of floating objects; Segmenting the outline of the floating object 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; A three-dimensional model of the floating object is reconstructed based on the pixel-level mask of the floating object to obtain the volume of the floating object; Based on the position of the floating object in the image and the preset pixel depth value, the space where the floating object is located is reconstructed in three dimensions to obtain the distance of the floating object from the shore. The pixel depth value represents the straight-line distance from the camera that takes the image to each point in the image.

3. The floating matter analysis and disposal method according to claim 1, It is characterized in that The river and lake hydrological data include topographic information, water depth, initial flow velocity and initial flow direction of the water body. The flow velocity and flow direction of each point in the water body are calculated based on the river and lake hydrological data and the relationship between the flow velocity and flow direction of the water body, including: Divide the water body into multiple calculation units according to the topographic information of the water body; A group of water body dynamic equations is established for each calculation unit according to the topographic information, water depth, initial flow velocity and initial flow direction of the water body; The water body dynamics equations are solved to obtain the flow velocity and flow direction of each point in the water body.

4. The floating matter analysis and disposal method according to claim 1, It is characterized in that The method of simulating the movement of floating objects according to the image acquisition coordinates of the floating objects, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of the floating objects includes: Initialize the initial position, initial velocity and initial direction of the Lagrangian particles representing the floating objects in the water body according to the image acquisition coordinates of the floating objects and the distance from the river bank; Determine the movement speed, direction and position of the particle at the next time point based on the flow velocity, flow direction, initial position, initial velocity and initial direction of each point in the water body; According to the position, speed, direction of the particle at each time point, the flow velocity and flow direction of each point in the water body, the position of the particle at the next time point is repeatedly calculated and updated to obtain the movement trajectory of the floating object.

5. The floating matter analysis and disposal method according to claim 1, It is characterized in that The river and lake hydrological data, floating object volume, and floating object movement trajectory are input into the preset flood analysis model to obtain the flood impact area, including: Obtaining the location of the floating object based on the movement trajectory of the floating object; Cluster all floating objects according to their resting positions to obtain the water area where floating objects gather; The area where the volume of floating objects in the floating object accumulation water area exceeds the set threshold is regarded as the flood discharge impact area.

6. The floating matter analysis and disposal method according to claim 1, It is characterized in that The hydrological data of rivers and lakes, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects are input into the preset water quality analysis model to obtain the water quality impact area, including: When the floating object type is pollutants, 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; The water area where the pollutant diffusion amount is greater than the set threshold is regarded as the water quality impact area.

7. The floating matter analysis and disposal method according to claim 6, It is 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 according to the relationship between the pollutant concentration at each time point, the flow velocity at each point of the water body and the pollutant diffusion amount, the method includes: The pollutant concentration at each time point is calculated based on the relationship between light intensity, temperature, pH value, nutrient concentration and pollutant concentration, and the pollutant concentration is the phytoplankton concentration.

8. A floating object analysis and disposal device, It is characterized in that The device comprises: An acquisition module is used to acquire floating object monitoring information and river and lake hydrological data, wherein the floating object monitoring information includes floating object monitoring images and acquisition coordinates; The recognition module is used to extract and recognize the image features of the floating object monitoring image to obtain the type, volume and distance from the river bank of the floating object; A calculation module is used to calculate the flow velocity and flow direction of each point in the water body based on the relationship between the river and lake hydrological data and the flow velocity and flow direction of the water body; The simulation module is used to simulate the movement process of floating objects according to the image acquisition coordinates of floating objects, the distance from the river bank, and the flow velocity and flow direction of each point in the water body to obtain the movement trajectory of the floating objects; Aggregation module, used to input river and lake hydrological data, floating object volume, and floating object movement trajectory into the preset flood analysis model to obtain information on the flood-affected area; The analysis module is used to input the river and lake hydrological data, the flow velocity and direction of each point in the water body, the type of floating objects and the movement trajectory of floating objects into the preset water quality analysis model to obtain the information of the water quality impact area; The processing module is used to obtain the disposal location and disposal time of the floating objects according to the movement trajectory of the floating objects, the information of the flood-affected area and the information of the water quality-affected area.

9. A terminal device, It is characterized in that The device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the floating object analysis and disposal method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the floating object analysis and disposal method according to any one of claims 1 to 7 is implemented.

11. A computer program product, It is characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the floating matter analysis and disposal method according to any one of claims 1 to 7.

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