Suspended aquatic product state monitoring method and system based on unmanned aerial vehicle image

Abstract

The invention provides a suspended aquatic product state monitoring method and system based on unmanned aerial vehicle images, and the method comprises the steps: obtaining images of a plurality of floating bodies and a sea water surface in a breeding device in a breeding region through an unmanned aerial vehicle, and obtaining a breeding region image through processing; identifying the position of the floating body and extracting water elevation data relative to the sea surface; outputting the biomass value of the suspended aquatic products in each culture district through a preset biomass estimation model; and carrying out space-time characteristic analysis on the state of the suspended aquatic products in each culture district in the culture area. According to the hanging aquatic product state monitoring method based on the unmanned aerial vehicle image, the relation model between the overwater height of the floating body and the biomass is utilized, the biomass value is estimated according to the actually measured overwater elevation data to monitor the state of the hanging aquatic product, so that the unmanned aerial vehicle can rapidly monitor a large-range fishery production scene; compared with manual ship inspection, energy consumption is saved, efficiency is higher, and meanwhile interference of ship noise and the like on the breeding process can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent fishery, and particularly to a method and system for monitoring the state of suspended aquaculture products based on UAV images. Background Art

[0002] With the rise of the low-altitude economy, the application scenarios of UAV low-altitude remote sensing have been continuously enriched. In the agricultural field, due to the characteristics of UAVs such as being lightweight, flexible, having good spatial accessibility, and being easy to carry various sensors, they are mainly used to measure the landscape characteristics of ground vegetation such as large-scale crops. At the same time, with the update and replacement of sensors, especially the transformation of large sensors such as lidar towards lightweight and miniaturization, UAVs can carry more types of sensors, obtain more multi-source data, and have more diverse derivative functions. While meeting the demand for plant height monitoring, they also have higher monitoring accuracy. Currently, the research on measuring the plant height and biomass of short-stem plants based on UAV low-altitude remote sensing is becoming increasingly extensive, and the advantages of remote sensing measurement are becoming increasingly prominent, but such applications are rarely reported in aquaculture.

[0003] Aquaculture systems such as floating rafts, cages, and longline suspended culture are fishery engineering facilities used for aquaculture of aquatic products in estuaries and coastal waters with deep water and strong currents. They can be used for cage and rope culture of benthic economic products such as sea cucumbers, scallops, oysters, abalones, and crabs. Floating bodies such as floats and floating rafts, as the above-water part of the facilities, have important functions such as representing position information and supporting the system structure. In recent years, the aquaculture area has developed from nearshore intertidal zones and other areas towards areas farther from the coast. Due to the use of fewer infrastructure facilities, it is widely used, and its standardization degree has gradually increased. At the same time, by expanding the aquaculture system from the intertidal zone to high-hydrodynamic areas farther from the coast, the limitation of development space is effectively reduced, production capacity is improved, and potential ecological impacts are reduced. Since the underwater part is the key content, it is usually inspected irregularly by special personnel by boat to the aquaculture area.

[0004] However, as the aquaculture system facilities are getting farther and farther from the coast, the round-trip fuel consumption is higher. And with the increase in aquaculture density, when the floating bodies are spaced closely, it is difficult to reach during inspection and it takes a long time. In addition, the offshore operation environment is harsh, and its inspection and aquaculture management are becoming increasingly difficult. Summary of the Invention

[0005] The present invention provides a method and system for monitoring the state of suspended aquaculture products based on UAV images to solve the problems in the prior art that when monitoring the state of suspended aquaculture products through manual irregular inspections, it is impossible to timely obtain and process large-scale information and there are missed inspections.

[0006] In a first aspect, the present invention provides a method for monitoring the state of suspended aquaculture products based on UAV images, including: S1. Obtain images of multiple floating bodies in the aquaculture devices and images of the sea surface in the aquaculture area of the aquaculture products to be monitored by drones, and process the images of each floating body and the images of the sea surface to obtain an image of the aquaculture area; any one of the floating bodies is used to support an aquaculture plot to float on the water surface; S2. Based on the image of the aquaculture area, identify the position information of each floating body, and extract the water elevation data of each floating body relative to the sea surface; S3. Input the water elevation data into a preset biomass estimation model to obtain the biomass values of the aquaculture products suspended in each aquaculture plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values; S4. Based on the biomass values, perform spatio-temporal characteristic analysis on the states of the aquaculture products suspended in each aquaculture plot in the aquaculture area to obtain an analysis result, and visually display the analysis result.

[0007] In one embodiment, extract the point cloud images of each floating body and the point cloud image of the sea surface from the image of the aquaculture area; convert the point cloud images of each floating body into single-band images of each floating body, and convert the point cloud image of the sea surface into a single-band image of the sea surface; Perform band difference operations on the single-band images of each floating body and the single-band image of the sea surface respectively to construct a floating body surface model; Calculate the mean value of all pixel values corresponding to each floating body in the floating body surface model to obtain the water elevation data of each floating body relative to the sea surface; Or, divide the elevations corresponding to the point clouds of each floating body in the floating body surface model from low to high according to the elevation cumulative percentage, and determine the elevation corresponding to each percentile; determine the elevation corresponding to the first target percentile as the reference plane height, and determine the elevation corresponding to the second target percentile as the upper boundary height of the floating body water height; the first target percentile is less than the second target percentile; perform a difference operation on the upper boundary height and the reference plane height to obtain the water elevation data of the floating body relative to the sea surface.

[0008] In one embodiment, the preset biomass estimation model is obtained by the following method: Obtain the measured elevation values of the floating body samples relative to the sea surface in the aquaculture area at each growth stage and the measured biomass values of the aquaculture products suspended in the aquaculture plot samples supported by the floating body samples; Construct multiple initial biomass estimation models at different growth stages; Based on the measured elevation values and measured biomass values within each growth stage, select the model with the optimal accuracy from multiple initial biomass estimation models within each growth stage to obtain the target biomass estimation model within each growth stage; According to the target biomass estimation model within each growth stage, construct a piecewise model and determine the piecewise model as the preset biomass estimation model.

[0009] In one embodiment, when constructing multiple initial biomass estimation models for different growth stages, the following steps are performed for each growth stage: Establish a first functional relationship between the above-water elevation data of the floating body sample on the sea surface and the volume below the sea surface; Establish a second functional relationship between the volume and the buoyancy generated by the floating body sample; Establish a third functional relationship between the buoyancy and the biomass value of the aquaculture products suspended in the aquaculture plot sample; According to the first functional relationship, the second functional relationship, and the third functional relationship, establish a fourth functional relationship between the above-water elevation data and the biomass value; According to the fourth functional relationship, construct multiple initial biomass estimation models within the growth stage.

[0010] In one embodiment, the spatio-temporal characteristic analysis of the states of the aquaculture products suspended in each aquaculture plot in the aquaculture area based on each biomass value to obtain an analysis result includes: Obtain the biomass values of the aquaculture products suspended in the aquaculture plot at different times to form a biomass sequence with a time sequence relationship; If the biomass sequence does not satisfy continuous monotonic change, it is determined that the state of the suspended aquaculture products is abnormal; If the biomass sequence satisfies continuous monotonic change, compare the preset standard biomass corresponding to each time with the obtained biomass value; if the absolute value of the difference between the preset standard biomass and the obtained biomass value corresponding to any time does not satisfy within the preset difference range, it is determined that the state of the suspended aquaculture products is normal; if the absolute value of the difference between the preset standard biomass and the obtained biomass value corresponding to any time does not satisfy within the preset difference range, it is determined that the state of the suspended aquaculture products is abnormal.

[0011] In one embodiment, the spatio-temporal characteristic analysis of the states of the aquaculture products suspended in each aquaculture plot in the aquaculture area based on each biomass value to obtain an analysis result further includes: Obtain the biomass values of the suspended aquaculture products in multiple different aquaculture areas within the aquaculture region at the current moment, and determine the maximum biomass value and the minimum biomass value among the multiple biomass values; Perform a difference operation on the maximum biomass value and the minimum biomass value to obtain a biomass difference; If the biomass difference is less than or equal to a preset threshold, determine that the state of the suspended aquaculture products in the multiple different aquaculture areas is normal; If the biomass difference is greater than the preset threshold, determine that there is an abnormality in the state of the suspended aquaculture products in the multiple different aquaculture areas.

[0012] In one embodiment, after determining that there is an abnormality in the state of the suspended aquaculture products, it further includes: Perform a difference operation on the biomass value of the suspended aquaculture products in each aquaculture area and the preset standard biomass corresponding to the current moment to obtain a difference result; Generate multiple types of legends based on the position information of the floating bodies supporting each aquaculture area and their corresponding difference results; Visually display the multiple types of legends, combine with the threshold to generate a warning message, so as to take aquaculture management measures according to the multiple types of legends and the warning message.

[0013] In a second aspect, the present invention also provides a monitoring system for the state of suspended aquaculture products based on UAV images, including: An image acquisition module based on a UAV, which is used to obtain images of multiple floating bodies in the aquaculture device and images of the sea surface in the aquaculture area to be monitored by the UAV, and process the images of each floating body and the images of the sea surface to obtain an image of the aquaculture area; any one of the floating bodies is used to support an aquaculture area to float on the water surface; An underwater elevation data extraction module, which is used to identify the position information of each floating body based on the image of the aquaculture area and extract the underwater elevation data of each floating body relative to the sea surface; A biomass estimation module, which is used to input the underwater elevation data into a preset biomass estimation model to obtain the biomass values of the suspended aquaculture products in each aquaculture area output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the underwater elevation data and the biomass values; A growth state detection module, which is used to perform spatio-temporal characteristic analysis on the state of the suspended aquaculture products in each aquaculture area in the aquaculture region based on the biomass values, obtain an analysis result, and visually display the analysis result; A management and warning module, which is used to perform visual aquaculture management, generate a warning message and operation guidance when it is detected that there is an abnormality in the state of the suspended aquaculture products.

[0014] In a third aspect, the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of any one of the above-mentioned methods for monitoring the state of suspended aquaculture products based on UAV images are implemented.

[0015] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the above-mentioned methods for monitoring the state of suspended aquaculture products based on UAV images are implemented.

[0016] The method and system for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention use a UAV to obtain the point cloud images of floating bodies in the aquaculture area, calculate the water elevation data of each floating body relative to the sea surface, and further estimate the biomass value through a pre-established relationship model between the height of the above-water part of the floating body and the biomass of the suspended aquaculture products. Then, the growth state of the suspended aquaculture products is analyzed spatiotemporally based on the estimated biomass value, enabling the UAV to quickly and effectively monitor the biomass in large water surface fishery production scenarios such as floating raft and longline aquaculture. In addition, the application of the UAV is more energy-saving, more efficient, and has better spatial accessibility than manual boat inspection. At the same time, it reduces the interference of ship noise and the like during manual inspection on the aquaculture process and can achieve visual management. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic flow chart of the method for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention.

[0019] Figure 2 It is a schematic flow chart of calculating the above-water height of the floating body provided by the present invention.

[0020] Figure 3 It is a schematic flow chart of constructing a preset biomass estimation model provided by the present invention.

[0021] Figure 4 It is a schematic flow chart of monitoring the state of suspended aquaculture products in the time dimension provided by the present invention.

[0022] Figure 5It is a schematic flow chart of the state monitoring of suspended aquaculture products in the spatial dimension provided by the present invention.

[0023] Figure 6 It is a schematic structural diagram of the state monitoring system of suspended aquaculture products provided by the present invention.

[0024] Figure 7 It is a schematic structural diagram of the electronic device provided by the present invention. Specific embodiments

[0025] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0026] The terms "first", "second", etc. in the present invention are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein.

[0027] The following Figures 1-7 Describe the method and system for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention.

[0028] Combined with Figure 1 , Figure 1 It is a schematic flow chart of the method for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention.

[0029] As Figure 1 shown, the method includes the following: S1. Obtain images of multiple floating bodies in the aquaculture device in the aquaculture area of the suspended aquaculture products to be monitored and an image of the sea surface through a UAV, and process the images of each floating body and the image of the sea surface to obtain an image of the aquaculture area; any one of the floating bodies is used to support a aquaculture plot to float on the water surface; S2. Based on the image of the aquaculture area, identify the position information of each floating body, and extract the water elevation data of each floating body relative to the sea surface; S3. Input the water elevation data into a preset biomass estimation model to obtain the biomass values of the suspended aquaculture products in each aquaculture plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values; S4. Based on each of the biomass values, analyze the spatio-temporal characteristics of the states of the suspended aquaculture products in each aquaculture plot within the aquaculture area to obtain an analysis result, and visually display the analysis result.

[0030] It should be noted that the method for monitoring the state of suspended aquaculture products based on UAV images provided in the embodiments of the present invention is implemented based on a system for monitoring the state of suspended aquaculture products. The image of the aquaculture area after UAV image processing includes, but is not limited to, a point cloud image. Taking the system for monitoring the state of suspended aquaculture products as the execution subject, the embodiments of the present invention describe the method for monitoring the state of suspended aquaculture products, and the index reflecting the growth state is biomass.

[0031] The method for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention is applicable to the monitoring of large-scale fishery production, such as aquaculture scenarios like floating rafts, cages, and longline suspension culture. The embodiments of the present invention take the scenario of longline suspension culture of oysters as an example for illustration, and can also be deduced to similar aquaculture scenarios such as floating raft culture. During the aquaculture cycle, due to factors such as the growth curve of the suspended aquaculture products themselves, environmental stress, and the occurrence of diseases, the biomass will change, which is an important parameter for farmers to evaluate the growth state of the suspended aquaculture products underwater. First, when oysters are diseased and stressed, it will cause adhesion attenuation, death, etc., and they will fall off the hanging ropes, affecting the overall biomass weight. Second, as the aquaculture time changes, the cumulative biomass gradually increases, and the total output of the suspended aquaculture products can be estimated. Floats, floating rafts and other floating bodies, as the structures on the water surface in the longline suspension culture oyster aquaculture system, not only have the functions of providing buoyancy and position indication, but can also be used to characterize the state information of the aquaculture facilities / aquaculture objects, so as to estimate the biomass and realize the indication of environmental and disease stress. Based on the above understanding, it is also applicable to the monitoring of the growth state of benthic aquaculture products cultured in facilities such as gravity cages, that is, to monitor the growth state based on the estimation of the water surface elevation. The "aquaculture area of the suspended aquaculture products to be monitored" hereinafter may be simply referred to as the "aquaculture area".

[0032] It should be noted that in the embodiments of the present method, for the raft cage, longline hanging culture systems and structures based on benthic aquatic products, the floating bodies (such as floating balls or floating rafts) are mainly used to provide buoyancy, and the towing ropes are mainly used to fix the positions. The floating body refers to the smallest indivisible connected entity that can provide buoyancy. The aquaculture community or aquaculture unit is one or more cages, hanging ropes and their aquaculture products within a certain range supported by the corresponding floating body. The aquaculture aquatic products refer to benthic economic products such as sea cucumbers, scallops, oysters, abalones, crabs, etc. that are suitable for cage and hanging rope culture. Specifically, when the biomass of the hanging aquaculture products changes, such as increasing or decreasing, it can cause changes in the water surface height of the floating body. Especially during the critical periods of aquaculture, such as the fattening period or the rapid growth stage, this change is obvious, that is, the more mature the biomass accumulation is, the lower the water surface height of the floating body is. Therefore, by monitoring the height of the floating body on the water surface by an unmanned aerial vehicle, the estimation of the biomass (weight) of the hanging aquaculture products under the water surface can be realized, and further the effective monitoring and management of the growth state of the hanging aquaculture products under the water surface can be realized.

[0033] Specifically, before monitoring the state of the hanging aquaculture products, an image acquisition device needs to be deployed on the unmanned aerial vehicle. Thus, target images can be obtained through image acquisition devices such as lidar carried by the unmanned aerial vehicle and processed by rasterization, etc. The subsequent image processing methods include but are not limited to three-dimensional point cloud processing methods, image processing methods, and multi-modal data fusion methods, etc. In this embodiment, an example is given of obtaining point cloud data by carrying a lidar device on an unmanned aerial vehicle.

[0034] There are multiple floating bodies in the aquaculture area to be monitored, and each floating body can correspondingly support one or more hanging ropes, cages, boxes, etc. to form an aquaculture community / unit floating on the water surface. Specifically, the aquaculture community / unit hangs and raises aquaculture products through cages. One aquaculture community / unit is not limited to one cage and can have multiple cages. This method is mainly for monitoring the growth state of all the hanging aquaculture products in the aquaculture community / unit supported by the smallest indivisible connected floating body.

[0035] First, the unmanned aerial vehicle is used to obtain images of each floating body and the sea water surface in the aquaculture area of the hanging aquaculture products to be monitored, and the images of each floating body and the sea water surface are processed to obtain the lidar point cloud image of the aquaculture area. Specifically, the point cloud images of each floating body and the sea water surface can be extracted from it, that is, the point cloud data in the aquaculture area. Further, a surface model of each floating body can be generated based on the point cloud images of each floating body and the sea water surface, and the water surface elevation data of each floating body relative to the sea water surface can be calculated by the method of averaging the point cloud elevations of each floating body in the floating body surface model. Or, the water surface elevation data of each floating body relative to the sea water surface can be calculated by using the percentile method of cumulative distribution of the point cloud image elevations of each floating body in the floating body surface model, so as to accurately estimate the water surface elevation data of each floating body above the water surface.

[0036] It should be noted that since floating bodies are usually arranged at intervals, images containing the floating bodies and the sea surface height can be obtained simultaneously throughout the entire period. However, it is necessary to correct the problems of sea surface / water surface fluctuations caused by waves and the like. Therefore, an adaptive sampling interval is proposed according to the wave fluctuations, and a method for estimating the water elevation data of the above-water part of the floating body is established based on the mean method of multiple samplings, that is, the error caused by wave fluctuations is eliminated through multiple samplings during a single voyage. At the same time, in order to eliminate the influence of the tide level on the water surface height of the floating body, the sampling time of the unmanned aerial vehicle is generally selected at a relatively fixed time period during the day.

[0037] Secondly, the calculated effective water elevation data of the floating body relative to the sea surface is input into a preset biomass estimation model to obtain the biomass value of the suspended aquaculture products in the aquaculture plot / unit output by the preset biomass estimation model. Among them, the preset biomass estimation model is pre-constructed based on the water elevation data and the measured standard biomass value, and this preset biomass estimation model can be used to realize the mapping between the real-time water elevation data and the real-time biomass.

[0038] Then, based on the analysis of the spatio-temporal relationship of the biomass values of the suspended aquaculture products at the positions of the floating bodies in the aquaculture area, the monitoring of the growth status of the suspended aquaculture products is realized. Since the aquaculture area includes multiple aquaculture plots / units, and an aquaculture plot floats on the water surface relying on a floating body. Therefore, based on the accurate acquisition of the biomass values of the suspended aquaculture products, continuous monitoring and analysis of the growth status of the suspended aquaculture products in a certain aquaculture plot / unit can be carried out at multiple moments, the monitoring and analysis of the spatial characteristics of the growth status of the suspended aquaculture products in multiple aquaculture plots / units at the same moment can be carried out, or the synchronous detection and analysis of the spatio-temporal relationship can be carried out. Specifically, the monitoring of the biomass of the suspended aquaculture products in a certain aquaculture plot at multiple moments can realize the monitoring and analysis of the growth status of the suspended aquaculture products in the aquaculture plot / unit at a fixed spatial position from the time dimension; the monitoring of the biomass of the suspended aquaculture products in multiple aquaculture plots at the same moment can realize the monitoring and analysis of the spatial characteristics of the growth status of the suspended aquaculture products in multiple aquaculture plots / units in the aquaculture area at a certain moment from the spatial dimension.

[0039] The method for monitoring the state of suspended aquaculture products based on UAV images provided by the present invention uses a UAV to obtain images of floating bodies in the aquaculture area and calculates the water elevation data of each floating body relative to the sea surface / water surface. Then, through a pre-established relationship model between the water elevation of the floating body and the biomass of the suspended aquaculture products, the biomass value is estimated. Finally, through the estimated biomass value, a spatio-temporal analysis of the growth state of the suspended aquaculture products is carried out, enabling the UAV to quickly monitor large-scale fishery production scenarios such as floating rafts and longline suspended culture. In addition, the application of the UAV and its new technologies is more energy-saving, more efficient, and has better spatial accessibility than manual ship inspections, while reducing the interference of ship noise during manual inspections on the aquaculture process.

[0040] In some embodiments, based on the image of the aquaculture area described in step S2, identifying the position information of each floating body and extracting the water elevation data of each floating body relative to the sea surface includes: Extracting the point cloud images of each floating body and the point cloud image of the sea surface from the image of the aquaculture area; converting the point cloud images of each floating body into single-band images of each floating body, and converting the point cloud image of the sea surface into a single-band image of the sea surface; Performing a band difference operation on the single-band images of each floating body and the single-band image of the sea surface respectively to construct a floating body surface model; Calculating the average value of all pixel values corresponding to each floating body in the floating body surface model to obtain the water elevation data of each floating body relative to the sea surface; Alternatively, dividing the elevations corresponding to the point clouds of each floating body in the floating body surface model from low to high according to the elevation cumulative percentage, and determining the elevation corresponding to each percentile; determining the elevation corresponding to the first target percentile as the reference plane height, and determining the elevation corresponding to the second target percentile as the upper boundary height of the floating body water height; the first target percentile is less than the second target percentile; performing a difference operation on the upper boundary height and the reference plane height to obtain the water elevation data of the floating body relative to the sea surface.

[0041] In some embodiments, based on step S2, based on the image, identifying the position information of each floating body. Specifically, the central position information of the floating body used to support each aquaculture plot can be obtained through a deep learning method or a relative elevation threshold method. Based on this central position, a coordinate system of the aquaculture area can be constructed and a spatial position label j corresponding to the floating body can be generated. Of course, the method for determining the position of the floating body is described here, which does not mean that the positions of the floating bodies in the aquaculture area to be monitored must be determined before the growth state monitoring and analysis. The positions of each floating body also need to be obtained and used when monitoring whether there are abnormalities in the growth state and for visualization.

[0042] Specifically, taking the threshold method based on water elevation data to identify the position of floating bodies as an example, this method is simple and easy to implement. First, based on the images obtained by the drone, and based on the constructed floating body surface model, circular focus statistics is performed on the floating body surface model, that is, the elevation values of adjacent regions are assigned to the focus positions through operations, and the required elevation model is obtained through calculation. Then, according to the morphological characteristics of the floating bodies, relative heights in different ranges are set as segmentation thresholds, and the optimal threshold T is selected to accurately identify the positions of each floating body. Finally, the distribution map of the images of the positions of each floating body is obtained. The calculation formula is as follows: In the formula, f(I, J) represents the difference between the floating body surface model I(x, y) and the sea level J(x, y); is the segmentation threshold, which is selected according to the elevation data corresponding to the actual characteristics of the floating body and based on empirical values. For example, 30% of the maximum elevation data can be selected; represents the binary image model after processing, output by is the foreground of the image, is the binary image g(x, y) of the background of the image. Finally, according to the attributes of each connected region in the binary image, based on the average value of the coordinates of all points within a single closed region in the foreground image, the central position points of each floating body in the aquaculture area are calculated.

[0043] Specifically, the position information of each floating body is represented in the plane coordinates of the area to be monitored, and its position label j is determined to clarify the position and label of each floating body for the spatial characteristic analysis of the biomass value. After determining the position of the floating body, the water surface elevation corresponding to each floating body is obtained accordingly, so that the position information of each floating body and the water elevation data can be clarified.

[0044] It should be noted that for the extraction of the water height of floating bodies relying on drone images, the mean method or the elevation cumulative distribution percentile method can be used, and both methods can be carried out in the remote sensing image processing platform (The Environment for Visualizing Images, ENVI). As Figure 2 shown, Figure 2 is the schematic flow chart of calculating the water height of floating bodies provided by the present invention.

[0045] For the mean method, specifically, it can be applied to floating bodies with a flat-top feature. First, the point cloud image obtained by the drone is input into the ENVI software. Through the ENVI software, the point cloud image of the floating body is converted into a single-band image of the floating body, and the point cloud image of the sea surface is converted into a single-band image of the sea surface. That is, the point cloud image of the floating body is converted into two-dimensional image data, and the point cloud image of the sea surface is converted into two-dimensional image data. Since the floating bodies are sparsely distributed on the water surface, the two point cloud images can be obtained in one flight, that is, the images of the floating bodies and the sea surface can be obtained simultaneously. Even if they are obtained in two separate flights, because they are both carried out under the same flight settings, the generated pixels, sizes, and resolutions can all correspond one by one. Then, using the Layer Stacking package in the built-in toolbox of the ENVI software, a band difference operation is performed on the single-band image of the floating body and the single-band image of the sea surface to find the relative height difference between each floating body and the sea surface, thereby constructing the surface model of the floating body. By calculating the mean value of the elevation values of all rasterized point clouds of each floating body in the surface model of the floating body, the above-water elevation data of each floating body relative to the sea surface can be obtained.

[0046] For the cumulative percentile method, specifically, it can be applied to spherical floating bodies such as ellipsoids. First, the point cloud image of the floating body is input into the ENVI software. The elevation data corresponding to the point clouds of each floating body are grouped from low to high in sequence and divided according to a 0.5 percentage interval, such as 0, 0.5%, 1%, 1.5%,...., 100%. Of course, the division is not limited to 0.5 for division and can be divided according to actual needs. Based on the cumulative distribution of elevation, the percentile elevation data boundary values corresponding to each percentage interval are screened out to determine the elevation corresponding to each percentile. Then, a low percentile is selected as the first target percentile, and the elevation corresponding to the first target percentile is used as the reference surface height, which is usually a relatively low height representing the height of the sea surface. A high percentile is selected as the second target percentile, and the elevation corresponding to the second target percentile is used as the upper boundary height of the above-water height of the floating body, which is usually a relatively high height representing the highest point of the floating body. Finally, a difference operation is performed on the selected upper boundary height and the reference surface height to obtain the above-water elevation data of the floating body relative to the sea surface. For example, the first target percentile can be selected as 1%, and the second target percentile can be selected as 99%. Then, the effective value of the above-water elevation of the floating body is the difference between the elevation corresponding to the second target percentile and the elevation corresponding to the first target percentile. Specifically, a more optimal combination of target percentiles is selected according to the shape of the floating body to obtain a relatively accurate above-water elevation value.

[0047] In the embodiments of the present invention, the images obtained by the unmanned aerial vehicle, especially the point cloud images, are used to accurately calculate the elevation of the floating body relative to the sea surface, and then used to calculate the biomass values of the suspended aquaculture products in the aquaculture areas corresponding to each floating body, which can effectively improve the convenience and automation level of the state monitoring of the suspended aquaculture products, and greatly improve the accuracy and timeliness of the data, providing reliable technical support for aquaculture management.

[0048] In some embodiments, the preset biomass estimation model in step S3 is obtained in the following manner: Obtain the measured elevation values of the floating body samples in the aquaculture area relative to the sea surface and the measured biomass values of the suspended aquaculture products in the aquaculture area samples supported by the floating body samples during each growth stage; Construct a variety of initial biomass estimation models for different growth stages; Based on the measured elevation values and measured biomass values during each growth stage, select the model with the optimal accuracy from the variety of initial biomass estimation models during each growth stage to obtain the biomass estimation target models for each growth stage; According to the biomass estimation target models for each growth stage, construct a segmented model and determine the segmented model as the preset biomass estimation model.

[0049] The following content is combined with Figure 3 , Figure 3 is a schematic flow chart of constructing a preset biomass estimation model provided by the present invention.

[0050] Specifically, first, on the basis of obtaining the aquaculture varieties and the structure of the aquaculture devices in the aquaculture area of the suspended aquaculture products to be monitored, and combining the growth stage characteristics of the suspended aquaculture product varieties, divide their aquaculture cycle into several growth stages. Secondly, obtain the measured elevation values Hi of the floating body samples in the aquaculture area relative to the sea surface and the measured biomass values Bi (standard biomass based on the standard growth curve) of the suspended aquaculture products in the aquaculture area samples supported by the floating body samples during each growth stage to form a data set. Then, construct a variety of initial biomass estimation models for different growth stages, such as basic unary functions and their composite functions like Y = aX + b, Y = aX 2 + bX + c, etc. Further, based on the measured elevation values and measured biomass values during each growth stage, divide these data pairs into training groups, calibration groups, etc., and the fitting of unary functions can be completed through methods such as unary linear regression, least squares regression method and non-linear algorithms to complete the training of the model. Then, select the model with the optimal accuracy from the variety of initial biomass estimation models during each growth stage to obtain the biomass estimation target models for each growth stage.

[0051] According to the target model for estimating biomass in each growth stage, a segmented model is constructed. The segmentation basis is the growth stage, and the number of stages is greater than 2. This segmented model is a preset biomass estimation model for estimating the biomass value of suspended aquaculture products by measuring water surface elevation data in real time, and can output relatively accurate biomass based on the water surface elevation data of each floating body measured in real time.

[0052] It should be noted that the measured value of the biomass of the suspended aquaculture products in the aquaculture plot sample refers to the optimal standard biomass value that conforms to the growth curve, or is close to the standard value. After the variety and device structure are determined, the mapping relationship is determined. There are specificities such as coefficients in the preset biomass estimation model corresponding to specific varieties and devices, but the principles and steps are the same.

[0053] In the embodiment of the present invention, the optimal biomass estimation model in different growth stages is selected through measured data, and the optimal biomass estimation models in each growth stage are used to construct a segmented model, ensuring that the preset biomass estimation model can accurately reflect the biomass in different growth stages, and high-precision estimation of the biomass of suspended aquaculture products can be achieved.

[0054] In some embodiments, when constructing multiple initial biomass estimation models in different growth stages, the following steps are performed for each growth stage: Establish a first functional relationship between the water surface elevation data of the floating body sample above the sea surface and the volume below the sea surface; Establish a second functional relationship between the volume and the buoyancy generated by the floating body sample; Establish a third functional relationship between the buoyancy and the biomass value of the suspended aquaculture products in the aquaculture plot sample; According to the first functional relationship, the second functional relationship, and the third functional relationship, establish a fourth functional relationship between the water surface elevation data and the biomass value; According to the fourth functional relationship, construct multiple initial biomass estimation models in the growth stage.

[0055] It should be noted that the fourth functional formula is the mapping relationship between the water surface elevation data and the biomass, that is, the response relationship of the measured water surface elevation of the floating body to the change of biomass. When the biomass of the suspended aquaculture products changes, it will cause the change of the water surface height data of the floating body. Therefore, the mathematical relationship between the water surface elevation data and the biomass can be constructed. For scenarios where a strict quantitative relationship cannot be established, the detailed mapping relationship can be established. Specifically, the principle basis and mathematical analysis are as follows.

[0056] First, establish the water surface elevation H of the floating body and the underwater volume V of the floating body 水下The first functional relationship between them. In actual production, floating bodies are generally rotating bodies such as spheres and ellipsoids, and their volumes can be obtained by integrating the relevant cross-sectional areas. Generally, the cross-sectional area is determined by the shape parameters of the floating body. Let the cross-section of the floating body parallel to the sea surface be , and take its fixed axis perpendicular to the sea level as axis, then represents the cross-sectional area passing through the point and perpendicular to axis, is the integration variable. Further, for the rotating body within the two planes passing through the point and perpendicular to axis, its integration interval is , and for any small interval on , the volume of a thin slice is approximately equal to the volume of a flat cylinder with a bottom area of and a height of , that is, the volume element is . Thus, the volume of the rotating body in the interval is .

[0057] Specifically, taking an ellipsoidal floating body as an example. The floating body can be approximately represented as the figure formed by the upper half of the ellipse (a, b are constants) and the axis, and rotating around the axis to generate a rotating ellipsoid. The underwater volume can be transformed into calculating the volume of the rotating body formed by rotating the figure enclosed by the ellipse around the axis in the corresponding integration interval of the underwater part. This interval is transformed from the underwater part. That is, let the total length of the floating body in the long-axis direction x-axis be 2a, corresponding to the total height of the rotating ellipsoid; let the water surface height be H, then the length of the underwater part of the corresponding floating body is 2a - H. Considering the weight of the cage's own structure, 2a is the upper limit of the water surface height of the floating body, and it is easy to know that H < 2a. Thus, at when the cross-sectional area . Then, the relationship between its underwater volume and the water surface height H of the floating body is: ; Secondly, the second functional relationship between the underwater volume and the buoyancy is F 浮力 = ρgV(H). Where ρ is the density of seawater, which can be taken as 1.02 - 1.07 g / cm 3; g is a constant, which is the ratio of gravity to mass, and g = 9.8 N / Kg; V(H) is the volume of water displaced by a single floating body, representing the relationship between the above-water height H of the floating body and the underwater volume V(H), that is, the first functional relationship, which is determined by the shape and parameters of the floating body. The buoyancy force is the net buoyancy force, F' 浮力 = F 浮力 - m 浮体 g, that is, the self-weight of the floating body needs to be subtracted. On the other hand, the self-weight of the floating body m 浮体 g is relatively small and can be ignored subsequently.

[0058] Then, based on the equilibrium analysis of the planar force system, there is a force balance in the vertical direction of the aquaculture system. Therefore, the relationship between the buoyancy force F of the floating body and the biomass B mas at a certain moment can be established, that is, the third functional relationship. Since it adopts a standardized aquaculture form in water, it can be roughly divided into the form of a single floating body and a single net cage or the form of multiple floating bodies and multiple hanging cages / hanging ropes. According to ∑F x = 0, for any aquaculture device system with m (m≥1) floating bodies, each floating body corresponding to n (n≥1) hanging cages or hanging ropes, and the self-weight of a single hanging cage or hanging rope being W (excluding organisms and its buoyancy force being negligible), it can be approximately expressed as m F 浮力 = m n W + m B mas + s F 牵引绳 cosθ. Further, the biomass of a single aquaculture community / unit is: ; As the third functional relationship between the biomass value and the buoyancy force. Among them, parameters such as W, m, n, s are determined by the structure of the aquaculture device. m is the number of floating bodies, mn is the total number of hanging cages in the aquaculture device, F 浮力 is the buoyancy force of the floating body, B mas is the biomass value of the aquaculture products in suspension, s is the number of towing ropes, F 牵引绳 is the traction force of the towing rope, and θ is the angle between the towing rope and the vertical direction.

[0059] Since the towing rope mainly provides a downward force and the floating body provides the only upward force. In the initial stage of aquaculture, the F towing rope provides a downward force, forming an equilibrium state with the buoyancy force of the floating body; as the biomass (weight) increases, the binding force of F 牵引绳 gradually decreases, and as the biomass continues to increase, the upward buoyancy force increases. Particularly obviously, when the F 牵引绳 constraint is zero, F 浮力It starts to increase with the increase of biomass, and the increase in buoyancy is reflected as a decrease in the water surface height. To a certain extent, the biomass accumulation can be reflected by the height H above the water surface. Specifically, for gravity-type aquaculture cages, etc., there is also an additional traction weight F and a fixed weight.

[0060] It should be noted that after the aquaculture area is determined, the aquaculture varieties it contains are also determined, that is, the aquaculture mode is determined. That is, the structural parameters of the aquaculture devices such as W, m, n, s, etc., the aquaculture varieties, and their aquaculture cycles are determined and fixed, and their functional relationships or mapping relationships are also determined. Specifically, when m = 1 and n = 1, the principle of this method can be used to estimate the change in biomass in cages or aquaculture facilities with similar structures, so as to realize the monitoring of biomass in facilities with similar principles. Based on the above understanding, this method is also applicable to benthic aquatic products cultured in aquaculture facilities such as gravity cages.

[0061] Combining the first functional relationship, the second functional relationship, and the third functional relationship, a fourth functional relationship between the water surface elevation data and the biomass value is constructed. To a certain extent, the biomass accumulation M can be reflected by the height H above the water surface, that is, the fourth functional relationship.

[0062] According to the fourth functional relationship, a variety of initial biomass estimation models within the current multiple growth stages are constructed. In this way, a variety of initial biomass estimation models within each different growth stage can be constructed.

[0063] In the embodiment of the present invention, by establishing a functional mapping relationship between the water surface elevation data of the floating body and the biomass value, the estimation of the biomass of aquaculture aquatic products based on the water surface elevation data is realized, thereby providing a variety of initial estimation models for the biomass monitoring in different growth stages, and significantly improving the accuracy and efficiency of the growth state management during the aquaculture process.

[0064] In some embodiments, based on step S4, the spatio-temporal characteristics of the state of the suspended aquaculture aquatic products in each aquaculture plot in the aquaculture area are analyzed based on each of the biomass values, and the analysis results are obtained, including: Obtain the biomass values of the suspended aquaculture aquatic products in the aquaculture plot at different times, and form a biomass sequence with a time series relationship; If the biomass sequence does not satisfy continuous monotonic change, it is determined that the state of the suspended aquaculture aquatic products is abnormal; If the biomass sequence satisfies continuous monotonic change, compare the preset standard biomass corresponding to each moment with the obtained biomass value; if there is no absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy within the preset difference range, determine that the state of the suspended aquaculture products is normal; if there is an absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy within the preset difference range, determine that there is an abnormality in the state of the suspended aquaculture products.

[0065] The following describes the process of monitoring and analyzing the state of suspended aquaculture products in the aquaculture area corresponding to a floating body from the time dimension, combined with Figure 4 , Figure 4 is a schematic flow chart of the state monitoring of suspended aquaculture products in the time dimension provided by the present invention.

[0066] Specifically, obtain an image of the floating body in the aquaculture area at the current moment through a drone, identify the position information of the floating body j, and calculate the water elevation data of the floating body j relative to the sea surface at the i-th moment, denoted as H ij (j represents the label of the floating body, which is related to the position, and j is fixed in this example; i represents a certain moment, i = 1, 2, 3,...); subsequently, input the water elevation data H ij into the preset biomass estimation model M to output the biomass value M of the suspended aquaculture products in the aquaculture area corresponding to the floating body j at the i-th moment ij , and temporarily store it, and judge whether the current temporary storage quantity is greater than the preset threshold quantity T1 (for example, T1 = 5 can be taken, which together with the sampling interval constitutes the monitoring period); if it is less than the preset threshold quantity T1, further judge whether the aquaculture cycle has ended. If the aquaculture cycle has not ended, return to the first step, obtain the point cloud image of the floating body in the aquaculture area at the next moment (i = i + 1) (not necessarily continuous, but in a sequential order) through the drone, and then calculate the water elevation data H of the floating body j relative to the sea surface ij , estimate through the preset biomass estimation model, and obtain the biomass value M of the suspended aquaculture products corresponding to the position of the floating body j in the aquaculture area at the next moment ij , and temporarily store it, and then judge whether the temporary storage quantity at the next moment is greater than the preset threshold quantity T1, and iterate and repeat multiple times until the temporary storage quantity is greater than the preset threshold quantity T1, that is, obtain the biomass values of the suspended aquaculture products in the aquaculture area corresponding to the floating body at multiple different moments, so as to form a biomass sequence S with a time series relationship M , that is, form the biomass sequence S of the floating body j at consecutive multiple moments M= (M ij , M (i+1)j , M (i+2)j , M (i+3)j , M(i+4)j , M (i+5)j ), or can be briefly noted as (M i , M (i+1) , M (i+2) , M (i+3) , M (i+4) , M (i+5) ).

[0067] Then, judge whether the biomass sequence S M satisfies continuous monotonic change through the formula to judge whether S M satisfies continuous monotonic change, represents the difference in the time series serial numbers at two consecutive moments, refers to the difference in biomass at two consecutive moments.

[0068] If the biomass sequence does not satisfy continuous monotonic change, it is determined that the state of the suspended aquaculture products is abnormal. Based on the abnormal state, refined management measures are taken. Then continue to judge whether the aquaculture cycle has ended. If it has ended, end the status monitoring. If it has not ended, return to the first step to continue collecting data at the next moment.

[0069] If the biomass sequence satisfies continuous monotonic change, then compare the preset standard biomass B ij corresponding to each moment with the obtained biomass value M ij . If there is no absolute value η ij of the difference between the preset standard biomass and the obtained biomass value corresponding to any moment that does not satisfy within the preset difference range T2, it is determined that the state of the suspended aquaculture products is normal. Then continue to judge whether the aquaculture cycle has ended. If it has ended, end the status monitoring. If it has not ended, return to the first step to continue collecting data at the next moment; if there is an absolute value η ij of the difference between the preset standard biomass and the obtained biomass value corresponding to any moment that does not satisfy within the preset difference range T2, it is determined that the growth state of the suspended aquaculture products is abnormal. Optionally, take T2 = 0.1 kg = 2σ, where σ refers to the upper and lower deviation. Assume η ij = 0.3 kg, then there is η ij> > T2, which is an abnormal state. Then, based on the abnormal state, refined management measures are taken. Then continue to judge whether the aquaculture cycle has ended. If it has ended, end the status monitoring. If it has not ended, return to the first step to continue collecting data at the next moment.

[0070] In the embodiments of the present invention, by establishing a biomass sequence and analyzing its change trend, multi-moment monitoring of the state of suspended aquaculture products in a farming area can be achieved, and abnormal changes in biomass can be effectively identified, thereby improving the timeliness and accuracy of aquaculture state monitoring, contributing to the stability of the aquaculture process and the healthy growth of aquaculture products, and providing important technical support for aquaculture management.

[0071] In some embodiments, based on step S4, the spatio-temporal characteristics analysis of the state of the suspended aquaculture products in each aquaculture area in the farming area based on the respective biomass values to obtain an analysis result further includes: Obtain the biomass values of the suspended aquaculture products in multiple different aquaculture areas in the farming area at the current moment, and determine the maximum biomass value and the minimum biomass value among the multiple biomass values; Perform a difference operation on the maximum biomass value and the minimum biomass value to obtain a biomass difference; If the biomass difference is less than or equal to a preset threshold, it is determined that the state of the suspended aquaculture products in the multiple different aquaculture areas is normal; If the biomass difference is greater than the preset threshold, it is determined that the state of the suspended aquaculture products in the multiple different aquaculture areas is abnormal.

[0072] The following describes the process of monitoring and analyzing the state of the suspended aquaculture products in a floating body aquaculture area with multiple floating bodies in terms of the spatial dimension, in combination with Figure 5 , Figure 5 is a schematic flow chart of the state monitoring of the suspended aquaculture products in the spatial dimension provided by the present invention.

[0073] Specifically, images of multiple floating bodies in the farming area at the current moment are obtained by an unmanned aerial vehicle, the position information of each floating body is identified, and the water elevation data of each floating body relative to the sea surface is calculated and denoted as H ij (i represents a certain moment, i = 1, 2, 3,..., i is fixed in this example; j represents the label of the floating body, which is related to the position); the water elevation data of each floating body is input into a preset biomass estimation model M to output the biomass value M of the suspended aquaculture products in the aquaculture area corresponding to each floating body j at the moment i ij , and finally the biomass values of the suspended aquaculture products in the aquaculture areas corresponding to multiple floating balls in the farming area at the moment i are obtained.

[0074] Traverse the biomass values of the suspended aquaculture products in each aquaculture area in the farming area, and determine the maximum biomass value M max and the minimum biomass value M min , perform a difference operation on the maximum biomass value M max and the minimum biomass value M min to obtain a biomass difference λ ij (or simply denoted as λj ).

[0075] Then, determine whether the biomass difference is greater than a preset threshold T3.

[0076] If the biomass difference is less than or equal to the preset threshold T3, for example, optionally T3 = 0.2 kg, it is determined that the state of the suspended aquaculture products in multiple different aquaculture areas is normal, and then continue to determine whether the aquaculture cycle has ended. If it has ended, end the status monitoring. If it has not ended, return to the first step to continue collecting data at a new moment.

[0077] If the biomass difference is greater than the preset threshold T3, it is determined that the state of the suspended aquaculture products in multiple different aquaculture areas is abnormal, and refined management measures in response to the abnormal state are taken, and then continue to determine whether the aquaculture cycle has ended. If it has ended, end the status monitoring. If it has not ended, return to the first step to continue collecting data at a new moment.

[0078] In the embodiment of the present invention, by comparing the differences in biomass values in the aquaculture areas corresponding to multiple floating bodies in the aquaculture area, synchronous monitoring of the state of the suspended aquaculture products in the spatial dimension is realized, the phenomenon of biomass imbalance in the aquaculture area is effectively identified, and it is used to maintain the uniformity of the aquaculture environment and the consistency of the growth of the suspended aquaculture products, providing important technical support for aquaculture management.

[0079] In some embodiments, based on step S4, for analyzing the spatio-temporal characteristics of the state of the suspended aquaculture products in each aquaculture area in the aquaculture area based on each biomass value to obtain an analysis result, it further includes: Simultaneously analyze the time characteristics of a single floating body and the spatial variation of the aquaculture product biomass in the aquaculture areas corresponding to multiple floating bodies in the aquaculture area at the same moment. That is, monitor and analyze the aquaculture product biomass from both the spatio-temporal dimensions simultaneously. That is, refer to Figure 4 , Figure 5 for simultaneous analysis.

[0080] In some embodiments, based on step S4, after determining that the state of the suspended aquaculture products is abnormal, it further includes: Perform a difference operation on the biomass value of the suspended aquaculture products in each aquaculture area and the preset standard biomass corresponding to the current moment to obtain a difference result; Generate multiple types of legends based on the position information of the floating body supporting each aquaculture area and its corresponding difference result; Visually display the multiple types of legends, combine with the threshold to generate a warning message, and take aquaculture management measures according to the multiple types of legends and the warning message.

[0081] Specifically, determine the position information of the floating bodies used to support each aquaculture area obtained in step S2. In addition, the biomass value M of the aquaculture products suspended in the aquaculture area corresponding to each floating ball ij is subtracted from the preset standard biomass B corresponding to the current moment i to perform a difference operation, obtaining a difference result w i . It should be noted that there is a preset standard growth curve for the aquaculture products suspended, which includes the standard biomass corresponding to different growth stages, that is, the preset standard biomass

[0082] Furthermore, based on the position information of the floating bodies used to support each aquaculture area and their corresponding difference results w i , generate multiple types of legends, such as heatmaps and other visualization legends. The specific process of generating a heatmap is as follows: use the position information of each floating body as the planar coordinates of the heatmap to clarify the position of each floating body, and use the difference result corresponding to each floating body as the ordinate of the heatmap. The larger the difference result, the darker the color used, to represent the deviation degree between the biomass value and the preset standard biomass

[0083] Visualize the generated results through legends such as heatmaps and generate warning information, so that the aquaculture manager can judge whether artificial intervention is needed based on the heatmap and warning information, and take aquaculture management measures, such as planning a path to guide the drone or intervening manually to strengthen aquaculture management

[0084] This embodiment of the method generates a heatmap by integrating position information and biomass difference results, and realizes visual display and warning information output, providing an intuitive monitoring tool for the aquaculture manager, enabling abnormal states to be quickly located and responded to, thus significantly improving the response speed and decision-making efficiency of aquaculture management, and ensuring the stability of the aquaculture process and the aquaculture quality of the suspended aquaculture products

[0085] Next, a monitoring system for the state of suspended aquaculture products provided by the present invention will be described. The monitoring system for the state of suspended aquaculture products described below can be mutually referred to the monitoring method for the state of suspended aquaculture products described above

[0086] Refer to Figure 6 , Figure 6 which is a schematic structural diagram of the monitoring system for the state of suspended aquaculture products provided by the present invention

[0087] The monitoring system for the state of suspended aquaculture products includes: The UAV-based image acquisition module 610 is used to acquire images of multiple floating bodies in the aquaculture devices in the aquaculture area of the aquaculture products to be monitored by the UAV and images of the sea surface, and process the images of each floating body and the images of the sea surface to obtain images such as point clouds of the aquaculture area; any one of the floating bodies is used to support an aquaculture plot to float on the water surface.

[0088] The water elevation data extraction module 620 is used to identify the position information of each floating body based on the point cloud and other images, and extract the water elevation data of each floating body relative to the sea surface.

[0089] The biomass estimation module 630 is used to input the water elevation data into a preset biomass estimation model to obtain the biomass values of the aquaculture products suspended and cultured in each aquaculture plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values.

[0090] The growth state detection module 640 is used to perform spatio-temporal characteristic analysis on the states of the aquaculture products suspended and cultured in each aquaculture plot in the aquaculture area based on the biomass values, obtain the analysis results, and visually display the analysis results.

[0091] The management and warning module 650 is used to perform visual aquaculture management, generate warning information and operation guidance when it is detected that the state of the aquaculture products suspended and cultured is abnormal.

[0092] The aquaculture product state monitoring system provided by the present invention uses a UAV to acquire point cloud images of floating bodies in the aquaculture area, calculates the water elevation data of each floating body relative to the sea surface, further estimates the biomass values through a pre-established relationship model between the height of the water part of the floating body and the biomass of the aquaculture products suspended and cultured, and further performs spatio-temporal analysis on the growth states of the aquaculture products suspended and cultured through the estimated biomass values, enabling the UAV to quickly monitor large water surface fishery production scenarios such as raft and longline aquaculture. In addition, the application of the UAV and its technology is more energy-saving and efficient than manual ship patrol, and at the same time reduces the interference of ship noise and the like during manual patrol on the aquaculture process.

[0093] Furthermore, the water elevation data extraction module 620 is further used for: Extracting the point cloud images of each floating body and the point cloud image of the sea surface from the point cloud image of the aquaculture area; converting the point cloud images of each floating body into single-band images of each floating body, and converting the point cloud image of the sea surface into a single-band image of the sea surface; Performing band difference operations on the single-band images of each floating body and the single-band image of the sea surface respectively to construct a floating body surface model; Calculate the average of all pixel values corresponding to each floating body in the floating body surface model to obtain the water elevation data of each floating body relative to the sea surface; Alternatively, divide the elevations corresponding to the point clouds of each floating body in the floating body surface model from low to high into elevation cumulative percentages, and determine the elevation corresponding to each percentile; determine the elevation corresponding to the first target percentile as the reference surface height, and determine the elevation corresponding to the second target percentile as the upper boundary height of the water height of the floating body; the first target percentile is less than the second target percentile; perform a difference operation on the upper boundary height and the reference surface height to obtain the water elevation data of the floating body relative to the sea surface.

[0094] Further, the suspended aquaculture product status monitoring system is also used for: Obtain the measured elevation values of the floating body samples in the aquaculture area relative to the sea surface and the measured biomass values of the suspended aquaculture products in the aquaculture plot samples supported by the floating body samples in each growth stage; Construct multiple initial biomass estimation models in different growth stages; Based on the measured elevation values and measured biomass values in each growth stage, select the model with the optimal accuracy from the multiple initial biomass estimation models in each growth stage to obtain the biomass estimation target model in each growth stage; According to the biomass estimation target model in each growth stage, construct a segmented model, and determine the segmented model as the preset biomass estimation model.

[0095] Further, the suspended aquaculture product status monitoring system is also used for: Establish a first functional relationship between the water elevation data of the floating body sample on the sea surface and the volume under the sea surface; Establish a second functional relationship between the volume and the buoyancy generated by the floating body sample; Establish a third functional relationship between the buoyancy and the biomass value of the suspended aquaculture products in the aquaculture plot sample; According to the first functional relationship, the second functional relationship, and the third functional relationship, establish a fourth functional relationship between the water elevation data and the biomass value; According to the fourth functional relationship, construct multiple initial biomass estimation models in the growth stage.

[0096] Further, the growth status detection module 640 is also used for: Obtain the biomass values of the suspended aquaculture products in the aquaculture plot at different times to form a biomass sequence with a time series relationship; If the biomass sequence does not satisfy continuous monotonic change, it is determined that the status of the suspended aquaculture products is abnormal; If the biomass sequence satisfies continuous monotonic change, compare the preset standard biomass corresponding to each moment with the obtained biomass value; if there is no absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy within the preset difference range, determine that the state of the suspended aquaculture products is normal; if there is an absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy within the preset difference range, determine that there is an abnormality in the state of the suspended aquaculture products.

[0097] Further, the growth state detection module 640 is further configured to: Obtain the biomass values of the suspended aquaculture products in multiple different aquaculture areas within the aquaculture area at the current moment, and determine the maximum biomass value and the minimum biomass value among the multiple biomass values; Perform a difference operation on the maximum biomass value and the minimum biomass value to obtain a biomass difference; If the biomass difference is less than or equal to a preset threshold, determine that the state of the suspended aquaculture products in the multiple different aquaculture areas is normal; If the biomass difference is greater than the preset threshold, determine that there is an abnormality in the state of the suspended aquaculture products in the multiple different aquaculture areas.

[0098] Further, the suspended aquaculture product state monitoring system is further configured to: Perform a difference operation on the biomass value of the suspended aquaculture products in each aquaculture area and the preset standard biomass corresponding to the current moment to obtain a difference result; Generate multiple types of legends based on the position information of the floating bodies supporting each aquaculture area and their corresponding difference results; Visually display the multiple types of legends, combine with the threshold to generate a warning message, so as to take aquaculture management measures according to the multiple types of legends and the warning message.

[0099] It should be noted that the suspended aquaculture product state monitoring system provided by the present invention can execute the suspended aquaculture product state monitoring method described in any of the above embodiments during specific operation, and this embodiment will not be elaborated here.

[0100] Figure 7 is a schematic structural diagram of the electronic device provided by the present invention, as Figure 7As shown in the figure, the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communications interface 720, and the memory 730 complete communication with each other through the communication bus 740. The processor 710 may call logic instructions in the memory 730 to execute the method for monitoring the state of aquaculture products in suspension. The method includes: obtaining images of a plurality of floating bodies in a cultivation device and an image of the sea surface in the cultivation area of the aquaculture products in suspension to be monitored by a drone, and processing the images of each floating body and the image of the sea surface to obtain a point cloud image of the cultivation area; any one of the floating bodies is used to support a cultivation plot to float on the water surface; based on the point cloud image, identifying the position information of each floating body, and extracting the water elevation data of each floating body relative to the sea surface; inputting each water elevation data into a preset biomass estimation model to obtain the biomass values of the aquaculture products in suspension in each cultivation plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values; based on each biomass value, performing spatio-temporal characteristic analysis on the state of the aquaculture products in suspension in each cultivation plot in the cultivation area to obtain an analysis result, and visually displaying the analysis result.

[0101] In addition, when the logic instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0102] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method for monitoring the state of aquaculture products in suspension provided in the above embodiments. The method includes: obtaining images of a plurality of floating bodies in a cultivation device and an image of the sea surface in the cultivation area of the aquaculture products in suspension to be monitored through a drone, and processing the images of each floating body and the image of the sea surface to obtain a point cloud image of the cultivation area; any one of the floating bodies is used to support a cultivation plot to float on the water surface; based on the point cloud image, identifying the position information of each floating body, and extracting the water elevation data of each floating body relative to the sea surface; inputting each water elevation data into a preset biomass estimation model to obtain the biomass values of the aquaculture products in suspension in each cultivation plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values; based on each biomass value, performing spatio-temporal characteristic analysis on the state of the aquaculture products in suspension in each cultivation plot in the cultivation area to obtain an analysis result, and visually displaying the analysis result.

[0103] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the method for monitoring the state of aquaculture products in suspension provided in the above embodiments. The method includes: obtaining images of a plurality of floating bodies in a cultivation device and an image of the sea surface in the cultivation area of the aquaculture products in suspension to be monitored through a drone, and processing the images of each floating body and the image of the sea surface to obtain a point cloud image of the cultivation area; any one of the floating bodies is used to support a cultivation plot to float on the water surface; based on the point cloud image, identifying the position information of each floating body, and extracting the water elevation data of each floating body relative to the sea surface; inputting each water elevation data into a preset biomass estimation model to obtain the biomass values of the aquaculture products in suspension in each cultivation plot output by the preset biomass estimation model; the preset biomass estimation model is used to map the relationship between the water elevation data and the biomass values; based on each biomass value, performing spatio-temporal characteristic analysis on the state of the aquaculture products in suspension in each cultivation plot in the cultivation area to obtain an analysis result, and visually displaying the analysis result.

[0104] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative effort.

[0105] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for monitoring the status of suspended aquatic products based on drone images, characterized in that: include: S1. Acquire images of a plurality of floating bodies in aquaculture devices and images of the sea surface in aquaculture areas of suspended aquatic products to be monitored by using a drone, and process the images of the floating bodies and the sea surface to obtain images of the aquaculture areas; any of the floating bodies is used to support an aquaculture community floating on the water surface; S2. Based on the image of the aquaculture area, identifying the position information of each of the floating bodies, and extracting the water elevation data of each of the floating bodies relative to the sea surface; S3, inputting each of the above-water elevation data into a preset biomass estimation model to obtain the biomass value of the suspended aquatic products in each of the aquaculture areas output by the preset biomass estimation model; The preset biomass estimation model is used to map the relationship between water elevation data and biomass values; S4. Based on each of the biomass values, perform spatiotemporal characteristic analysis on the state of the suspended aquatic products in each of the breeding areas in the breeding area to obtain analysis results, and visualize the analysis results.

2. The method for monitoring the state of suspended aquatic products based on drone images according to claim 1 is characterized in that: The method of identifying the position information of each of the floating bodies based on the image of the aquaculture area and extracting the water elevation data of each of the floating bodies relative to the sea surface includes: Extracting a point cloud image of each of the floating bodies and a point cloud image of the sea surface from the image of the aquaculture area; converting the point cloud image of each of the floating bodies into a single-band image of each of the floating bodies, and converting the point cloud image of the sea surface into a single-band image of the sea surface; Performing band difference calculation on the single-band image of each floating body and the single-band image of the sea surface to construct a floating body surface model; Calculate the mean of all pixel values ​​corresponding to each floating body in the floating body surface model to obtain the water elevation data of each floating body relative to the sea surface; Or, the elevations corresponding to the floating point clouds in the floating body surface model are divided into cumulative percentages from low to high, and the elevation corresponding to each percentile is determined; the elevation corresponding to the first target percentile is determined as the reference surface height, and the elevation corresponding to the second target percentile is determined as the upper boundary height of the floating body's water height; the first target percentile is less than the second target percentile; the upper boundary height and the reference surface height are differenced to obtain the water elevation data of the floating body relative to the sea surface.

3. The method for monitoring the state of suspended aquatic products based on drone images according to claim 1 is characterized in that: The preset biomass estimation model is obtained by: Obtaining the measured values ​​of the elevation of the floating body sample in the aquaculture area relative to the sea surface and the measured values ​​of the biomass of suspended aquatic products in the aquaculture area sample supported by the floating body sample in each growth stage; Constructing various initial models for biomass estimation at different growth stages; Based on the measured values ​​of elevation and biomass in each growth stage, the model with the best accuracy is selected from a variety of initial models for biomass estimation in each growth stage to obtain the target model for biomass estimation in each growth stage; According to the biomass estimation target model in each growth stage, a segmented model is constructed, and the segmented model is determined as the preset biomass estimation model.

4. The method for monitoring the state of suspended aquatic products based on drone images according to claim 3 is characterized in that: When constructing the initial models for estimating multiple biomass at different growth stages, the following steps were performed for each growth stage: Establishing a first functional relationship between the water elevation data of the floating body sample on the sea surface and the volume under the sea surface; Establishing a second functional relationship between the volume and the buoyancy generated by the floating sample; Establishing a third functional relationship between the buoyancy and the biomass value of the suspended aquatic products in the aquaculture area sample; Establishing a fourth functional relationship between water elevation data and biomass value according to the first functional relationship, the second functional relationship and the third functional relationship; Based on the fourth functional relationship, multiple initial models for estimating biomass in the growth stage are constructed.

5. The method for monitoring the state of suspended aquatic products based on drone images according to claim 1 is characterized in that: Based on each of the biomass values, the spatiotemporal characteristics of the state of the suspended aquatic products in each of the aquaculture areas in the aquaculture area are analyzed to obtain analysis results, including: Obtaining the biomass values ​​of the suspended aquatic products in the aquaculture area at different times to form a biomass sequence with a time series relationship; If the biomass sequence does not satisfy continuous monotonic changes, it is determined that the state of the suspended aquatic product is abnormal; If the biomass sequence satisfies continuous monotonic change, the preset standard biomass corresponding to each moment and the obtained biomass value are compared; if there is no absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy the preset difference range, it is determined that the state of the hanging aquatic product is normal; if there is an absolute value of the difference between the preset standard biomass corresponding to any moment and the obtained biomass value that does not satisfy the preset difference range, it is determined that the state of the hanging aquatic product is abnormal.

6. The method for monitoring the state of suspended aquatic products based on drone images according to claim 1 is characterized in that: The step of performing a spatiotemporal characteristic analysis on the state of the suspended aquatic products in each of the aquaculture plots in the aquaculture area based on each of the biomass values ​​to obtain an analysis result further includes: Obtaining biomass values ​​of suspended aquatic products in a plurality of different aquaculture plots within the aquaculture area at the current moment, and determining a maximum biomass value and a minimum biomass value among the plurality of biomass values; Performing a difference operation on the maximum biomass value and the minimum biomass value to obtain a biomass difference; If the biomass difference is less than or equal to a preset threshold, it is determined that the status of the suspended aquatic products in the multiple different breeding areas is normal; If the biomass difference is greater than the preset threshold, it is determined that there is an abnormality in the state of the suspended aquatic products in the multiple different breeding areas.

7. The method for monitoring the state of suspended aquatic products based on drone images according to claim 6 is characterized in that: After determining that the state of the suspended aquatic product is abnormal, the method further includes: Perform a difference calculation on the biomass value of the suspended aquatic products in each breeding area and the preset standard biomass corresponding to the current moment to obtain a difference result; Generate multiple types of legends based on the position information of the floating body supporting each aquaculture plot and its corresponding difference results; The multi-type legends are displayed visually, and warning information is generated in combination with thresholds, so that breeding management measures can be taken according to the multi-type legends and the warning information.

8. A system for monitoring the status of suspended aquatic products based on drone images, characterized in that: include: The drone-based image acquisition module is used to acquire images of multiple floating bodies in the aquaculture device and the sea surface in the aquaculture area of ​​the suspended aquatic products to be monitored through the drone, and process the images of each of the floating bodies and the sea surface to obtain an image of the aquaculture area; any of the floating bodies is used to support a aquaculture community floating on the water surface; An above-water elevation data extraction module is used to identify the position information of each of the floating bodies based on the image of the aquaculture area, and to extract the above-water elevation data of each of the floating bodies relative to the sea surface; A biomass estimation module, used to input each of the above-water elevation data into a preset biomass estimation model to obtain the biomass value of the suspended aquatic products in each of the aquaculture areas output by the preset biomass estimation model; The preset biomass estimation model is used to map the relationship between water elevation data and biomass values; A growth status detection module is used to perform spatiotemporal characteristic analysis on the status of the suspended aquatic products in each of the aquaculture areas in the aquaculture area based on each of the biomass values, obtain analysis results, and visualize the analysis results; The management and early warning module is used to perform visual breeding management, generate early warning information and provide operation guidance when abnormalities are detected in the status of the suspended aquatic products.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for monitoring the status of suspended aquatic products based on drone images as described in any one of claims 1 to 7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the method for monitoring the status of suspended aquatic products based on drone images as described in any one of claims 1 to 7 are implemented.

Images