Nitrogen and phosphorus pollution monitoring system for multi-pilot-point culture water area

Abstract

The invention provides a multi-pilot-point culture water area nitrogen and phosphorus pollution monitoring system, and relates to the technical field of computer processing, and the system comprises a first data acquisition module which is used for acquiring nitrogen and phosphorus content data of a current detection point according to a predetermined window period; the second data acquisition module is used for capturing photo data a of the first data acquisition module and photo data b in a preset water area range around the first data acquisition module; the image recognition and analysis module is used for respectively extracting green alga characteristics on the photo data a and the photo data b in the same time unit, and evaluating interference parameters on nitrogen and phosphorus content data according to an extraction result; and the interference model matching and calibration parameter generation module is used for matching based on the obtained interference parameters. According to the invention, the problem of inaccurate monitoring data caused by interference of green algae and attached substances is effectively solved, and reliable technical support is provided for nitrogen and phosphorus pollution management of an aquaculture water area.

Description

Technical Field

[0001] The present invention relates to the technical field of computer processing, and particularly to a multi-pilot aquaculture water area nitrogen and phosphorus pollution monitoring system. Background Art

[0002] The detection of nitrogen and phosphorus pollution in water areas is divided into two types: online monitoring and sampling detection, where:

[0003] Online monitoring belongs to monitoring. It periodically extracts liquid through an online detector to collect water samples at regular intervals for detection. The characteristic of this technology is that it can monitor in real time for a long time.

[0004] Compared with online monitoring, sampling detection involves a richer variety of equipment, so the authenticity and accuracy of the detected water sample data are higher.

[0005] However, for the monitoring of nitrogen and phosphorus pollution in aquaculture water areas, long-term real-time monitoring is required. Therefore, online monitoring technology is generally adopted. For example, in Chinese Patent, Publication No. CN119248900 A, a method and system for tracing the trajectory of nitrogen and phosphorus pollutants using a GIS system are disclosed. This method realizes the tracing and positioning of nitrogen and phosphorus pollutants through steps such as constructing an initial vector line segment, detecting the concentration of nitrogen and phosphorus pollutants, and generating a tracing direction. This technology and system help to accurately identify pollution sources and provide a scientific basis for the prevention and control of nitrogen and phosphorus pollution.

[0006] In the prior art including the above patent, in the detection link for nitrogen and phosphorus pollution, it mainly focuses on the detection and analysis of pollution, tracing, or predicting future threats to aquaculture through analysis and evaluation, so as to prompt early treatment. However, one problem that has been overlooked is that the nitrogen and phosphorus pollution detected in aquaculture water areas mainly comes from shallow-water fish rather than deep-water fish. However, the deployed nitrogen and phosphorus pollution monitoring instruments are all arranged in shallow water. After being irradiated by sunlight for a long time, certain aquatic plants will inevitably grow on the instruments. Since the attached algae and other substances may contain chemical components similar to nitrogen and phosphorus, this will interfere with the progress of chemical reactions. This may cause the monitoring results to be too high or too low, and unable to truly reflect the nitrogen and phosphorus pollution status of the aquaculture water area. Removing them using external equipment obviously has little effect. Therefore, how to solve this technical problem has become an urgent problem to be solved at the present stage. Summary of the Invention

[0007] In view of the above technical problems, the technical solution adopted by the present invention is a multi-pilot aquaculture water area nitrogen and phosphorus pollution monitoring system, including:

[0008] A first data acquisition module, which is used to acquire nitrogen and phosphorus content data of the current detection point according to a predetermined window period;

[0009] The second data acquisition module is used to capture the photo data a of the first data acquisition module and the photo data b within a predetermined water area around the first data acquisition module;

[0010] The image recognition and analysis module extracts the green algae features on the photo data a and the photo data b of the same time unit respectively, and evaluates the interference parameter for the nitrogen and phosphorus content data according to the extraction results;

[0011] The interference model matching and calibration parameter generation module performs matching based on the obtained interference parameter, obtains the most suitable model in the pre-stored interference models, and generates calibration parameters;

[0012] The data correction module corrects the nitrogen and phosphorus content data based on the X′ = X×(1 + C) algorithm to obtain the corrected nitrogen and phosphorus content data, where: X is the nitrogen and phosphorus content data, and C is the calibration parameter;

[0013] The data comparison and verification module is used to verify the corrected nitrogen and phosphorus content data of the current detection point and judge whether the correction result is supported:

[0014] If it is not supported, the second data acquisition module is re-executed to correct the interference parameter;

[0015] If it is supported, the data is output.

[0016] Preferably, the first data acquisition module is a diving collection execution component of a nitrogen and phosphorus monitor, and the diving collection execution component can be a buoy type integrated monitor or a detection end.

[0017] Preferably, the second data acquisition module includes:

[0018] The first underwater high-definition camera group, which includes a plurality of underwater high-definition camera groups distributed in a circumferential array around the diving collection execution component, where:

[0019] There are identical parts in the photos obtained by two adjacent underwater high-definition camera groups of the diving collection execution component, and the specifications of the identical parts are known;

[0020] The photo fusion unit is used to overlap the multiple groups of photos obtained by the first underwater high-definition camera group according to the identical parts to obtain a holographic photo of the diving collection execution component, and the photo data a includes the holographic photo;

[0021] The second underwater high-definition camera is arranged along the water flow direction of the current detection point water area, captures panoramic photos within a predetermined range around the diving collection execution component, and other features in the panoramic photos except the diving collection execution component are pre-entered in advance. The other features include stones, dead wood or fishing nets, and the photo data b includes panoramic photos.

[0022] Preferably, the image recognition and analysis module includes:

[0023] An image data acquisition execution unit that acquires no less than ten consecutive frames of photo data a and photo data b before the first data acquisition module executes, and no less than ten consecutive frames of photo data a and photo data b after the first data acquisition module executes;

[0024] A multi-channel data processing unit that creates processing channels corresponding to the number of photos based on the cloud;

[0025] A feature extraction unit that is used to respectively capture and extract the green algae features in each frame of the photo;

[0026] A coverage judgment unit that creates a grid on the photo, extracts the coordinate set of the green algae features of the photo regarding the photo data a and the coordinate set of the green algae features of the photo regarding the photo data b, and obtains the green algae feature coverage area according to the coordinate sets of the corresponding photos;

[0027] Calculate the average value a of the green algae feature coverage area of the photo data a in the multiple frames 平 and the average value b of the green algae feature coverage area of the photo data b in the multiple frames 平 ;

[0028] Then, based on the obtained average value a 平 and average value b 平 Perform a ratio calculation with the photo grid area to obtain the coverage ratio of the photo data a and the coverage ratio of the photo data b.

[0029] Preferably, the calculation of the interference parameter for evaluating the nitrogen and phosphorus content data according to the extraction result in the image recognition and analysis module includes

[0030] Y = (β * X1 + β * X2) + ∈;

[0031] Wherein, Y is the coverage ratio of the photo data a and the coverage ratio of the photo data b, β represents the interference parameter for the green algae coverage ratio, X1 is the nitrogen content value in the nitrogen and phosphorus content data, and X2 is the phosphorus content value in the nitrogen and phosphorus content data.

[0032] Preferably, the interference model matching and calibration parameter generation module includes:

[0033] A database, which includes a plurality of pre-stored interference models, the interference models including green algae species, interference parameters under the coverage of green algae of corresponding species, and a corresponding set of calibration parameters;

[0034] A target positioning unit, which obtains the green algae features on the photo data a and the green algae features on the photo data b, and obtains the corresponding green algae species from the extracted green algae features.

[0035] Preferably, the data comparison and verification module executes a method for verifying the corrected nitrogen and phosphorus content data of the current detection point, including:

[0036] S10. Obtain the corrected nitrogen and phosphorus content data of the only adjacent detection point adjacent to the relevant current detection point;

[0037] S11. (The corrected nitrogen and phosphorus content data of the current detection point / the corrected nitrogen and phosphorus content data of the only adjacent detection point) * 100%. If the result is less than or equal to 20%, it is determined that the result output is correct, and continue to execute the next step. If the result is greater than 20%, it is determined that the result output is incorrect, and then return to the second data acquisition module to execute again;

[0038] S12. Obtain the historical data of the corrected nitrogen and phosphorus content data of the current detection point. The historical data is not less than the data of at least ten predetermined window periods. Then calculate the average change factor of the data of multiple predetermined window periods, and then calculate the simulated value of the corrected nitrogen and phosphorus content data of the current detection point;

[0039] S13. Subtract the obtained simulated value from the corrected nitrogen and phosphorus content data of the current detection point. If the difference does not exceed 5, it is determined that the result holds. If it exceeds, it is determined that the result does not hold, and then return to the second data acquisition module to execute again.

[0040] Preferably, the acquisition of the change factor in step S12 includes:

[0041] S121. Calculate the change rate of the corrected nitrogen and phosphorus content data of two adjacent predetermined windows. The formula is as follows:

[0042] (Nitrogen and phosphorus content in the current period - nitrogen and phosphorus content in the previous period) / nitrogen and phosphorus content in the previous period × 100%;

[0043] S122. Average the change rates of all predetermined window periods to obtain an average change factor;

[0044] S123. Select the corrected nitrogen and phosphorus content data of the most recent predetermined window period as the reference value, then the simulated value = reference value × (1 + average change factor).

[0045] The present invention has at least the following beneficial effects:

[0046] 1. By integrating a high-definition underwater camera (the second data acquisition module), the system can capture the green algae situation of the nitrogen and phosphorus monitor (the first data acquisition module) and the surrounding waters. The image recognition and analysis module can extract the green algae features in the photos and evaluate the interference parameters that the green algae may generate on the nitrogen and phosphorus content data. The interference model matching and calibration parameter generation module then selects the most suitable model from the pre-stored interference models based on these interference parameters and generates the corresponding calibration parameters.

[0047] 2. Using the generated calibration parameters, the original nitrogen and phosphorus content data is corrected through a specific algorithm to obtain more accurate nitrogen and phosphorus content data. And by further verifying the corrected data, through comparison with the data of adjacent monitoring points and the simulation volume comparison of historical data, the accuracy and reliability of the data are ensured.

[0048] 3. It helps the managers of aquaculture waters to understand the water pollution situation in a timely manner, formulate effective management strategies, provides real-time data support, helps the managers to discover and handle potential pollution problems in a timely manner, and protects the ecological environment of aquaculture waters. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only 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.

[0050] Figure 1 It is a module diagram of a multi-pilot aquaculture water area nitrogen and phosphorus pollution monitoring system provided in Embodiment 1 of the present invention;

[0051] Figure 2 It is a unit architecture diagram of the second data acquisition module provided in Embodiment 1 of the present invention;

[0052] Figure 3 It is a unit architecture diagram of the image recognition and analysis module provided in Embodiment 1 of the present invention;

[0053] Figure 4 It is a unit architecture diagram of the interference model matching and calibration parameter generation module provided in Embodiment 1 of the present invention;

[0054] Figure 5 It is a flowchart of the data comparison and verification module provided in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0056] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data used in appropriate cases can be interchanged so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0057] Embodiment 1

[0058] This embodiment provides a multi-pilot aquaculture water area nitrogen and phosphorus pollution monitoring system, as Figure 1 shown, the above system architecture includes:

[0059] The first data acquisition module is used to acquire the nitrogen and phosphorus content data of the current detection point according to a predetermined window period;

[0060] Specifically, the first data acquisition module is the diving acquisition execution component of the nitrogen and phosphorus monitor, and the diving acquisition execution component can be a buoy-type integrated monitor or a detection end. And according to the predetermined window period includes how long the interval is and the duration of data acquisition.

[0061] The second data acquisition module is used to capture the photo data a of the first data acquisition module and the photo data b within a predetermined water area range around the first data acquisition module;

[0062] Specifically, as combined with Figure 2 shown, the above second data acquisition module includes:

[0063] The first underwater high-definition camera group, which includes a plurality of underwater high-definition camera groups distributed in a circumferential array around the diving acquisition execution component, where:

[0064] There are the same parts in the photos obtained by two adjacent underwater high-definition camera groups of the diving acquisition execution component, and the specifications of the same parts are known;

[0065] A photo fusion unit, which is used to overlap multiple groups of photos obtained from the first underwater high-definition camera set according to the same parts to obtain a holographic photo of the diving collection execution component, and the photo data a includes the holographic photo;

[0066] A second underwater high-definition camera, which is arranged along the water flow direction of the current detection point water area, captures a panoramic photo within a predetermined range around the diving collection execution component, and other features except the diving collection execution component in the panoramic photo are pre-recorded in advance. The other features include stones, dead wood or fishing nets, and the photo data b includes the panoramic photo.

[0067] In the above technology, the photo fusion unit overlaps according to the same coverage area of the pictures obtained from the two known underwater high-definition camera sets, so as to overlap the same parts of multiple photos in a predetermined azimuth order to obtain a complete holographic photo. That is to say, the formed photo data a is composed of multiple holographic photos.

[0068] Similarly, the photos obtained by the second underwater high-definition camera include the identification of other features and the identification of the features of the diving collection execution component. Through the extraction of known features, it is convenient to identify and extract the green algae coverage of the target features. And the above photo data b is composed of multiple panoramic photos.

[0069] The first underwater high-definition camera set can capture the green algae situation on the monitor omni-directionally and multi-angularly to ensure the comprehensiveness and accuracy of the image data. The second underwater high-definition camera can capture the green algae distribution in a wider water area range, which helps to more deeply analyze the interference of green algae on the monitoring data. Through the cooperation of these two groups of cameras, the system can more comprehensively understand the green algae situation in the aquaculture water area and provide strong support for subsequent data correction.

[0070] An image recognition and analysis module, which extracts the green algae features on the photo data a and the photo data b in the same time unit respectively, and evaluates the interference parameters on the nitrogen and phosphorus content data according to the extraction results;

[0071] Specifically, as Figure 3 shown, the above image recognition and analysis module includes:

[0072] An image data acquisition execution unit, which acquires continuously no less than ten frames of photo data a and photo data b before the execution of the first data acquisition module, and continuously no less than ten frames of photo data a and photo data b after the execution of the first data acquisition module;

[0073] A multi-channel data processing unit, which creates processing channels corresponding to the number of photos based on the cloud;

[0074] A feature extraction unit, which is used to capture and extract the green algae features in each frame of photo respectively;

[0075] A coverage judgment unit creates a grid on the photo, extracts the coordinate sets of the green algae features of the photo regarding photo data a and the coordinate sets of the green algae features of the photo regarding photo data b, and obtains the coverage area of the green algae features based on the coordinate sets of the corresponding photo;

[0076] Obtain the average value a of the coverage areas of the green algae features of photo data a in multiple frames 平 and the average value b of the coverage areas of the green algae features of photo data b in multiple frames 平 ;

[0077] Then, based on the obtained average value a 平 and average value b 平 perform a ratio calculation with the photo grid area to obtain the coverage ratios of photo data a and photo data b.

[0078] And the calculation of the interference parameter for the nitrogen and phosphorus content data according to the extraction results in the image recognition and analysis module includes

[0079] Y = (β * X1 + β * X2) + ∈;

[0080] where Y is the coverage ratio of photo data a and the coverage ratio of photo data b, β represents the interference parameter for the green algae coverage ratio, X1 is the nitrogen content value in the nitrogen and phosphorus content data, and X2 is the phosphorus content value in the nitrogen and phosphorus content data.

[0081] In the above technology, each photo in each frame includes a holographic photo and a panoramic photo. The extraction of the green algae features uses a well-known image feature extraction algorithm, which belongs to the prior art, so it will not be elaborated in detail.

[0082] Furthermore, the specifications of the obtained photos in the above embodiments are fixed, that is, the area of the photos is fixed, and the green algae features extracted can be obtained according to the extracted coordinates and then the coverage area of the green algae features can be calculated. This belongs to the conventional basis, and then through the ratio algorithm, the ratio of the current coverage area of the green algae features occupying the area of the photo can be obtained.

[0083] Furthermore, the image recognition and analysis module acquires continuous photo data through the image data acquisition execution unit, and uses the multi-channel data processing unit and the feature extraction unit to capture and extract the green algae features in each frame of photo. Then, the coverage judgment unit calculates the coverage ratio of the green algae features and evaluates the interference parameter for the nitrogen and phosphorus content data based on the extraction results. It can automatically and quickly extract the green algae features in the photo and calculate their coverage ratio. This step is crucial for evaluating the interference of green algae on the monitoring data. At the same time, the module can also match the pre-stored interference model according to the extracted green algae features and generate calibration parameters to provide key information for subsequent data correction.

[0084] The interference model matching and calibration parameter generation module performs matching based on the obtained interference parameter, obtains the most suitable model in the pre-stored interference models, and generates calibration parameters;

[0085] Specifically, as Figure 4 shown, the interference model matching and calibration parameter generation module includes:

[0086] The database, which includes multiple pre-stored interference models. The interference model includes the green algae species, the interference parameters under the coverage of the corresponding species of green algae, and the corresponding calibration parameter set;

[0087] The target positioning unit acquires the green algae features on photo data a and the green algae features on photo data b, and obtains the corresponding green algae species from the extracted green algae features.

[0088] For the above technology, the interference model matching and calibration parameter generation module is the key part for the system to achieve automatic correction. It uses the pre-collected and created interference model library and can automatically match the most suitable interference model according to the green algae species and coverage. This step not only improves the automation degree of the system but also ensures the accuracy and reliability of data correction. The generated calibration parameters will be used in the subsequent data correction process to eliminate the interference of green algae on the monitoring data. And the database is the data result obtained from the experimental sampling research on this water area for at least four years in advance.

[0089] The data correction module corrects the nitrogen and phosphorus content data based on the X′ = X×(1 + C) algorithm to obtain the corrected nitrogen and phosphorus content data, where: X is the nitrogen and phosphorus content data, and C is the calibration parameter;

[0090] The data comparison and verification module is used to verify the corrected nitrogen and phosphorus content data of the current detection point and judge whether the correction result is supported:

[0091] If it is not supported, the second data acquisition module is re-executed to correct the interference parameter;

[0092] If it is supported, the data is output.

[0093] Detailed: As Figure 5 shown, the data comparison and verification module executes a method for verifying the corrected nitrogen and phosphorus content data of the current detection point, including:

[0094] S10. Obtain the corrected nitrogen and phosphorus content data of the only adjacent detection point adjacent to the relevant current detection point;

[0095] S11. (Corrected nitrogen and phosphorus content data of the current detection point / corrected nitrogen and phosphorus content data of the only adjacent detection point) * 100%. If the result is less than or equal to 20%, it is determined that the result output is correct, and the next step is continued. If the result is greater than 20%, it is determined that the result output is incorrect, and the second data acquisition module is returned to execute again;

[0096] S12. Obtain the historical data of the corrected nitrogen and phosphorus content data of the current detection point. The historical data is not less than the data of at least ten predetermined window periods. Then, calculate the average change factor of the data of multiple predetermined window periods, and then calculate the analog value of the corrected nitrogen and phosphorus content data of the current detection point;

[0097] S13. Subtract the obtained analog value from the corrected nitrogen and phosphorus content data of the current detection point. If the difference does not exceed 5, it is determined that the result holds. If it exceeds, it is determined that the result does not hold, and the second data acquisition module is returned to execute again.

[0098] Furthermore, in the above embodiment, the acquisition of the change factor in step S12 includes:

[0099] S121. Calculate the change rate of the corrected nitrogen and phosphorus content data of two adjacent predetermined windows. The formula is as follows:

[0100] (Nitrogen and phosphorus content in the current period - nitrogen and phosphorus content in the previous period) / nitrogen and phosphorus content in the previous period × 100%;

[0101] S122. Average the change rates of all predetermined window periods to obtain the average change factor;

[0102] S123. Select the corrected nitrogen and phosphorus content data of the most recent predetermined window period as the reference value, then the analog value = reference value × (1 + average change factor).

[0103] The above data comparison and verification module is an important part to ensure the accuracy of the system monitoring results. It uses the data of adjacent detection points and historical data to double-verify the corrected nitrogen and phosphorus content data. If the data difference is too large or exceeds the predetermined range, the module will determine that the correction fails and return to the second data acquisition module to execute again. This step not only improves the accuracy and reliability of the system, but also ensures the authenticity and credibility of the monitoring results. Through the implementation of this module, the system can provide users with more accurate and reliable nitrogen and phosphorus pollution monitoring data.

[0104] In summary, by integrating a high-definition underwater camera (the second data acquisition module), the system can capture the green algae situation of the nitrogen and phosphorus monitor (the first data acquisition module) and the surrounding waters. The image recognition and analysis module can extract the green algae features in the photos and evaluate the interference parameters that the green algae may have on the nitrogen and phosphorus content data. The interference model matching and calibration parameter generation module then selects the most suitable model from the pre-stored interference models based on these interference parameters and generates the corresponding calibration parameters. Furthermore, using the generated calibration parameters, the original nitrogen and phosphorus content data is corrected through a specific algorithm to obtain more accurate nitrogen and phosphorus content data. And by further verifying the corrected data, through the comparison with the data of adjacent monitoring points and the simulation volume comparison of historical data, the accuracy and reliability of the data are ensured. This invention helps the managers of aquaculture waters to understand the water pollution situation in a timely manner, formulate effective management strategies, provides real-time data support, helps managers to discover and handle potential pollution problems in a timely manner, and protects the ecological environment of aquaculture waters.

[0105] Embodiment 2

[0106] An embodiment of the present invention provides a non-transitory computer-readable storage medium, in which at least one instruction or at least one program segment is stored, and at least one instruction or at least one program segment is loaded and executed by a processor to implement the steps of:

[0107] Obtain the nitrogen and phosphorus content data of the current detection point according to a predetermined window period as the first data;

[0108] Capture the photo data a of the first data acquisition module and the photo data b within a predetermined water area range around the first data acquisition module to obtain the second data and the third data respectively;

[0109] Extract the green algae features of several photos within the second data and the third data of the same time unit respectively, and evaluate the interference parameters on the nitrogen and phosphorus content data according to the extraction results;

[0110] Match the obtained interference parameters to obtain the most suitable model in the pre-stored interference models and generate calibration parameters;

[0111] The nitrogen and phosphorus content data is corrected based on the algorithm of X′ = X×(1 + C) to obtain the corrected nitrogen and phosphorus content data, where: X is the nitrogen and phosphorus content data, and C is the calibration parameter;

[0112] Verify the corrected nitrogen and phosphorus content data of the current detection point, and determine whether the correction result is supported:

[0113] If it is not supported, the second data acquisition module is re - executed to correct the interference parameter;

[0114] If it is supported, the data is output.

[0115] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above - mentioned embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non - volatile computer - readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above - mentioned methods. Among them, any reference to the memory, storage, database or other media used in the various embodiments provided by the present invention can include non - volatile and / or volatile memories. Non - volatile memories can include read - only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double - data - rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0116] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above - mentioned division of each functional unit and module is used as an example. In actual applications, the above - mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0117] Embodiment III

[0118] The embodiment of the present invention provides an electronic device, including a processor and a memory. At least one instruction or at least one program segment is stored in the memory, and the at least one instruction or the at least one program segment is loaded and executed by the processor to implement the steps:

[0119] Obtain the nitrogen and phosphorus content data of the current detection point according to a predetermined window period as the first data;

[0120] Capture the photo data a of the first data acquisition module and the photo data b within a predetermined water area around the first data acquisition module to obtain the second data and the third data respectively;

[0121] Extract the green algae characteristics of several photos in the second data and the third data in the same time unit respectively, and evaluate the interference parameter for the nitrogen and phosphorus content data according to the extraction results;

[0122] Match the obtained interference parameter to obtain the most suitable model in the pre-stored interference model and generate a calibration parameter;

[0123] Based on the algorithm of X′ = X×(1 + C), correct the nitrogen and phosphorus content data to obtain the corrected nitrogen and phosphorus content data, where: X is the nitrogen and phosphorus content data, and C is the calibration parameter;

[0124] Verify the corrected nitrogen and phosphorus content data of the current detection point and determine whether the correction result is supported:

[0125] If it is not supported, re-execute the second data acquisition module to correct the interference parameter;

[0126] If it is supported, output the data.

[0127] The above is only a preferred embodiment of the present invention, and does not impose any form of limitation on the present invention. Although the present invention has been disclosed above with a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the equivalent embodiments by using the above-disclosed technical content within the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system, characterized in that: include: A first data acquisition module, which is used to acquire nitrogen and phosphorus content data of a current detection point according to a predetermined window period; A second data acquisition module, which is used to capture the photo data a of the first data acquisition module and the photo data b about the predetermined water area around the first data acquisition module; An image recognition and analysis module extracts the green algae features on the photo data a and the photo data b of the same time unit, respectively, and evaluates the interference parameters on the nitrogen and phosphorus content data according to the extraction results; An interference model matching and calibration parameter generation module performs matching based on the obtained interference parameters to obtain the most suitable model among the pre-stored interference models and generates calibration parameters; A data correction module, which corrects the nitrogen and phosphorus content data based on the algorithm X′=X×(1+C) to obtain corrected nitrogen and phosphorus content data, wherein: X is the nitrogen and phosphorus content data, and C is a calibration parameter; A data comparison and verification module is used to verify the corrected nitrogen and phosphorus content data of the current detection point and determine whether the correction result is supported: If no support is obtained, re-executing the second data acquisition module to correct the interference parameter; If supported, the data is output.

2. A multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 1, characterized in that: The first data acquisition module is a submersible data collection execution component of the nitrogen and phosphorus monitor, and the submersible data collection execution component can be a floating integrated monitor or a detection terminal.

3. A multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 1, characterized in that: The second data acquisition module includes: The first underwater high-definition camera group includes a plurality of underwater high-definition camera groups distributed in a circular array about a diving acquisition execution component, wherein: There are common parts in the photos acquired by two adjacent underwater high-definition camera groups of the diving data acquisition execution component, and the specifications of the common parts are known; A photo integration unit, which is used to overlap the multiple groups of photos obtained by the first underwater high-definition camera group according to the same parts to obtain a holographic photo of the diving collection execution component, wherein the photo data a includes a holographic photo; A second underwater high-definition camera is arranged along the flow direction of the water area of ​​the current detection point, and captures panoramic photos within a predetermined range around the diving collection execution component, and other features in the panoramic photos except the diving collection execution component are recorded in advance, and the other features include stones, dead trees or fishing nets, and the photo data b includes panoramic photos.

4. A multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 1, characterized in that: The image recognition and analysis module includes: an image data acquisition execution unit, which acquires at least ten consecutive frames of photo data a and photo data b before the execution of the first data acquisition module, and acquires at least ten consecutive frames of photo data a and photo data b after the execution of the first data acquisition module; A multi-channel data processing unit, which creates processing channels corresponding to the number of photos based on the cloud; A feature extraction unit, which is used to capture and extract the features of green algae in each frame of the photo; A coverage judgment unit creates a grid on the photo, extracts a coordinate set of green algae features of the photo data a and a coordinate set of green algae features of the photo data b, and obtains a coverage area of ​​green algae features according to the coordinate sets of the corresponding photos; Calculate the average value a of the green algae characteristic coverage area of ​​the photo data a in the multiple frames 平 and an average value b of the characteristic coverage area of ​​green algae for the photo data b in the multiple frames 平 ; Then, based on the obtained average value a 平 and the average value b 平 The coverage ratio of photo data a and the coverage ratio of photo data b are calculated by proportional calculation with the photo grid area.

5. A multi-test aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 4, characterized in that: The image recognition and analysis module calculates interference parameters for nitrogen and phosphorus content data based on the extraction results, including Y=(β*X1+β*X2)+∈; Among them, Y is the coverage ratio of photo data a and the coverage ratio of photo data b, β represents the interference parameter on the coverage ratio of green algae, X1 is the nitrogen content value in the nitrogen and phosphorus content data, and X2 is the phosphorus content value in the nitrogen and phosphorus content data.

6. A multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 1, characterized in that: The interference model matching and calibration parameter generation module includes: A database including a plurality of pre-stored interference models, wherein the interference models include green algae species, interference parameters under green algae coverage under corresponding species, and corresponding calibration parameter sets; The target positioning unit obtains the green algae features on the photo data a and the green algae features on the photo data b, and obtains the corresponding green algae species based on the extracted green algae features.

7. The multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system according to claim 1 is characterized in that: The method in which the data comparison and verification module verifies the corrected nitrogen and phosphorus content data of the current detection point includes: S10, obtaining the corrected nitrogen and phosphorus content data of the only adjacent detection point adjacent to the current detection point; S11, the corrected nitrogen and phosphorus content data of the current detection point / the corrected nitrogen and phosphorus content data of the only adjacent detection point*100%, if the result is less than or equal to 20%, it is determined that the result output is correct, and the next step is continued; if the result is greater than 20%, it is determined that the result output is wrong, and the second data acquisition module is returned to re-execution; S12, obtaining historical data of the corrected nitrogen and phosphorus content data of the current detection point, wherein the historical data is no less than data of at least ten predetermined window periods, and then calculating an average change factor of the data of multiple predetermined window periods, and then calculating an analog value of the corrected nitrogen and phosphorus content data of the current detection point; S13, subtract the obtained analog value from the corrected nitrogen and phosphorus content data of the current detection point. If the difference does not exceed 5, the result is determined to be valid. If it exceeds, the result is determined to be invalid, and the process returns to the second data acquisition module for re-execution.

8. A multi-test aquaculture waters nitrogen and phosphorus pollution monitoring system according to claim 7, characterized in that: The acquisition of the change factor in step S12 includes: S121, obtaining the change rate of the corrected nitrogen and phosphorus content data of two adjacent predetermined windows, the formula is as follows: (nitrogen and phosphorus content in the current cycle - nitrogen and phosphorus content in the previous cycle) / nitrogen and phosphorus content in the previous cycle × 100%; S122, averaging the change rates of all predetermined window periods to obtain an average change factor; S123. Select the corrected nitrogen and phosphorus content data of the most recent predetermined window period as the reference value, then the simulation value = reference value × (1 + average change factor).

9. A non-transitory computer-readable storage medium, wherein at least one instruction or at least one program is stored in the non-transitory computer-readable storage medium, characterized in that: The at least one instruction or the at least one program is loaded and executed by the processor to implement the method of the multi-pilot aquaculture water nitrogen and phosphorus pollution monitoring system as described in any one of claims 1-8.

10. An electronic device, characterized in that: It includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the method of the nitrogen and phosphorus pollution monitoring system for multiple pilot aquaculture waters as described in any one of claims 1 to 8.

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