A fishery water quality monitoring system and method

Abstract

The present invention provides a fishery water quality monitoring system and method. The fishery water quality monitoring system includes: floating collection points distributed at different position points in the fishpond for collecting water quality data of the fishpond and feeding it back to the server; the server for receiving and storing the collected water quality data, correcting the initial coordinate positions of the floating collection points, and obtaining a fishpond water quality status distribution map according to the corrected initial coordinate positions of the floating collection points and the corresponding water quality data. The present invention can obtain a more accurate fishpond water quality status distribution map, provide data reference for fishpond water quality monitoring personnel, more comprehensively understand the fishpond water quality status, so as to monitor and warn the fishpond water quality and perform operations such as directional and / or quantitative oxygenation and injection of new water.

Description

Technical Field

[0001] The present invention relates to the technical field of agriculture, and more particularly, to a fishery water quality monitoring system and method. Background Art

[0002] In the traditional aquaculture mode, due to the inability to monitor water quality in real time, it is difficult to adjust the water quality in a timely manner, which is likely to cause large-area water pollution, resulting in slow growth of aquatic products and the inability to guarantee the safety and quality of the meat, bringing significant economic losses to farmers. Therefore, it is necessary to monitor the fishery water quality.

[0003] The Chinese invention patent with the application number CN201610199787.8 discloses a fishery breeding system, including a water quality multi-parameter detector, an aerator, an aerator controller, a GSM wireless transmission module and a monitoring terminal, which provides a monitoring and control method for aquaculture technicians, greatly saving labor, reducing breeding costs and improving the production efficiency of breeding. Another example is the Chinese invention patent with the application number CN201911169925.8, which discloses a method and system for evaluating the water quality of a fishery habitat. It only collects the density of copepods, and based on the density of copepods, the water quality evaluation result can be quickly obtained without many physical and chemical indexes. Another example is the Chinese invention patent with the application number CN201711010423.1, which discloses a method for analyzing and monitoring fishery water quality. Through machine learning model analysis, it can early warn of possible abnormalities in fish ponds and provide data index guidance for farmers to optimize the water, ensuring the growth of aquatic products in the most suitable environment.

[0004] Therefore, there are still many technical problems to be solved urgently in the practical application of fishery water quality monitoring, and many solutions have not been proposed. Summary of the Invention

[0005] Based on this, in order to better monitor the fishery water quality, the present invention provides a fishery water quality monitoring system and method, and its specific technical solutions are as follows:

[0006] A fishery water quality monitoring system includes floating collection points and a server.

[0007] The floating collection points are distributed at different positions in the fish pond, and are used to collect the water quality data of the fish pond and feedback it to the server.

[0008] The server is used to receive and store the collected water quality data, correct the initial coordinate positions of the floating collection points, and obtain the water quality state distribution map of the fish pond according to the corrected initial coordinate positions of the floating collection points and the corresponding water quality data.

[0009] Through the fishery water quality monitoring system, a more accurate distribution map of the water quality status of the fish pond can be obtained, providing data reference for the fish pond water quality monitoring personnel to more comprehensively understand the water quality status of the fish pond, so as to monitor and warn the water quality of the fish pond and perform operations such as directional and / or quantitative oxygenation and injection of new water.

[0010] Further, the fishery water quality monitoring system further includes a plurality of signal receivers. A signal transmitter is installed on the floating collection point. The signal transmitter is communicatively connected to the signal receiver, and the signal transmitter is used to send the water quality data collected at the floating collection point to the signal receiver;

[0011] The signal receiver is communicatively connected to the server. The floating collection point feeds back the water quality data to the server through the signal transmitter and the signal receiver.

[0012] Further, the server calculates the distance d between the signal receiver and the signal transmitter according to the formula and obtains the reference coordinate position of the floating collection point according to the distance d, and corrects the initial coordinate position according to the reference coordinate position;

[0013] where d0 represents the reference distance of the transmitting node, PL(d0) represents the signal strength at a distance d0 from the transmitting node, n is the signal attenuation exponent, PL(d) represents the signal strength at a distance d from the transmitting node; N0 represents a Gaussian random noise variable with a mean of 0 and a standard deviation of σ.

[0014] Further, the fishery water quality monitoring system further includes an anemometer for obtaining the wind direction and wind speed parameters of the fish pond. The anemometer is signal-connected to the server and feeds back the wind direction parameter and wind speed parameter of the environment where the fish pond is located to the server;

[0015] The server corrects the initial coordinate position according to the received wind direction parameter, wind speed parameter and reference coordinate position, and obtains the distribution map of the fish pond water quality status according to the corrected initial coordinate position of the floating collection point and the corresponding water quality data.

[0016] Further, a fishery water quality monitoring method includes the following steps:

[0017] S1, collecting the water quality data of the fish pond through the floating collection point and feeding it back to the server;

[0018] S2, correcting the initial coordinate position of the floating collection point, and obtaining the distribution map of the fish pond water quality status according to the corrected initial coordinate position of the floating collection point and the corresponding water quality data.

[0019] Further, in step S2, the specific method for correcting the initial coordinate position includes the following steps:

[0020] S20. Install multiple signal receivers around the edges of the fishpond, and install a signal transmitter on the floating collection point. Transmit the water quality data collected at the floating collection point to the signal receivers through the signal transmitter, and transmit the water quality data to the server by the signal receivers;

[0021] S21. The server calculates the distance d between the signal receiver and the signal transmitter according to the formula and obtains the reference coordinate position of the floating collection point according to the distance d, and corrects the initial coordinate position according to the reference coordinate position;

[0022] wherein, d0 represents the reference distance of the sending node, PL(d0) represents the signal strength at a distance d0 from the sending node, n is the signal attenuation exponent, PL(d) represents the signal strength at a distance d from the sending node; N0 represents a Gaussian random noise variable with a mean of 0 and a standard deviation of σ.

[0023] Further, the fishery water quality monitoring method further includes the following steps:

[0024] Obtain the wind direction parameter and wind speed parameter of the fishpond;

[0025] Correct the initial coordinate position according to the received wind direction parameter, wind speed parameter and reference coordinate position.

[0026] Further, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the fishery water quality monitoring method is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but the emphasis is placed on showing the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0028] Figure 1 is the overall flowchart of a fishery water quality monitoring method in an embodiment of the present invention;

[0029] Figure 2 is the overall flowchart of a fishery water quality monitoring method in another embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with its embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0031] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this invention belongs. The terms used herein in the specification of this invention are for the purpose of describing specific implementations only and are not intended to limit this invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0033] In this invention, the so-called "first" and "second" do not represent specific quantities and orders, but are only used for name distinction.

[0034] Due to the inability to monitor water quality in real time, the traditional aquaculture mode is difficult to adjust water quality in a timely manner, which is prone to cause large-area water pollution, resulting in slow growth of aquatic products and the inability to guarantee the safety and quality of the meat, bringing significant economic losses to farmers. Therefore, it is necessary to monitor the water quality of fisheries.

[0035] In the prior art, a variety of methods and / or systems for real-time monitoring of fishery water quality have been proposed. However, the existing fishery water quality monitoring methods / systems only monitor the water quality data at a few sampling points in the fishpond to achieve the monitoring of fishery water quality. They often do not construct a fishpond water quality state distribution map based on the collected water quality data, and it is difficult to provide a comprehensive and overall reference decision-making basis for fishpond managers, and there is room for improvement.

[0036] In order to construct a fishpond water quality state distribution map to facilitate fishpond managers to adjust the fishpond water quality directionally and quantitatively according to the overall state distribution of the fishpond water quality, a fishery water quality monitoring system in an embodiment of this invention includes floating collection points and a server.

[0037] The floating collection points are distributed at different position points in the fishpond and are used to collect the water quality data of the fishpond and feedback it to the server.

[0038] Specifically, at least one collection sensor is installed on the floating collection point, and the collection sensor is used to collect the water quality data of the fishpond.

[0039] The water quality data includes but is not limited to dissolved oxygen content and pH value, etc. Each floating collection point corresponds to an initial coordinate position.

[0040] When placing the buoy collection point at the fishpond location point, the initial coordinate position of the buoy collection point can be set.

[0041] For a fishpond, according to its length, width, and depth, it can be regarded as an XYZ-axis coordinate, with the center point of the coordinate or a certain vertex point as the origin.

[0042] The server is used to receive and store the collected water quality data, correct the initial coordinate position of the floating collection point, and obtain the fishpond water quality status distribution map based on the corrected initial coordinate position of the floating collection point and the corresponding water quality data.

[0043] Since the floating collection point floats in the fishpond water and is affected by factors such as water flow disturbance or wind force, its initial coordinate position will change to a certain extent. The change in the initial coordinate position of the floating collection point will cause the corresponding relationship between the collected water quality data and the initial coordinate position to change. That is to say, there is an error between the initial coordinate position corresponding to the water quality data collected by the floating collection point and the initial coordinate position fed back to the server.

[0044] If the initial coordinate position of the floating collection point is not corrected, the accuracy of the fishpond water quality status distribution map obtained based on the initial coordinate position and water quality data fed back to the server needs to be further improved.

[0045] After the server corrects the initial coordinate position of the floating collection point, and obtains the fishpond water quality status distribution map based on the corrected initial coordinate position of the floating collection point and the corresponding water quality data, a more accurate fishpond water quality status distribution map can be obtained.

[0046] Based on the obtained fishpond water quality status distribution map, it can provide data reference for fishpond water quality monitoring personnel, enabling them to more comprehensively understand the fishpond water quality status, so as to monitor and warn the fishpond water quality and perform operations such as directional and / or quantitative oxygenation and injection of new water.

[0047] In addition, first automatically obtaining water quality data through the floating collection point, and then the server generating the fishpond water quality status distribution map according to the water quality data and the corresponding initial coordinate position can overcome the problems of time-consuming, laborious, and low efficiency in making the water quality status distribution map based on manual multi-point collection of fishpond water quality data, and improve the degree of intelligence.

[0048] In summary, through the fishery water quality monitoring system, a more accurate distribution map of the fishpond water quality state can be obtained, providing data reference for fishpond water quality monitoring personnel, enabling a more comprehensive understanding of the fishpond water quality state, so as to monitor and warn the fishpond water quality and perform operations such as directional and / or quantitative oxygenation and injection of new water. It can also overcome the problems of time-consuming, laborious and low efficiency in making the water quality state distribution map according to manually collected fishpond water quality data at multiple points, and improve the degree of intelligence.

[0049] In one embodiment, the fishery water quality monitoring system further includes a plurality of signal receivers. A signal transmitter is installed on the floating collection point. The signal transmitter is communicatively connected with the signal receivers, and the signal transmitter is used to send the water quality data collected at the floating collection point to the signal receivers.

[0050] The signal receivers are communicatively connected with the server. The floating collection point feeds back the water quality data to the server through the signal transmitter and the signal receivers. The signal receivers can be installed on the four peripheral edges of the fishpond.

[0051] Wherein, the server calculates the distance d between the signal receiver and the signal transmitter according to the formula and obtains the reference coordinate position of the floating collection point according to the distance d, and corrects the initial coordinate position according to the reference coordinate position; wherein, d0 represents the reference distance of the transmitting node, PL(d0) represents the signal strength at a distance d0 from the transmitting node, which can be obtained from the instruction manual of the signal transmitter or the hardware definition table; n is the signal attenuation exponent, usually taking values of 2-4, PL(d) represents the signal strength at a distance d from the transmitting node; N0 represents a Gaussian random noise variable with a mean of 0 and a standard deviation of σ.

[0052] Here, the transmitting node refers to the signal transmitter.

[0053] After the server calculates the distances d between the plurality of signal receivers and the signal transmitter according to the formula it calculates the reference coordinate position of the floating collection point according to the distances d between the plurality of signal receivers and the signal transmitter.

[0054] Specifically, taking the plurality of signal receivers as the centers of circles and taking the distance d between the signal receiver and the signal transmitter as the radius to make a reference sphere. If there is no overlapping and intersecting part between the reference spheres corresponding to the plurality of signal receivers, the distances d between the plurality of signal receivers and the signal transmitter are obtained again according to the formula until there is an overlapping and intersecting part between the spheres corresponding to the plurality of signal receivers. After there is an overlapping and intersecting part between the spheres corresponding to the plurality of signal receivers, the centroid of the overlapping and intersecting part is used as the reference coordinate position of the floating collection point.

[0055] If there is no overlapping or intersecting part between the reference spheres corresponding to multiple signal receivers, it is difficult to calculate the reference coordinate position based on the distances d between the multiple signal receivers and the signal transmitter. Therefore, by obtaining the distances d between the multiple signal receivers and the signal transmitter until there is an overlapping or intersecting part between the spheres corresponding to the multiple signal receivers, it is possible to avoid the problem that it is difficult to calculate the reference coordinate position of the floating acquisition point due to calculation errors or signal sensor accuracy issues caused by the lack of overlapping or intersecting parts between the spheres corresponding to the multiple signal receivers.

[0056] Due to different wind speeds and directions in the fishpond environment, it will also affect the initial coordinate position of the buoy acquisition point. Therefore, it is necessary to take into account the influence of wind speed and direction on the initial coordinate position to further correct the initial coordinate position according to the wind speed and direction, so as to obtain a more accurate coordinate position of the floating acquisition point.

[0057] In order to obtain a more accurate coordinate position of the floating acquisition point and further improve the accuracy of the water quality status distribution map, in one embodiment, the fishery water quality monitoring system further includes a wind speed and direction meter for obtaining the wind direction and wind speed parameters of the fishpond. The wind speed and direction meter is signal-connected to the server and feeds back the wind direction parameters and wind speed parameters of the environment where the fishpond is located to the server.

[0058] The server corrects the initial coordinate position according to the received wind direction parameters, wind speed parameters and reference coordinate position, and obtains the water quality status distribution map of the fishpond according to the initial coordinate position of the corrected floating acquisition point and the corresponding water quality data.

[0059] In this way, by jointly correcting the initial coordinate position with the wind direction parameters, wind speed parameters and reference coordinate position, taking into account the wind direction parameters and wind speed parameters that will affect the initial coordinate position of the buoy acquisition point, the error between the corrected initial coordinate position and the actual coordinate position of the floating acquisition point can be further reduced.

[0060] That is to say, by jointly correcting the initial coordinate position with the wind direction parameters, wind speed parameters and reference coordinate position, the accuracy of the water quality status distribution map of the fishpond can be further improved, and the accuracy of the fishpond water quality regulation can be improved.

[0061] In one embodiment, as Figure 1 shown, the present invention provides a fishery water quality monitoring method, and the fishery water quality monitoring method includes the following steps:

[0062] S1, collecting the water quality data of the fishpond through the floating acquisition point and feeding it back to the server.

[0063] S2. Correct the initial coordinate positions of the floating collection points, and obtain the distribution map of the fishpond water quality status based on the corrected initial coordinate positions of the floating collection points and the corresponding water quality data.

[0064] Specifically, the floating collection points are distributed at different position points in the fishpond, and at least one collection sensor is installed on them. The collection sensor is used to collect the water quality data of the fishpond.

[0065] The water quality data includes but is not limited to dissolved oxygen content and pH value, etc. Each floating collection point corresponds to an initial coordinate position.

[0066] The initial coordinate positions of the buoy collection points can be set when placing the buoy collection points at the position points in the fishpond.

[0067] For the fishpond, according to its length, width, and depth, it can be regarded as an XYZ-axis coordinate, and the center point of the coordinate or a certain vertex point is used as the origin. The initial coordinate positions are set according to the relative positions between the floating collection points and the origin.

[0068] As a preferred technical solution, as Figure 2 shown, in step S2, the specific method for correcting the initial coordinate positions includes the following steps:

[0069] S20. Install multiple signal receivers on the four peripheral edges of the fishpond, and install signal transmitters on the floating collection points. The water quality data collected by the floating collection points is sent to the signal receivers through the signal transmitters, and the signal receivers transmit the water quality data to the server.

[0070] S21. The server calculates the distance d between the signal receiver and the signal transmitter according to the formula and obtains the reference coordinate position of the floating collection point according to the distance d. The initial coordinate position is corrected according to the reference coordinate position; where d0 represents the reference distance of the sending node, PL(d0) represents the signal strength at a distance d0 from the sending node, which can be obtained from the instruction manual of the signal transmitter or the hardware definition table; n is the signal attenuation exponent, usually taking values from 2 to 4, PL(d) represents the signal strength at a distance d from the sending node; N0 represents a Gaussian random noise variable with a mean of 0 and a standard deviation of σ.

[0071] Here, the sending node refers to the signal transmitter. After the server calculates the distances d between multiple signal receivers and the signal transmitter according to the formula it calculates the reference coordinate position of the floating collection point according to the distances d between the signal receivers and the signal transmitter.

[0072] After selecting the origin of the X, Y, and Z axes, the coordinate position of each signal receiver is determined. Based on the coordinate position of the signal receiver and the distance d, the reference coordinate position of the floating collection point is obtained. The specific method for correcting the initial coordinate position includes: if the absolute value between the initial coordinate position and the reference coordinate position is greater than a preset threshold, the reference coordinate position is used as the corrected initial coordinate position; otherwise, the initial coordinate position is not corrected, and a fish pond water quality status distribution map is constructed based on the initial coordinate position and the corresponding water quality data.

[0073] Preferably, each type of water quality data corresponds to a state distribution diagram. The system visualizes the water quality state distribution diagram through a front-end device such as a client.

[0074] If the absolute value between the initial coordinate position and the reference coordinate position exceeds a preset threshold, the floating acquisition point is considered to have deviated significantly from the initial coordinate position. In this case, the reference coordinate position is more consistent with the actual coordinate position of the floating acquisition point. Conversely, the floating acquisition point is considered to have deviated less from the initial coordinate position. By setting a preset threshold and applying the above method to correct the initial coordinate position, a more accurate initial coordinate position can be obtained based on actual conditions.

[0075] Specifically, a reference sphere is made with multiple signal receivers as the center and the distance d between the signal receiver and the signal transmitter as the radius. If there is no overlapping or intersecting part between the spheres corresponding to the multiple signal receivers, then the reference sphere is re-made according to the formula The distances d between the multiple signal receivers and the signal transmitter are obtained until there are overlapping and intersecting parts between the spheres corresponding to the multiple signal receivers.

[0076] When there are overlapping and intersecting parts between the spheres corresponding to multiple signal receivers, when there are two signal receivers, the coordinates of the intersection point of the two reference spheres located in the XYZ axis are used as the reference coordinate position of the floating collection point; when there are three signal receivers, the center of mass of the overlapping and intersecting parts located in the XYZ axis is used as the reference coordinate position of the floating collection point; when there are more than three signal receivers, the center of mass of the overlapping and intersecting parts between the reference spheres corresponding to three or more signal receivers can be obtained first. If the number of center of mass is one, the center of mass is used as the reference coordinate position; if the number of center of mass is two, the midpoint of the line connecting the two center of mass is used as the reference coordinate position; if the number of center of mass is three or more, the center of the smallest sphere that can include all the center of mass is selected as the reference coordinate position.

[0077] When the number of signal receivers is more than three, the center of a smallest sphere that can include the initial coordinate position and all mass centers can be selected as the corrected initial coordinate position.

[0078] Preferably, the number of signal receivers is more than three. By setting multiple signal receivers, the reference coordinate position can be obtained more accurately according to the distances between the multiple signal receivers and the signal transmitter, so as to better correct the initial coordinate position.

[0079] If there is no overlapping intersection between the spheres corresponding to the multiple signal receivers, it is difficult to calculate the reference coordinate position based on the distances d between the multiple signal receivers and the signal transmitter. Therefore, by obtaining the distances d between the multiple signal receivers and the signal transmitter until there is an overlapping intersection between the spheres corresponding to the multiple signal receivers, it is possible to avoid the problem that it is difficult to calculate the reference coordinate position of the floating acquisition point due to calculation errors or signal sensor accuracy problems caused by the lack of overlapping intersection between the spheres corresponding to the multiple signal receivers.

[0080] In one embodiment, when there are multiple centroids, the multiple centroids can also be clustered, and a minimum-radius sphere that can include all the clustered centroids (i.e., a minimum-radius sphere that can include the centroids of the same class) is respectively selected, the spherical center distance value between the spherical center of the minimum-radius sphere and the initial coordinate position is calculated, the centroids of the same class included in the minimum-radius sphere corresponding to the spherical center whose spherical center distance threshold is greater than the preset distance threshold are removed, and finally, the spherical center of the minimum-radius sphere that includes the remaining centroids is obtained as the corrected initial coordinate position.

[0081] In this way, by clustering the multiple centroids and removing the centroids of the same class included in the minimum-radius sphere corresponding to the spherical center whose spherical center distance value is greater than the preset distance threshold, the centroids with large calculation errors can be removed. Then, taking the spherical center of the minimum-radius sphere corresponding to the remaining centroids as the corrected initial coordinate position, a more accurate initial coordinate position can be obtained.

[0082] In one embodiment, the fishery water quality monitoring method further includes the following steps:

[0083] Obtain the wind direction parameter and wind speed parameter of the fish pond;

[0084] Correct the initial coordinate position according to the received wind direction parameter, wind speed parameter, and reference coordinate position.

[0085] Specifically, the specific method for correcting the initial coordinate position according to the received wind direction parameter, wind speed parameter, and reference coordinate position includes the following steps:

[0086] Construct a neural network model;

[0087] Obtain the coordinate offset vectors of the floating acquisition points under different wind direction parameters and corresponding wind speed parameters;

[0088] A training data set is formed among different wind direction parameters, corresponding wind speed parameters, and coordinate offset vectors, and the neural network model is trained with the training data set;

[0089] Obtain the real-time wind direction and real-time wind speed of the floating acquisition point, input the real-time wind direction and real-time wind speed into the trained neural network model, and obtain the real-time coordinate offset vector;

[0090] Obtain the reference coordinate vector between the reference coordinate position and the initial coordinate position;

[0091] Calculate the included angle between the real-time coordinate offset vector and the reference coordinate vector. If the included angle is less than the preset angle threshold, correct the initial coordinate position according to the real-time coordinate offset vector or the reference coordinate position, otherwise correct the initial coordinate vector according to the real-time coordinate offset vector.

[0092] That is to say, when the included angle between the real-time coordinate offset vector and the reference coordinate vector is too large, the initial coordinate position is corrected based on the real-time coordinate offset vector. Otherwise, the initial coordinate position is corrected according to the real-time coordinate offset vector or the reference coordinate position.

[0093] The method of correcting the initial coordinate vector with the real-time coordinate offset vector is: obtain the real-time coordinate offset value according to the real-time coordinate offset vector, and correct the initial coordinate position according to the real-time coordinate offset value.

[0094] The method of correcting the initial coordinate position with the reference coordinate position is: use the reference coordinate position as the corrected initial coordinate position.

[0095] By jointly correcting the initial coordinate position with the wind direction parameter, wind speed parameter, and reference coordinate position, taking into account the wind direction parameter and wind speed parameter that will affect the initial coordinate position of the buoy acquisition point, the error between the corrected initial coordinate position and the actual coordinate position of the floating acquisition point can be further reduced.

[0096] In one embodiment, when there are multiple centroids, multiple centroids can also be clustered, and a minimum radius sphere that can include all the clustered centroids (i.e., a minimum radius sphere that can include the centroids of the same class) is respectively selected. Calculate the distance value between the center of the minimum radius sphere and the initial coordinate position, and eliminate the centroids of the same class included in the minimum radius sphere corresponding to the center of the sphere whose center distance threshold is greater than the preset distance threshold. Finally, obtain the center of the minimum radius sphere that includes the remaining centroids as the corrected initial coordinate position.

[0097] Preferably, the center of the smallest radius sphere that includes the remaining centroids and the end coordinates of the real-time coordinate offset vector is obtained as the corrected initial coordinate position.

[0098] In this way, by clustering multiple centroids and removing the centroids of the same category included in the smallest radius sphere corresponding to the center of the sphere whose center distance value is greater than the preset distance threshold, the centroids with large calculation errors can be removed. Then, taking the center of the smallest radius sphere that includes the remaining centroids and the end coordinates of the real-time coordinate offset vector as the corrected initial coordinate position, combining the clustering and screening process of the centroids and the wind direction and wind speed parameters, a more accurate initial coordinate position can be obtained.

[0099] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0100] The above-described embodiments only represent several implementation manners of the present invention, and the description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent should be subject to the appended claims.

Claims

1. A fishery water quality monitoring system, characterized in that, The fishery water quality monitoring system includes: Floating collection points, which are distributed at different positions in the fishpond and are used to collect the water quality data of the fishpond and feedback it to the server; A server, which is used to receive and store the collected water quality data, correct the initial coordinate positions of the floating collection points, and obtain the water quality state distribution map of the fishpond according to the corrected initial coordinate positions of the floating collection points and the corresponding water quality data; The fishery water quality monitoring system further includes a plurality of signal receivers. A signal transmitter is installed on the floating collection point. The signal transmitter is communicatively connected to the signal receiver, and the signal transmitter is used to send the water quality data collected by the floating collection point to the signal receiver; The signal receiver is communicatively connected to the server, and the floating collection point feeds back the water quality data to the server through the signal transmitter and the signal receiver; The server calculates according to the formula the distance between the signal receiver and the signal transmitter , and obtains the reference coordinate position of the floating acquisition point according to the distance to correct the initial coordinate position according to the reference coordinate position; Among them, represents the reference distance of the sending node, represents the signal strength at a distance from the sending node, is the signal attenuation exponent, represents the signal strength at a distance from the sending node; represents a Gaussian random noise variable with a mean of 0 and a standard deviation of ; Centered on multiple signal receivers and with the distance between the signal receiver and the signal transmitter as the radius, a reference sphere is drawn. If there is no overlapping or intersecting part between the spheres corresponding to the multiple signal receivers, then the distance between the multiple signal receivers and the signal transmitter is re-obtained according to the formula until there is an overlapping or intersecting part between the spheres corresponding to the multiple signal receivers; ​ After there is an overlapping intersection part between the spheres corresponding to the multiple signal receivers, when there are two signal receivers, the intersection point coordinates of the two reference spheres in the XYZ axis are used as the reference coordinate position of the floating collection point; when there are three signal receivers, the centroid of the overlapping intersection part in the XYZ axis is used as the reference coordinate position of the floating collection point; when the number of signal receivers is greater than three, first obtain the centroid of the overlapping intersection part between the reference spheres corresponding to three or more signal receivers. If the number of centroids is one, use the centroid as the reference coordinate position. If the number of centroids is two, use the midpoint of the line connecting the two centroids as the reference coordinate position. If the number of centroids is three or more, select the center of the smallest sphere that includes all the centroids as the reference coordinate position; When there are multiple centroids, cluster the multiple centroids, and respectively select a smallest radius sphere that includes all the centroids after clustering, that is, respectively select a smallest radius sphere that includes the centroids of the same category, calculate the center distance value between the center of the smallest radius sphere and the initial coordinate position, eliminate the centroids of the same category included in the smallest radius sphere corresponding to the center whose center distance threshold is greater than the preset distance threshold, and finally obtain the center of the smallest radius sphere that includes the remaining centroids as the corrected initial coordinate position; The fishery water quality monitoring system further includes a wind direction and speed meter for obtaining the wind direction and wind speed parameters of the fishpond. The wind direction and speed meter is signal-connected to the server and feeds back the wind direction parameter and the wind speed parameter of the environment where the fishpond is located to the server; The server corrects the initial coordinate position according to the received wind direction parameter, wind speed parameter and reference coordinate position, and specifically includes the following steps: Construct a neural network model; Obtain the coordinate offset vectors of the floating collection points under different wind direction parameters and corresponding wind speed parameters; A training data set is formed among different wind direction parameters, corresponding wind speed parameters and coordinate offset vectors, and the neural network model is trained with the training data set; Obtain the real-time wind direction and real-time wind speed of the floating collection point, input the real-time wind direction and real-time wind speed into the trained neural network model, and obtain the real-time coordinate offset vector; Obtain the reference coordinate vector between the reference coordinate position and the initial coordinate position; Calculate the angle between the real-time coordinate offset vector and the reference coordinate vector. If the angle is less than the preset angle threshold, correct the initial coordinate position according to the real-time coordinate offset vector or the reference coordinate position; otherwise, correct the initial coordinate vector according to the real-time coordinate offset vector.

2. A method for monitoring fishery water quality, characterized in that, The fishery water quality monitoring method includes the following steps: S1. Collect the water quality data of the fish pond through the floating collection points and feedback it to the server; S2. Correct the initial coordinate position of the floating collection points, and obtain the water quality state distribution map of the fish pond according to the corrected initial coordinate position of the floating collection points and the corresponding water quality data; In step S2, the specific method for correcting the initial coordinate position includes the following steps: S20. Install multiple signal receivers on the four edges of the fish pond, and install a signal transmitter on the floating collection point. Transmit the water quality data collected by the floating collection point to the signal receivers through the signal transmitter, and the signal receivers transmit the water quality data to the server; S21, the server calculates the distance between the signal receiver and the signal transmitter according to the formula and obtains the reference coordinate position of the floating acquisition point according to the distance, and corrects the initial coordinate position according to the reference coordinate position; According to the distance ​ Among them, represents the reference distance of the sending node, represents the signal strength at a distance from the sending node ; is the signal attenuation exponent, represents the signal strength at a distance from the sending node ; represents a Gaussian random noise variable with a mean of 0 and a standard deviation of ; Taking multiple signal receivers as the centers, and using the distance between the signal receiver and the signal transmitter as the radius to make a reference sphere. If there is no overlapping intersection between the spheres corresponding to the multiple signal receivers, then re-obtain the distances between the multiple signal receivers and the signal transmitter according to the formula until there is an overlapping intersection between the spheres corresponding to the multiple signal receivers; ​ After there is an overlapping intersection part between the spheres corresponding to the multiple signal receivers, when there are two signal receivers, use the intersection point coordinates of the two reference spheres in the XYZ axis as the reference coordinate position of the floating collection point; when there are three signal receivers, use the centroid of the overlapping intersection part in the XYZ axis as the reference coordinate position of the floating collection point; when the number of signal receivers is greater than three, first obtain the centroid of the overlapping intersection part between the reference spheres corresponding to three or more signal receivers. If the number of centroids is one, use the centroid as the reference coordinate position. If the number of centroids is two, use the midpoint of the line connecting the two centroids as the reference coordinate position. If the number of centroids is three or more, select the center of a smallest sphere that includes all the centroids as the reference coordinate position; When there are multiple centroids, cluster the multiple centroids, and respectively select a smallest radius sphere that includes all the clustered centroids, that is, respectively select a smallest radius sphere that includes the centroids of the same category. Calculate the center distance value between the center of the smallest radius sphere and the initial coordinate position, and eliminate the centroids of the same category included in the smallest radius sphere corresponding to the center whose center distance threshold is greater than the preset distance threshold. Finally, obtain the center of a smallest radius sphere that includes the remaining centroids as the corrected initial coordinate position; It also includes the following steps: Obtain the wind direction parameter and wind speed parameter of the fish pond; Correct the initial coordinate position according to the received wind direction parameter, wind speed parameter and reference coordinate position, which specifically includes the following steps: Construct a neural network model; Obtain the coordinate offset vector of the floating collection point under different wind direction parameters and corresponding wind speed parameters; Form a training data set among different wind direction parameters, corresponding wind speed parameters and coordinate offset vectors, and train the neural network model with the training data set; Obtain the real-time wind direction and real-time wind speed of the floating collection point, input the real-time wind direction and real-time wind speed into the trained neural network model, and obtain the real-time coordinate offset vector; Obtain the reference coordinate vector between the reference coordinate position and the initial coordinate position; Calculate the angle between the real-time coordinate offset vector and the reference coordinate vector. If the angle is less than the preset angle threshold, correct the initial coordinate position according to the real-time coordinate offset vector or the reference coordinate position, otherwise correct the initial coordinate vector according to the real-time coordinate offset vector.

3. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which implements the fishery water quality monitoring method as described in claim 2 when executed by a processor.

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