Marine ranch three-dimensional monitoring method, system and device

Abstract

The invention discloses a marine ranch three-dimensional monitoring method, system and device, and the system comprises a plurality of water sensors, an underwater camera and a data collection unit, and the data collection unit is used for receiving detection data and underwater image information of each marine ranch and transmitting the detection data and the underwater image information to the outside. According to the invention, the plurality of water body sensors are arranged, so that marine ranch detection data can be acquired from a plurality of different positions of a marine ranch, underwater image information is shot by using the underwater camera, and the marine ranch detection data and the underwater image information are collected and sent to the outside by using the data collection unit; therefore, data support can be provided for monitoring and analysis of the marine ranching; the water body sensor and the underwater camera can be distributed in the marine ranch, so that data can be collected in a large range for real-time analysis, the water body sensor and the underwater camera can be arranged at fixed points, patrol observation and other operations are not needed, and the cost is saved. The method is widely applied to the technical field of ocean information.

Description

Technical Field

[0001] The present invention relates to the field of marine information technology, and in particular to a method, system and device for three-dimensional monitoring of marine ranches. Background Art

[0002] "Marine ranching" refers to the use of large-scale fishery facilities and a systematic management system in a certain sea area, utilizing the natural marine ecological environment to gather artificially released economic marine organisms, and carry out planned and purposeful stocking of marine resources such as fish, shrimp, shellfish, and algae at sea, just like grazing cattle and sheep on land.

[0003] In marine ranches, water quality, meteorology, hydrology and other conditions directly affect the distribution and growth of aquatic organisms and are key factors in determining the output and quality of marine ranch aquatic products. Monitoring marine ranches can timely understand and grasp the entire process of marine ranch environment and resource quality and development trends. The various indicators and data obtained through monitoring provide a scientific basis for the management of marine ranches. However, due to the large spatial range of marine ranches, existing technologies for monitoring marine ranches have disadvantages such as small coverage, high cost and poor real-time performance. Summary of the invention

[0004] In view of the technical problems of current marine ranch monitoring technology such as small coverage, high cost, and poor real-time performance, the purpose of the present invention is to provide a three-dimensional monitoring method, system and device for marine ranches.

[0005] On the one hand, an embodiment of the present invention includes a three-dimensional monitoring system for marine ranches, and the three-dimensional monitoring system for marine ranches includes:

[0006] A plurality of water body sensors; the water body sensors are used to be distributed and arranged at corresponding positions of the marine ranch to detect and obtain marine ranch detection data;

[0007] Underwater camera; the underwater camera is used to be set underwater in the ocean ranch to capture underwater image information;

[0008] Data collection unit; the data collection unit is used to establish a connection with each of the water body sensors and the underwater camera, receive each of the marine ranch detection data and the underwater image information, and send each of the marine ranch detection data and the underwater image information to the outside.

[0009] Furthermore, the marine ranch stereoscopic monitoring system also includes:

[0010] Data processing unit; the data processing unit is used to receive the marine ranch detection data and the underwater image information, analyze and process the marine ranch detection data and the underwater image information, and obtain marine monitoring indicators.

[0011] Furthermore, the analysis and processing of each of the marine ranch detection data and the underwater image information to obtain marine monitoring indicators includes:

[0012] fusing the marine ranch detection data to obtain fused data;

[0013] Identifying the underwater image information to obtain time series data of the number of fish schools;

[0014] Perform principal component analysis on the fused data and the fish population time series data to obtain at least one of the ocean monitoring indicators.

[0015] Furthermore, the analyzing and processing of the marine ranch detection data and the underwater image information to obtain the marine monitoring index also includes:

[0016] A comprehensive environmental index is determined based on each of the marine monitoring indicators and their corresponding first weights.

[0017] Furthermore, the said fusing the said marine ranch detection data to obtain the fused data includes:

[0018] Determine a second weight corresponding to each of the water body sensors;

[0019] For any of the marine ranch detection data, the second weight corresponding to the water body sensor that detects the marine ranch detection data is used as the weight corresponding to the marine ranch detection data, and weighted averaging is performed on each of the marine ranch detection data to obtain the fused data.

[0020] Further, the determining of the second weight corresponding to each of the water body sensors includes:

[0021] Obtaining the spatial distance between each of the water body sensors and the underwater camera;

[0022] For any of the water body sensors, the size of the second weight corresponding to the water body sensor is set according to the spatial distance corresponding to the water body sensor; wherein the size of the second weight is negatively correlated with the spatial distance.

[0023] Further, the determining of the second weight corresponding to each of the water body sensors includes:

[0024] Determining the movement directions of multiple schools of fish according to the time series data of the number of the school of fish;

[0025] Performing divergence analysis on the fish school vector field to obtain divergence data of multiple positions within the field of view of the underwater camera; wherein the fish school vector field is a vector field formed by the movement directions of each of the fish schools;

[0026] The second weight corresponding to each of the water body sensors is determined according to each of the divergence data.

[0027] Further, determining the second weight corresponding to each of the water body sensors according to each of the divergence data includes:

[0028] Determine the convergence center and the divergence center within the field of view of the underwater camera according to each of the divergence data;

[0029] For any of the water body sensors, when the distance between the water body sensor and the convergence center is less than the distance between the water body sensor and the divergence center and less than a distance threshold, the second weight corresponding to the water body sensor is determined to be a first value; when the distance between the water body sensor and the divergence center is less than the distance between the water body sensor and the convergence center and less than a distance threshold, the second weight corresponding to the water body sensor is determined to be a third value; otherwise, the second weight corresponding to the water body sensor is determined to be a second value;

[0030] The first value is greater than the second value, and the second value is greater than the third value.

[0031] On the other hand, an embodiment of the present invention further includes a method for three-dimensional monitoring of a marine ranch, the method comprising:

[0032] The marine ranch detection data is obtained by respectively detecting through a plurality of water body sensors; each of the water body sensors is used to be distributed and arranged at a corresponding position of the marine ranch;

[0033] Underwater image information is obtained by shooting with an underwater camera; the underwater camera is used to be set underwater in the ocean ranch;

[0034] The marine ranch detection data and the underwater image information are received by a data collection unit, and the marine ranch detection data and the underwater image information are sent to the outside; the data collection unit is used to establish a connection with each of the water body sensors and the underwater camera;

[0035] The marine ranch detection data and the underwater image information are analyzed and processed to obtain marine monitoring indicators.

[0036] On the other hand, an embodiment of the present invention also includes a computer device, including a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the marine ranch stereoscopic monitoring method in the embodiment.

[0037] The beneficial effects of the present invention are as follows: the ocean ranch three-dimensional monitoring system in the embodiment can collect ocean ranch detection data from multiple different locations of the ocean ranch by setting up multiple water body sensors, and use underwater cameras to capture underwater image information, and use a data collection unit to collect and externally send the ocean ranch detection data and underwater image information, thereby providing data support for the monitoring and analysis of the ocean ranch; since the water body sensors and underwater cameras can be distributed in the ocean ranch, data can be collected over a large area for real-time analysis, and the water body sensors and underwater cameras can be set at fixed points, without the need for patrol observation and other operations, thereby saving costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the structure of the three-dimensional monitoring system of the marine ranch in the embodiment;

[0039] Figure 2 Schematic diagram of the arrangement of the three-dimensional monitoring system of the marine ranch in the embodiment;

[0040] Figure 3 This is a schematic diagram of the principle of the step of determining the second weight corresponding to each water body sensor in the embodiment;

[0041] Figure 4 Schematic diagram of the steps of the three-dimensional monitoring method of the marine ranch in the embodiment. DETAILED DESCRIPTION

[0042] In this embodiment, the structure of the marine ranch three-dimensional monitoring system is as follows: Figure 1 As shown, it includes a land base station, a power module, a data collection unit, an underwater camera and multiple water sensors.

[0043] Reference Figure 2 , each water body sensor is distributed and arranged at a corresponding position of the marine ranch, such as the water surface, in the water, under the water, etc., and the water body sensor detects and obtains the marine ranch detection data. Specifically, in this embodiment, different types of water body sensors such as type A, type B and type C are provided, wherein the water body sensor belonging to type A is used to detect water quality detection data such as salinity, turbidity, chlorophyll concentration, etc., the water body sensor belonging to type B is used to detect hydrological detection data such as water temperature, pH value, dissolved oxygen, etc., and the water body sensor belonging to type C is used to detect meteorological detection data such as air temperature, air pressure, wind speed, etc. Therefore, in this embodiment, the marine ranch detection data includes water quality detection data, hydrological detection data and meteorological detection data, etc.

[0044] In this embodiment, there are multiple water body sensors of various types.

[0045] The underwater camera is used to be set in the water or underwater of the marine ranch to capture underwater image information. The underwater image information can be a single or multiple static images, or a dynamic video.

[0046] The power module can power devices such as data collection units, underwater cameras and water sensors.

[0047] In this embodiment, the data collection unit includes a single chip microcomputer and a data transmission end. Each water body sensor sends the detected marine ranch detection data (specifically, it may be water quality detection data, hydrological detection data or meteorological detection data) to the single chip microcomputer, and the underwater camera also sends the captured underwater image information to the single chip microcomputer.

[0048] In this embodiment, each water body sensor can perform preliminary processing on the collected marine ranch detection data. For example, the water body sensor belonging to type A performs preliminary filtering and linearization processing on the collected water quality detection data to reduce noise and nonlinear errors; the water body sensor belonging to type B uses the Kalman filter algorithm (Kalman Filter) to smooth the collected hydrological detection data, thereby improving the stability and accuracy of the data; the water body sensor belonging to type C compresses the collected meteorological detection data to reduce communication delay. Each water body sensor sends out the marine ranch detection data that has been preliminarily processed.

[0049] The single chip microcomputer pre-processes the received marine ranch detection data, for example, converts the marine ranch detection data into binary, compresses the underwater image information, etc., and then sends the pre-processed data to the data sending end.

[0050] Specifically, the microcontroller transmits the processed marine ranch detection data and underwater image information compressed by H.264 encoding to the data transmitter through the UART (Universal Asynchronous Receiver / Transmitter) interface. The data transmitter uses the CRC (Cyclic Redundancy Check) algorithm to generate a checksum to ensure data integrity during transmission. Subsequently, the data is encapsulated in a UDP (User Datagram Protocol) data packet and prepared for modulation processing.

[0051] In this embodiment, the data transmitter uses the underwater acoustic communication protocol to send data. Specifically, the data transmitter uses MFSK (Multi-Frequency Shift Keying) as the modulation method to convert digital data into acoustic signals, effectively reducing the impact of multipath effects and frequency selective fading; before performing signal modulation, the data transmitter encodes the data through LDPC (Low-Density Parity Check), which significantly improves the bit error rate performance in underwater acoustic communication, so that the system can still work stably in an underwater environment with interference.

[0052] In this embodiment, the data transmitting end converts the modulated electrical signal into an acoustic signal through a piezoelectric transducer and transmits the acoustic signal to the outside. In this way, the detection data of each marine ranch and the underwater image information are transmitted in the form of an acoustic signal.

[0053] Since the preprocessing, modulation, encoding and transduction processes do not change the content of the information such as the marine ranch detection data and underwater image information, in this embodiment, the marine ranch detection data and underwater image information are still called marine ranch detection data and underwater image information after the preprocessing, modulation, encoding and transduction processes.

[0054] In this embodiment, since the acoustic signal propagates at a specific frequency in water, the data transmitter can adjust the transmission power and frequency to ensure that the signal can penetrate the seawater during long-distance underwater transmission and maintain a high signal strength in a multipath propagation environment. In order to cope with the multipath propagation effect and delay spread in the underwater channel, the data transmitter can use an adaptive equalization algorithm to perform real-time channel equalization to optimize the quality of the received signal.

[0055] In this embodiment, the ocean ranch three-dimensional monitoring system can collect ocean ranch detection data from multiple different locations of the ocean ranch by setting up multiple water body sensors, and use underwater cameras to capture underwater image information, and use a data collection unit to collect and externally send the ocean ranch detection data and underwater image information, thereby providing data support for the monitoring and analysis of the ocean ranch; since water body sensors and underwater cameras can be distributed in the ocean ranch, data can be collected over a large area for real-time analysis, and water body sensors and underwater cameras can be set at fixed points, without the need for patrol observation and other operations, thereby saving costs.

[0056] In this embodiment, refer to Figure 2 , the land base station performs the steps of receiving and demodulating, data storage and processing, which specifically include:

[0057] Reception and demodulation:

[0058] 1) Signal reception: The land-based base station receives the acoustic signals transmitted underwater through the hydrophone array. Beamforming technology is used to improve the signal reception capability in a specific direction and suppress background noise.

[0059] 2) Signal demodulation: After the received signal is amplified and filtered, it is converted back into digital data by the MFSK demodulator. The demodulator performs soft decision decoding using the Viterbi Algorithm to further correct possible transmission errors.

[0060] 3) Error detection and correction: The demodulated data is again subjected to CRC verification and combined with LDPC decoding for error detection and correction to ensure high data reliability.

[0061] Data storage and processing:

[0062] 1) Data storage: The successfully received data is stored in the SQL database of the land base station with timestamp and location information to facilitate subsequent data analysis and retrieval.

[0063] 2) Real-time processing and feedback: The system can analyze the received environmental parameters in real time and trigger alarms or execute predetermined control strategies according to preset thresholds, such as adjusting the water quality or environment of the aquaculture area.

[0064] By setting up a land base station, the marine ranch detection data and underwater image information collected by the marine ranch stereo monitoring system set up in the water body can be received for further analysis.

[0065] In this embodiment, the marine ranch three-dimensional monitoring system also includes a data processing unit. Figure 1 and Figure 2 The data processing unit can be set at a location such as a land base station. After receiving the detection data and underwater image information of each marine ranch sent by the data collection unit, the data processing unit analyzes and processes the detection data and underwater image information of each marine ranch to obtain marine monitoring indicators. Marine monitoring indicators can be used to assist the operator of the marine ranch in analysis and decision-making.

[0066] In this embodiment, when the data processing unit performs the step of analyzing and processing the detection data of each marine ranch and the underwater image information to obtain the marine monitoring index, the following steps may be specifically performed:

[0067] S401. Fusing the detection data of each marine ranch to obtain fused data;

[0068] S402. Identify underwater image information to obtain time series data of fish population;

[0069] S403. Perform principal component analysis on the fused data and the fish population time series data to obtain at least one marine monitoring indicator;

[0070] S404. Determine a comprehensive environmental index based on each ocean monitoring indicator and their corresponding first weights.

[0071] Before executing step S401, each marine ranch detection data can be standardized, for example, each marine ranch detection data is normalized to eliminate the influence of different dimensions of marine ranch detection data detected by different types of water body sensors, so that the marine ranch detection data detected by different types of water body sensors can be compared and analyzed under the same framework.

[0072] When executing step S401, that is, fusing the detection data of each marine ranch to obtain fused data, the following steps may be specifically performed:

[0073] S40101. Determine the second weight corresponding to each water body sensor;

[0074] S40102. For any marine ranch detection data, the second weight corresponding to the water sensor that detected the marine ranch detection data is used as the weight corresponding to the marine ranch detection data, and weighted average is performed on each marine ranch detection data to obtain fused data.

[0075] In step S40101, the reliability can be determined based on the historical working parameters and real-time working parameters of each water body sensor, and a corresponding second weight can be assigned based on the reliability, wherein the value of the second weight assigned to each water body sensor is positively correlated with the reliability of the water body sensor.

[0076] In step S40102, assuming that there are M water body sensors in total, the value of the second weight corresponding to the mth water body sensor is w′ m , the value of the marine ranch detection data detected by the mth water body sensor after standardized processing is value m , then the weighted average of the marine ranch detection data detected by all M water sensors is

[0077]

[0078] The weighted average value VALUE can be used as the fusion data obtained by executing step S401.

[0079] In this embodiment, when executing step S401, that is, fusing the detection data of each marine ranch to obtain fused data, the Bayesian Estimation method can also be used to perform data fusion. Specifically, the Bayesian Estimation introduces prior information and observation data to update the fusion result and improve the accuracy of data fusion.

[0080] In step S402, the data processing unit identifies the underwater image information to obtain time series data of the number of fish schools.

[0081] Specifically, the data processing unit can first adjust the frame rate and eliminate noise on the received underwater image information. For example, Gaussian Blur and Median Filtering are used to reduce noise in the underwater image information, and Histogram Equalization is used to enhance the contrast of the underwater image information. Then, the data processing unit uses the Yolov8 algorithm to detect and count fish on the pre-processed underwater image information.

[0082] YOLO (You Only Look Once) is an efficient target detection algorithm based on convolutional artificial neural network (CNN). It converts the target detection task into a regression problem and predicts the location and category of the target at one time through a single neural network, thereby achieving fast target detection. Compared with other target detection algorithms, such as those based on sliding windows or region proposals, YOLO is faster. Yolov8 is a SOTA model that builds on the historical versions of the Yolo series and introduces new features and improvements to further improve performance and flexibility, making it a good choice for tasks such as target detection and image segmentation.

[0083] Taking underwater image information in the form of video as an example, the data processing unit uses the Yolov8 algorithm to identify each frame in the underwater image information, marks and counts the target fish in each frame, and the system calculates the number of fish per unit time based on the counting results, thereby obtaining the fish number data of this frame. Since the underwater image information contains multiple frames, each frame has corresponding fish number data, so the multiple fish number data can form a time series, thereby forming the fish number time series data series = {number1, number2...}, where number1 represents the number of fish in the first frame of the underwater image information (it can also include information such as the location of certain specific fish), and so on.

[0084] For the time series data of fish population obtained by Yolov8 algorithm, the exponential smoothing algorithm can be used to predict the time series data of fish population to provide trend analysis of the dynamic changes of fish population.

[0085] In this embodiment, the "fish school" may refer to a group of fish biologically classified as saury, tuna, etc., and may also include a group of squid, etc., which are not biologically fish but are fished like fish.

[0086] In step S403, principal component analysis (PCA) is performed on the fused data VALUE and the fish population time series data series to obtain at least one ocean monitoring indicator.

[0087] Specifically, before performing PCA, all input fused data VALUE and fish population time series data series can be standardized to ensure that data of different units or orders of magnitude can be compared on the same scale. Then calculate the covariance matrix of the fused data VALUE and the fish population time series data serises, perform eigenvalue decomposition on the covariance matrix, and obtain the eigenvalue and corresponding eigenvector of each component. The larger the eigenvalue of a component, the greater the variance contribution of the eigenvector corresponding to this component in the original data, that is, it can better represent the main change trend of the data. The system sorts according to the size of the eigenvalue, selects the largest k eigenvectors (i.e., principal components) as the basis vectors of the new data space, and constructs the main indicators.

[0088] In step S403, the obtained eigenvector is used as the ocean monitoring index, and the corresponding first weight is calculated according to the eigenvalue corresponding to the eigenvector. By executing step S403, PC1, PC2, ..., PC k The k principal components are the ocean monitoring indicators, as well as the eigenvalue λ1 corresponding to the ocean monitoring indicator PC1, the eigenvalue λ2 corresponding to the ocean monitoring indicator PC2, etc. k The corresponding eigenvalue λ k .

[0089] In step S403, the formula

[0090]

[0091] Calculate the ocean monitoring index PC i The corresponding first weight w i Traverse i=1, 2, ..., k, and thus obtain the first weight w1 corresponding to the ocean monitoring index PC1, the first weight w2 corresponding to the ocean monitoring index PC2, ..., the ocean monitoring index PC k The corresponding first weight w k Each marine monitoring indicator represents the environmental status of a certain aspect of the marine ranch. The first weight w k Reflects the ocean monitoring indicator PC k Contribution to the total variance.

[0092] In step S404, the data processing unit can process the data according to PC1, PC2, ... k etc. ocean monitoring indicators and their corresponding w1, w2…wk The first weight is equal to the first weight, and the comprehensive environment index CEI is calculated. In this embodiment, the calculation formula of the comprehensive environment index CEI is:

[0093]

[0094] In this embodiment, the calculation formula of the comprehensive environmental index CEI takes into account the weighted impact of water quality, hydrology, meteorological conditions and fish population, and can quantify the environmental conditions that comprehensively consider water quality, hydrology, meteorological conditions and fish population, providing a scientific basis for the management and decision-making of marine ranches.

[0095] In this embodiment, when executing step S40101, that is, determining the second weight corresponding to each water body sensor, the following steps may be specifically performed:

[0096] S4010101A. Obtain the spatial distance between each water sensor and the underwater camera;

[0097] S4010102A. For any water body sensor, set the size of the second weight corresponding to the water body sensor according to the spatial distance corresponding to the water body sensor; wherein the size of the second weight is negatively correlated with the spatial distance.

[0098] Steps S4010101A-S4010102A are the first execution method of step S40101.

[0099] In step S4010101A, the spatial distance between the water body sensor and the underwater camera specifically refers to the distance between the spatial position of the water body sensor in the water body and the spatial position of the underwater camera in the water body, which can be calculated by recording the coordinates of the water body sensor and the underwater camera when the water body sensor and the underwater camera are arranged. In actual use, it can be considered that the spatial distance between each water body sensor and the underwater camera is constant.

[0100] In step S4010102A, the value of the second weight corresponding to each water body sensor can be set to be negatively correlated with the spatial distance corresponding to the water body sensor. For example, for the mth water body sensor, assuming that the spatial distance between it and the underwater camera is distance m , then we can use the formula

[0101]

[0102] Calculate the value w′ of the second weight corresponding to the mth water body sensor m , where DISTANCE is a fixed value.

[0103] In this embodiment, the principle of executing steps S4010101A-S4010102A is that the time series data of the number of fish schools is obtained by analyzing the underwater image information. Since the underwater image information is obtained by taking pictures with an underwater camera, this indicates that the fish schools are active near the underwater camera. By executing steps S4010101A-S4010102A, a water body sensor that is closer to the underwater camera can be set with a larger second weight. Therefore, the marine ranch detection data detected at a position closer to the fish school will be given a larger second weight, so that when monitoring the marine ranch, it is possible to focus on using the data collected near the fish school, thereby increasing the monitoring attention to the fish school, which is conducive to realizing the economy of the marine ranch.

[0104] In this embodiment, when executing step S40101, that is, determining the second weight corresponding to each water body sensor, the following steps may be specifically performed:

[0105] S4010101B. Determine the movement directions of multiple schools of fish based on the time series data of the number of schools of fish;

[0106] S4010102B. Perform divergence analysis on the fish school vector field to obtain divergence data at multiple positions within the field of view of the underwater camera;

[0107] S4010103B. Determine the second weight corresponding to each water body sensor according to each divergence data.

[0108] Steps S4010101B-S4010103B are a second execution method of step S40101.

[0109] The principle of steps S4010101B-S4010103B is as follows Figure 3 shown.

[0110] Reference Figure 3 In step S4010101B, for the fish school quantity time series data series output by the Yolov8 algorithm, multiple target fish can be marked out, and the positions of these target fish in each frame of the fish school quantity time series data series are tracked, and the fish in the fish school that are not target fish are ordinary fish. A fish school movement direction can be calculated based on the position of the same target fish in any two adjacent frames in the fish school quantity time series data series. In this way, when the fish school quantity time series data series has multiple frames and each frame has multiple target fish, multiple fish school movement directions can be obtained, and each fish school movement direction can be expressed in vector form. Multiple fish school movement directions form a vector field, namely, a fish school vector field. The distribution range of the fish school vector field is the field of view of the underwater camera.

[0111] In step S4010102B, for the fish school vector field, the divergence data of each position therein can be solved. Among them, the position where the divergence data is greater than 0 is the convergence center, indicating the position where the fish school as a whole swims close to; the position where the divergence data is less than 0 is the divergence center, indicating the position where the fish school as a whole swims away from; the position where the divergence data is equal to 0 is neither a convergence center nor a divergence center, indicating the position where the fish school as a whole swims past.

[0112] Assume that by executing step S4010102B, multiple convergence centers and multiple divergence centers are determined.

[0113] In step S4010103B, taking the mth water body sensor as an example, the convergence center closest to the mth water body sensor is searched, and the distance between them is d convergence ; Search for the divergent center closest to the mth water body sensor, the distance between them is d divergence ;

[0114] Set the following judgment conditions:

[0115] (1)d convergence < distance threshold, and d convergence <d divergence ;

[0116] (2)d divergence < distance threshold, and d divergence <d convergence ;

[0117] (3) Other situations that do not meet judgment conditions (1) or (2).

[0118] When the judgment condition (1) is met, the second weight w′ corresponding to the mth water body sensor is m is determined to be a larger first value; when the judgment condition (2) is met, the second weight w′ corresponding to the mth water body sensor is m is determined to be a smaller third value; when the judgment condition (3) is met, the second weight w′ corresponding to the mth water body sensor is m Determined as a medium second value.

[0119] In this embodiment, the principle of executing steps S4010101B-S4010103B is: in the judgment condition (1), d convergence < distance threshold means that the mth water body sensor is quite close to the convergence center, d convergence <d divergenceIt means that the convergence center is closer to the mth water body sensor than the divergence center, that is, the mth water body sensor is closer to the position where the fish school swims as a whole, so the second weight with the largest value (first value) is set for the mth water body sensor; accordingly, in judgment condition (2), d divergence < distance threshold means that the mth water body sensor is quite close to the divergence center, d divergence <d convergence It means that the divergence center is closer to the mth water body sensor than the convergence center, that is, the mth water body sensor is closer to the position where the fish school swims away as a whole, so the second weight with the smallest value (third value) is set for the mth water body sensor; and if both judgment conditions (1) and (2) are not met, then judgment condition (3) is met, indicating that the mth water body sensor is not relatively closer to any convergence center or divergence center, and the mth water body sensor is at the position where the fish school swims past as a whole, so the second weight with a medium value (second value) is set for the mth water body sensor;

[0120] By executing steps S4010101B-S4010103B, a water body sensor that is closer to the convergence center can be set with a larger second weight, and a water body sensor that is closer to the divergence center can be set with a smaller second weight. Therefore, the marine ranch detection data detected at a location closer to the location where the fish school gathers will be given a larger second weight. This allows the monitoring of the marine ranch to focus on the data collected near the fish school, thereby increasing the monitoring attention on the fish school, which is conducive to achieving the economy of the marine ranch.

[0121] In this embodiment, by running the ocean ranch stereoscopic monitoring system, the ocean ranch stereoscopic monitoring method can be executed. Figure 4 , the marine ranch three-dimensional monitoring method includes the following steps:

[0122] S1. Using multiple water sensors to detect and obtain marine ranch detection data; each water sensor is used to be distributed and set at a corresponding position in the marine ranch;

[0123] S2. Underwater image information is obtained by shooting with an underwater camera; the underwater camera is used to be set underwater in the ocean ranch;

[0124] S3. Receive the detection data and underwater image information of each marine ranch through the data collection unit, and send the detection data and underwater image information of each marine ranch to the outside; the data collection unit is used to establish a connection with each water sensor and underwater camera;

[0125] S4. Analyze and process the detection data and underwater image information of each marine ranch to obtain marine monitoring indicators.

[0126] In this embodiment, when executing the marine ranch stereoscopic monitoring method, the marine ranch stereoscopic monitoring system can be divided into four parts: a data collection layer, a data transmission layer, a data processing and analysis layer, and a user interaction layer.

[0127] Data acquisition layer: In the data acquisition layer, the system comprehensively collects environmental data of the marine ranch by arranging various types of sensors and high-definition underwater cameras. The sensors include salinity, turbidity and chlorophyll sensors for water quality detection, water temperature, pH value and dissolved oxygen sensors for hydrological detection, and air temperature, air pressure and wind speed sensors for meteorological detection. These sensors are all waterproof and corrosion-resistant, and are connected to the microcontroller through I2C, SPI or UART interfaces to ensure the accuracy and stability of data acquisition. The microcontroller is responsible for collecting sensor data at a high sampling rate and performing preliminary processing such as noise filtering and data linearization. The high-definition underwater camera is used to collect underwater video in real time. It is connected to the microcontroller through the MIPI interface, and the video data is stored in the external memory for subsequent processing.

[0128] Data transmission layer: At the data transmission layer, the system first compresses and encodes the collected data to reduce the transmission bandwidth requirements and improve the reliability of the data. The video data is compressed using the H.264 encoding algorithm, and the sensor data is reduced in redundancy through differential encoding technology. All data is error-corrected by LDPC coding before transmission to cope with noise interference in the underwater environment. The compressed and encoded data is converted into an acoustic signal by MFSK modulation and transmitted to the land base station through the underwater acoustic communication module. The receiving end of the land base station is equipped with a hydrophone array, which is responsible for receiving and demodulating the underwater acoustic signal, and restoring the original digital data through the LDPC decoder to ensure the integrity and accuracy of the data.

[0129] Data processing and analysis layer: In the data processing and analysis layer, the system fuses and analyzes the received data from various sensors. First, the data is standardized to eliminate the dimensional differences between different sensors, and then the noise is eliminated through Kalman filtering and smoothing. Data fusion uses a combination of weighted averaging and Bayesian estimation to adaptively adjust the weights according to the historical confidence of the sensor data to generate comprehensive environmental parameters. After the video data is preprocessed by Gaussian blur and histogram equalization, the Yolov8 deep learning algorithm is used to detect and count fish targets to obtain the number of fish per unit time. Subsequently, the system combines the fused sensor data with the fish quantity data, extracts the key monitoring indicators reflecting the overall status of the marine ranch through principal component analysis, and calculates the comprehensive environmental index (CEI) to provide users with a scientific decision-making basis.

[0130] User interaction layer: At the user interaction layer, the system provides users with intuitive monitoring and early warning functions through the human-machine interface (HMI). Real-time monitoring data is displayed on the interface, and users can view the historical and real-time change trends of various environmental parameters. The interface also provides a customized report generation function, which is convenient for users to export detailed monitoring reports. When the monitoring indicators exceed the preset safety threshold, the system automatically triggers an alarm and sends the alarm information to relevant personnel via SMS or email to ensure that necessary response measures can be taken in time. The user interface is simple and intuitive, and supports access from multiple devices, making it easy for users to monitor the operation of the ocean ranch anytime, anywhere.

[0131] A computer program for executing the ocean ranch stereoscopic monitoring method in this embodiment can be written and written into a computer device or storage medium. When the computer program is read out and run, the ocean ranch stereoscopic monitoring method in this embodiment is executed, thereby achieving the same technical effect as the ocean ranch stereoscopic monitoring method in the embodiment.

[0132] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, etc. used in the present disclosure are only relative to the relative positional relationship of the components of the present disclosure in the accompanying drawings. The singular forms of "a", "" and "the" used in the present disclosure are also intended to include the plural forms, unless the context clearly indicates other meanings. In addition, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those generally understood by those skilled in the art. The terms used in the specification of this embodiment are only for describing specific embodiments and are not intended to limit the present invention. The term "and / or" used in this embodiment includes any combination of one or more related listed items.

[0133] It should be understood that, although the term first, second, third etc. may be adopted to describe various elements in the present disclosure, these elements should not be limited to these terms. These terms are only used to distinguish the same type of elements from each other. For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element. The use of any and all examples or exemplary language ("for example", "such as" etc.) provided by the present embodiment is only intended to better illustrate embodiments of the present invention, and unless otherwise required, the scope of the present invention will not be limited.

[0134] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed dedicated integrated circuit for this purpose.

[0135] In addition, the operations of the process described in this embodiment may be performed in any suitable order, unless otherwise indicated in this embodiment or otherwise clearly contradicted by the context. The process described in this embodiment (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as a code (e.g., executable instructions, one or more computer programs, or one or more applications) executed on one or more processors in common, by hardware or a combination thereof. A computer program includes a plurality of instructions that may be executed by one or more processors.

[0136] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself.

[0137] The computer program can be applied to input data to perform the functions of the present embodiment, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on the display.

[0138] The above are only preferred embodiments of the present invention. The present invention is not limited to the above embodiments. As long as the technical effects of the present invention are achieved by the same means, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention. Within the scope of protection of the present invention, its technical solutions and / or implementation methods may have various modifications and changes.

Claims

1. A three-dimensional monitoring system for marine ranches, characterized in that: The marine ranch three-dimensional monitoring system comprises: A plurality of water body sensors; the water body sensors are used to be distributed and arranged at corresponding positions of the marine ranch to detect and obtain marine ranch detection data; Underwater camera; the underwater camera is used to be set underwater in the ocean ranch to capture underwater image information; Data collection unit; the data collection unit is used to establish a connection with each of the water body sensors and the underwater camera, receive each of the marine ranch detection data and the underwater image information, and send each of the marine ranch detection data and the underwater image information to the outside.

2. The three-dimensional monitoring system for marine ranching according to claim 1 is characterized in that: The marine ranch three-dimensional monitoring system also includes: Data processing unit; the data processing unit is used to receive the marine ranch detection data and the underwater image information, analyze and process the marine ranch detection data and the underwater image information, and obtain marine monitoring indicators.

3. The three-dimensional monitoring system for marine ranching according to claim 2 is characterized in that: The analysis and processing of the marine ranch detection data and the underwater image information to obtain marine monitoring indicators includes: fusing the marine ranch detection data to obtain fused data; Identifying the underwater image information to obtain time series data of the number of fish schools; Perform principal component analysis on the fused data and the fish population time series data to obtain at least one of the ocean monitoring indicators.

4. The three-dimensional monitoring system for marine ranching according to claim 3 is characterized in that: The analyzing and processing of the marine ranch detection data and the underwater image information to obtain the marine monitoring index also includes: A comprehensive environmental index is determined based on each of the marine monitoring indicators and their corresponding first weights.

5. The three-dimensional monitoring system for marine ranching according to claim 3 or 4, characterized in that: The step of fusing the marine ranch detection data to obtain fused data includes: Determine a second weight corresponding to each of the water body sensors; For any of the marine ranch detection data, the second weight corresponding to the water body sensor that detects the marine ranch detection data is used as the weight corresponding to the marine ranch detection data, and weighted averaging is performed on each of the marine ranch detection data to obtain the fused data.

6. The three-dimensional monitoring system for marine ranching according to claim 5 is characterized in that: The determining of the second weight corresponding to each of the water body sensors includes: Obtaining the spatial distance between each of the water body sensors and the underwater camera; For any of the water body sensors, the size of the second weight corresponding to the water body sensor is set according to the spatial distance corresponding to the water body sensor; wherein the size of the second weight is negatively correlated with the spatial distance.

7. The three-dimensional monitoring system for marine ranching according to claim 5 is characterized in that: The determining of the second weight corresponding to each of the water body sensors includes: Determining the movement directions of multiple schools of fish according to the time series data of the number of the school of fish; Performing divergence analysis on the fish school vector field to obtain divergence data of multiple positions within the field of view of the underwater camera; wherein the fish school vector field is a vector field formed by the movement directions of each of the fish schools; The second weight corresponding to each of the water body sensors is determined according to each of the divergence data.

8. The three-dimensional monitoring system for marine ranching according to claim 7 is characterized in that: The determining, according to each of the divergence data, the second weight corresponding to each of the water body sensors, comprises: Determine the convergence center and the divergence center within the field of view of the underwater camera according to each of the divergence data; For any of the water body sensors, when the distance between the water body sensor and the convergence center is less than the distance between the water body sensor and the divergence center and less than a distance threshold, the second weight corresponding to the water body sensor is determined to be a first value; when the distance between the water body sensor and the divergence center is less than the distance between the water body sensor and the convergence center and less than a distance threshold, the second weight corresponding to the water body sensor is determined to be a third value; otherwise, the second weight corresponding to the water body sensor is determined to be a second value; The first value is greater than the second value, and the second value is greater than the third value.

9. A three-dimensional monitoring method for marine ranches, characterized in that: The marine ranch three-dimensional monitoring method comprises: The marine ranch detection data is obtained by respectively detecting through a plurality of water body sensors; each of the water body sensors is used to be distributed and arranged at a corresponding position of the marine ranch; Underwater image information is obtained by shooting with an underwater camera; the underwater camera is used to be set underwater in the ocean ranch; The marine ranch detection data and the underwater image information are received by a data collection unit, and the marine ranch detection data and the underwater image information are sent to the outside; the data collection unit is used to establish a connection with each of the water body sensors and the underwater camera; The marine ranch detection data and the underwater image information are analyzed and processed to obtain marine monitoring indicators.

10. A computer device, characterized in that: It includes a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the marine ranch stereoscopic monitoring method described in claim 9.

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