Smart fishery fishing data processing method and system

Abstract

The invention is suitable for the technical field of fishing data processing, and particularly relates to a smart fishery fishing data processing method and system, and the method comprises the steps: delimiting the fishing range of a fishery, determining an operation unit, drawing an operation distribution diagram, positioning the real-time position of the operation unit, and marking the real-time position in the operation distribution diagram. And calculating the number of the operation units, configuring a corresponding relationship between the number and time, defining the corresponding time as a target moment when the number reaches the maximum, and intercepting a snapshot at the target moment from the distribution map. By calculating the average fish quantity and the total fish quantity, the fishery resource condition in the fishing range can be determined, the resource consumption speed can be measured, and the fishing intensity can be dynamically adjusted, so that the fishing efficiency and the economic benefit are improved, excessive fishing is avoided, the ecological integrity is protected, and efficient and lasting operation of a smart fishery is maintained.

Description

Technical Field

[0001] The present invention relates to the technical field of fishing data processing, and particularly to a method and system for processing fishing data in an intelligent fishing ground. Background Art

[0002] An intelligent fishing ground refers to a production means that integrates modern information technologies, such as the Internet of Things, remote sensing, big data, and scientific computing, on the basis of traditional fisheries to guide the operation of fishing boats; the intelligent fishing ground can assist fishermen in scientifically setting nets and fishing, improving the unit output and resource utilization rate, and at the same time ensuring the sustainable development of the fishing ground.

[0003] The existing fishing data in fishing grounds generally relies on fixed sensors, which can only collect partial information, easily leading to large deviations in fishing data, and the update frequency of fishing data is low and the delay is high, greatly affecting the accuracy of processing fishing data in fishing grounds.

[0004] Therefore, "how to obtain more comprehensive fishing data" is the technical problem to be solved by the present invention. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for processing fishing data in an intelligent fishing ground to solve the problem of "how to obtain more comprehensive fishing data" proposed in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A method for processing fishing data in an intelligent fishing ground, the method comprising:

[0008] Defining the fishing range of the fishing ground, determining the operation units, drawing an operation distribution map, positioning the real-time positions of the operation units, and marking them in the operation distribution map, calculating the number of the operation units, configuring the corresponding relationship between the number and time, when the number reaches the maximum, defining the corresponding time as the target time, and extracting a snapshot at the target time from the distribution map;

[0009] In the snapshot, collecting the attribute data of the operation units, where the attribute data at least includes: type and number, configuring a monitoring distance corresponding to each operation unit, taking the real-time position as the center of a circle and the monitoring distance as the radius to construct a fishing influence circle, and marking it in the snapshot;

[0010] Performing grid division on the snapshot, defining the grids located within the fishing influence circle as accurate grids, and the grids located outside the fishing influence circle as estimated grids, collecting the fishing data of each operation unit, calculating the average fish quantity of each accurate grid, defining the accurate grid closest to the estimated grid as the reference grid, and writing the average fish quantity of the reference grid into the estimated grid;

[0011] Calculate the total fish quantity within the fishing range via the average fish quantity, receive the operation route uploaded by the operation unit, traverse the estimated grids passed by the operation unit to obtain the target grid, calculate the true fish quantity of the target grid, and correct the total fish quantity.

[0012] Further, the steps of demarcating the fishing range of the fishing ground, determining the operation unit, drawing the operation distribution map, and positioning the real-time position of the operation unit include:

[0013] Use the sensing devices pre-deployed within the fishing range to collect the fish quantity data within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend;

[0014] Generate an offset suggestion for the total fish quantity based on the fish quantity data and send it to the preset terminal.

[0015] Further, the steps of constructing the fishing impact circle and marking it in the snapshot include:

[0016] Traverse the overlapping area of the fishing impact circle from the snapshot and split it into several estimated grids;

[0017] Divide the total fish quantity into several levels, where each level corresponds to an adjustment suggestion, and send the adjustment suggestions to all operation units.

[0018] Further, the steps of calculating the average fish quantity of each precise grid include:

[0019] Create several ladder items based on the average fish quantity, where each ladder item corresponds to a color;

[0020] Use the color to change the color of all grids in the operation distribution map to generate a fish quantity heat map.

[0021] Further, the steps of calculating the total fish quantity within the fishing range via the average fish quantity include:

[0022] Take the time as the abscissa and the total fish quantity as the ordinate to draw a change trend graph, and use the box plot method to delete the outliers;

[0023] Establish a positive correlation between the total fish quantity and the fishing range.

[0024] Further, the method further includes:

[0025] Collect the influencing factors of the average fish quantity, where the influencing factors at least include: water flow and terrain;

[0026] Based on the influencing factors, traverse the feature blocks from the estimation grids, integrate all the feature blocks, generate a verification task, and integrate it into the adjustment suggestions.

[0027] Further, the system includes:

[0028] An interception module, used to delimit the fishing range of the fishing ground, determine the operation units, draw an operation distribution map, locate the real-time positions of the operation units, and mark them on the operation distribution map, calculate the number of the operation units, configure the corresponding relationship between the number and time, when the number reaches the maximum, define the corresponding time as the target time, and intercept a snapshot at the target time from the distribution map;

[0029] A marking module, used to collect the attribute data of the operation units in the snapshot, where the attribute data at least includes: type and number, configure a monitoring distance corresponding to each operation unit one by one, use the real-time position as the center of the circle and the monitoring distance as the radius to construct a fishing influence circle, and mark it on the snapshot;

[0030] A writing module, used to perform grid segmentation on the snapshot, define the grids located within the fishing influence circle as accurate grids, and the grids located outside the fishing influence circle as estimation grids, collect the fishing data of each operation unit, calculate the average fish quantity of each accurate grid, define the accurate grid closest to the estimation grid as the reference grid, and write the average fish quantity of the reference grid into the estimation grid;

[0031] A correction module, used to calculate the total fish quantity within the fishing range through the average fish quantity, receive the operation route uploaded by the operation unit, traverse the estimation grids passed by the operation unit to obtain the target grids, calculate the real fish quantity of the target grids, and correct the total fish quantity.

[0032] Further, the interception module includes:

[0033] A collection unit, used to collect the fish quantity data within the fishing range by using the sensing devices pre-deployed within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend;

[0034] An offset unit, used to generate an offset suggestion for the total fish quantity according to the fish quantity data and send it to a preset terminal;

[0035] A creation unit, used to create a time window with a preset time as the starting point and the current time as the ending point;

[0036] A definition unit, used to traverse the moment when the number of operation units reaches the maximum within the time window and define it as the target time.

[0037] Further, the annotation module includes:

[0038] Traverse the overlapping areas of the fishing impact circles from the snapshot and split them into several estimation grids;

[0039] Divide the total fish quantity into several grades, where each grade corresponds to an adjustment suggestion, and send the adjustment suggestions to all operating units.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] By determining the real-time positions of the operating units, the activity patterns of the fish schools can be accurately deduced, providing a data basis for the fishing activities in the intelligent fishing ground. By generating snapshots, the fishing hotspots and resource distributions can be accurately analyzed, enhancing the balance of fishing operations, ensuring the sustainable development of the intelligent fishing ground. By calculating the average fish quantity and the total fish quantity, the fishery resources within the fishing range can be determined, quantifying the resource consumption rate, and dynamically adjusting the fishing intensity. Thus, while improving fishing efficiency and economic benefits, overfishing can be avoided, the ecological integrity can be protected, and the efficient and sustainable operation of the intelligent fishing ground can be maintained. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flowchart of the method for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0043] Figure 2 It is the first sub-flowchart of the method for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0044] Figure 3 It is the second sub-flowchart of the method for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0045] Figure 4 It is the third sub-flowchart of the method for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0046] Figure 5 It is the fourth sub-flowchart of the method for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0047] Figure 6 It is the block diagram of the composition of the system for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0048] Figure 7 It is the block diagram of the composition of the interception module in the system for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0049] Figure 8 It is the block diagram of the composition of the annotation module in the system for processing fishing data in the intelligent fishing ground provided by the embodiment of the present invention;

[0050] Figure 9 It is the block diagram of the writing module in the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention;

[0051] Figure 10 It is the block diagram of the calibration module in the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention. Specific embodiments

[0052] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0053] In Embodiment 1, Figure 1 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown, and the details are as follows:

[0054] S100: Define the fishing range of the fishing ground, determine the operation units, draw an operation distribution map, locate the real-time positions of the operation units, and mark them on the operation distribution map, calculate the number of the operation units, configure the corresponding relationship between the number and time, when the number reaches the maximum, define the corresponding time as the target time, and extract a snapshot at the target time from the distribution map.

[0055] Define the fishing range of the fishing ground, clarify the operation boundary, generate the fishing range, and determine the operation units that can carry out fishing activities within the fishing range. The operation units include fishing boats and near-shore operators, etc.; according to the sea area geographical features and resource distribution within the fishing range, etc., draw an operation distribution map, and use on-board positioning equipment and communication systems to collect the real-time positions of each operation unit, and dynamically mark the real-time positions on the operation distribution map.

[0056] Calculate the number of operation units in the operation distribution map, construct a corresponding relationship curve between the number and time, match and record each time point with the corresponding number of operation units to form a time series data set, identify the peak value of the number of operation units in the time series data set, and define the corresponding time point as the target time; in other words, the target time is also the time when there are the most operation units within the fishing range.

[0057] Real-time update the spatial distribution state of the operation units; the specific operation is to extract the operation position information of all operation units at the target time from the time series data of the operation distribution map and generate a static spatial snapshot; this snapshot fully reflects the geographical positions, distribution densities and operation postures, etc. of each operation unit within the fishing range at the target time.

[0058] S200: In the snapshot, collect the attribute data of the operation unit, where the attribute data includes at least: type and number, configure a monitoring distance corresponding to the operation unit one by one, with the real-time position as the center and the monitoring distance as the radius, construct a fishing impact circle, and mark it on the snapshot.

[0059] Determine the attribute data of each operation unit, where the attribute data is mainly used to identify the identity information of the operation unit, and the core element in the attribute data is the detection range of the fish school, that is, the fish-finding range or scanning radius of devices such as sonars and underwater cameras in the operation unit, define the corresponding scanning radius as the monitoring distance, with the real-time position of the operation unit as the center and the monitoring distance as the radius, construct a fishing impact circle, and the operation unit can estimate the number of fish schools within the fishing impact circle.

[0060] Use devices such as sonars or underwater cameras in the operation unit to collect acoustic or image data such as the detection echo intensity, the number of underwater targets, and the fish activity frequency within the fishing impact circle, and upload it to a preset data processing platform. Use the estimation model built in the data processing platform to preliminarily evaluate the approximate number of fish schools within the fishing impact circle, and mark the evaluation result on the snapshot.

[0061] S300: Perform grid division on the snapshot, define the grids located within the fishing impact circle as precise grids, and define the grids located outside the fishing impact circle as estimation grids. Collect the fishing data of each operation unit, calculate the average fish quantity of each precise grid, define the precise grid closest to the estimation grid as the reference grid, and write the average fish quantity of the reference grid into the estimation grid.

[0062] Divide the entire fishing range into several regularly spaced grid units, define the grids that completely fall within the fishing impact circle as precise grids, and define the grids that do not fall or do not completely fall within the fishing impact circle as estimation grids; use the approximate number of fish schools within the estimated fishing impact circle, divide by the area of the precise grid, and calculate the average fish quantity of each precise grid; in the snapshot, construct a coordinate system, determine the coordinates of the center point (intersection of the diagonals) of each grid, use this coordinate, combined with the Euclidean distance calculation formula, determine the precise grid closest to the estimation grid, and define this precise grid as the reference grid; use the average fish quantity of the reference grid to represent the fish quantity within the estimation grid.

[0063] S400: Calculate the total fish quantity within the fishing range through the average fish quantity, receive the operation route uploaded by the operation unit, traverse the estimation grids passed by the operation unit to obtain the target grids, calculate the real fish quantity of the target grids, and correct the total fish quantity.

[0064] Calculate the total fish quantity within the fishing range based on the average fish quantities in the precise grid and the estimated grid; in a data processing platform or other fishery management systems, collect the operation routes of the operation units, traverse all the estimated grids crossed by the operation routes, and define them as target grids; based on the actual operation data of the operation units within the target grids (such as catch quantity, echo intensity change, sonar density map, etc.), and in combination with the estimation model, calculate the real fish quantity within the target grids, where the real fish quantity is also an estimated value; use the real fish quantity to adjust the average fish quantity in the estimated grids and simultaneously correct the total fish quantity.

[0065] In Embodiment 2, Figure 2 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown. The following details the steps of delimiting the fishing range of the fishing ground, determining the operation units, drawing the operation distribution map, and positioning the real-time positions of the operation units, as follows:

[0066] S101: Use the sensing devices pre-deployed within the fishing range to collect the fish quantity data within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend.

[0067] Use the sensing devices pre-deployed within the fishing range, such as acoustic detectors, underwater cameras, and environmental monitoring sensors, etc., to collect the fish quantity data within the fishing range.

[0068] S102: Generate an offset suggestion for the total fish quantity based on the fish quantity data and send it to a preset terminal.

[0069] Generate an offset suggestion according to the total fish quantity, where the offset suggestion should include: the latest position of the high-density fish school area, the trend analysis of the fish school quantity, and the recommended operation position adjustment direction, range, etc., and send the offset suggestion to a preset terminal, where the preset terminal is the management terminal of the operation unit.

[0070] In Embodiment 3, Figure 2 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown. The following details the steps of when the quantity reaches the maximum, defining the corresponding time as the target time, as follows:

[0071] S103: Create a time window with a preset moment as the starting point and the current moment as the ending point.

[0072] The time window refers to all the time periods between the preset starting point and the current moment; by constructing the time window, it is possible to more conveniently extract, aggregate, and analyze data such as fish quantity data, operation unit behavior, fishing influence range change, and environmental parameters.

[0073] S104: In the time window, traverse to find the moment when the number of job units reaches the maximum, and define it as the target moment.

[0074] Define the moment when the number of job units in the time series dataset is the largest as the target moment.

[0075] In Embodiment 4, Figure 3 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown. The following details the steps of constructing the fishing impact circle and marking it in the snapshot, as follows:

[0076] S201: From the snapshot, traverse to find the overlapping area of the fishing impact circle and split it into several estimation grids.

[0077] In the snapshot, determine the overlapping area of the fishing impact circle, and define the grids that fall into or partially fall into the overlapping area as estimation grids.

[0078] S202: Divide the total fish quantity into several levels, where each level corresponds to an adjustment suggestion, and send the adjustment suggestion to all job units.

[0079] Divide the total fish quantity according to a certain numerical interval to divide into several levels; for example, divide to obtain multiple levels such as "high fish quantity", "medium fish quantity", "low fish quantity", etc. The level can represent the abundance of fish stock resources; set a corresponding adjustment suggestion for each level; for example, the adjustment suggestion corresponding to the "low fish quantity" level can be: the current total fish quantity is small, reduce the fishing range.

[0080] In Embodiment 5, Figure 4 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown. The following details the steps of calculating the average fish quantity of each precise grid, as follows:

[0081] S301: Based on the average fish quantity, create several ladder items, where each ladder item corresponds to a color.

[0082] Divide the average fish quantity into several levels, that is, ladder items, and set a corresponding color for each ladder item.

[0083] S302: Use the color to change the color of all grids in the operation distribution map to generate a fish quantity heat map.

[0084] Map different fish quantity intervals to different colors. For example, use blue to represent low fish quantity, green to represent medium fish quantity, and red to represent high fish quantity; use the color to perform color-changing processing on all grids in the operation distribution map, so as to convert the original operation distribution map into a fish quantity heat map reflecting the distribution intensity of the fish school.

[0085] In Embodiment 6, Figure 5 The implementation process of the intelligent fishing ground fishing data processing method provided by the embodiment of the present invention is shown. The following details the step of calculating the total fish volume within the fishing range via the average fish volume, as follows:

[0086] S401: Taking the time as the abscissa and the total fish volume as the ordinate, draw a trend chart, and use the box plot method to delete outliers.

[0087] Select multiple time points, infer the corresponding total fish volume, take the time as the abscissa and the total fish volume at the corresponding moment as the ordinate, and sequentially draw a total fish volume trend chart; by analyzing the total fish volume trend chart, the fluctuation of fishery resources in the time dimension can be intuitively presented; adopt the box plot method to identify and remove outliers; the specific operation is as follows: calculate the quartiles (Q1, Q3, and IQR) of the total fish volume, and calculate the upper and lower bounds, where the lower bound = Q1 - 1.5×IQR, the upper bound = Q3 + 1.5×IQR, and IQR is the interquartile range (Q3 - Q1). Consider all total fish volume data outside the upper and lower bounds as outliers and delete the outliers.

[0088] S402: Establish a positive correlation between the total fish volume and the fishing range.

[0089] Establish a positive correlation between the total fish volume and the fishing range. In other words, when the total fish volume is large, it indicates that the fishery resources within the fishing range are relatively rich, and the fishing range should be expanded.

[0090] In Embodiment 7, different from Embodiment 1, in the embodiment of the present invention, the method further includes:

[0091] Collect the influencing factors of the average fish volume, where the influencing factors at least include: water flow and terrain;

[0092] Based on the influencing factors, traverse the feature blocks from the estimation grids, integrate all the feature blocks, generate a verification task, and integrate it into the adjustment suggestion.

[0093] Select the estimation grids that may have influencing factors and define them as feature blocks. Feature blocks usually show areas such as abnormal fish volume and sudden changes in environmental conditions. Use the feature blocks to generate a verification task and send the verification task to all job units for on-site verification and supplementary monitoring operations of the feature blocks, etc., so as to further improve the accuracy of the total fish volume.

[0094] Figure 6 The composition structure block diagram of the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention is shown. The intelligent fishing ground fishing data processing system 1 includes:

[0095] The extraction module 11 is used to delimit the fishing range of the fishing ground, determine the operation units, draw an operation distribution map, locate the real-time positions of the operation units, mark them in the operation distribution map, calculate the number of the operation units, configure the corresponding relationship between the number and time, and when the number reaches the maximum, define the corresponding time as the target time, and extract a snapshot at the target time from the distribution map;

[0096] The annotation module 12 is used to collect the attribute data of the operation units in the snapshot, where the attribute data at least includes: type and number, configure a monitoring distance corresponding to each operation unit one by one, take the real-time position as the center of a circle and the monitoring distance as the radius to construct a fishing influence circle, and mark it in the snapshot;

[0097] The writing module 13 is used to perform grid segmentation on the snapshot, define the grids located within the fishing influence circle as precise grids, and the grids located outside the fishing influence circle as estimation grids, collect the fishing data of each operation unit, calculate the average fish quantity of each precise grid, define the precise grid closest to the estimation grid as the reference grid, and write the average fish quantity of the reference grid into the estimation grid;

[0098] The correction module 14 is used to calculate the total fish quantity within the fishing range through the average fish quantity, receive the operation routes uploaded by the operation units, traverse the estimation grids passed by the operation units to obtain the target grids, calculate the real fish quantity of the target grids, and correct the total fish quantity.

[0099] Figure 7 The block diagram of the composition of the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention is shown. The extraction module 11 includes:

[0100] The collection unit 111 is used to collect the fish quantity data within the fishing range by using the sensing devices pre-deployed within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend;

[0101] The offset unit 112 is used to generate an offset suggestion for the total fish quantity according to the fish quantity data and send it to a preset terminal;

[0102] The creation unit 113 is used to create a time window with a preset time as the starting point and the current time as the ending point;

[0103] The definition unit 114 is used to traverse the time when the number of operation units reaches the maximum in the time window and define it as the target time.

[0104] Figure 8The block diagram of the composition structure of the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention is shown. The annotation module 12 includes:

[0105] The splitting unit 121 is used to traverse the overlapping areas of the fishing influence circles from the snapshot and split them into several estimation grids.

[0106] The issuing unit 122 is used to divide the total fish quantity into several levels, where each level corresponds to an adjustment suggestion, and issue the adjustment suggestion to all operation units.

[0107] Figure 9 The block diagram of the composition structure of the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention is shown. The writing module 13 includes:

[0108] The ladder unit 131 is used to create several ladder items based on the average fish quantity, where each ladder item corresponds to a color.

[0109] The generating unit 132 is used to change the color of all grids in the operation distribution map using the color, and generate a fish quantity heat map.

[0110] Figure 10 The block diagram of the composition structure of the intelligent fishing ground fishing data processing system provided by the embodiment of the present invention is shown. The correction module 14 includes:

[0111] The deleting unit 141 is used to draw a change trend graph with the time as the abscissa and the total fish quantity as the ordinate, and use the box plot method to delete outliers.

[0112] The establishing unit 142 is used to establish a positive correlation between the total fish quantity and the fishing range.

[0113] Among them, the intercepting module 11 is mainly used to complete step S100, the annotation module 12 is mainly used to complete step S200, the writing module 13 is mainly used to complete step S300, and the correction module 14 is mainly used to complete step S400;

[0114] The collecting unit 111 is mainly used to complete step S101, the offset unit 112 is mainly used to complete step S102, the creating unit 113 is mainly used to complete step S103, and the defining unit 114 is mainly used to complete step S104;

[0115] The splitting unit 121 is mainly used to complete step S201, and the issuing unit 122 is mainly used to complete step S202;

[0116] The ladder unit 131 is mainly used to complete step S301, and the generating unit 132 is mainly used to complete step S302;

[0117] The deletion unit 141 is mainly used to complete step S401, and the establishment unit 142 is mainly used to complete step S402.

[0118] 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 recorded in this specification.

[0119] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. 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 patent for the present invention should be subject to the appended claims.

[0120] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing fishing data in an intelligent fishing ground, characterized in that, The method includes: Defining the fishing range of the fishing ground, determining the operation units, drawing an operation distribution map, locating the real-time positions of the operation units, and marking them on the operation distribution map, calculating the number of the operation units, configuring the corresponding relationship between the number and time, when the number reaches the maximum, defining the corresponding time as the target time, and extracting a snapshot at the target time from the distribution map; In the snapshot, collecting the attribute data of the operation units, where the attribute data at least includes: type and number, configuring a monitoring distance corresponding to each operation unit, taking the real-time position as the center and the monitoring distance as the radius to construct a fishing influence circle, and marking it on the snapshot; Performing grid division on the snapshot, defining the grids located within the fishing influence circle as accurate grids, and the grids located outside the fishing influence circle as estimated grids, collecting the fishing data of each operation unit, calculating the average fish quantity of each accurate grid, defining the accurate grid closest to the estimated grid as the reference grid, and writing the average fish quantity of the reference grid into the estimated grid; Calculating the total fish quantity within the fishing range via the average fish quantity, receiving the operation routes uploaded by the operation units, traversing the estimated grids passed by the operation units to obtain the target grids, calculating the real fish quantity of the target grids, and correcting the total fish quantity.

2. The intelligent fishing ground fishing data processing method according to claim 1, wherein The steps of defining the fishing range of the fishing ground, determining the operation units, drawing an operation distribution map, and locating the real-time positions of the operation units include: Using the sensing devices pre-deployed within the fishing range to collect the fish quantity data within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend; Generating an offset suggestion for the total fish quantity based on the fish quantity data, and sending it to a preset terminal.

3. The method for processing fishing data of an intelligent fishing ground according to claim 1, wherein, The step of when the number reaches the maximum, defining the corresponding time as the target time includes: Creating a time window with a preset time as the starting point and the current time as the ending point; In the time window, traversing the time when the number of operation units reaches the maximum, and defining it as the target time.

4. The intelligent fishing ground fishing data processing method according to claim 2, wherein, The steps of constructing the fishing influence circle and marking it on the snapshot include: Traversing the overlapping area of the fishing influence circle from the snapshot, and splitting it into several estimated grids; Dividing the total fish quantity into several levels, where each level corresponds to an adjustment suggestion, and sending the adjustment suggestion to all operation units.

5. The method for processing fishing data of an intelligent fishing ground according to claim 1, wherein The step of calculating the average fish quantity of each accurate grid includes: Based on the average fish quantity, creating several ladder items, where each ladder item corresponds to a color; Using the color to change the colors of all grids in the operation distribution map to generate a fish quantity heat map.

6. The method for processing fishing data of an intelligent fishing ground according to claim 1, wherein The step of calculating the total fish quantity within the fishing range via the average fish quantity includes: Taking the time as the abscissa and the total fish quantity as the ordinate to draw a change trend graph, and using the box plot method to delete the outliers; Establishing a positive correlation between the total fish quantity and the fishing range.

7. The intelligent fishing ground fishing data processing method according to claim 4, characterized in that, The method further includes: Collecting the influencing factors of the average fish quantity, where the influencing factors at least include: water flow and terrain; Based on the influencing factors, traverse the feature blocks from the estimation grids, integrate all the feature blocks to generate a verification task, and integrate it into the adjustment suggestions.

8. An intelligent fishing ground fishing data processing system, characterized in that, The system includes: An interception module, configured to delimit the fishing range of the fishing ground, determine the operation units, draw an operation distribution map, locate the real-time positions of the operation units, mark them on the operation distribution map, calculate the number of the operation units, configure the corresponding relationship between the number and time, and when the number reaches the maximum, define the corresponding time as the target time, and intercept a snapshot at the target time from the distribution map; A labeling module, configured to collect the attribute data of the operation units in the snapshot, where the attribute data at least includes: type and number, configure a monitoring distance corresponding to each operation unit one by one, take the real-time position as the center of the circle and the monitoring distance as the radius to construct a fishing influence circle, and label it on the snapshot; A writing module, configured to perform grid segmentation on the snapshot, define the grids located within the fishing influence circle as accurate grids, and the grids located outside the fishing influence circle as estimation grids, collect the fishing data of each operation unit, calculate the average fish quantity of each accurate grid, define the accurate grid closest to the estimation grid as the reference grid, and write the average fish quantity of the reference grid into the estimation grid; A correction module, configured to calculate the total fish quantity within the fishing range through the average fish quantity, receive the operation routes uploaded by the operation units, traverse the estimation grids passed by the operation units to obtain the target grids, calculate the real fish quantity of the target grids, and correct the total fish quantity.

9. The intelligent fishing ground fishing data processing system according to claim 8, wherein The interception module includes: A collection unit, configured to collect the fish quantity data within the fishing range by using the sensing devices pre-deployed within the fishing range, where the fish quantity data at least includes: fish school density and fish quantity change trend; An offset unit, configured to generate an offset suggestion for the total fish quantity according to the fish quantity data and send it to a preset terminal; A creation unit, configured to create a time window with a preset time as the starting point and the current time as the ending point; A definition unit, configured to traverse the time when the number of operation units reaches the maximum within the time window and define it as the target time.

10. The intelligent fishing ground fishing data processing system according to claim 9, wherein The labeling module includes: Traverse the overlapping areas of the fishing influence circles from the snapshot and split them into several estimation grids; Divide the total fish quantity into several levels, where each level corresponds to an adjustment suggestion, and send the adjustment suggestions to all the operation units.

Images