A water body pollutant tracing method, device, computer equipment and storage medium

Abstract

The application relates to a water body pollutant tracing method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining water body monitoring data corresponding to a target area, and obtaining geographical positioning information corresponding to the water body monitoring data; at least one concentration peak abnormal point corresponding to the target area is marked according to the water body monitoring data and the geographical positioning information; at least one target object corresponding to each concentration peak abnormal point is traced according to each concentration peak abnormal point, the geographical positioning information and a tracing range corresponding to the target area, and a target tracing result is obtained; and a water body pollution cruise analysis report corresponding to each target object is generated according to the target tracing result, the water body monitoring data and the geographical positioning information. The method can realize online real-time and historical monitoring, alarm and dynamic direct reading of a tracing result of water body pollutants, and improves the tracing efficiency of pollution sources in a large range.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a water pollutant tracing method and device, computer equipment, storage medium and computer program product. BACKGROUND

[0002] With the development of computer technology, water pollution tracing technology appears. The technology collects water quality pollution fingerprint data set of typical spatial distribution of sewage outlet and complete flow information. Then, the technology superimposes the data set on corresponding spatial distribution of receiving water body spatial distribution data to determine real-time pollution contribution rate. By using scientific settings, monitoring means and sampling strategies of pollution discharge points and river sections, the feasibility and effectiveness of water pollution tracing can be obviously increased.

[0003] In the traditional technology, in the field of water environment monitoring, as the monitoring space gradually expands, the collected data needs to be expanded from point to surface. However, in the traditional technology, various data need to be manually sampled, laboratory tested, manually traced and analyzed, and finally a tracing report is output. Using the traditional technology to trace water pollution leads to low efficiency of tracing the target area. SUMMARY

[0004] Therefore, it is necessary to provide a water pollutant tracing method, device, computer equipment, computer readable storage medium and computer program product capable of improving the tracing efficiency of the target area.

[0005] In a first aspect, the present application provides a water pollutant tracing method. The method is applied to a server and includes: obtaining water body monitoring data corresponding to a target area, and obtaining geographical positioning information corresponding to the water body monitoring data; marking at least one concentration peak abnormal point corresponding to the target area according to the water body monitoring data and the geographical positioning information; the concentration peak abnormal point represents that the water body monitoring data exceeds a preset concentration peak data point in the corresponding geographical positioning information; tracing at least one target object corresponding to each concentration peak abnormal point according to each concentration peak abnormal point, the geographical positioning information and a tracing range corresponding to the target area to obtain a target tracing result; the tracing range is determined according to the geographical positioning information and each target object; and generating a water body pollution cruise analysis report corresponding to each target object according to the target tracing result, the water body monitoring data and the geographical positioning information.

[0006] In a second aspect, the application provides a water pollutant tracing method. The method is applied to a terminal and includes: obtaining a system working state corresponding to a ship control system of the terminal and a device working state corresponding to a monitoring device of the terminal; sending the system working state and the device working state to a server implementing a water pollutant tracing method for confirmation; accepting a start command sent by the server in a case where a confirmation result returned by the server indicates that the system working state corresponding to the ship control system and the device working state corresponding to the monitoring device are both normal; and the start command indicates that the terminal starts to perform a walk.

[0007] In a third aspect, the application further provides a water pollutant tracing device. The device is applied to a server and includes: a data acquisition module configured to acquire water monitoring data corresponding to a target region and acquire geographic positioning information corresponding to the water monitoring data; a data analysis module configured to mark at least one concentration peak abnormal point corresponding to the target region according to the water monitoring data and the geographic positioning information; the concentration peak abnormal point indicates that the water monitoring data exceeds a preset concentration peak data point in the corresponding geographic positioning information; a data tracing module configured to trace at least one target object corresponding to each of the concentration peak abnormal points according to each of the concentration peak abnormal points, the geographic positioning information, and a tracing range corresponding to the target region, to obtain a target tracing result; the tracing range is determined according to the geographic positioning information and each of the target objects; and a report generation module configured to generate a water pollution walk analysis report corresponding to each of the target objects according to the target tracing result, the water monitoring data, and the geographic positioning information.

[0008] In a fourth aspect, the application further provides a water pollutant tracing device. The device is applied to a terminal and includes: a state acquisition module configured to acquire a system working state corresponding to a ship control system of the terminal and a device working state corresponding to a monitoring device of the terminal; a state sending module configured to send the system working state and the device working state to a server implementing a water pollutant tracing method for confirmation; and a walk module configured to accept a start command sent by the server in a case where a confirmation result returned by the server indicates that the system working state corresponding to the ship control system and the device working state corresponding to the monitoring device are both normal; and the start command indicates that the terminal starts to perform a walk.

[0009] In a fifth aspect, the present application also provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program: obtaining water body monitoring data corresponding to a target area, and obtaining geographical positioning information corresponding to the water body monitoring data; marking at least one concentration peak abnormal point corresponding to the target area according to the water body monitoring data and the geographical positioning information; the concentration peak abnormal point represents that the water body monitoring data exceeds a preset concentration peak data point in the corresponding geographical positioning information; performing tracing on at least one target object corresponding to each concentration peak abnormal point according to each concentration peak abnormal point, the geographical positioning information, and a tracing range corresponding to the target area, to obtain a target tracing result; the tracing range is determined according to the geographical positioning information and each target object; and generating a water body pollution walk analysis report corresponding to each target object according to the target tracing result, the water body monitoring data, and the geographical positioning information.

[0010] In a sixth aspect, the present application also provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the following steps: obtaining water body monitoring data corresponding to a target area, and obtaining geographical positioning information corresponding to the water body monitoring data; marking at least one concentration peak abnormal point corresponding to the target area according to the water body monitoring data and the geographical positioning information; the concentration peak abnormal point represents that the water body monitoring data exceeds a preset concentration peak data point in the corresponding geographical positioning information; performing tracing on at least one target object corresponding to each concentration peak abnormal point according to each concentration peak abnormal point, the geographical positioning information, and a tracing range corresponding to the target area, to obtain a target tracing result; the tracing range is determined according to the geographical positioning information and each target object; and generating a water body pollution walk analysis report corresponding to each target object according to the target tracing result, the water body monitoring data, and the geographical positioning information.

[0011] The water body pollutant tracing method, device, computer device, storage medium, and computer program product described above obtain water body monitoring data corresponding to a target region, obtain geographic positioning information corresponding to the water body monitoring data, mark at least one concentration peak abnormal point corresponding to the target region according to the water body monitoring data and the geographic positioning information, trace at least one target object corresponding to each concentration peak abnormal point according to each concentration peak abnormal point, the geographic positioning information, and a tracing range corresponding to the target region to obtain a target tracing result, and generate a water body pollution underway analysis report corresponding to each target object according to the target tracing result, the water body monitoring data, and the geographic positioning information.

[0012] By using an underway system equipped with an unmanned ship, a precise mass spectrometer, a ship control system, and a global positioning system are installed on the unmanned ship, so that the corresponding water body monitoring data is obtained while the unmanned ship is running. By obtaining the water body monitoring data and the positioning of the global positioning system in real time, online automatic tracing and historical data tracing of water body pollutants can be realized by means of 3D map technology and underway monitoring software, and a tracing report can be output. Online real-time and historical monitoring, alarm, and dynamic reading of tracing results of water body pollutants can be realized, and the tracing efficiency of pollution sources in a large range can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 An application environment diagram of a water body pollutant tracing method in one embodiment;

[0014] Figure 2 A flowchart of a water body pollutant tracing method in one embodiment;

[0015] Figure 3 A flowchart of a target tracing result obtaining method in one embodiment;

[0016] Figure 4 A flowchart of a historical data tracing method in one embodiment;

[0017] Figure 5 A flowchart of a water pollution correlation coefficient determining method in one embodiment;

[0018] Figure 6 A flowchart of a concentration peak abnormal point obtaining method in one embodiment;

[0019] Figure 7 A flowchart of a water body pollutant tracing method in another embodiment;

[0020] Figure 8 A structural block diagram of a water body pollutant tracing device in one embodiment;

[0021] Figure 9 A structural block diagram of a water body pollutant tracing device in another embodiment;

[0022] Figure 10 An internal structural diagram of a computer device in one embodiment;

[0023] Figure 11 An internal structural diagram of a computer device in another embodiment. DETAILED DESCRIPTION

[0024] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is 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 application and not to limit the present application.

[0025] The water body pollutant tracing method provided by the embodiments of the present application can be applied in an application environment as shown in Figure 1 The terminal 102 communicates with the server 104 through a network. The data storage system can store data required to be processed by the server 104. The data storage system can be integrated on the server 104, or placed on a cloud or other network server. The server 104 acquires water body monitoring data corresponding to a target area and geographical positioning information corresponding to the water body monitoring data through the terminal 102; marks at least one concentration peak abnormal point corresponding to the target area according to the water body monitoring data and the geographical positioning information; the concentration peak abnormal point represents a data point of the water body monitoring data exceeding a preset concentration peak in the corresponding geographical positioning information; traces at least one target object corresponding to each concentration peak abnormal point according to each concentration peak abnormal point, the geographical positioning information and a tracing range corresponding to the target area, to obtain a target tracing result; the tracing range is determined according to the geographical positioning information and each target object; and generates a water body pollution cruise analysis report corresponding to each target object according to the target tracing result, the water body monitoring data and the geographical positioning information. The terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0026] In one embodiment, as shown in Figure 2 A water body pollutant tracing method is provided, and the method is applied inFigure 1 Taking the server in the example, the following steps are included:

[0027] Step 202: Obtain water monitoring data corresponding to the target area, and obtain the geographic location information corresponding to the water monitoring data.

[0028] The target area can be an area where water monitoring is required by business needs using mobile surveying. Generally, the water monitoring content is VOCs in the water, which are volatile organic compounds in the water.

[0029] Among them, the water monitoring data can be the data collected by the water monitoring instruments of the unmanned vessel's navigation system during navigation in the target area.

[0030] Among them, the geographic positioning information can be the positioning data obtained by the positioning instrument of the mobile system in the mobile vehicle during the mobile navigation in the target area. Generally, the Global Positioning System or the BeiDou positioning system is used for positioning.

[0031] Specifically, the server responds to the terminal's instructions, retrieves water monitoring data corresponding to the target area and the corresponding geographic location information from the terminal, and stores the acquired water monitoring data and geographic location information in a storage unit. When the server needs to process any data record from the water monitoring data and geographic location information, it retrieves volatile storage resources from the storage unit for the central processing unit to perform calculations. This arbitrary data record can be a single data input to the central processing unit, or multiple data records can be input to the central processing unit simultaneously.

[0032] The mobile monitoring software on the server initiates the mobile monitoring process, sending commands to the unmanned surface vessel (USV) to control the monitoring instruments to initiate sample introduction and monitoring. The detection results are then linked to the current geographic location information. The terminal on the USV then sends the data back to the mobile monitoring software on the server. There is a mapping relationship between the water monitoring data and the geographic location information; that is, any given set of water monitoring data corresponds to a specific geographic location. For example, water monitoring data A corresponds to geographic location 'a', while water monitoring data B corresponds to geographic location 'b'. Water monitoring data A and B are from different times, and geographic location information 'a' and 'b' can have the same latitude and longitude, or they can have different latitude and longitudes.

[0033] Step 204: Based on water monitoring data and geographic location information, mark at least one concentration peak anomaly point corresponding to the target area.

[0034] Among them, the concentration peak anomaly point can be a data point in which the water pollution concentration detected by the water monitoring instrument exceeds the preset concentration peak during the navigation process using various monitoring devices on the unmanned vessel.

[0035] Specifically, during the navigation process using various monitoring devices on the unmanned vessel, the water monitoring devices maintain a connection with the server and continuously send water monitoring data to the server. At the same time, as the various monitoring devices on the unmanned vessel navigate, the positioning instruments of the navigation system continuously record the corresponding positioning information, which can be latitude and longitude or polar coordinates.

[0036] Based on the collected water monitoring data and geographic location information, the navigation trajectory is drawn in real time on a three-dimensional map, and the water pollution concentration corresponding to each geographic location information is marked, resulting in a concentration distribution map of the navigation trajectory.

[0037] Meanwhile, the collected water monitoring data is compared with the preset concentration peaks of water pollution in the target area. If the water monitoring data does not exceed the preset concentration peak, the water pollution status of the corresponding geographical location is considered normal. If the water monitoring data exceeds the preset concentration peak, the water pollution status of the corresponding geographical location is considered abnormal. Based on the geographic location information corresponding to the water monitoring data, it is marked on the concentration distribution map of the navigation trajectory to obtain at least one abnormal point of water concentration peak corresponding to the target area, and alarms are pushed in real time for factors that exceed the preset concentration peak.

[0038] Step 206: Based on the peak anomaly points of each concentration, geographic location information, and the source tracing range corresponding to the target area, trace the source of at least one target object corresponding to each peak anomaly point of the concentration to obtain the target source tracing result.

[0039] The scope of source tracing can be defined within the target area based on business needs, specifying the area from which water pollution source tracing needs to be conducted.

[0040] The target can be an enterprise in the target area that has the potential to discharge pollutants, including water pollution, air pollution, and solid waste pollution.

[0041] Among them, the source tracing result can be the result of tracing using the online source tracing mode and the historical data source tracing mode in the source tracing model, representing the correlation coefficient between at least one target object corresponding to each concentration peak anomaly point and the concentration peak anomaly point.

[0042] Specifically, since there are at least two source tracing modes for water pollution, including real-time online source tracing mode and historical data source tracing mode, and the source tracing scope includes the online source tracing scope corresponding to the real-time online source tracing mode and the historical source tracing scope corresponding to the historical data source tracing mode, then according to business needs, if the real-time online source tracing mode needs to be run, then the real-time online source tracing mode is activated, and the online source tracing scope is delineated in real time according to actual needs; if the historical data source tracing mode needs to be run, then the historical data source tracing mode is activated, and the historical source tracing scope is delineated according to actual needs. Both the real-time online source tracing mode and the historical data source tracing mode include the Pearson correlation coefficient, but the parameter adjustments in the Pearson correlation coefficient of the real-time online source tracing mode and the historical data source tracing mode are different.

[0043] In the first scenario, based on business needs, a real-time online traceability mode is activated. The first step is to leverage this mode. Since the various devices on the unmanned surface vessel (USV) include GPS devices, the monitoring data packets transmitted to the server include various geographic location information during the navigation process. Next, based on this geographic location information, the navigation direction of the USV during navigation is determined, which is the tangent direction at any point on the curve of the 3D map. This tangent direction is then input into the navigation monitoring software on the server. Simultaneously, based on business needs or water monitoring data, a corresponding area is drawn within the target region as the online traceability range. This online traceability range includes at least one target object.

[0044] The second step is to create a unique pollution fingerprint database for each water-related pollution target in the target area using mobile monitoring software. Then, based on business needs, within the online source tracing range defined by the concentration distribution map of the mobile trajectory, and at least one concentration peak anomaly point within the online source tracing range, each target object within the online source tracing range is scanned as the scanned target object. Finally, the data of the scanned target objects is compared with the data in the pollution fingerprint database, and the scanned target objects with a data overlap greater than a preset threshold are extracted as the water-related pollution target objects within the online source tracing range.

[0045] Step 3: Based on the anomalies in concentration peaks and the target objects, select the most suitable tracing algorithm from the real-time online tracing mode. During the selection process, the algorithm with the highest matching degree needs to be chosen from multiple tracing algorithms based on the specific characteristics of the anomalies in concentration peaks and the target objects. These specific characteristics can include distribution patterns, density per unit area, etc.

[0046] Step 4: First, based on each different water pollution target, determine the signal intensity of each target. This signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the target signal intensity is X. Similarly, based on each different concentration peak anomaly point, determine the anomaly point signal intensity corresponding to each anomaly point. This anomaly point signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the anomaly point signal intensity is Y.

[0047] Secondly, based on the signal strength X of the target object and the signal strength Y of the outlier, calculate the sum of squared deviations l of the target object's signal strength from the mean. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0048]

[0049]

[0050]

[0051] Secondly, based on the sum of squared deviations of the target object's signal strength from the mean, l XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0052]

[0053] Finally, the correlation between the various water pollution correlation coefficients and geographic location information is established in a three-dimensional map to form a relationship network and display the close values, thus obtaining the target source tracing result corresponding to the real-time online source tracing.

[0054] The second scenario involves initiating a historical data tracing mode based on business needs. The first step, based on this mode, is to utilize GPS devices on the unmanned surface vessel (USV). Since these devices include GPS, the monitoring data packets transmitted to the server contain geolocation information from the navigation process. Next, based on this geolocation information, the navigation path of the USV during navigation is determined, specifically the tangent direction at any point on the curve of the 3D map. This tangent direction is then input into the navigation monitoring software on the server. Simultaneously, based on business needs or water monitoring data, a corresponding area is drawn within the target region as the historical data tracing range. This historical data tracing range can be the same as the online tracing range or it can be a newly selected range. The historical tracing range must include at least one target object.

[0055] The second step involves creating a unique pollution fingerprint database for each water-related pollution target in the target area using mobile monitoring software. Then, based on operational needs, within the historical source tracing range defined by the concentration distribution map of the mobile monitoring trajectory, and at least one concentration peak anomaly point within that range, each target object within the historical source tracing range is scanned as a new target object. Finally, the data of the scanned target objects is compared with the data in the pollution fingerprint database. Target objects with a data overlap greater than a preset threshold are extracted and designated as water-related pollution targets within the historical source tracing range. Simultaneously, pollution factors at anomalies obtained in real-time through mobile monitoring are retrieved from the water body monitoring data. These pollution factors can be automatically acquired or manually labeled according to operational needs.

[0056] Step 3: Based on the concentration peak anomalies and the target objects, select the most suitable source tracing algorithm from the historical data source tracing patterns. During the selection process, the algorithm with the highest matching degree needs to be chosen from multiple source tracing algorithms based on the specific characteristics of the concentration peak anomalies and the target objects. These specific characteristics can include distribution patterns, density per unit area, etc.

[0057] Step 4: First, based on each different water pollution target, determine the signal intensity of each target. This signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the target signal intensity is X. Similarly, based on each different concentration peak anomaly point, determine the anomaly point signal intensity corresponding to each anomaly point. This anomaly point signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the anomaly point signal intensity is Y.

[0058] Secondly, based on the signal strength X of the target object and the signal strength Y of the outlier, calculate the sum of squared deviations l of the target object's signal strength from the mean. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0059]

[0060]

[0061]

[0062] Secondly, based on the sum of squared deviations of the target object's signal strength from the mean, l XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0063]

[0064] Finally, the correlation between the various water pollution correlation coefficients and geographic location information is established in a three-dimensional map to form a relationship network and display the close values, thus obtaining the target source tracing results corresponding to the historical data source tracing.

[0065] Step 208: Based on the source tracing results, water body monitoring data, and geographic location information, generate a mobile water pollution analysis report for each target object.

[0066] Among them, the water pollution mobile analysis report can be an analysis report that analyzes information such as the degree and scope of water pollution caused by the target object.

[0067] Specifically, based on the source tracing results, water body monitoring data, and geographic location information, the relationship between the three is analyzed according to a pre-set report format, and a water pollution mobile analysis report for each target object is provided. The source tracing results include the water pollution correlation coefficients between each target object and each concentration peak anomaly point.

[0068] In the aforementioned method for tracing the source of water pollutants, the following steps are taken: First, water monitoring data corresponding to the target area is acquired, along with corresponding geographic location information. Based on the water monitoring data and geographic location information, at least one concentration peak anomaly point corresponding to the target area is marked. The concentration peak anomaly point represents a data point where the water monitoring data exceeds a preset concentration peak value within the corresponding geographic location information. Based on each concentration peak anomaly point, the geographic location information, and the tracing range corresponding to the target area, at least one target object corresponding to each concentration peak anomaly point is traced to obtain the target tracing result. The tracing range is determined based on the geographic location information and each target object. Finally, based on the target tracing result, the water monitoring data, and the geographic location information, a water pollution mobile analysis report corresponding to each target object is generated.

[0069] By utilizing a mobile navigation system on an unmanned surface vessel (USV), equipped with precision mass spectrometry, a ship control system, and a global positioning system (GPS), the USV can simultaneously acquire relevant water monitoring data during operation. Through real-time acquisition of water monitoring data and GPS positioning, and with the aid of 3D mapping technology and mobile monitoring software, online automatic source tracing and historical data tracing of water pollutants can be achieved, generating source tracing reports. This system enables online real-time and historical monitoring of water pollutants, dynamic direct reading of alarms and source tracing results, and improves the efficiency of tracing pollution sources over a wide area.

[0070] In one embodiment, such as Figure 3 As shown, based on the anomalies in concentration peaks, geographic location information, and the source tracing range corresponding to the target area, at least one target object corresponding to each anomaly in concentration peaks is traced to obtain the target source tracing results, including:

[0071] Step 302: Based on the peak anomaly points of each concentration, geographic location information, and tracing range, perform real-time automatic tracing of at least one target object corresponding to each peak anomaly point to obtain the target tracing result.

[0072] Specifically, based on business needs, a real-time online traceability mode is initiated. The first step: Based on the real-time online traceability mode, since the various devices on the unmanned surface vessel (USV) include GPS devices, the monitoring data packets transmitted to the server include various geographic location information during the navigation process. Further, based on the various geographic location information during the navigation process, the navigation direction information of the USV during navigation is determined, which is the tangent direction at any point on the curve of the 3D map. This tangent direction at any point on the curve of the 3D map is also input into the navigation monitoring software on the server. Simultaneously, based on business needs or water monitoring data, a corresponding area is drawn in the target area as the online traceability range, which includes at least one target object.

[0073] The second step is to create a unique pollution fingerprint database for each water-related pollution target in the target area using mobile monitoring software. Then, based on business needs, within the online source tracing range defined by the concentration distribution map of the mobile trajectory, and at least one concentration peak anomaly point within the online source tracing range, each target object within the online source tracing range is scanned as the scanned target object. Finally, the data of the scanned target objects is compared with the data in the pollution fingerprint database, and the scanned target objects with a data overlap greater than a preset threshold are extracted as the water-related pollution target objects within the online source tracing range.

[0074] Step 3: Based on the anomalies in concentration peaks and the target objects, select the most suitable tracing algorithm from the real-time online tracing mode. During the selection process, the algorithm with the highest matching degree needs to be chosen from multiple tracing algorithms based on the specific characteristics of the anomalies in concentration peaks and the target objects. These specific characteristics can include distribution patterns, density per unit area, etc.

[0075] Step 4: First, based on each different water pollution target, determine the signal intensity of each target. This signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the target signal intensity is X. Similarly, based on each different concentration peak anomaly point, determine the anomaly point signal intensity corresponding to each anomaly point. This anomaly point signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the anomaly point signal intensity is Y.

[0076] Secondly, based on the signal strength X of the target object and the signal strength Y of the outlier, calculate the sum of squared deviations l of the target object's signal strength from the mean. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0077]

[0078]

[0079]

[0080] Secondly, based on the sum of squared deviations of the target object's signal strength from the mean, l XX Squared deviation of signal intensity from the mean at outlier points YYAnd the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0081]

[0082] Finally, the correlation between the various water pollution correlation coefficients and geographic location information is established in a three-dimensional map to form a relationship network and display the close values, thus obtaining the target source tracing result corresponding to the real-time online source tracing.

[0083] Alternatively, in step 304, a new traceability range is obtained as the historical data traceability range.

[0084] Among them, the historical data tracing range can be the tracing range that is redefined using historical water body monitoring data.

[0085] Specifically, based on business needs, the historical data tracing mode is activated. The first step: Based on the historical data tracing mode, since the various devices on the unmanned surface vessel (USV) include GPS devices, the monitoring data packets transmitted to the server include various geographic location information during the navigation process. Further, based on the geographic location information during the navigation process, the navigation direction information when using the USV for navigation is determined, which is the tangent direction at any point on the curve of the 3D map. This tangent direction at any point on the curve of the 3D map is also input into the navigation monitoring software on the server. Simultaneously, based on business needs or water monitoring data, a corresponding area is drawn in the target area as the historical data tracing range. The historical data tracing range can be the same as the online tracing range, or it can be reselected. The historical tracing range includes at least one target object.

[0086] Step 306: Based on the peak anomaly points of each concentration, geographic location information, and historical data tracing range, perform real-time historical data tracing on at least one target object corresponding to each peak anomaly point to obtain the target tracing result.

[0087] Specifically, the first step is to create a unique pollution fingerprint database for each water-related pollution target in the target area using mobile monitoring software. Then, based on operational needs, within the historical source tracing range defined by the concentration distribution map of the mobile monitoring trajectory, and at least one concentration peak anomaly point within that range, each target object within the historical source tracing range is scanned as a new target object. Finally, the data of the scanned target objects is compared with the data in the pollution fingerprint database. Target objects with a data overlap greater than a preset threshold are extracted and used as water-related pollution targets within the historical source tracing range. Simultaneously, pollution factors at anomalies obtained in real-time through mobile monitoring are retrieved from water body monitoring data. These pollution factors can be automatically acquired or manually labeled according to operational needs.

[0088] Step 2: Based on the concentration peak anomalies and the target objects, select the most suitable source tracing algorithm from the historical data source tracing patterns. During the selection process, the algorithm with the highest matching degree needs to be chosen from multiple source tracing algorithms based on the specific characteristics of the concentration peak anomalies and the target objects. These specific characteristics can include distribution patterns, density per unit area, etc.

[0089] Step 3: First, based on each different water pollution target, determine the signal intensity of each target. This signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the target signal intensity is X. Similarly, based on each different concentration peak anomaly point, determine the anomaly point signal intensity corresponding to each anomaly point. This anomaly point signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the anomaly point signal intensity is Y.

[0090] Secondly, based on the signal strength X of the target object and the signal strength Y of the outlier, calculate the sum of squared deviations l of the target object's signal strength from the mean. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0091]

[0092]

[0093]

[0094] Secondly, based on the sum of squared deviations of the target object's signal strength from the mean, l XXSquared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0095]

[0096] Finally, the correlation between the various water pollution correlation coefficients and geographic location information is established in a three-dimensional map to form a relationship network and display the close values, thus obtaining the target source tracing results corresponding to the historical data source tracing.

[0097] In this embodiment, by subdividing the traceability mode into online automatic traceability and historical data traceability, and simultaneously establishing different traceability modes to define the corresponding traceability scope, the goal of tracing the same data multiple times can be achieved, reducing the number of repeated tracings and improving the efficiency of traceability.

[0098] In one embodiment, such as Figure 4 As shown, based on the anomalies of each concentration peak, geographic location information, and the historical data tracing range, historical data tracing is performed on at least one target object corresponding to each concentration peak anomaly, yielding target tracing results, including:

[0099] Step 402: Identify at least one water pollution target based on the historical data source tracing scope.

[0100] Among them, the target objects of water pollution can be any target objects suspected of causing water pollution in the historical source tracing scope.

[0101] Specifically, a unique pollution fingerprint database is created for each water-related pollution target in the target area using mobile monitoring software. Then, based on operational needs, each target within the historical source tracing range defined by the concentration distribution map of the mobile monitoring trajectory, and at least one concentration peak anomaly point within that range, is scanned as the scanned target objects. Finally, the data of the scanned target objects is compared with the data in the pollution fingerprint database, and the scanned target objects with a data overlap greater than a preset threshold are extracted and used as the water-related pollution target objects within the historical source tracing range. Simultaneously, pollution factors at anomalies obtained in real-time through mobile monitoring are retrieved from water body monitoring data. These pollution factors can be automatically acquired or manually labeled according to operational needs.

[0102] Step 404: Based on the abnormal concentration peaks and the target objects of water pollution, determine the water pollution correlation coefficient between each target object of water pollution and each abnormal concentration peak.

[0103] Among them, the water pollution correlation coefficient can be the Pearson correlation coefficient, which is used to calculate the correlation between the target water pollution and the peak anomalies of each concentration.

[0104] Specifically, the third step is to select the most suitable source tracing algorithm from historical data source tracing modes based on the concentration peak anomalies and the specific characteristics of the target objects. During this selection process, the algorithm with the highest matching degree needs to be chosen from multiple source tracing algorithms based on the specific characteristics of the concentration peak anomalies and the target objects. These specific characteristics can include distribution patterns, density per unit area, etc.

[0105] Step 4: First, based on each different water pollution target, determine the signal intensity of each target. This signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the target signal intensity is X. Similarly, based on each different concentration peak anomaly point, determine the anomaly point signal intensity corresponding to each anomaly point. This anomaly point signal intensity is determined on the signal spectrum using water monitoring data and geographic location information, and the symbol representing the anomaly point signal intensity is Y.

[0106] Secondly, based on the signal strength X of the target object and the signal strength Y of the outlier, calculate the sum of squared deviations l of the target object's signal strength from the mean. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0107]

[0108]

[0109]

[0110] Secondly, based on the sum of squared deviations of the target object's signal strength from the mean, l XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0111]

[0112] Step 406: Based on the water pollution correlation coefficient and geographic location information, integrate the water pollution target objects corresponding to each concentration peak anomaly point to obtain the target source tracing results.

[0113] Specifically, the correlation coefficients of various water pollution factors and geographic location information are established in a three-dimensional map to form a relationship network and display the close values, thus obtaining the target source tracing results corresponding to the historical data source tracing.

[0114] In this embodiment, historical source tracing is performed using water monitoring data obtained from previous mobile surveys. Based on specific business needs, previous target source tracing results can be obtained, avoiding the need to conduct mobile monitoring every time source tracing is required, thus reducing the source tracing cost of the target area.

[0115] In one embodiment, such as Figure 5 As shown, based on the anomalies in concentration peaks and the target objects of water pollution, the water pollution correlation coefficients between each target object and each anomaly in concentration peaks are determined, including:

[0116] Step 502: Determine the target object signal strength corresponding to each water pollution target object based on each target object.

[0117] The signal strength of the target object can be the peak value of the water-related pollution target object in the signal spectrum.

[0118] Specifically, based on each different water pollution target, the signal strength of the target object corresponding to each water pollution target is determined. The signal strength of the target object is determined on the signal spectrum map through water body monitoring data and geographic location information, and the representative symbol of the signal strength of the target object is X.

[0119] Step 504: Determine the signal intensity of the abnormal point corresponding to each concentration peak abnormal point based on each concentration peak abnormal point.

[0120] Among them, the signal intensity of anomalies can be the peak value of the water-related pollution target on the signal spectrum.

[0121] Specifically, based on each different concentration peak anomaly point, the anomaly point signal intensity corresponding to each concentration peak anomaly point is determined. The anomaly point signal intensity is determined on the signal spectrum using water body monitoring data and geographic location information, and the representative symbol for the anomaly point signal intensity is Y.

[0122] Step 506: Determine the water pollution correlation coefficient between each water-related pollution target and each concentration peak anomaly point based on the signal strength of the target object and the signal strength of the anomaly point.

[0123] Specifically, based on the signal strength X of the target object and the signal strength Y of the outlier, the sum of squared deviations l of the target object's signal strength from the mean is calculated. XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The calculation formula is as follows:

[0124]

[0125]

[0126]

[0127] Based on the sum of squared deviations of the target object's signal strength l XX Squared deviation of signal intensity from the mean at outlier points YY And the sum of the product of the target object signal strength and the anomaly point signal strength. XY The correlation coefficient between each target object and each concentration peak anomaly point in water pollution can be calculated, i.e., the Pearson correlation coefficient. The calculation formula is as follows:

[0128]

[0129] In this embodiment, by using the signal strength of the target object and the signal strength of the anomaly point, the water pollution correlation coefficient between the target object of water pollution and the anomaly point of concentration peak can be accurately calculated, which greatly improves the accuracy of source tracing.

[0130] In one embodiment, such as Figure 6 As shown, based on water monitoring data and geographic location information, at least one concentration peak anomaly point corresponding to the target area is marked, including:

[0131] Step 602: Generate a concentration distribution map of the navigation trajectory based on water monitoring data and geographic location information.

[0132] Among them, the concentration distribution map of the navigation trajectory can be a correspondence map between the navigation trajectory and the concentration peak anomaly point. For example, the geographic location information corresponding to the concentration peak anomaly point 1 is a, while the geographic location information corresponding to the concentration peak anomaly point 2 is b, and so on.

[0133] Specifically, during the navigation process using various monitoring devices on the unmanned vessel, the water monitoring devices maintain a connection with the server and continuously send water monitoring data to the server. At the same time, as the various monitoring devices on the unmanned vessel navigate, the positioning instruments of the navigation system continuously record the corresponding positioning information, which can be latitude and longitude or polar coordinates.

[0134] Based on the collected water monitoring data and geographic location information, the navigation trajectory is drawn in real time on a three-dimensional map, and the water pollution concentration corresponding to each geographic location information is marked, resulting in a concentration distribution map of the navigation trajectory.

[0135] Step 604: If at least one pollution concentration value in the water monitoring data exceeds a preset concentration threshold, mark at least one concentration peak anomaly point corresponding to the target area on the concentration distribution map of the navigation trajectory.

[0136] The concentration threshold can be a preset peak concentration of water pollution in the target area.

[0137] Specifically, the collected water monitoring data is compared with the preset peak concentration of water pollution in the target area. If the water monitoring data does not exceed the preset peak concentration, the water pollution status of the corresponding geographical location is considered normal. If the water monitoring data exceeds the preset peak concentration, the water pollution status of the corresponding geographical location is considered abnormal. Based on the geographic location information corresponding to the water monitoring data, it is marked on the concentration distribution map of the navigation trajectory to obtain at least one abnormal point of water concentration peak corresponding to the target area, and an alarm is pushed in real time for factors that exceed the preset peak concentration.

[0138] In this embodiment, by using the concentration distribution map of the mobile trajectory, the location points in the water monitoring data that exceed the preset concentration can be further determined, which can identify the location of water pollution exceeding the standard, avoid importing too much data when tracing the source, and improve the efficiency of tracing the source.

[0139] In one embodiment, such as Figure 7 As shown, a method for tracing the source of water pollutants, applied at the terminal, includes:

[0140] Step 702: Obtain the system operating status of the ship control system corresponding to the terminal, and the device operating status of the monitoring equipment corresponding to the terminal.

[0141] Among them, the system working status can be the working message of the ship control system of the unmanned vessel, which can detect whether the ship control system has a fault.

[0142] Among them, the equipment working status can be the working message of the monitoring equipment, which can detect whether the monitoring equipment has a fault.

[0143] Specifically, the terminal's control center issues commands and simulates navigation tasks, operating the unmanned surface vessel's (USV) ship control system and monitoring equipment. It also receives work messages from the USV's ship control system and monitoring equipment, respectively, and determines the operational status of these systems based on these messages. If the USV is equipped with a positioning device, its operational status also needs to be assessed.

[0144] Step 704: Send the system operating status and equipment operating status to the server implementing a water pollutant tracing method for confirmation.

[0145] Specifically, the terminal's control center generates a set of operating statuses based on the system's and equipment's operating statuses, and sends the set of operating statuses to a server with mobile monitoring software via a communication network. The mobile monitoring software confirms that all instruments are operating normally and provides reverse control functions for various instruments on the unmanned vessel.

[0146] Step 706: If the confirmation result returned by the server indicates that the system working status of the ship control system and the equipment working status of the monitoring equipment are both normal, accept the start command sent by the server; the start command indicates that the terminal starts to sail.

[0147] Specifically, if the confirmation result returned by the server indicates that the system operating status of the ship control system and the equipment operating status of the monitoring equipment are both normal, then the terminal chip receives the navigation start command from the server and starts the ship control system and monitoring equipment on the unmanned vessel (if there is a positioning device, it is also started at the same time); if the confirmation result returned by the server indicates that either the system operating status or the equipment operating status is abnormal, then the terminal chip returns the information that the navigation cannot be started to the server to stop the navigation from starting, until all faults are eliminated.

[0148] In this embodiment, by checking the device through the terminal and exchanging data with the server to determine whether to start the mobile survey, the authenticity of the data collected during the mobile survey can be ensured and the efficiency of mobile survey data collection can be improved.

[0149] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0150] Based on the same inventive concept, this application also provides a water pollutant tracing device for implementing the above-mentioned water pollutant tracing method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more water pollutant tracing device embodiments provided below can be found in the above-described limitations of a water pollutant tracing method, and will not be repeated here.

[0151] In one embodiment, such as Figure 8 As shown, a water pollutant tracing device is provided, applied to a server, including: a data acquisition module 802, a data analysis module 804, a data tracing module 806, and a report generation module 808, wherein:

[0152] The data acquisition module 802 is used to acquire water body monitoring data corresponding to the target area, and to acquire the geographic location information corresponding to the water body monitoring data;

[0153] Data analysis module 804 is used to mark at least one concentration peak anomaly point corresponding to the target area based on water body monitoring data and geographic location information; the concentration peak anomaly point represents the data point where the water body monitoring data exceeds the preset concentration peak in the corresponding geographic location information;

[0154] The data tracing module 806 is used to trace at least one target object corresponding to each concentration peak anomaly point based on the concentration peak anomaly point, geographic location information, and the tracing range corresponding to the target area, and to obtain the target tracing result; the tracing range is determined based on the geographic location information and each target object.

[0155] The report generation module 808 is used to generate water pollution mobile analysis reports for each target object based on the target source tracing results, water body monitoring data and geographic location information.

[0156] In one embodiment, the data tracing module 806 is further configured to perform real-time automatic tracing of at least one target object corresponding to each concentration peak anomaly point based on each concentration peak anomaly point, geographic location information, and tracing range, to obtain target tracing results; or, to re-acquire a new tracing range as the historical data tracing range; and to perform real-time historical data tracing of at least one target object corresponding to each concentration peak anomaly point based on each concentration peak anomaly point, geographic location information, and historical data tracing range, to obtain target tracing results.

[0157] In one embodiment, the data tracing module 806 is further configured to determine at least one water pollution target based on the historical data tracing range; determine the water pollution correlation coefficient between each water pollution target and each concentration peak anomaly point based on each concentration peak anomaly point and each water pollution target; and integrate each water pollution target corresponding to each concentration peak anomaly point based on the water pollution correlation coefficient and geographic location information to obtain the target tracing result.

[0158] In one embodiment, the data tracing module 806 is further configured to determine the target object signal intensity corresponding to each water pollution target object based on each target object; determine the abnormal point signal intensity corresponding to each concentration peak abnormal point based on each concentration peak abnormal point; and determine the water pollution correlation coefficient between each water pollution target object and each concentration peak abnormal point based on the target object signal intensity and the abnormal point signal intensity.

[0159] In one embodiment, the data analysis module 804 is further configured to generate a cruise trajectory concentration distribution map based on water monitoring data and geographic location information; and to mark at least one concentration peak anomaly point corresponding to the target area on the cruise trajectory concentration distribution map if at least one pollution concentration value in the water monitoring data exceeds a preset concentration threshold.

[0160] In one embodiment, such as Figure 9 As shown, a water pollutant tracing device is provided, applied to a terminal, including: a status acquisition module 902, a status transmission module 904, and a mobile monitoring module 906, wherein:

[0161] The status acquisition module 902 is used to acquire the system operating status corresponding to the ship control system of the terminal, and the equipment operating status corresponding to the monitoring equipment of the terminal.

[0162] The status sending module 904 is used to send the system operating status and equipment operating status to the server that implements a water pollutant tracing method for confirmation;

[0163] The navigation module 906 is used to accept the start command sent by the server when the confirmation result returned by the server indicates that the system working status of the ship control system and the equipment working status of the monitoring equipment are both normal; the start command indicates that the terminal starts navigation.

[0164] The various modules in the aforementioned water pollutant tracing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0165] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores server data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for tracing the source of water pollutants.

[0166] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 11 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for tracing the source of water pollutants. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0167] Those skilled in the art will understand that Figure 10and Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0168] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0169] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0170] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0171] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0172] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0173] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for tracing the source of water pollutants, characterized in that, Applied to a server, the method includes: Obtain water body monitoring data corresponding to the target area, and obtain the geographic location information corresponding to the water body monitoring data; Based on the water body monitoring data and the geographic location information, at least one concentration peak anomaly point corresponding to the target area is marked; the concentration peak anomaly point represents the data point where the water body monitoring data exceeds the preset concentration peak in the corresponding geographic location information; Based on each concentration peak anomaly point, the geographic location information, and the source tracing range corresponding to the target area, at least one target object corresponding to each concentration peak anomaly point is traced to obtain the target source tracing result; the source tracing range is determined based on the geographic location information and each target object. Based on the source tracing results of the targets, the water body monitoring data, and the geographic location information, a water pollution mobile analysis report corresponding to each of the target objects is generated. The step of tracing the source of at least one target object corresponding to each concentration peak anomaly point based on the concentration peak anomaly point, the geographic location information, and the source tracing range corresponding to the target area, to obtain the target source tracing result, includes: A unique pollution fingerprint database is created for each water-related pollution target object in the target area using mobile monitoring software; based on the source tracing range and at least one concentration peak anomaly point in the source tracing range, each target object in the source tracing range is scanned as the scanned target object; The data of the scanned target object is compared with the data of the pollution fingerprint database. The scanned target objects with a data overlap greater than a preset threshold are extracted and used as the water pollution target objects in the source tracing range. Based on the concentration peak anomaly points, the geographic location information, and the source tracing range, the source of each water pollution target object is automatically traced in real time. Through the water body monitoring data and the geographic location information, the signal intensity of the target object corresponding to the water pollution target object and the signal intensity of the anomaly point corresponding to the concentration peak anomaly point are obtained on the signal spectrum. Based on the signal strength of the target object and the signal strength of the anomaly point, calculate the sum of squares of the deviations from the mean of the target object signal strength, the sum of squares of the deviations from the mean of the anomaly point signal strength, and the sum of the products of the deviations from the mean of the target object signal strength and the anomaly point signal strength; based on the sum of squares of the deviations from the mean of the target object signal strength, the sum of squares of the deviations from the mean of the anomaly point signal strength, and the sum of the products of the deviations from the mean, calculate the water pollution correlation coefficient between each of the water-related pollution target objects and each of the concentration peak anomaly points; form a relationship network between the water-related pollution target objects, the water pollution correlation coefficients, and the geographic location information in a three-dimensional map and display the close values ​​to obtain the target source tracing results corresponding to real-time online source tracing.

2. The method according to claim 1, characterized in that, The step of tracing the source of at least one target object corresponding to each concentration peak anomaly point based on the concentration peak anomaly point, the geographic location information, and the source tracing range corresponding to the target area, to obtain the target source tracing result, includes: Re-acquire the new source range as the historical data source range; Based on each of the concentration peak anomaly points, the geographic location information, and the historical data tracing range, real-time historical data tracing is performed on at least one of the target objects corresponding to each of the concentration peak anomaly points to obtain the target tracing result.

3. The method according to claim 2, characterized in that, The step of tracing historical data for at least one target object corresponding to each concentration peak anomaly point based on the concentration peak anomaly point, the geographic location information, and the historical data tracing range, to obtain the target tracing result, includes: Based on the historical data, at least one water-related pollution target should be identified within the source tracing scope. Based on each of the aforementioned concentration peak anomalies and each of the aforementioned water pollution target objects, determine the water pollution correlation coefficient between each of the aforementioned water pollution target objects and each of the aforementioned concentration peak anomalies; Based on the water pollution correlation coefficient and the geographic location information, the target objects of each water pollution corresponding to each concentration peak anomaly point are integrated to obtain the target source tracing results.

4. The method according to claim 3, characterized in that, The step of determining the water pollution correlation coefficient between each of the water pollution target objects and each of the concentration peak anomalies based on each of the concentration peak anomalies includes: Determine the target object signal strength corresponding to each of the aforementioned target objects based on each of the aforementioned target objects; Determine the signal strength of the abnormal point corresponding to each of the aforementioned concentration peak abnormal points; Based on the signal strength of the target object and the signal strength of the anomaly point, the water pollution correlation coefficient between each of the water-related pollution target objects and each of the concentration peak anomaly points is determined.

5. The method according to any one of claims 1 to 4, characterized in that, Based on the water monitoring data and the geographic location information, at least one concentration peak anomaly point corresponding to the target area is marked, including: Based on the water body monitoring data and the geographic location information, a concentration distribution map of the navigation trajectory is generated; If at least one pollution concentration value in the water monitoring data exceeds a preset concentration threshold, at least one concentration peak anomaly point corresponding to the target area is marked on the concentration distribution map of the navigation trajectory.

6. A method for tracing the source of water pollutants, characterized in that, Applied to a terminal, the method includes: The system operating status of the ship control system corresponding to the terminal and the device operating status of the monitoring device corresponding to the terminal are obtained. The system operating status and the device operating status are sent to a server implementing the method of any one of claims 1 to 5 for confirmation; If the confirmation result returned by the server indicates that the system working status of the ship control system and the equipment working status of the monitoring device are both normal, the terminal accepts the start command sent by the server; the start command indicates that the terminal begins to conduct navigation.

7. A water pollutant tracing device, characterized in that, Applied to a server, the device includes: The data acquisition module is used to acquire water body monitoring data corresponding to the target area, and to acquire the geographic location information corresponding to the water body monitoring data; The data analysis module is used to mark at least one concentration peak anomaly point corresponding to the target area based on the water body monitoring data and the geographic location information; the concentration peak anomaly point represents the data point where the water body monitoring data exceeds the preset concentration peak in the corresponding geographic location information; The data tracing module is used to create a unique pollution fingerprint database for each water-related pollution target object in the target area using mobile monitoring software; based on the tracing range and at least one concentration peak anomaly point within the tracing range, it scans each target object within the tracing range as a scanned target object; it compares the data of the scanned target objects with the data in the pollution fingerprint database, and extracts the scanned target objects with a data overlap greater than a preset threshold as water-related pollution target objects within the tracing range; it performs real-time automatic tracing of each water-related pollution target object based on each concentration peak anomaly point, the geographic location information, and the tracing range, and obtains the target corresponding to the water-related pollution target object on the signal spectrum using the water body monitoring data and the geographic location information. The target signal strength and the signal strength of the abnormal point corresponding to the concentration peak anomaly point are calculated. Based on the target signal strength and the abnormal point signal strength, the sum of squares of the deviations from the mean of the target signal strength, the sum of squares of the deviations from the mean of the abnormal point signal strength, and the sum of the products of the deviations from the mean of the target signal strength and the abnormal point signal strength are calculated. Based on the sum of squares of the deviations from the mean of the target signal strength, the sum of squares of the deviations from the mean of the abnormal point signal strength, and the sum of the products of the deviations from the mean, the water pollution correlation coefficient between each of the water-related pollution target objects and each of the concentration peak anomaly points is calculated. A relationship network between the water-related pollution target objects, the water pollution correlation coefficient, and the geographic location information is formed in a three-dimensional map and the closeness values ​​are displayed to obtain the target source tracing results corresponding to real-time online source tracing. The report generation module is used to generate a water pollution mobile analysis report corresponding to each of the target objects based on the target source tracing results, the water body monitoring data and the geographic location information.

8. A water pollutant tracing device, characterized in that, Applied to a terminal, the device includes: The status acquisition module is used to acquire the system operating status corresponding to the ship control system of the terminal, and the device operating status corresponding to the monitoring device of the terminal. A status sending module is used to send the system operating status and the device operating status to a server implementing the method of any one of claims 1 to 5 for confirmation. The navigation module is used to accept a start command sent by the server when the confirmation result returned by the server indicates that the system working status of the ship control system and the equipment working status of the monitoring equipment are both normal; the start command indicates that the terminal starts navigation.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images